Inclusive Wealth Report 2012
Measuring progress toward sustainability

The Inclusive Wealth Report 2012 is a joint initiative of the United Nations University
International Human Dimensions Programme on Global Enivronmental Change(UNU-IHDP) and the United Nations Environment Programme (UNEP) in collaboration with the UN Water Decade Programme on Capacity Development (UNW-DPC)
and the Natural Capital Project.
This volume may be cited as: UNU-IHDP and UNEP (2012). Inclusive Wealth Report 2012.
Measuring progress toward sustainability. Cambridge: Cambridge University Press.

Inclusive WealthReport 2012
Measuring progress toward sustainability

UNU-IHDPCAMBRIDGE UNIVERSITY PRESS
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Cambridge University Press
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Programme on Global Environmental Change 2012
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First published 2012
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The views and opinions expressed herein do not necessarily represent

Editorial Consultant: Stu Slayen Consulting

the position of United Nations University International Human

Cover illustration: Louise Smith © UNU-IHDP

Dimensions Programme on Global Environmental Change, United

Design and layout: Louise Smith

Nations Environment Programme, UN-Water Decade Programme on

Project assistant: Pablo Fuentenebro

Capacity Development, Natural Capital Project, nor those of theirsponsors.

Contents

ix

Contributors

xi

Foreword by Achim Steinerxiii

Prefacexvi

Acknowledgements

Part II
121

Natural capital as economic assets: a review

xviii Abbreviations
xxi

Partha Dasgupta

Executive summary
143

1

The road to wealth accounting

Inclusive wealth: an overview

Charles Perrings
165

Chapter 1

Partha Dasgupta and Anantha Duraiappah

Edward B. Barbier
195

Chapter 2

Accounting for the inclusive wealth ofnations: empirical evidence

Heather Tallis, Stephen Polasky, Juan Sebastian
Lozano, and Stacie Wolny
215

Chapter 3

Leonie Pearson, Pablo Muñoz, and Elorm Darkey

Chris Perry231

Measuring inclusive wealth at the Statelevel in the United States

87

Paul Ekins
267 Conclusion

Lessons, findings, and recommendations

Chapter 5

Are national economies (virtually) sustainable?: an empirical analysis of natural
assets in international trade
Giles Atkinson, Matthew Agarwala and Pablo
Muñoz

Chapter 11

Safeguarding the future of the wealth ofnatureChapter 4

Kevin J. Mumford

Chapter 10

Accounting for water: stocks, flows, andvalues

The significance of the natural wealth ofnations

69

Chapter 9

Inclusive wealth accounting for regulating
ecosystem services

Pablo Muñoz, Elorm Darkey, Kirsten Oleson, andLeonie Pearson
51

Chapter 8

Ecosystem services and wealth accounting

Well-being and wealth27

Chapter 7

Introduction

Part I
13

Chapter 6

Anantha Duraiappah and Pablo Fuentenebro
281

Methodological annex

292 Data annex: wealth by country
332 Glossary of terms
335 Contributing organizationsv

Figures
Chapter 1

Chapter 4

1. The productive base and human well-being . . . . .  15

1. Per capita inclusive wealth and GDP annual growth
rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

Chapter 2

2. Inclusive wealth + TFP growth rate . . . . . . . . . . . . . .  77

1. Map: Average IWI per capita growth rate  . . . . . . . . 29

3. State-level inclusive wealth Lorenz curve  . . . . . . . 78

2. Average annual growth rates (per capita) disaggregated by capital form . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3. Map: Inclusive wealth index and Inclusive wealthindex per capita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4. Composition of the productive base of theeconomy. Average from 1990-2008.  . . . . . . . . . . . . 39
5. Composition of productive base for France,

Chapter 5

1. Schematic representation of an extended multiregional input-output (MRIO) Table . . . . . . . . . . . . . 95
2. Production and consumption-based resource
depletion (millions, US$) . . . . . . . . . . . . . . . . . . . . . . . . 101
3. Average per capita resource depletion (US$) . . . . 101

Germany, Japan, Norway, United States, and United

4. Production - minus consumption-based resource

Kingdom,  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

depletion (in millions, US$)  . . . . . . . . . . . . . . . . . . . . 102

6. Change in productive base for China, Chile, India,
and Kenya  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
7. Change in productive base for Brazil, Kenya andSaudi Arabia  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  41

5. Ratio of per capita production-based resource
depletions to the global average . . . . . . . . . . . . . . . 103
6. Ratio of per capita consumption-based resource
depletions to the global average  . . . . . . . . . . . . . . 104

8. Adjusted IWI  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Chapter 6
Chapter 3

1. Measuring per capita changes in natural capitaland IWI: average annual growth rates  . . . . . . . . . . . 54

1. The theory and the practice: GDP and emissions inOECD countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1242. Concentrations of sulfur dioxide . . . . . . . . . . . . . . .  125

2. Average annual growth rates disaggregated bynatural capital and population change . . . . . . . . . . . 56
3. Average annual growth rates disaggregated bynatural capital and population change in France
and Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4. Average annual growth rates disaggregated bynatural capital and population change, with focus

Chapter 7

1. Gross national savings and adjusted net savings
rates, 2008 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
2. Adjusted net savings rates: high-, middle- andlow-income countries plus heavily indebted poor
countries, 1970–2005  . . . . . . . . . . . . . . . . . . . . . . . . . 149

on fossil fuels  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  57
5. Average annual growth rates disaggregated bynatural capital and population change with a focus

1. Key interrelated steps in valuing ecosystem goods

on forests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  57

and services  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  175

6. Percentage change in natural capital,
1990-2008  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

2. Economic valuation of ecosystem goods andservices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  176

7. Percentage change in fish stocks, 1990-2008 . . . 58

3. Estimated mangrove area, Thailand, 1961–2009 182

8. Transformation rate of capital assets in the United

4. GDP and ANDP per capita, Thailand, 1970-2009 184

Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  61
9. Transformation rate of capital assets in Norway  . 62

vi

Chapter 8

Boxes
Chapter 9

Chapter 1

1. Hypothetical depiction of servicesheds for

1. Chance, thresholds, bifurcations, and potential

water-related regulating services. In watershedcatastrophes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Area “0”  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
2. Projected land use change, carbon stocks andChapter 2

sequestration from 2000 to 2030 in Colombia and1. Key variables used in the measurement of wealth 31

Ecuador.  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  206

2. Health Capital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

3. Nutrient regulation for drinking water quality in theyear 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2084. Erosion regulation for drinking water quality andreservoir maintenance in 2000. . . . . . . . . . . . . . . .  209

Chapter 6

1. Timber export and wealth transfers . . . . . . . . . . . .  1282. Payment for ecosystem services . . . . . . . . . . . . . . .  1333. Valuing Options  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  138

Chapter 11

1. A four-capitals model of wealth creation through aprocess of production . . . . . . . . . . . . . . . . . . . . . . . . . 233

Chapter 8

1. Adjusting net domestic product (NDP) for the

2. The relationship between environmental functions

contributions of ecological capital  . . . . . . . . . . . . .  179

and human benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . 246

2. The value of ecosystem resilience in the Goulburn-

3. A safe operating space for humanity . . . . . . . . . . . 249
4. Income and happiness in the United States  . . . . 256
5. Income and happiness for different countries  . . 257

Broken Catchment of southeast Australia . . . . . . . 181
3. Valuation estimates used in accounting for mangrove wealth, Thailand . . . . . . . . . . . . . . . . . . . . . . . . .  183

6. Illustration of linkages between ecosystem services and human well-being . . . . . . . . . . . . . . . . . . . 259

vii

Tables
Chapter 2

1. Measuring countries’ progress. Average annual
growth rates, period 1990-2008. . . . . . . . . . . . . . . . . 36

2. Wealth accounting for mangrove capital, Thailand,
1970–2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
3. Wealth accounting, Thailand – 1970–2009 . . . . . 186

2. Comparing average growth rates per annum in IWI
per capita, GDP per capita and HDI. . . . . . . . . . . . . . 44

Chapter 10

1. Global water distribution  . . . . . . . . . . . . . . . . . . . . . . 218
Chapter 3

2. Water supply and use statement, Denmark . . . . . 220

1. Measuring Changes in Natural Capital: Average

3. Statement of stocks (Mm3) . . . . . . . . . . . . . . . . . . . . 223

Annual Growth Rates, 1990–2008 . . . . . . . . . . . . . . . 55

4. Water accounts for Australia, 2004–05  . . . . . . . . 228

2. Understanding How Change in Wealth and Natural
Capital is Different When Considered in Absolute

Chapter 11

and Per Capita Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

1. Headings for indicators of social capital . . . . . . . . 237
2. Structure of the environmental indicator sets ofChapter 4

1. Real GDP per capita growth rate by state . . . . . . . . 79
2. Exhaustible natural capital . . . . . . . . . . . . . . . . . . . . . . 80
3. Non-federal rural land value . . . . . . . . . . . . . . . . . . . .  81
4. Physical capital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5. Human capital  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

EUROSTAT and OECD . . . . . . . . . . . . . . . . . . . . . . . . . 238
3. Various sustainability measures for the
Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2514. A classification of resources and theirindicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
5. Summary impacts for the change from the 2000

6. Change in comprehensive wealth (millions of 2005

baseline to 2060 under each of the NEA scenarios:

dollars) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

Great Britain. All values given in £Million per annum.

7. Change in comprehensive wealth per capita (2005261

dollars) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
8. Annual growth rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

Methodological Annex

1. Key variables and data sources used in the meaChapter 5

1. Resource depletion for selected economies . . . . . 99
2. Percentage contribution to global sustainability byregion (percentage of gross world income) . . . . . 105
3. Genuine saving and “virtual sustainability” byselected countries and regions  . . . . . . . . . . . . . . . . 106

surement of human capital . . . . . . . . . . . . . . . . . . . . 282
2. Key variables and data sources used in the measurement of manufactured capital  . . . . . . . . . . . . 282
3. Key variables and data sources used in the measurement of natural capital . . . . . . . . . . . . . . . . . . . . 284
4. Key variables and data sources used in the measurement of health capital . . . . . . . . . . . . . . . . . . . . . 288

Chapter 7

1. Traditional and externality-adjusted TFPG for 23
OECD countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1472. SNA environmental assets . . . . . . . . . . . . . . . . . . . . . 154
3. SEEA environmental assets . . . . . . . . . . . . . . . . . . . .  1554. Methods used to estimate asset values in the
SEEA  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  157

Chapter 8

1. Various non-market valuation methods applied toecosystem services  . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177

viii

5. Key variables and data sources used in the measurement of adjusted IWI . . . . . . . . . . . . . . . . . . . . . . 288

Contributors

Science Advisor
Partha Dasgupta – University of Cambridge
Report Director
Anantha Duraiappah – IHDP Executive Director
Science Director
Pablo Muñoz – IHDP Academic Officer
Authors
Matthew Agarwala – London School of Economics and Political
Science
Giles Atkinson – London School of Economics and Political
Science / Centre for Climate Change Economics and Policy
Edward B. Barbier – University of Wyoming
Elorm Darkey – University of Bonn
Partha Dasgupta – University of Cambridge
Anantha Duraiappah – IHDP Secretariat
Paul Ekins – University College London
Pablo Fuentenebro – IHDP Secretariat
Juan Sebastian Lozano – The Nature Conservancy (Colombia)
Kevin Mumford – Purdue University
Pablo Muñoz – IHDP Secretariat
Kirsten Oleson – University of Hawaii
Leonie Pearson – University of Melbourne
Charles Perrings – Arizona State University
Chris Perry – UN-Water Decade Programme on Capacity
Development (UNW-DPC)
Steve Polasky – University of Minnesota
Heather Tallis – Stanford University
Stacie Wolny – Stanford Universityix

Review Board
John Agnew – University of California, Los AngelesPeter Bartelmus – Bergische Universitaet Wuppertal / Columbia
University
Julia Bucknall – World Bank
Dabo Guan – University of Leeds
Michael Harris – University of Sydney
Rashid Hassan – University of Pretoria
Nicolas Kosoy – McGill University
Jens Liebe – UN-Water Decade Programme on Capacity
Development (UNW-DPC)
Hal Mooney – Stanford University
Eric Neumayer – London School of Economics and Political
Science
Timothée Ollivier – Centre d’Économie Industrielle
Unai Pascual – Basque Centre for Climate Change (BC3) /University of Cambridge
Alan Randall – University of Sydney
Bart Schultz – UNESCO-IHE Institute for Water Education
Stanislav Shmelev – University of Oxford
R. Kerry Turner – University of East Anglia
Jeff Vincent – Duke University
Aart de Zeeuw – Tilburg UniversityxForeword

The preliminary findings of the Inclusive Wealth Report (IWR) initiative are presented in this publication: they provide for policymakers an initial analysis towards a broader and comprehensive
way of measuring inclusive progress within their economies.
There has for some time been a shared recognition that conventional indicators such as gross domestic product (GDP) or
the Human Development Index (HDI) are failing to capture thefull wealth of a country. These limitations may be in part fueling environmental decline and degradation because changes innatural or “nature-based” assets are not factored into national
accounts, rendering those accounts less useful as an indicator ofchanges in human well-being.
This report, produced by the UN University International
Human Dimensions Programme on Global Environmental
Change and UNEP, builds on the findings of the Millennium
Ecosystem Assessment of 2005. It echoes, too, the conclusions of
the Stiglitz-Sen-Fitoussi Commission of 2009 which argued thatmeasuring well-being requires a shift from conventional production indicators to metrics that incorporate non-economic markets-based aspects of well-being, including sustainability issues.
The preliminary IWR gives an overview on the evolution of somerelevant categories of natural capital, such as forests, for a range ofcountries over a 19-year period, comparing their decline or increaseagainst two other areas: produced capital, such as roads and factories;
and human capital, including levels of education, knowledge, andcreativity. The preliminary findings indicate that it is possible to trace
the changes of the components of wealth by country and link theseto economic growth, including highlighting the impact of declines orincreases in natural capital as an economic productive base.
While many economies do appear to be getting wealthier, it ishappening often at the expense of the natural capital base which,in the future and over generations, may move the Inclusive
Wealth Index (IWI) from the black into the red.

Achim Steiner
UN Under-Secretary-General and UNEP Executive DirectorxiPreface

Although there have been a number of successes in creating a moresustainable global economy, a new report by the United Nations
Secretary-General’s High-Level Panel on Global Sustainability —Resilient People, Resilient Planet: A future worth choosing — recognizes the current global political-economic order’s failures, eveninability, to implement the drastic changes necessary to bringabout true “sustainability.”
The Panel’s report presents a vision for a“sustainable planet, just society, and growing Despite significant advances in
economy,” as well as 56 policy recommendations for realizing that goal. It is arguably the the past 25 years, humanity has
most prominent international call for a radical failed to conserve resources,
redesign of the global economy ever issued.
But, for all its rich content, Resilient People, safeguard natural ecosystems, orResilient Planet is short on concrete, practical otherwise ensure its own longsolutions. Its most valuable short-term recommendation — the replacement of current devel- term viability.
opment indicators (gross domestic product orvariants thereof) with more comprehensive, inclusive metrics for
wealth — seems tacked on almost as an afterthought. Without
quick, decisive international action to prioritize sustainability
over the status quo, the report risks suffering the fate of its 1987predecessor, the pioneering “Brundtland Report”, which introduced the concept of sustainable development, called for a paradigm shift, and was then largely ignored. Resilient People, Resilient
Planet opens by paraphrasing Charles Dickens: the world today
is “experiencing the best of times, and the worst of times.” As
a whole, humanity has achieved unparalleled prosperity; great
strides are being made to reduce global poverty; and technological advances are revolutionizing our lives, stamping out diseases,
and transforming communication.
That said, inequality remains stubbornly high, and is increasing in many countries. Short-term political and economic strategies are driving consumerism and debt, which, together with agrowing global population — set to reach nearly nine billion by
2040 — is subjecting the natural environment to growing stress.
By 2030, notes the Panel, “the world will need at least 50 percent
more food, 45 percent more energy, and 30 percent more water —all at a time when environmental limits are threatening supply.”xiii

Despite significant advances in the past 25 years, humanity has
failed to conserve resources, safeguard natural ecosystems, orotherwise ensure its own long-term viability.
Can a report — however powerful — create change? Will theworld now rally, unlike in 1987, to the Panel’s call to “transformthe global economy”? Perhaps, in fact, real action is born of crisis
itself. As the Panel points out, it has never been
more clear that we need a paradigm shift toachieve truly sustainable global development.
We need new indicators that tell
But who will coordinate an international
us if we are destroying the proprocess to study how to encourage such a shift,
and who will ensure that scientific findings leadductive base that supports ourto meaningful public-policy processes?
well-being.
The 2010 Report by the Commission on
the Measurement of Economic Performanceand Social Progress, commissioned by French President Nicolas
Sarkozy, echoed the current consensus among social scientists
that we are mis-measuring our lives by using per capita GDP as ayardstick for progress.
The United Nations University’s International Human
Dimensions Programme (UNU-IHDP) and the United Nations
Environment Programme (UNEP), together with other partners,
have been working to find these indicators for this Inclusive
Wealth Report (IWR), which proposes an approach to sustainability based on measuring natural, manufactured, human, andsocial forms of capital. The IWR aims to provide a comprehensive
analysis of the different components of wealth by country; theirlinks to economic development and human well-being; and policies that are based on social management of these assets.
The IWR represents a crucial first step in transforming the
global economic paradigm, by ensuring that we have the correct
information with which to assess our economic development
and well-being — and to reassess our needs and goals. While itis not intended as a universal indicator for sustainability, it does
offer a framework for dialogue with multiple constituencies fromthe environmental, social, and economic fields.
The report might suffer from incompleteness in data but it
presents a valuable framework for tracking sustainability. This
report also highlights where more work is needed in plugging
the data gaps and adding more information incrementally as it
becomes available. But rather than wait for complete accuracy,
the report makes a bold attempt to illustrate with the available
data whether countries are sustainable and, if not, where they are
under-performing and where interventions are needed to rectify
the situation. The framework also offers a useful tool for macroeconomic planning agencies as it pays equal attention to all
three pillars of sustainable development (social, environmental,
xiv

Inclusive Wealth Reportand economic). It also talks the language of economic and social
institutions and not just the language of the environmental
community.
Our situation is critical. As Resilient People, Resilient Planet
aptly puts it, “tinkering around the margins” will no longer suffice—a warning to those counting on renewable-energy technologies and a green economy to solve our problems. The Panel has
revived the call for far-reaching change in the global economic
system. Our challenge is to follow words with action this time.

Partha Dasgupta			Anantha Duraiappah

Science Advisor to the Inclusive

Report Director to the Inclusive

Wealth Report 2012, and Frank

Wealth Report 2012, andRamsey Professor Emeritus of

Executive Director of the

Economics at the University ofInternational Human Dimensions

Cambridge

Programme on Global
Environmental Change

Prefacexv

Acknowledgements

The Inclusive Wealth Report (IWR) is an outcome of a cooperative
effort. Many individuals and organizations participated in various capacities. The IWR would not have been possible without
the numerous contributions from authors, reviewers, UNU-IHDP
staff members, funding agencies, and many others who at one
point or another contributed to the project. We are extremely
grateful to all of them and would like to thank and acknowledge
them here for their dedication and long hours.
Science Advisor
We would like to begin by extending special thanks to Professor Sir
Partha Dasgupta, Chair of the International Human Dimensions
Programme Scientific Committee, who served as the report’s
Science Advisor. His untiring efforts as an author and advisor
were instrumental in the production of this report.
Authors
We would like to thank all authors who contributed to this report:
Matthew Agarwala, Giles Atkinson, Edward B. Barbier, Elorm
Darkey, Partha Dasgupta, Anantha Duraiappah, Paul Ekins, Pablo
Fuentenebro, Juan Sebastian Lozano, Kevin Mumford, Pablo
Muñoz, Kirsten Oleson, Leonie Pearson, Charles Perrings, Chris
Perry, Steve Polasky, Heather Tallis, and Stacie Wolny.
Reviewers
The IWR benefited greatly from all of the feedback and comments provided by our reviewers, including John Agnew, Peter
Bartelmus, Patrick ten Brink, Julia Bucknall, Dabo Guan, Michael
Harris, Rashid Hassan, Nicolas Kosoy, Jens Liebe, Hal Mooney,
Edwin Muchapondwa, Eric Neumayer, Timothée Ollivier, Unai
Pascual, Alan Randall, Bart Schultz, Stanislav Shmelev, R. Kerry
Turner, Marcelo Villena, Jeff Vincent, and Aart de Zeeuw.
UNU-IHDP
As a core project of the UNU-IHDP Secretariat, the IWR project has
involved many people from its early stages. Anantha Duraiappah,
Executive Director of IHDP, who conceived of the idea for an IWR
as early as 2008, took the lead as the IWR Director. Pablo Muñoz,
Academic Officer at IHDP, who coordinated and oversaw thexviscientific inputs to the report served as Science Director of thereport. Elorm Darkey provided analytical support in the production of the database and numerical computations. Special thanks
to Anne-Kathrin Raab, Communications Manager; Lou Smith,art and layout designer; and Carmen Scherkenbach, our editor.
We would like to thank Pablo Fuentenebro, Benjamin Zhu, andSabrina Zwick for their technical and logistical support.
We are equally grateful to our interns who devoted their timeto this project, including Workineh Asmare, Ara Beittoei, Mert
Cetinkaya, Elorm Darkey, Pablo Fuentenebro, Michelle Lowe,
Umberto Muratori, Carlos Torres, Ekaterine Rogava, and Sijia Yi.
Finally, the report benefited significantly from the editorial
expertise of Stu Slayen.
UNEP
This is a joint project with the United Nations Environment
Programme, and many people from UNEP played a role in developing this report. We would like to specifically acknowledge the support of Ibrahim Thiaw, Director of the Division of Environmental
Policy Implementation, for providing the institutional support forthis initiative. Special thanks also go to Pushpam Kumar, Chiefof the Ecosystem Services; Neville Ash, Coordinator, Biodiversity
and Ecosystem Services Branch, and Chief, Biodiversity Unit andchief of the Biodiversity Branch; and Makiko Yashiro Programme
officer, the Ecosystem Services Unit.
Funding bodies
The IWR was made possible by a grant from the United
Nations Environment Programme (UNEP). The National Science
Foundation and the German Federal Ministry of Education andResearch (BMBF) provided additional funding through their core
support to the UNU-IHDP. The Chinese National Committee for
the International Human Dimensions Programme (CNC-IHDP)
provided additional funds to facilitate outreach and dissemination of the IWR. The project also received in-kind support fromthe UN Water Decade Programme on Capacity Development(UNW-DPC) and the Natural Capital Project.
Finally, we would like to thank our publisher, Cambridge
University Press, for the time and flexibility given to us throughout the production and printing of the report. Special thanks
to Chris Harrison, Publishing Director for Social Sciences at
Cambridge University Press.

xvii

Abbreviations

6EAP. . . . . . . Sixth Environmental Action
Programme
ANDP. . . . . . . adjusted net domestic product
ANS. . . . . . . . adjusted net savings
BEA . . . . . . . . Bureau of Economic Analysis
C. . . . . . . . . . . carbon
CBP. . . . . . . . consumption-based principle
CES. . . . . . . . constant elasticity of substitution
CGSDI. . . . . . Consultative Group on
Sustainable Development
Indicators
CIA. . . . . . . . . United States Central Intelligence
AgencyCO2. . . . . . . . carbon dioxide
CNC. . . . . . . . critical natural capital
CPR. . . . . . . . common property resources
CVM. . . . . . . . contingent valuation method
DMC . . . . . . . domestic material consumption
DMI . . . . . . . . direct material input
EA1. . . . . . . . . SEEA Environmental Asset:
Natural resources
EA2. . . . . . . . SEEA Environmental Asset: Landand surface water
EA3. . . . . . . . SEEA Environmental Asset:
Ecosystems
EF. . . . . . . . . . ecological footprint
EFTA. . . . . . . European Free Trade Association
EPA . . . . . . . . United States Environmental
Protection Agency
ESI. . . . . . . . . Ecological Sustainability Index
ESP . . . . . . . . ecosystem services productEU. . . . . . . . . . European Union
GBC. . . . . . . . Goulburn-Broken Catchment
FAO. . . . . . . . Food and Agriculture
Organization
GDI. . . . . . . . . gross domestic income
GDP. . . . . . . . gross domestic productGF. . . . . . . . . . UKNEA scenario: Go with the
Flow
xviii

GHG. . . . . . . . greenhouse gas
GNS. . . . . . . . gross national savings
GPI. . . . . . . . . Genuine Progress Indicator
GPL . . . . . . . . UKNEA scenario: Green andPleasant Land
GS. . . . . . . . . . genuine savings
GTAP. . . . . . . Global Trade Analysis Project
HC . . . . . . . . . human capital
HDI. . . . . . . . . Human Development Index
HIPC . . . . . . . heavily indebted poor country
ICID. . . . . . . . International Commission on
Irrigation & Drainage
IGBP. . . . . . . . International Geosphere–
Biosphere Programme
IMF. . . . . . . . . International Monetary FundIO. . . . . . . . . . input-output
IOT. . . . . . . . . input-output tables
IPCC. . . . . . . . Intergovernmental Panel on
Climate Change
ISEW. . . . . . . Index of Sustainable Economic
WelfareIWI. . . . . . . . . Inclusive Wealth Index
IWIadj . . . . . . Adjusted Inclusive Wealth Index
IWR . . . . . . . . Inclusive Wealth Report
LS. . . . . . . . . . UKNEA scenario: Local
stewardship
MA. . . . . . . . . Millennium Ecosystem
Assessment
MAG. . . . . . . Ministerio de Agricultura yGanadería del Ecuador
MRIO. . . . . . . multi-regional input-output
NC . . . . . . . . . natural capital
NCI. . . . . . . . . Natural Capital Index
NDP. . . . . . . . net domestic product
NIPA. . . . . . . . national income and productaccounts
NNI. . . . . . . . . net national income
NNP. . . . . . . . net national productNOx. . . . . . . . nitrous oxides
NPV. . . . . . . . net present value
NS . . . . . . . . . UKNEA scenario: National
security
NSGAP. . . . . normalized sustainability gap
NTFB. . . . . . . non-timber forest benefits
NW. . . . . . . . . UKNEA scenario: Nature at work
OECD . . . . . . Organisation for Economic
Co-operation and Development

PBP . . . . . . . . production-based principle
PES . . . . . . . . payment for ecosystem services
PF. . . . . . . . . . production function
PIM. . . . . . . . . Perpetual Inventory Method
PM-10. . . . . . particulate matter
PPP. . . . . . . . purchasing power parity
PPP. . . . . . . . polluter-pays-principle (Chapter 6)
PSR . . . . . . . . pressure-state-response
R&D. . . . . . . . research and development
Rio+20 . . . . . 2012 Earth Summit
SC. . . . . . . . . . social capital
SCC. . . . . . . . social cost of carbon
SDI. . . . . . . . . sustainable development
indicators
SEEA. . . . . . . System of Environmental andEconomic Accounts
SEEAW. . . . . System of EnvironmentalEconomic Accounting for Water
SGAP. . . . . . . sustainability gap
SNA. . . . . . . . System of National Accounts
SOx . . . . . . . . sulfur oxides
SW. . . . . . . . . soil water
TEEB . . . . . . . The Economics of Ecosystems
and Biodiversity
TFP. . . . . . . . . total factor productivity
TMC. . . . . . . . total material consumption
TMDL. . . . . . . total maximum daily loads
TMI. . . . . . . . . total material input
TMO. . . . . . . . total material output
TMR. . . . . . . . total material requirement
TN. . . . . . . . . . total nitrogen
UKNEA. . . . . U.K. National Ecosystem
Assessment
UN . . . . . . . . . United Nations
UNCSD. . . . . United Nations Conference on
Sustainable Development
UNDP . . . . . . United Nations Development
Programme
UNEP. . . . . . . United Nations Environment
Programme
UNFCCC . . . United Nations Framework
Convention on Climate Change
USGS. . . . . . . United States Geological Survey
UNU. . . . . . . . United Nations University

Abbreviations

UNU-IHDP. . United Nations University
International Human
Dimensions Programme on
Global Environmental Change
USDA. . . . . . . United States Department ofAgriculture
USGS. . . . . . . United States Geological Survey
USLE. . . . . . . universal soil loss equation
VSL. . . . . . . . . value of a statistical life
WAVES. . . . . Wealth Accounting and Valuationof Ecosystem Services
WC. . . . . . . . . water closet
WM . . . . . . . . UKNEA scenario: World markets
WWF. . . . . . . World Wildlife Fund
YS. . . . . . . . . . years-to-sustainability

xixExecutive summary

This Inclusive Wealth Report (IWR) is the first of
a biennial series of reports on the sustainabilityof countries. The report looks at the productive base of economies, based on capital assets– produced or manufactured capital; humancapital; and natural capital. This first report ofthe series is focused on natural capital and will
be released at the Earth Summit 2012 (Rio+20)
to be held in Rio de Janeiro, Brazil, in June 2012.
The two main themes of Rio+20 will be thegreen economy and international environmental governance. The United Nations SecretaryGeneral’s high level panel report on global sustainability – Resilient People, Resilient Planet: A
Future Worth Choosing – was released in April of2012 to inform the discussions and negotiations
at the summit. The report highlights the potential of a green economy and also calls for new
ways of measuring progress in a green economy.
The IWR provides such a measure.
The IWR is a joint collaboration between the
United Nations University International Human
Dimensions Programme (UNU-IHDP) and theUnited Nations Environment Programme(UNEP). The group of authors for the report was
selected based on their expertise in inclusive
wealth and environmental economics, and an
extensive publication record in the area of natural capital, human well-being, social welfare, andvaluation, among others. A review process was
also established and each chapter was reviewed
by a minimum of two external referees using
standard academic criteria. The reviewers werechosen again based on their expertise in thefield, strong academic credentials, and a good
publishing record in the relevant fields coveredby this report.

The goals of the Inclusive Wealth Report
The primary objective of the Inclusive WealthReport is to provide quantitative information
and analysis that present a long-term perspective on human well-being and measures of sus-xxi

tainability. In addition, the main objectives of
the IWR are:• to undertake a preliminary analysis ofwhether countries were on a sustainable
path, and provide national governmentswith a metric to assess transitions towards the so-called “Green Economy”;• to carry out a comprehensive analysisof the various components of wealth bycountry and their link to economic development, highlighting in particular theimportance of natural capital;• to become an indicator of progress towards sustainable development with the
production of biennial reports monitoring the well-being of countries. In thelong-term, we expect inclusive wealth tobecome an important criterion in assessments of societal progress;• to help countries formulate and stimulate policies based on the notion of asset
portfolio management, wherein nations
follow plans to comprehensively manage diverse assets – natural, manufactured, and human – to create productive
and sustainable economic bases for the
future, and emphasize how an inclusive
wealth report can be used by nations toguide their investment strategies for sustainability; and• to highlight where extra research is needed to make the Inclusive Wealth Index
and the report a useful tool for economic,
environmental and social planning.

and a guide for international negotiations on
the consideration of transboundary assets. The
report will also be useful for national economicplanning agencies when considering macroeconomic fiscal policies. Changes in the various
capital assets and their contribution towards theinclusive wealth of a country can provide information on where to target future investments
in order to get the best returns for increasing
the productive base of the country.
The report is presented in two parts. Part I(Chapters 1–5) introduces the concept of inclusive wealth and provides the first results for aset of 20 countries used as a pilot in the 2012
report.
In Part II of this report (Chapters 6–11), we
present some key insights on developing ecosystem services accounts and the challenges
faced when attempting to value the changes in
the capital stocks over time.
Each chapter presents a number of “key messages,” as presented in the next pages.

Structure and content of the report
The primary audience of the Inclusive WealthReport will be governments. More broadly,
the report will be of use to development practitioners as well as researchers and the wider
development community. The inclusion ofenvironmental damage in the accounts – aswell as damages from global environmental
change such as climate change – can be useful
in determining cross-country compensations
xxii

Inclusive Wealth ReportKey Messages•

PART I•

Chapter 1

Well-being and wealth
•

•

•

•

The true achievement of sustainable development must focus on human well-being.
When we talk about human well-being, wecannot only talk about today. The definition of human well-being – and, indeed, ourefforts to achieve it – must entail the wellbeing of future generations.
Studies on sustainable development performance evaluate societal change over time.
To be complete, these studies must effectively evaluate a society’s productive base.
Wealth is the social worth of an economy’s
assets: reproducible capital; human capital; knowledge; natural capital; population;
institutions; and time.
Shadow prices are key to understanding
inclusive wealth. The shadow price for manymarket-traded goods is the market price, butthese should be used with caution as many
prices do not take account of externalities.

•

•

•

6 out of the 20 countries analyzed decreased
their IWI per capita in the last 19 years. In 5
out of 20 countries, population increased ata faster rate than inclusive wealth, resulting
in negative changes in the IWI per capita.
The majority of the countries in our sample have had an increase in their stocks ofmanufactured capital per capita. In China,
India and Chile, the positive changes in IWI
has been mainly driven by manufactured
capital. Russia, Nigeria, and Venezuela saw adecrease in their manufactured capital base.
When the three capital forms measured
are adjusted for total factor productivity –oil capital gains and carbon damages theperformance of some countries increases
considerably, particularly for Nigeria, Saudi
Arabia and Venezuela.
Human capital, being the prime capital form
that offsets the decline in natural capital inmost of the economies, has increased inevery country.
This chapter demonstrates that the IWI
provides a different perspective for assessing the performance of an economy - thisby switching the focus of attention fromflows (income) to stock metrics (wealth).
This stresses the importance of preserving
a portfolio of capital assets to ensure thatthe productive base can ultimately be maintained to sustain the well-being of future
generations.

Chapter 2

Chapter 3

Accounting for the inclusive wealthof nations

The significance of the natural
wealth of nations••

This chapter analyzes changes in the inclusive wealth index (IWI) and its components
for 20 countries for the period from 1990
to 2008. Wealth is primarily assessed here
as the value of manufactured, human, andnatural capital stocks. The Index is additionally adjusted for population changes by presenting per capita measures.

Executive Summary•

This first IWR focuses on quantifying components of natural capital that are largely
driven by those resources for which markets
exist. It is easier to obtain physical inventories and data on these stocks.
Shadow prices would be an effective tool formeasuring an asset’s contribution to wellbeing because they also reflect the relative
importance of the different capital formsxxiiiwithin the wealth accounting framework.
The lack of such shadow prices presents asignificant shortcoming. So instead, thisanalysis relies on rental prices, meaning
market prices minus production costs of theresources.
• We see that in almost all countries, potential gains in renewable resources were notenough to compensate for the depletion of
exhaustible stocks, like fossil fuels. The fishery is a specific illustration where, althougha renewable resource, fish are being “mined”
at a rate that challenges renewal of thestock.
• The general trend is that population has
been growing in most of the countries, exacerbating thereby the decline in natural capital growth rates, as resources are accounted
for among a larger number of people.
Readers are encouraged to review theMethodological Annex and the Data Annex at theend of the publication. These annexes shed light on
the processes used to arrive at the information in
Chapters 2 and 3.
Chapter 4

Measuring inclusive wealth at a
sub-national level: lessons from theUnited States

•

•

•

cient is 0.09, which represents a fairly equal
distribution of wealth.
The study demonstrates that the rate of
economic growth as measured by inclusive
wealth can be quite different than the rate of
economic growth suggested by GDP figures.
Data show that those states with high GDP
growth rates tend to have much lower rates
of inclusive wealth growth.
It is essential that governments collect capitalstock data so that inclusive wealth accounting can become increasingly accurate, comprehensive, and useful. More complete data
would enable states to measure their rate ofinclusive investment. Such data would also
make it clear to policy-makers whether current GDP growth rates are sustainable in thelong-run.
An important conclusion drawn here is that
if states with an inclusive wealth per capita
annual growth rate that is less than their
GDP per capita annual growth rate want tosustain higher GDP growth rates for the longterm, increased inclusive investment will
be required. This means that state governments would have to encourage education,
reduce the extraction of natural resources,
and increase the construction of public
infrastructure.

Chapter 5

•

•

•

xxiv

This chapter is the first attempt to construct
an accounting of the capital assets of each of Are national economies (virtually)
the 48 contiguous U.S. states.
sustainable?: an empirical analysis
The study looks at four types of capital: of natural assets in international
exhaustible natural capital (mainly coal, oil, tradeand natural gas); land; physical capital (likebuildings, homes, and equipment); and • This chapter explores the impact of internahuman capital (based on education, wages,
tional trade on sustainable development andand number of working years remaining).
the measurement of genuine (or adjusted
Despite the limitations in data availability,net) savings at both the global and domestic
using housing and stock market data tolevels.
value physical capital is an important contri- • The chapter draws crucial distinctions
bution to the literature on sustainability.
between production- and consumptionThe results show a very low level of wealthbased approaches to measuring changes
inequality across states. The Gini coeffiin inclusive wealth, as well as between thenotions of domestic and global sustainability,
Inclusive Wealth Report

•

•

•

•

where the latter is defined in terms of the
global genuine savings rate.
By looking only at per-country inclusive
wealth accounting, we potentially weaken
our understanding of global performance.
The chapter addresses this by examining howchanges in resource wealth are embodied ininternationally traded goods and services.
Specifically, the chapter uses a disaggregatedmulti-regional input-output model (MRIO)
to measure the value of resource depletionand the social costs of carbon emissions in
the context of international trade.
The term “virtual sustainability” is introduced here as a way to consider the implications of trade and the role of consumptionin understanding a country’s contribution
to global sustainability.
Our empirical findings indicate that themagnitudes of the (change in) natural assets
embodied in trade can be substantial, bothin dollar value terms and in relation tonational economies. This could challengeboth the conventional thinking on sustainability and the claims of progress made on
this front by individual countries.

•

•

•

of upstream deforestation on downstream
farmers. Without correction, the use of natural capital is implicitly subsidized by people
who suffer from the externalities.
A large part of what nature offers is a necessity and not a luxury. There are options forsome level of substitutability, but in consideration, caution must be taken for irreversible processes that might cause a decrease inwell-being.
The social worth of natural resources can bedivided into three parts: use value, intrinsic value, and option value – in varying
proportions.
Property rights are currently focused on
individual ownership. However, many of
nature’s services are public and therefore itis difficult to assign property rights to them.
Moreover, if those rights are assigned, they
are typically assigned without due accord
to social justice. Ill-specified or unprotected
property rights typically prevent markets
from forming or make markets function
wrongly when they do.

Chapter 7

The road to wealth accounting
PART II•
Chapter 6

Natural capital as economic assets:a review••

In calculating total wealth, depleting a typeof natural capital and substituting it withanother form of natural capital or with
manufactured capital is frequently uneconomical in most countries. The assumptionof absolute substitutability is not a realistic
one.
Externalities are the effects of activities
on the well-being of people who have notbeen parties to the negotiations that led tothose activities. An example is the impact

Executive Summary••

It is clear that human activity has had a profound effect on our environment, and thatthese effects, in turn, have had an impact onhuman well-being. While the importanceof this relationship is appreciated, there arestill few reliable indicators of the value topeople of biosphere change.
The Millennium Ecosystem Assessment
was able to quantify the physical changes inecosystem services that had occurred in theprevious half century, but it was unable toassign a value to the loss of non-marketed
ecosystem services.
This chapter considers the issues involved
in developing metrics of the social importance of biosphere change. What is needed
is a measure of the impact of biospherechange on wealth and wealth distribution.
xxv

•

•

•

•

The chapter discusses the welfare-theoretic
foundations of wealth accounting, and thesteps taken so far to build wealth accounts.
It then considers what is required to evolve
wealth accounts from the current system ofnational accounts (SNA).
The SNA provides an incomplete picture of
wealth because it includes only property
that generates private claims to future benefits. It therefore excludes parts of natural
capital that is essential to human well-being
but cannot be privately held (e.g., the atmosphere or the open oceans).
Two major efforts to advance our understanding of wealth are discussed here: theWorld Bank’s idea of adjusted net savings,
and the System of Environmental andEconomic Accounts (SEEA). Both are important steps on the road to wealth accounting,but neither fully address the issues of whatenvironmental stocks should be included,
and how they should be measured andvalued (the double counting caused by the
SEEA’s inclusion of ecosystems is particularly
problematic).
Ultimately, country wealth measurements
should include all natural assets that areunder a country’s jurisdiction and that contribute to human well-being, whether thoseassets are privately owned or not.
More work is still required on understanding and measuring the relationship amongassets, environmental externalities, andpoverty in an effort to advance human wellbeing.

Chapter 8

•

•

•

•

•

Chapter 9

Inclusive wealth accounting for
regulating ecosystem services•

Ecosystem services and wealth accounting•

xxvi

Ecosystems should be treated as an important asset in an economy and, in principle,
ecosystem services should be valued ina similar manner as any other form ofwealth. Quantifying these services is very
challenging.

The purpose of this chapter is to review
progress in economics and ecology in assessing ecosystem services and their values, andto discuss the resulting implications forincluding such services in a wealth accounting framework.
Understanding the relationship between
ecosystems, their structure and functions,and the ecological services they generate is
essential to determining how the structureand functions of an ecosystem provide valuable goods and services to humans.
Since the purpose of new investment is toincrease the quantity and quality of theeconomy’s total capital stock, or wealth,adjusting gross domestic product (GDP) for
depreciation in this stock would measure
more accurately whether net additions tocapital are occurring.
If net domestic product (NDP) is to serve as atrue measure of the changes in an economy’s
wealth, it must include any appreciation or
depreciation to human and natural capitalas well.
The approach developed here requires, first,
recognizing ecosystems as a component of
natural capital, or ecological capital; andsecond, measuring these important assets
in terms of the land area, or ecological landscape, which defines their boundaries.

•

Studies that have sought to value natural
capital have typically focused on “provisioning” services or natural resource stocks suchas oil and natural gas, minerals, timber, andfisheries. Other than the cost of CO2 emissions vis-à-vis climate regulation, regulating
services have not been considered in any
great depth.
An important first step for including regulating services in an inclusive wealth framework
is to have well-defined individual services.
Inclusive Wealth Report

•

•

•

The present typology of regulating services
does not lend itself well to wealth accounts
because multiple services are embedded
within common regulating service category.
Identifying individual services also simplifies the valuation process.
It is important to identify servicesheds inorder to estimate the value of ecosystem services. A serviceshed is the area that provides
a specific benefit to a specific individual orgroup of people. It is further characterized
by three factors: (1) ecosystem supply; (2)institutions; and (3) physical access.
Due to the high degree of uncertainty inestimating the value of regulating services,it will be useful for policy-makers to see a
range of values with lower and upper boundestimates. We provide such uncertainty
analyses for climate regulation through carbon sequestration.
The marginal net benefit of regulating services is large enough to justify undertaking
future research in identifying servicesheds,
unbundling regulatory services into explicit
benefits, and producing value estimates forinclusion in wealth accounts.

•

The UN’s System of EnvironmentalEconomic Accounting for Water (SEEAW) is
an important step forward in understanding the flows and stocks of water. The flows
comprise abstraction, consumption, andreturn flows; the stocks, which are harder toassess, look at groundwater resources, lakes,
snowpack, and the like.
• SEEAW has important strengths. It is multisectoral; it clearly distinguishes between
consumptive and non-consumptive uses ofwater; it is hydrologically consistent withthe law of conservation of mass; and it canbe applied at various scales (project, sector,
region, country, and basin).
• While SEEAW has been promoted for a few
years, Australia is the only country for which
detailed implementation plans and progress
seem to be available. The process has been
lengthy and detailed and has resulted inmany reports, reviews, and studies.
• SEEAW accounts should be expanded toinclude the “unmanaged” natural landscape;“managed” areas; and rainfed agriculture.
Chapter 11

Safeguarding the future of thewealth of nature: sustainability, substitutability, measurement,
Accounting for water: stocks, flows,
thresholds, and aggregation issues
and values
in natural capital accounting for hu• As water becomes increasingly scarce, as sec- man well-being
Chapter 10•

toral competition for water intensifies, andas humanity increasingly interferes withnature’s hydrological cycle, the need to measure and value water flows and stocks has
increased.
Such evaluation must proceed in two discrete steps: first, the construction of physicalwater accounts, designed to figure out how
much water there is, where it is, when it isavailable, how accessible it is, and with what
reliability; and second, when the accounts
are in place, the analysis can proceed towards
placing a value on these resources.

Executive Summary••

Nature is very different from human, social,
and manufactured capital stocks in that it
predates humanity and it operates throughits own complex laws and systems.
Most accounting for natural capital involves
assigning monetary values to the flows
of benefits from that capital. A monetarymeasure suggests that one capital stock canbe substituted for another when trying tomeasure a country’s total wealth in a multicapital model. For natural capital, there
is an emerging body of opinion that such
substitutability is not complete, therefore
xxvii

•

•

•

xxviiiaccounting for it in this way could be seriously misleading.
The assumption of more or less complete
substitutability between natural capital andother capital stocks is sometimes referred
to as the “weak sustainability” assumption;
while an assumption of limited substitutability is termed the “strong sustainability”
assumption.
The assumption of strong sustainability
in respect of certain important aspects ofnatural capital would seem more consistent
with the scientific evidence. Starting withthis assumption when trying to understandthe interactions between different forms ofcapital allows substitutability to be considered to the extent appropriate. Starting withan assumption of complete substitutability(the weak sustainability perspective), andproceeding directly to monetary valuation,
tends to obscure those situations where thisassumption is not valid.
While consumption is important to wellbeing, it is also affected by a number of othercrucial factors. The contribution of natural
capital to well-being has not been widely
recognized in the literature, but that has
started to change in recent years as diverse
contributions have been revealed throughecosystem assessments.

Inclusive Wealth ReportOverall lessons,findings, andrecommendations
Lessons learned
A number of key lessons emerge from this firstreport, including: 1. substitutions among thedifferent capital assets vary and in many cases
become uneconomical; 2. the importance of notjust one capital but the emphasis on a basket ofinter-dependent capital assets; 3. population
changes and their impact on the returns to anation’s productive base; 4. interconnected
externalities that accrue, particularly from thedegradation and decline of the natural capitalbase; and 5. estimation of shadow prices, which
are so critical in computing the inclusive wealthof a country. These are elaborated upon in theConclusion.

Key findings
Key finding 1

70 percent of countries assessed in the 2012
Inclusive Wealth Report present a positive
Inclusive Wealth Index (IWI) per capita growth,
indicating sustainability.

Key finding 5

There are clear signs of trade-off effects among
different forms of capital (manufactured, human,and natural capital) as witnessed by increases
and declines of capital stocks for 20 countries
over 19 years.
Key finding 6

Technological innovation and/or oil capitalgains outweigh declines in natural capital anddamages from climate change, moving a number of countries from an unsustainable to a sustainable trajectory.
Key finding 7

25 percent of assessed countries, which showed
a positive trend when measured by GDP per
capita and the HDI, were found to have a negative IWI.
Key finding 8

The primary driver of the difference in performance was the decline in natural capital.
Key finding 9

Estimates of inclusive wealth can be improved
significantly with better data on the stocks ofnatural, human, and social capital and their values for human well-being.

Key finding 2

High population growth with respect to IWI
growth rates caused 25 percent of countries
assessed to become unsustainable.
Key finding 3

While 19 out of the 20 countries experienced adecline in natural capital, six of them also saw adecline in their inclusive wealth, thus following
an unsustainable track.
Key finding 4

Human capital has increased in every country,
being the prime capital form that offsets thedecline in natural capital in most economies.
Executive Summaryxxix

Recommendations
Inclusive wealth offers policy-makers a comprehensive accounting tool for measuring the assets
available in the economy. The understandingof such asset portfolios and their changes overtime has important implications for sustaining
the consumption needs of present and future
generations.
Recommendation 1

Countries witnessing diminishing returns
in their natural capital should build up theirinvestments in renewable natural capital toincrease their inclusive wealth and the wellbeing of their citizens.
Recommendation 2Countries should mainstream the Inclusive
Wealth Index within their planning and development ministries so that projects and activities are evaluated based on a balanced portfolio
approach that includes natural, human, andmanufactured capital.
Recommendation 3Countries should support/speed up the process
of moving from an income-based accounting
framework to a wealth accounting framework.
Recommendation 4

Governments should move away from GDP per
capita and instead evaluate their macroeconomic policies – such as fiscal and monetary
policies – based on their contribution to the IWIof the country.
Recommendation 5

Governments and international organizations
should establish research programs for valuing
key components of natural capital, particularly
ecosystem services.
The conclusion to the IWR elaborates upon
the findings and recommendations identified
here, and discusses the prospects for future for
future work on inclusive wealth.

xxx

Inclusive Wealth ReportIntroduction

Inclusive wealth:an overview

This is the first of a series of biennial reports on the sustainabilityof countries. The report looks at the productive base of economies, based on capital assets – produced or manufactured capital;
human capital; social capital; and natural capital. This first reportof the series is focused on natural capital and will be released atthe 2012 Earth Summit (Rio+20) to be held in Rio de Janeiro, Brazil,
in June 2012. The two main themes of the Rio+20 summit will be
the green economy and international environmental governance.
The report of the United Nations Secretary-General’s High-level
Panel report on Global Sustainability – Resilient People, Resilient
Planet: A future worth choosing – was released in April of 2012 to
inform the discussions and negotiations at the Rio+20 summit.
The report highlights the potential of a green economy and also
calls for new ways of measuring progress in a green economy.
This report provides such a measure.
The IWR is a joint collaboration of the United Nations
University International Human Dimensions Programme (UNUIHDP) and the United Nations Environment Programme (UNEP).
The group of authors for the report was selected based on theirexpertise in inclusive wealth and environmental economics, andan extensive publication record in the area of natural capital,
human well-being, social welfare, and valuation, among others. A review process was also established and each chapter was
1reviewed by a minimum of two external referees using standard
academic criteria. The reviewers were chosen again based on theirexpertise in the field, strong academic credentials, and a good
publishing record in the relevant fields covered by this report.

Context

The primary objective of the

The congruence of economic, social, andenvironmental crises over the past decade has
Inclusive Wealth Report is to proproforced political, business, and civil society leadvide quantitative information and ers – as well as the general public – to question
whether our present model of fostering humananalysis that present a long-termwell-being is sustainable or even ideologicallyperspective on human well-being correct. The focus on material wealth as the key
constituent of well-being and economic growthand measures of sustainability.
– and the only way to understand prosperity – isbeing increasingly questioned. We have forced
ourselves to believe that we can grow ourselves out of the multiple crises we face today. There is no doubt economic growthis an important determinant of well-being. But it is not the only
determinant and not should not be seen as an end in and of itself,
but simply as one of many means to improving human well-being.
Social and ecological factors are also important determinants ofwell-being, and in some cases, are direct constituents of well-being(MA 2005; Dasgupta 2001; Stiglitz et al. 2010). Examples are
education, health, clean air and water, and spiritually significant
ecological landscapes, among others. These things not only help
us achieve well-being, they are elements of well-being in and ofthemselves.
In addition to broadening the measurement of well-being,
there is also the issue of addressing the well-being of future generations. Some would say that focusing only on the present generation’s pursuit of well-being – however defined – is unethical.
The exact composition of the well-being of future generations ishard to determine as we have little idea of what the aspirations
and desires of future generations will look like. But that does
not exempt us from leaving a productive base from which thesefuture generations can determine the type of lives they would
value and pursue.
This report begins the unpacking of the various constituentsand determinants of well-being and explores the productive
base a country needs to ensure well-being is maintained and/or improved for future generations. The report provides suchan analysis for a group of 20 countries selected for their varietyof geographical, social, economic, and ecological characteristics.
The results reported should be seen as an exploratory exercise
2

Inclusive Wealth Reportinto the empirical estimations of many capital assets that do nothave market prices – and in fact exist outside of the market – butare still critical for the maintenance and improvement of wellbeing.

What we measure and what we manage
Traditional indicators such as gross domes- The flagship development reports
tic product (GDP) per capita and the Humanof the international institutions
Development Index (HDI) have been the main
determinants used to measure the progress of share a common weakness whennations. GDP per capita was developed just after
it comes to measuring social
World War II by economist Simon Kuznets. It
was constructed by Kuznets to measure the progress: they are all focusedlevel of economic production and to provide
on current, short-run measures
guidance to policy-makers on which sectors of
the economy are growing and which are slow- with little or no considerationing, and the throughput that is used by theof the natural capital base of an
economy. It was, therefore, always meant to
be used strictly as an indicator for economic economy.
production. But somewhere along the line, GDPcame to be used by policy-makers to measure the overall progress
and performance of a nation, and that implied the well-being of
its citizens. This caused some fundamental problems, not with
the indicator itself, but with the way it has been used. Increases
in total economic production do not translate into improvements in well-being. They might increase employment and might
increase the income of individuals, but all these are just possible
outcomes and not automatic consequences of economic growth.
In an attempt to broaden the perspective of well-being beyond
economic growth and income, the Human Development Index(HDI) was developed. The HDI added literacy and mortality to theequation of income. Although an improvement over just using
income to measure well-being, it has a number of internal inconsistencies that make it problematic to use to determine whether
the well-being of a country’s citizens has really improved or not.
We shall not go into details of these inconsistencies, as that is not
the main purpose of this report. Readers can refer to Sagar andNajam (1998) and others for a detailed discussion of the shortcomings of the HDI.
Putting aside the breadth of coverage of well-being and methodological issues, neither GDP nor the HDI reflect the state of thenatural environment and both focus on the short-term, with noindication of whether current well-being can be sustained. The
flagship development reports of the international institutions(the Human Development Report of UNDP; the World Economic
Introduction and Overview

3Outlook of the IMF; and the World Development Report of theWorld Bank) share a common weakness when it comes to measuring social progress: they are all focused on current, short-run
measures with little or no consideration of the natural capitalbase of an economy.
There have been recent advances in addressing the weaknesses in contemporary measures of welfare that are used tojudge the progress of nations. The World Bank’s Where is the
Wealth of Nations? (2006) and the more recent, The Changing
Wealth of Nations (2010) are two such initiatives. Using a welfare framework as the basis of computing the comprehensive
wealth of an economy, these reports provide for the first time an
accounting of the use of the natural capital base. However, there
are some strong assumptions behind the underlying model thatmight weaken its usefulness as a measure of sustainability. Someof these are discussed further in Chapter 1.
The main message is that important elements of a wealthreport do already exist, but there are significant gaps where
research and analysis will be required to increase the depth andbreadth of the wealth estimates. This report draws on the WorldBank measures of comprehensive wealth but goes beyond themby revising the theoretical framework and the methodology ofcomputing the various capital asset bases. These are clearly elaborated in the data and methodological annexes presented at theend of this report.

What we need to manage and what we need to measure
The call for going beyond material wealth to gauge our well-being
and make sure that well-being is achievable and sustainable for
future generations has long appeared in much of the sustainable
development, environmental, and ecological economics literature, significantly less in economics and development literature.
The present pre-occupation with the Green Economy, we fear,
will not provide the change we seek if we do not address the fundamental problem of what precisely we are measuring and theindicators we need to develop.
The concept of, if not the actual term, “sustainable development” has been around for centuries, but the most recent modernday expression can be traced back to 1983 (Duraiappah 2003). In
1983, then Secretary-General of the United Nations, Javier Pérez
de Cuellar, appointed Gro Harlem Brundtland from Norway tohead a special commission to address the rapid deterioration of
the human and ecological environments. The resolution establishing the commission by the General Assembly in A/RES/38/161
in 1983 stipulates the following terms of reference:
4

Inclusive Wealth Report(a) To propose long-term environmental strategies for achieving sustainable development to the year 2000 and beyond;(b) To recommend ways in which concern for the environment may be translated into greater co-operation among developing countries and between countries at different stages of economic and social development and lead to the achievement ofcommon and mutually supportive objectives which take accountof the interrelationships between people, resources, environment and development;(c) To consider ways and means by which the international
community can deal more effectively with environmental concerns, in the light of the other recommendations in its report;(d) To help define shared perceptions of long-term environmental issues and of the appropriate efforts needed to deal
successfully with the problems of protecting and enhancing theenvironment, a long-term agenda for action during the coming
decades, and aspirational goals for the world community.

In 1987, the commission published Our Common Future. The
report emphasized the notion of sustainable development anddefined it as “development that meets the needs of the present
without compromising the needs of future generations to meettheir own needs” (World Commission on Environment andDevelopment 1987). Although the terms of reference given to
the Commission might, at first sight, seem to have been narrowly confined to the environment, the Commission’s members
had the foresight to understand the importance of addressingthese issues within an integrated framework bringing together
the social, economic, and environmental spheres to address thenotion of sustainability. At the end of the day, it is the welfareof humans about which we are concerned, not just the present
generation but future generations as well.
The Commission called for a new era of economic growththat was socially and environmentally sustainable. The report
did an excellent job of informing us of the state of the planet,emphasizing the need for urgent action, and advising on what
needed to be done and where action was required both acrossregions as well as in key focus areas. But the report fell short onproviding guidance on how to quantify progress in a way that
could provide support to policy-makers in considering interventions and responses. The call for a new era of economic growth
without any suggestion for new metrics for evaluating progressleft countries with little choice but to continue using GDP to trackprogress.
The situation has changed in the follow-up to Rio+20. The
report of the High-Level Panel Global Sustainability of the UN
Secretary-General, Resilient People, Resilient Planet: A future worthchoosing, as emphasized earlier, calls for not just a new form ofIntroduction and Overview

5economic growth that works within ecological boundaries whilepursuing social equity, but also for new measures to track progress. And it calls explicitly for going beyond our present generation of indicators, such as GDP and the HDI. This report provides
such a metric and presents the strengths of the inclusive wealthmeasure but also its weaknesses and ways to improve the measure over time.

The inclusive wealth framework
The inclusive wealth framework proposed in this report is a theoretical framework based on social welfare theory to consider themultiple issues that sustainable development attempts to address.
First, the inclusive wealth framework moves away from the arbitrary notion of needs and redefines the objective of sustainable
development as a discounted flow of utility which, in this case,is consumption. The framework is flexible enough to allow consumption to include not just material goods, but also elements
such as leisure, spiritual aspirations, social relations, and environmental security, among others.
The elegance of the inclusive wealth framework comes fromthe equivalence theorem whereby the framework allows themove from the constituents of well-being to their determinants.
In this case, we refer to the various capital assets a country is able
to accumulate. This asset base is called the productive base of
the nation. The productive base forms the basis for sustainable
development and provides a tangible measure for governments
to use and track over time. But, more importantly, the framework provides information for policy-makers – particularly planning authorities – on which forms of capital investment should
be made for ensuring the sustainability of the productive base ofan economy.

The IWR 2012: natural capital
The report will be produced every two years. Each edition will
focus on a specific thematic area. In the case of this first report,
the focus is on natural capital and, in particular, “ecosystem services.” The concept of ecosystem services is relatively new andthere is a significant gap between using the term ecosystem services and accounting for these services within wealth accounts.
It was therefore felt that a first report focusing on natural capital and ecosystem services would serve to highlight the importance of natural capital, but also illustrate the work required toensure a near complete accounting of this critical capital for the6

Inclusive Wealth Reportproductive base of an economy – a task that has been ignored bymost planning strategies and tools. The IWR series will progressively increase the coverage of asset values over time, particularly
with respect to ecosystem assets (and their associated services) as
well as the impacts of climate change and other environmental
impacts on these assets. Underpinning this progressive increasein coverage will be a research program on theseand wider topics in asset accounting.

The framework emphasizes not

Audience and structure of report

only the importance of maintainmaintaining any one particular asset base,

The primary audience of the Inclusive Wealthbut also of maintaining the total
Report will be governments. More broadly, thereport will be of use to development practitio- capital asset base.
ners as well as researchers and the wider development community. The inclusion of environmental damage
in the accounts – as well as damages from global environmental change such as climate change – can be useful in determining cross-country compensations and a guide for international
negotiations on the consideration of transboundary assets. The
report will also be useful for national economic planning agencies when considering macroeconomic fiscal policies. Changes
in the various capital assets and their contribution towards theinclusive wealth of a country can provide information on where
future investments should be targeted to get the best returns forincreasing the productive base of the country.
The report is presented in two parts. Part I introduces theconcept of inclusive wealth and provides the first results for aset of 20 countries used as a pilot in the 2012 report. This section of the report has a total of five chapters. In Chapter 1, theconcept of sustainable development is revisited and the redefinition of sustainable development and sustainability from needs
to well-being is presented. This chapter also provides the theoretical framework wherein the link with well-being and wealthis made through a welfare theoretic conceptual framework. In
this chapter, the notion of the productive base of an economy,
the foundation for this productive base, and the maintenance ofwell-being are developed and introduced. The chapter also lays
down the necessary definitions and equations to make the linkwith well-being and the different forms of capital that constitute the productive base of the economy and the role of shadow
prices. Some of the key differences between the wealth accounts
presented in this report and the wealth accounts developed by
the World Bank are also discussed in Chapter 1. The final sectionof the chapter presents the key assumptions and caveats underlying the inclusive wealth framework.
Introduction and Overview

7

Chapter 2 presents the empirical computations of wealthacross 20 countries for the period of 1990–2008. The countries
were chosen in a manner to distinguish differences in stages ofdevelopment, natural resource bases, population dynamics, andgeographical locations. It is hoped that this list will be expanded
in future reports. Particular attention is paid to the changes ininclusive wealth and the respective changes across human, natural, and produced capita. Comparisons to GDP are made for all
countries to provide a comparative analysis between the inclusive
wealth and GDP accounts. A key component of this chapter is thedifferences between absolute changes in inclusive wealth and therespective capital asset bases with changes on a per capita basis
to demonstrate the role population growth plays in sustainability.
This chapter also provides some key policy guidance on where tofocus investments in order to improve the inclusive wealth of acountry. Chapter 3 follows with a more detailed analysis of thenatural capital accounts. The drawdown or build-up of the various assets within natural capital are analyzed, paying particularattention to forests and their role in the decline or increase ofnatural capital. Chapter 4 provides a more detailed analysis of
the wealth accounts of the United States of America and provides some key insights on how inclusive wealth accounts can beused at a sub-national level. Chapter 5 follows with an overview
of how trade influences wealth accounts and provides some preliminary findings on the dynamic role trade plays in determining
the inclusive wealth of nations.
In Part II of this report, we present some of the key lessons
learned on developing ecosystem services accounts and the challenges faced when attempting to value the changes in the capital stocks over time. Chapter 6 provides an overview of the role
natural capital plays within wealth accounts and sets the foundations of computing the value of natural capital. The chapter
discusses ecosystem services and the various ways shadow prices
can be computed for the various components of natural capital.
Chapter 7 makes the distinction between flows and stocks andtheir relevance to wealth accounts. In this chapter, the relevanceof the system of environmental accounts and the way ecosystemservices can be reflected in these accounts are discussed. The
primary objective of this chapter is to lay the groundwork for
future work in national accounts in order to capture the value of
ecosystem services. In Chapter 8, a more detailed description ofvaluing non-market ecosystem services is discussed. The use of
ecological production functions is expanded and the complexities of these functions are explored.
The next two chapters focus on regulating ecosystem services. Chapter 9 provides an overview of the three regulating
services of soil erosion control, water purification, and carbon
8

Inclusive Wealth Reportsequestration. Tools used to value these services such as InVEST
are described and some examples of valuation of these services
using these tools is provided. Chapter 10 provides an overview
of water services and describes the complexities of accountingchanges in water-related ecosystem services. The focus in thischapter is on the physical accounts and leaves the valuation ofthese stocks as a research question for future studies.
Chapter 11 completes part two of the report by highlightingsome of the issues relating to substitutability among the various
categories of capital and discusses the notion of strong and weak
substitutability. The chapter goes on to provide some information on ecological thresholds and the complexities of deriving
tipping points in both the social and ecological spheres expanding on issues discussed in Box 1 in Chapter 1. The chapter provides a discussion on the unique characteristics of natural capitaland the complexities of using the inclusive wealth accounting
framework from an empirical perspective.
The reader is encouraged to review the data and methodological annexed at the end of the report to get a more detailed
discussion of the methods used to get the results presented in
Chapters 2 and 3 of Part I.
The report ends with a concluding chapter, in which key lessons, findings, and recommendations are offered. In addition, abrief description of the next report is presented.

References
Dasgupta, P. (2001). Human well-being and the natural environment. Oxford:
Oxford University Press.
Duraiappah, A.K. (2003). Computational models in the economics of environmentand development. Dordrecht, Holland: Kluwer Academic Publishers.
Millennium Ecosystem Assessment (MA). (2005). Ecosystems and human wellbeing: Synthesis. Washington, DC: Island Press.
Sagar, A. & Najam, A. 1998. The human development index: A critical review.
Ecological Economics, 25(3), 249-264.
Stiglitz, J.E., Sen, A. & Fitoussi, J.P. (2010). Mismeasuring our lives: Why GDP
doesn’t add up. New York: The New Press.
United Nations General Assembly. (1983). Resolutions adopted by the general assembly at its 38th session. Retrieved from http://www.un.org/depts/dhl/resguide/
r38.htm
World Bank. (2006). Where is the wealth of nations? Washington, DC: WorldBank.
World Bank. (2011). The changing wealth of nations: Measuring sustainable development in the new millennium. Washington, DC: World Bank.
World Commission on Environment and Development. (1987). Our common
future. New York: Oxford University Press.

Introduction and Overview

9Part I

PART I Wealth Accounts

11

12

Inclusive Wealth ReportChapter 1

Well-being and wealthPartha Dasgupta and Anantha Duraiappah

Key Messages
The true achievement of sustainable
development must focus on human well-being.
When we talk about human well-being, wecannot only talk about today. The definition ofhuman well-being – and, indeed, our efforts toachieve it – must entail the well-being of future
generations.
Studies on sustainable development performance evaluate societal change over time.
To be complete, these studies must effectively
evaluate a society’s productive base.

Wealth is the social worth of an economy’s
assets: reproducible capital; human capital;
knowledge; natural capital; population; institutions; and time.
Shadow prices are key to understanding
inclusive wealth. The shadow price for manymarket-traded goods is the market price, butthese should be used with caution as many
prices do not take account of externalities.

131. Introduction
Economic development is customarily evaluated in terms of its contribution to human wellbeing. Well-being should not just be considered
for people living today, but for future populations as well. This inter-generational perspective on well-being is essential and is intended
in this chapter with the use of the term “wellbeing.” The term refers to today and tomorrow.
Economic development is evaluated fortwo purposes: prescribing and assessing. The
purpose of policy evaluation, including project
evaluation, is to arrive at policy prescriptions –for example, when a government project evaluator carries out a study to determine whether awetland should be drained to build a housing
estate. The idea is to evaluate a society at a point
in time before and after a hypothetical change(the policy change) has been made. In principle,
policy evaluation, including project evaluation,
can be used to identify optimum development,
which is a development path a society would
ideally wish to follow.
In contrast, the literature on sustainable
development studies ways to assess an economy’s performance. That literature has grown in
response to the realization that the development
process of nations and regions has been accompanied by deterioration of a number of key environmental characteristics. Sustainability analysis
is about evaluating societal change over time.
We will call the person doing the evaluation
the social evaluator. The social evaluator could
be a citizen (thinking about things before casting his or her vote on political candidates); he or
she could be an ethicist hired to offer guidance
to the government; she or he could be a government decision-maker, and so on. In what follows,modern convention is adopted by replacing the“social evaluator” with “society.”
Although the idea of optimum development
dominated development economics from the
1950s through the 1970s (Chakravatery 1969;
Little and Mirrlees 1968, 1974), interest has
shifted in recent years to the notion of sustainable development. The literature on the14

latter subject is now vast. The theory underlying the concept was presented by Hamilton andClemens (1999) and Dasgupta and Mäler (2000),
and reviewed with extensions by Dasgupta(2001 [2004], 2009). Empirical studies onwhether in recent decades economic development has been sustainable in various countries
have been conducted by Hamilton and Clemens(1999), Dasgupta (2001 [2004]), Arrow et al.
(2004), World Bank (2006, 2010), and Arrow etal. (2010).
The literature on sustainable development
grew in response to the concern that humanity’s
use of environmental natural resources is nottaken adequately into account in economic decisions. But writings on what one may call “natural
capital” are scattered in journals and books. This
chapter offers an organized view of how environmental natural resources can be introduced
seamlessly into sustainability analysis and contains an account of the way natural capital should
be included in the calculations that are necessary
for studies of sustainable development.

2. The idea of sustainable development
In their pioneering work, World Commission
on Environment and Development (1987: 70)
defined sustainable development as “... development that meets the needs of the present without compromising the ability of future generations to meet their own needs.”
What should we make of it?
Notice that the definition makes no specificreference to human well-being. Similarly, it
makes relatively weak demands about justiceamong the generations. In the Commission’sview, sustainable development requires that
future generations have no less of the means
to meet their needs than we do ourselves; it
requires nothing more. As needs are the austerecomponent of well-being, societal development
could be sustainable in the Commission’s sense
without having much to show for it.
Notice also that the Commission’s definition
is directed at sustaining the factors that satisfy
Inclusive Wealth ReportHuman well-being(individual and community)

Earth system processes,
ecological systems& services

Consumption

Human capitalSocial capital
Manufactured capital(positive and negative)
Limited substitutability
between capital forms determined by shadow prices

Natural capital

Economic
production
processes

WastesGoods & services

Evolving
cultural norms& policy

Investments

Figure 1

The productive base and human well-being

needs (food, clothing, shelter, personal relationships, leisure activities). But those factors would
be available only if the society in question had
an adequate productive base to produce them.
So, in the Commission’s view, sustainable development requires that relative to their populations, each generation should bequeath to its
successor at least as large a quantity of what
may be called a society’s productive base as it
had itself inherited from its predecessor. That
raises another problem with the Commission’s
reasoning: it doesn’t explain how the productive base should be measured.
The requirement that an object should besustained over a period of time means that itshouldn’t diminish over the period. In accordance with the recent literature on sustainable
development, we have
Definition 1. By sustainable development wemean a pattern of societal development along
which (inter-generational) well-being does
not decline.

A comparison of Definition 1 with that of
the Brundtland Commission suggests therefore
CHAPTER 1 Wealth and Well-Beingthat we should seek an aggregate measure of asociety’s productive base with the property thatit moves through time in the same manner as
does well-being. In other words, we should seeka measure of a society’s productive base that
increases during any specified period of time if
and only if well-being in that society increases
during that same period of time.

3. Capital assets
It is intuitive that the elements comprising asociety’s productive base are not only the capital assets to which people there have access, butalso the social infrastructure that influences theway those assets are put to work for human use,
now and in the future as illustrated in Figure
1. The conceptual framework we use for thereport begins with human well-being as theend. Well-being is to a large extent governed by
the evolving cultural norms and policy which
in turn influence the way societies use the different forms of capital assets. The capital asset
15

base is, according to the conceptual framework,
the foundation for the economic production
process which then goes on to produce thegoods and services which feed back into thenorms and policy before influencing well-being.
Ecosystems are critical in supplying the natural
capital asset base. The drawdown of natural
capital, subsequently impacting the way ecosystems are used, is heavily influenced by the evolving cultural norms and policy. The way the different capital assets are used is determined, to alarge extent, by the shadow prices of the various
capital assets and their respective components.
The foundational base for the economic production system is therefore the different formof capitals and their respective shadow prices
governing their use. It therefore makes sensethen to invoke a broad notion of assets. We dothat here and discover that the list includes atleast two categories of assets whose appearance
could seem quixotic. Several categories, however, are familiar.

3.1 Familiar assets
They include:(1) Reproducible or also called manufactured
capital or produced capital in this report (roads,
buildings, ports, machinery, equipment). In common parlance, including national accounts, thiscategory pretty much exhausts the list of capital
assets. When national income accountants andinternational organizations speak of investment, they usually mean the accumulation of
reproducible capital.1 Reproducible capital isfrequently called “manufactured capital.”(2) Human capital (education, skills, tacitknowledge, health). This category is embodied inpeople. As teachers are painfully aware, humancapital is not transferable without cost from one
person to another. Education, skills, and healthare ends as well as means. They have intrinsic
1 See, for example, the Tables on National
Investment at the end of the World Bank’s annual
World Development Report.

16

worth, but are also of indirect value (investment
in human capital raises a person’s productivity).
(3) Knowledge (science and technology). This
category includes such items as nature’s laws,
abstract theorems, formulae, and algorithms.
Once discovered, they are in principle there forall to use. But for someone to be able to apply
knowledge, three conditions must be met: (i) arecognition by that person that the knowledge
exists; (ii) the person should have the relevant
skills (human capital!); and (iii) there should be
no legal or social barrier to applying the knowledge. What one should broadly call “researchand development,” or R&D, are the investments
required to advance codified knowledge, unlessof course that knowledge can be obtained freely
from external sources.
(4) Natural capital (local ecosystems, biomes,
sub-soil resources). Today it has become commonplace that nature should enter explicitly ineconomic calculations. But because nature has
been neglected for so long in the literature onsocial and economic development, natural capital is the focus of this report.
(5) Population (size and demographic profile).
Conceptually, this category raises the deepest
problems; in as much as people are both thereason well-being should occupy the core ofsustainability analysis and the means to therealization of well-being.

3.2 Institutional capitalCategories (1)–(5) are not exhaustive. Today it
is not uncommon for people to refer to “religious capital,” “social capital,” “cultural capital,”and, more broadly, “institutional capital” whentrying to understand the progress or regressof societies. So, we have a further category ofassets to consider:(6) Institutions. By “institutions” we mean the
myriad of formal and informal arrangements
among people (the rule of law, social normsof behavior, habitual social practices) that
influence the allocation of resources both at a
moment in time and over time. Institutions are
Inclusive Wealth Report

“enabling” assets. Access to institutions shouldbe (i) non-rivalrous in character and should be(ii) freely open to all. Institutions are often seen
as public goods.
How do institutions enter sustainability analysis? They do so by influencing the value of othercapital assets. Suppose the state apparatus in acountry is corrupt, implying that the judicial system is unreliable. Because people find it difficult
to protect their property rights, the value of theircapital assets is small, other things being equal.
Corruption reduces the social worth of assets.2
Institutions influence the composition of
consumption and saving and the character of
future institutions. There are institutions that
foster progress by having in place a structureof incentives that encourage people to allocate
goods and services in their most productive
uses. But institutions aren’t enough. If they
are to progress, people must trust one anotherand have confidence in their institutions. Welldeveloped competitive markets, tight social
norms and codes of conduct, and good governance together can help create and maintain
trust and confidence. But mutual trust andthe cooperation that can result from it cannot
be guaranteed even, under sound institutions.
Opportunistic behavior can beget opportunistic
behavior. Institutions can break down under acascade of opportunism unless there are checks
and balances in place.3
In contrast, there are institutions that area hindrance from the start. Under weak, misguided, or corrupt governance, goods andservices end up in unproductive (even wrong)places. When vested interests govern social
decisions, neither efficiency nor more generally justice gets much of a look-in. A society’s
capacity to flourish shrinks when its institutions deteriorate (owing to civil wars, ethnic

2 No doubt the purpose of corrupt practice could beto enhance the market worth of assets owned by thepractitioner. In the text we are referring to the social
worth of assets.
3 On the role of trust in sustainable development,
see Dasgupta (2011).

CHAPTER 1 Wealth and Well-Being

strife, increased corruption) and its other assets
don’t accumulate sufficiently to compensate forthat deterioration. Likewise, a society’s capacity
to flourish shrinks when its material assets (e.g.,natural capital) depreciate and its institutions
aren’t able to improve sufficiently to compensate for that depreciation or turn behavior sothat the assets begin to accumulate.

3.3 Time as an asset
We haven’t quite yet covered the myriad ofassets that comprise a society’s productive base.
Consider a small oil-exporting country. Beingsmall, the country has no control over international oil prices. Meanwhile, or so let us imagine, an oil cartel, of which our country is not amember, raises the price of oil on a continual
basis. Our country therefore enjoys capitalgains on its reserves without having to engage
in any form of capital accumulation. Its productive base expands.4 Similarly, it could be that thecountry enjoys an expansion of its knowledge
base by deploying scientific advances elsewhere
without having to pay for that privilege. In both
circumstances our country enjoys an expansionof its productive base simply by waiting. Thattells us we should include time in a society’s
productive base.
The suggestion could seem perverse. We
usually regard a commodity to be an asset
only if it is durable, whereas time is fleeting.
Moreover, unlike assets in categories (1)–(6),which can be accumulated or decumulated atwill, time moves at a constant pace, namely,
the pace it has set itself. But classifications aremeant to serve a purpose, they are not cast iniron in some Platonic universe. A chief aim ofsustainability analysis is to construct a measureof a society’s productive base that can be used
to judge whether it is pursuing a sustainable

4 The same logic says that, other things being equal,an oil-importing country would find its productive
base to shrink as the international price of oil rose over
time.

17

development path. If that aim can only beachieved if we include time in the society’s productive base, we should regard it as an asset. So
we now have one further capital asset on ourlist, namely,(7) Time!

4. The social value of capital assets:shadow prices
Goods and services are of value because they
contribute to human well-being. What are thecontents of a person’s well-being? Here we notethat they include the engagements that areopen to a person; and that those in turn centre
on the person’s relationships with others, theconsumption of goods and services involving
herself and those to whom she relates, and her
ability to meet her obligations to others, andto pursue her projects, purposes, and the many
mundane things that define her life.5 Many of
those engagements we care about directly, others are of indirect value to us. That said, every
engagement requires goods and services ifthey are to be carried out. It follows that in its
reduced form, individual well-being, and therefore human well-being, is a function of the consumption and use of goods and services.
Capital assets in categories (1)–(6) are themeans by which consumption goods and services are produced. Several are ends as well(health, education). At any given date, (intergenerational) well-being is determined by (a)the assets a society has inherited from the past,(b) the society’s subsequent development (which
in turn will be shaped by that inheritance), and(c) chance.
We consider the role of chance in sustainability analysis in Box 1. Here we focus on (a) and (b).
Excepting for time, assets are durable goods.
Some are tangible (roads, wetlands), while others are not (knowledge, institutions, time). No
doubt capital assets depreciate (machines and
5 Williams (1985) is a classic study of the content of
human well-being.

18

equipment undergo wear and tear even whenleft unused, fisheries are destroyed when overharvested, and societies have been known toforget their traditional knowledge), but they
offer a flow of services over time. A desk offers
the scholar an object on which she is able toread, write, and type. The value of the desk is theworth of the contribution it is expected to maketo scholarly activity. In order to assess that worth,
we need to estimate the value of the scholarly
activity itself. The latter’s value will include theenjoyment the scholar experiences from theactivity and the benefits others enjoy from thefruits of that activity. Of course, it could be that
she is fully compensated for the benefits others
enjoy from her work, the compensation being,
say, higher earnings and increased adulation. But
it may be that the higher earnings and increased
adulation, when taken together, are less than the
totality of benefits others enjoy from the fruitsof her scholarly activity. In the latter case weshould estimate not only the value of the desk
to the scholar – that would be the desk’s private
value to the scholar – but also that part of thevalue to others that does not get reflected in her
increased emoluments and social esteem. In
short, we should be interested in the desk’s social
worth. But the desk in question is one among(hopefully!) many writing desks. That particular
desk can therefore be viewed as a marginal unitof the totality of all writing desks. The social
worth of a marginal unit of an asset is called its
shadow price. So we have
Definition 2. The shadow price of a capital
asset is the contribution a marginal unit of
it is forecast to make to human well-being.
For example, watersheds are known to provide water purification ecosystem services
for human health. The shadow price of thesewatersheds is then the net benefit an additional unit area of a watershed conserved willcontribute towards well-being which, in thiscase, will be the constituent of health.

An asset’s shadow price depends on its futureuse, which is to say that it is a function of theforecast of the asset’s use. That is an inevitablefeature of the worth of anything. A writing desk
Inclusive Wealth Reportthat is forecast to rest unused and unrecognizedis value-less. In contrast, if it is forecast that thedesk will be used to good effect, its shadow pricewould be positive. Social evaluators who agree
on everything but their forecasts would imputedifferent shadow prices to the desk.
Forecasts are not mere guesses. If they are tocarry conviction, forecasts must be based on a
defendable theory of the social and natural processes that shape a society’s future. That means
shadow prices are based on counter-factuals:
they are determined not only by the forecastof the shape of things to come, but also by theforecasts of future development had the current stocks of capital assets been otherwise. To
put it another way, if they are to carry conviction, forecasts have to be based on a defendable
theory of the evolving political economy shaping the society under study. Estimating shadow
prices involves counter-factuals. Shadow prices
contain an enormous quantity of information.
The inclusion of population change in sustainability analysis raises technical problems
that are best excluded here.6 The account ofinstitutions as a category of “enabling” assets
suggests that it will prove useful to keep themseparate from the other categories of assets.
Presently we will see why it proves useful tokeep time separate as well. That leaves us withreproducible capital, human capital, natural
capital, and knowledge (categories (1)–(4)). But
each of those four is itself a broad category of
goods, requiring disaggregation. In theory, thedisaggregation can be as fine as we care to makeit, but in empirical work it is inevitably coarse.
For example, it is common in government
and international publications to present estimates of investment in “industry,” the sector
being one that includes any number of capital
assets (factories, machines, automobiles, and soon). A similar form of aggregation is involved
in “mining” and “agriculture.” Of course, if
you are studying the automobile industry inan advanced industrial country, you will want
6 See Dasgupta (2001, [2004]) and Arrow, Dasgupta,
and Mäler (2003) for a detailed analysis.

CHAPTER 1 Wealth and Well-Being

to disaggregate some more and distinguishvarious brands of automobiles and the ancillary assets (repair and maintenance shops, gas
pumps) that go to provide for the industry. Here
we do not need to specify the extent to which
the assets have been disaggregated to form ourlist. So we take it that capital assets in categories(1)–(4) are indexed by i and number N; that is, i
ranges from 1 to N. The lack of specification of
the category to which any particular i belongsmeans we can arrive at a measure of a society’s
productive base without prior presumptions
about the relative importance of various capital
assets that comprise that base.
Let t denote time. For convenience, we suppose t is a continuous variable such that t ≥ 0.
Suppose t is the date at which sustainability
analysis is being conducted. We denote theevolving political economy by M and by V(t)inter-generational well-being at t. Let K i(t)be the stock of asset i at time t and K(t) the
N-vector of the stocks of capital assets (that is,K(t) = {K 1(t),..., K i(t),..., K N(t)}. An economic
forecast at t is a prediction of the future development path, based on K(t), M, and possibly titself. Thus we have:
Equation 1

V(t) = V(K(t),M,t )Let ΔKi(t) be a small increase in asset i at timet. We may interpret ΔKi as a gift some externalsource makes to the economy. The gift “perturbs” the economy. Other things remaining thesame, let ΔV(t) be the small change in V(t) consequent upon that gift. Let P i(t) be the shadow
price of asset i at time t. From Definition 2 andEquation (1) it follows that
Equation 2

Pi(t) = ΔV(t) ΔKi(t)i = 1,2,...,NIn very exceptional (i.e., idealized) circumstances, an asset’s shadow price would equal
its market price. Thus market prices of natural
capital are rarely equal to their shadow prices.
Those reasons have to do with the presenceof “externalities,” an ubiquitous phenomenon
that is linked to the weak property rights that19

Box 1Chance, thresholds, bifurcations, and potential catastrophes

Accommodating chance in sustainability analysis
is to invite the language of probabilities (be theysubjective probabilities or empirical probabilities,
or a combination of the two). Unless we need toconsider chance explicitly in our discussion, we
will embed it in our analysis without mention. For
example, readers could, should they wish, read“expected well-being” when we write “well-being,”
and the expectation could be thought of as being
constructed out of an implicit set of probabilities.
Here, we study the way to introduce uncertainty
explicitly into sustainability analysis.
In defining shadow prices (Definition 2), it was
assumed that a small increase or decrease in thestock of asset i(ΔK i) leads only to a small change
in human well-being (ΔV). That amounts to supposing that human well-being (V) is a smoothfunction of the stocks of capital assets (Ki). The
requirement would appear to go against a generalfinding, that the dynamics of natural systems (e.g.,
ecosystems, climate systems) are non-linear, harboring thresholds that have the property that if asystem would undergo discontinuous changes if itwere to cross one. Formally, thresholds are known
as separatrices.1
Thresholds are loci of points on the space ofcapital stocks that divide a dynamical system into
distinct regions. Dynamical systems are confinedto the region they happen to be in unless and until
external forces “tip” them into another region.
Classic examples of such tipping phenomena
include the destruction of previously thriving fisheries. Over-harvesting can reduce fish populations
to below their thresholds, tipping them into sizes
that spell doom.

1 Scheffer (2009) and Steffen et al. (2004) offer excellent accounts of the abrupt changes that nature andsociety are prone to in the face of non-linearities in the
dynamics that drive them.

20

Bifurcations are different from thresholds. Earthsystems operate at spatial scales ranging from the“miniscular” to the entire globe and running at
speeds that range from the “near-instantaneous” tothe “glacial.” Suppose the social evaluator is studying the ecology of a grassland. Although it is embedded in the climate system, the speed with which thegrassland’s cover responds to changes in the (local)
climate is at least an order of magnitude fasterthan the speed with which the local climate (as an
expression of, say, global climate change) shifts. So,
for all intents and purposes the social evaluator
can regard climate as one of the parameters defining the grassland system. But it is a parameter thatchanges slowly and inexorably.
Bifurcations in a dynamical system are criticalloci of points on the space of the system’s parameters. They are “critical,” in the sense that the locidivide the system’s space of parameter values into
separate regions, with the property that its dynamics differ from region to region. So it can be thata long-established grassland “tips” into a shrubland when the climate crosses a bifurcation. The
existence of both thresholds and bifurcations callinto question the assumption that V is a smoothfunction of (i) asset stocks and (ii) those relatively
constant parameters that characterize the society
under study. Let us see how we should respond to
the doubt.
Of the pair, (i) is of particular interest because
shadow prices have been defined on its basis(Equation [1]). In Equation (1) we assumed that V isa smooth function of K. How do we justify that in
the presence of thresholds? Note first that the location of a threshold is never known with certainty.
The social evaluator may know there is a thresholdfor, say, a population, but she or he would neverknow what it is. There are far too many particularities of the system the social evaluator will neverunderstand, which is why the location of thresholds

Inclusive Wealth Reportremains uncertain. Interestingly, that uncertainty
smoothes V.
As illustration, consider a fishery. Its stock isdenoted by K. We suppose the social evaluator hasstudied fisheries well enough to know that there isa threshold population size, call it Kc, such that thefishery would be doomed if the population were todrop below it, but would survive indefinitely if the
population remained above it. To formalize the loss
that would be suffered if the fishery were to crossthe threshold, imagine that V(K c) is the value of thefishery if K is marginally in excess of K c, but would
be a small fraction, α, of V(K c) if K were marginallyless than K c. Crossing the threshold would resultin a discrete loss in well-being, amounting to (1–α) V(K c). That means V(K) is discontinuous at K c.
Obviously, Equation (1) is meaningless at K c. What
could the fishery’s shadow price mean in such asituation?
Suppose that, even though the social evaluator
does not know the true value of Kc, she knows that
it is not above K** and not below K*. So she knowsthat Kc lies somewhere in the range [K*, K**]. To
have an interesting problem, imagine that the stock
is currently above K** but that there are signs ofover-fishing, which is why the social evaluator has
been called upon to study the fishery.
Let us imagine that the social evaluator constructs a discrete analogue of the fishery by dividing the interval [K*, K**] into N equal sub-intervalsof length Δ. So, Δ = (K**–K*)/N. For simplicity of
exposition we imagine that the social evaluator
believes that K c lies in one of those N sub-intervals
with equal probability. Currently the fishery’s size
is just above K**. Suppose under business-as-usual
the fish population at time t would drop to (K**–Δ).
The expected loss in well-being would be (1–α)
V(K c)/N. If N is large, the expected loss is small,meaning that the expected value of V is a smoothfunction of K at K c. But that means the shadow priceof a marginal unit of fish, P(K c), is well-defined.
Imagine that a policy analysis persuades thesocial evaluator that the risk to the fishery under

CHAPTER 1 Wealth and Well-Being

business as usual is worth it. She or he recommends business to remain as usual and the fisheryenters the interval [K** Δ),K**]. There are now two
possibilities:(a) It is discovered that the threshold did in factlie in the interval [K**–Δ,K**]. As the fishery is now
known to be doomed, society will have entered a
new accounting regime. All shadow prices will haveto be recomputed. But Proposition 1 (on page 55)
would continue to hold from that moment.
(b) The fishery is discovered to be safe. The
social evaluator realizes that the threshold lies in
the interval [K*,K**–Δ]. But now there are (N–1)
sub-intervals left. So, the social evaluator, being agood Bayesian probabilist, concludes that the probability that K c lies in any of them is 1/(N–1). That’s
still a small number, so the previous argument
continues to hold. And it will continue to hold solong as the probability that K c lies in the next subinterval remains small. But once that probability
becomes appreciable, the fishery’s “shadow price”
becomes a meaningless term. Both policy analysis
and sustainability analysis would require the social
evaluator to estimate the discrete loss in humanwell-being that would result from the fishery crossing its threshold.

21

prevail over environmental resources. Both sustainability analysis and policy analysis require
the use of shadow prices. Shadow prices are thelink between capital assets and the human wellbeing they are forecast to protect and promote.
It is customary to regard an asset as a “good”
if its shadow price is positive, and as a “bad” if
its shadow price is negative. The estimationof shadow prices involves “values” (the particular conception of human well-being thatis deployed); “theories” (the character of thesocial and natural processes on the basis ofwhich forecasts are made); and “facts” (the size
distribution of various capital assets, the extent
of their substitutability among one another,
the determinants of the demand and supply of
goods and services, and so forth). So it should be
no surprise that even reasonable people could
disagree over the magnitude of shadow prices.
In recent years, those disagreements havebeen sharpest over the social worth of natural
resources such as carbon and nitrogen concentrations (which at current levels are “bads”) andthe oceans (which taken together are a “good”
in a multitude of ways).
Shadow prices are not Platonic objects, nor
can they be plucked from air on mere whim
and prejudice. We will never get shadow prices“right,” but we can try to narrow the range inwhich they are taken by reasonable people tolie. The social evaluator estimates shadow prices,
but recognizes that others may question her estimates. In democratic societies those differences
are resolved through the ballot box. Chapterspresented in Part II of this report provide an
overview of many of methods that can be used
to estimate shadow prices and the challenges weface when estimating the shadow prices of themany components within natural capital.

5. Wealth and the productive base
How is a society’s productive base to be measured? We are interested, remember, in an index
that tracks human well-being over time. Below
we show that the required index is the society’s
22

wealth. Let us see how wealth should be measured if it is to have the property we want it tohave.
In empirical work, it has proved impossible to disaggregate assets to the extent wehave done in Equation (2). For example, whenenvironmental economists have recommended
that the shadow price of a ton of carbon in theatmosphere is of the order of 150 international
dollars today, they haven’t distinguished richpeople from poor people, nor people in the tropics from people in temperate zones. The figure
has been taken to be the shadow price of a tonof carbon in the atmosphere, period. In empirical work (Arrow et al. 2004; Dasgupta 2001
[2004]; Hamilton and Clemens 1999; WorldBank 2006), distributional issues were ignored
as a first cut into what is a new and very difficult
exercise. The shadow prices the authors estimated were of capital assets, not person-specificcapital assets.
Definition 3. Wealth is the social worth of an
economy’s capital assets.

Let Δt denote a small passage of time following t and let Q(t) be the shadow price of asset
time; that is,
Equation 3

Q(t) = ΔV(t) Δt
If W(t) denotes wealth at t, Definition 3 says
that
Equation 4

W(t) = Q(t)t + i∑Pi(t)Ki(t)Wealth is a weighted sum of a society’s
assets. Because the Index aggregates thesociety’s entire productive base (institutions
are reflected in the Pis via M, remember), W
is referred to as inclusive wealth by some(Dasgupta 2001 [2004]; World Bank 2006)
and comprehensive wealth by others (Arrow etal. 2010). In what follows, we continue to refer
to W simply as “wealth.”
Equation (4) is an expression for wealth, notwell-being. However, the two are synchronousin time. Formally, we have:

Inclusive Wealth ReportProposition 1: Inter-generational well-being
increases over a short period of time if and

6. Inclusive wealth and comprehensive
wealthonly if wealth at constant shadow prices
increases over that same period of time.

To prove Proposition 1, we return toEquation (1). Differentiating both sides of theequation with respect to t and using Equations
2 and 3 yields
Equation 5dV(t) dt = i∑Pi(t)dKi(t) dt + Q(t)From Equation (5) it follows that
Equation 6

dV(t) dt ≥ 0
if and only if i∑Pi(t)dKi(t) dt + Q(t)≥ 0
The condition expressed in Equation (6) is
Proposition 1.
Proposition 1 has become the basis for sustainability analysis. As it identifies wealth as theappropriate index of an economy’s productive
base, it is as well to illustrate its significancewith the help of a numerical example.
Imagine a closed economy. In a given year
it invests US$5 billion in reproducible capital,
human capital, and research and development. Assume too that time does not enter V
exogenously, implying that Q = 0. GDP would
be recorded as increasing, as would the United
Nations’ Human Development Index; but
suppose that natural capital is depleted anddegraded that year by US$6 billion. Equation (6)would record that the country was becoming
poorer in wealth by US$1 billion, implying thatdevelopment was unsustainable that year.
But for such exceptions as carbon in theatmosphere, forest as sources of timber, andsub-soil resources, natural capital is usuallyignored in national statistics. In Chapter 6, welook closely at the content of natural capitaland review the methods that are available
for estimating shadow prices for its various
constituents.

CHAPTER 1 Wealth and Well-Being

Many researchers working on wealth accounts
have used the terms inclusive wealth, comprehensive wealth, and just wealth interchangeably.
In this report, we use the terms inclusive andcomprehensive wealth to describe the wealthaccounts produced for this report. However, forthe purpose of this section only we refer to thewealth accounts developed by the World Bank ascomprehensive wealth accounts. In this section,
we highlight some of the key differences between
the inclusive wealth accounts we present in thisreport and the comprehensive wealth accounts
developed by the World Bank. The comprehensive wealth accounts and the genuine savings
indicator, also called adjusted net savings, weredeveloped by World Bank researchers in the late
1990s in an attempt to track the sustainability of
economies. The World Bank acknowledging thelimitations of GDP began developing comprehensive wealth accounts together with genuinesavings and have published estimates of these forcountries in a series of publications beginningwith the 1997 publication, Expanding the Measureof Wealth (World Bank 1997). There are similarities between the comprehensive wealth accounts
and the inclusive wealth accounts. They bothcome from an economic welfare model. However,there are some key differences between the two
worth highlighting here to give the reader a clear
understanding of the information each of thewealth accounts provide for policy-making andtheir underlying assumptions.

6.1 Comprehensive wealth accounts andthe genuine savings (GS)There are a number of significant differences
between comprehensive wealth and inclusive
wealth accounts on two fronts. The first is at
the theoretical level while the second is at theempirical computation of some of the assets
components within the wealth accounts. Let us
begin with the theoretical framework.
23

First, the World Bank computes comprehensive wealth in the following manner. It
begins by making the assumption that wealthis the discounted flow of consumption. The
formulation inadvertently assumes that consumption is always on a sustainable path. This
then implies that savings will be sufficient tooffset the depreciation of capital that mightoccur. In years where the adjusted net savings– gross national savings minus depreciation of
produced capital plus expenditures on education minus natural resource depletion minus
damage from pollutants and carbon emissions– is negative, then the negative adjusted net
savings is subtracted from consumption to get
a level of consumption which would have kept
the capital stock intact (World Bank 2006).
This adjusted level of consumption is called thesustainable consumption level. In the comprehensive wealth accounts framework, the threemain capitals computed were primarily natural,
human, and produced capitals. The remaining
capital category was called intangible and wastreated as a residual in the computation of thecapital asset base.
In the case of the inclusive wealth accounts,
no assumption of sustainability of consumption
is assumed. In the inclusive wealth framework
Proposition 1 in the previous section makes it
clear that inter-generational well-being increases
over a short period of time if and only if wealthat constant shadow prices increases over thatsame time period of time. And following definition three which explicitly states that wealth is
the social worth of an economy’s capital asset
base. Therefore, in the inclusive wealth accounts,changes in wealth are measured directly fromthe changes in the asset base. It therefore canand will reflect unsustainable trajectories andhighlight which capital assets are in decline andwhere investments might be needed to improve
the overall well-being of a country.
There are a number of important points tohighlight between the theoretical frameworks
used for comprehensive wealth and inclusive
wealth. In the case of comprehensive wealth,wealth is defined as the present value of an
24

exogenously defined flow of consumption. In
the case of inclusive wealth, wealth is defined as
the shadow value of all capital assets a countryowns. This implies that in the case of comprehensive wealth, sustainability is assumed whilein the case of inclusive wealth, sustainability is
analyzed. Arrow et al. (2012) highlight some of the
key problems policy-makers might face if using
comprehensive wealth as a measure of sustainability. Summarizing their main points: (i) if percapita consumption is taken to be known to be
growing at a positive rate, the sustainability of
economic development in their list of countries
is assumed, not studied; (ii) there is, and reallycan be, no empirical basis for estimating future
consumption without measuring the present
basis for it, namely, comprehensive wealth; and(iii) the identification of comprehensive wealthwith the present value of consumption is valid
only under the (stringent) assumptions that theeconomy under study is following an optimal
path and the production structure there exhibits constant returns to scale.
At the empirical level, the inclusive wealthaccounts presented in this report follows themethods used by Arrow et al. (2012) to computethe shadow values of four categories of capital.
These are the human, natural, produced, andhealth. Unlike comprehensive wealth accounting, where a major part of the wealth values areembedded in the intangible capital category,
the inclusive wealth accounts try to capture as
much as possible of the wealth within distinct
capital categories. This was done for two reasons. First, as illustrated above, the inclusive
wealth accounts do not assume a sustainableflow of consumption. Second, to provide as
much information for policy-makers on changes
in actual identifiable capital assets and therefore
provide guidance on future investments.
One of the critical advantages of using thewealth accounts is the direct accounting of environmental damages. The comprehensive wealthand inclusive wealth accounts account for thesedamages. However, the computation of carbon
emissions damage was fundamentally different.
In the case of comprehensive wealth, carbon
Inclusive Wealth Reportemissions damage was computed using a damage
estimate from climate change studies and thenmultiplied by the carbon emission for each country. In the case of the inclusive wealth accounts,
the damage accruing from carbon emissions wascomputed based on the global emission damages
and then using a formula developed by Nordhaus
and Boyer (2000) who appropriate proportionately the damage for each country. The basic
difference between the two is that in the case ofinclusive wealth, the assumption is that damages
to a country are not dependent on the actual
emission of that country but is based on global
emissions. We acknowledge that there is muchroom for improving the methodology and estimates for carbon emission damages across countries. The Nordhaus and Boyer estimates are now
quite outdated and new study figures will need
to be incorporated.
The inclusive wealth report has taken a firststep to untangle the ecosystem services typology and to provide a basis for including regulating and cultural ecosystem services in addition
to the present provisioning services. In this firstreport, an attempt was made to include fisheries in the actual estimates presented in Chapter
3 while Chapters 9 and 11 reflect on the challenges in including water-related ecosystems
services in future reports.
Last but not least, population has to beacknowledged as a critical factor in sustainability.
Although the comprehensive wealth accounts
do provide per capita figures, the underlying
assumption is that population is kept constant.
In the case of the inclusive wealth estimates,
population growth is intrinsically captured in
the framework and the growth rate has beenfactored in the analysis. Not surprisingly, results
show significant differences between estimateswith and without population growth.

7. Key assumptions and caveats
We complete this chapter with an explanationof some of the key assumptions adopted in the
inclusive wealth accounts presented in thisCHAPTER 1 Wealth and Well-Being

report and also some caveats underlying theframework that the reader should be aware.
First, shadow prices are key to inclusive
wealth. The shadow price for many markettraded goods is the market price. However,even these have to be cautiously used as market
prices of many traded goods do not take into
account of the externalities they might havecaused in the production process. Examples
would include prices of agricultural productsthat might have caused pollution of water bodies and degradation of soil. This however is not
to say that the methodology and framework
underlying the inclusive wealth accounts isflawed. What it highlights to us is the need tostart doing better at internalizing these externalities within the production process.
Second, valuing of non-market goods andservices poses a more serious problem. These
will include in particular the regulating and cultural services provided by ecosystems. Ecologists
and ecological economists consider many ofthese regulating services as services or goods
that cannot be substituted with other forms ofcapital. In the case of inclusive wealth, muchof this criticism is deflected, in a theoreticalsense by the use of shadow prices. The shadow
prices capture the substitutability of the capital
assets not just in the present period but also in
the future. Therefore, as some of the regulating
services reach thresholds, the shadow pricesof these services becomes exceedingly highmaking it uneconomical to further draw downthese assets. These high shadow prices will infact point to the need for reinvestment in thesecapital assets. The key challenge however is to
get the shadow prices of these ecosystem services. For example, the shadow price of the climate regulation service is extremely difficult tocompute, but a first order approximation basedon the damages occurring from a change in thatspecific service might suffice for our needs.
Third, the issue of non-linear process andin particular ecosystem processes where incremental changes might not result in any substantial changes in welfare till a threshold isreached whereby sudden shifts are observed.
25

Can the inclusive wealth framework accommodate these non-linear properties of natural
systems and provide the warnings early on in
the process to avert such thresholds from being
reached? The quick response to this factor is in
the shadow prices used in the computation. If
shadow prices are estimated using the production function approach whereby shadow prices
of many life-supporting systems are captured
through a production function, then a shadow
price function dependent on the level of natural
capital can be estimated and used in the computation of changes in natural capital and inadvertently changes in inclusive wealth. But we arefar from having these prices schedules and it isan area where much research is required. But
until those shadow price schedules are computed, the next best solution is to use the willingness to pay shadow prices. Then based on adual observation of the quantity and value of
assets available, expert opinions can be used toevaluate if thresholds are being reached in each
asset base and prudent measures can be taken
to re-invest in these asset categories.
Fourth, is the dichotomy between the scales
at which natural systems occur and at which
the inclusive wealth is computed. The unit ofanalysis at the moment is the national level.
However, many ecosystem services a country
enjoys are dependent on the use of natural
capital in neighboring countries but in somecases, in countries across the world. Therefore,
the shadow price of a ton of carbon is now
computed as the damage that a country occurs
because of the global pollution. But the onus of
responsibility is left wanting. For example, thecountries emitting the most carbon will havea larger part of their inclusive wealth reduced
because of the role they have on the inclusive
wealth of other countries. This is an important
extension of the framework that can be carriedout as a future feature of the framework. The
information released could be useful in computing the compensation countries might haveto pay for destroying a global natural capital,
the global common inclusive wealth, which isalso part of country national accounts.
26

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Inclusive Wealth ReportChapter 2

Accounting for the
inclusive wealth of nations:empirical evidence
Pablo Muñoz, Elorm Darkey, Kirsten Oleson, and Leonie Pearson

Key Messages
This chapter analyzes changes in the inclusive wealth index (IWI) and its components for
20 countries for the period from 1990 to 2008.
Wealth is primarily assessed here as the valueof manufactured, human, and natural capitalstocks. The Index is additionally adjusted for
population changes by presenting per capita
measures.
6 out of the 20 countries analyzed decreased
their IWI per capita in the last 19 years. In 5 out
of 20 countries, population increased at a fasterrate than inclusive wealth, resulting in negativechanges in the IWI per capita.
The majority of the countries in our sample
have had an increase in their stocks of manufactured capital per capita. In China, India andChile, the positive changes in IWI has been
mainly driven by manufactured capital. Russia,
Nigeria, and Venezuela saw a decrease in their
manufactured capital base.

When the three capital forms measured are
adjusted for total factor productivity – oil capitalgains and carbon damages the performance ofsome countries increases considerably, particularly for Nigeria, Saudi Arabia and Venezuela.
Human capital, being the prime capital form
that offsets the decline in natural capital inmost of the economies, has increased in every
country.
This chapter demonstrates that the IWI
provides a different perspective for assessing theperformance of an economy - this by switching
the focus of attention from flows (income) tostock metrics (wealth). This stresses the importance of preserving a portfolio of capital assets
to ensure that the productive base can ultimately be maintained to sustain the well-beingof future generations.

27

1. Introduction1
The aim of this chapter is to analyze changes
in “inclusive wealth” and its components for 20
countries from 1990 to 2008. Wealth is primarily assessed here as the value of manufactured,human, and natural capital stocks2 for eachnation (as discussed earlier) with the next chapter focusing specifically on the role and significance of natural capital. In wealth accounting,these forms of capital are crucial pillars that are
passed down from generation to generation tosustain future needs. Thus, the wealth-based
measure at hand can be used to determine
whether a nation is on a sustainable development path and whether its wealth is growing. If
so, then it can be said that the nation is developing sustainably. This condition would reflectthat we are passing on at least the same productive base that we use today to the next generation, in order to allow them to fulfill their own
needs. Conversely, a decline in the productive
base would compromise the ability of future
generations to meet their needs.
This chapter draws to a large extent on themethod outlined in Arrow et al. (2012), but also
goes beyond it by carrying out a more comprehensive assessment of natural capital. The
new assets included here are coal and fisheries.
Moreover, one of the important contributionsof the IWR wealth accounts refers to the elapsed
time span. While most of the studies built up
their accounts every five years (e.g., World Bank
[2011] or Arrow et al. [2012]), the IWR covers 19
years presenting annual wealth estimates from1990 to 2008, thereby enriching substantiallythe empirical evidence available so far. The
length of this period additionally corresponds
to almost one generation, shedding light on the
productive base down to the next generation.
This also facilitates the comparison of inclusive
1 We are most grateful to Kevin Mumford for very
valuable guidance and comments.

wealth with other common income-based measures of national progress, for example, thegross domestic product (GDP) and the Human
Development Index (HDI).
We investigate the change in wealth for 20
countries (see Figure 1), covering about 58 percent of the world’s population and 72 percent of
the world’s GDP in 2010. As natural capital is the
major focus in this first Inclusive Wealth Report,
we selected countries where nature plays animportant role for their economies, as with oil
in Ecuador, Nigeria, Norway, Saudi Arabia, andVenezuela; minerals in Chile; and forests as in
Brazil. We also sought to include major economies on all of the continents.
There are many challenges concerning aninter-country wealth-based analysis, not least
the fact that no government currently collects capital stock data. The ultimate target isto provide empirical insights to policy-makers
when determining whether a country is on asustainable development path. As much of thischapter is based on incomplete data, it should
not be read as a definitive assessment of wealthaccounting, but as a major step in the right
direction.
The rest of this chapter is organized as follows: Section 2 discusses the empirical construction of the wealth accounts for each capital form.
On methodology, we largely follow Arrow et al.
(2012). We refrain from presenting the computation of each capital category in detail. Instead,this section highlights the basic assumptions,the extensions to existing work in this field, andsome of the challenges in the construction of
wealth accounts. We then move to the analysisof the results in Section 3. In Section 4 we takethe analysis further by including three determinants (namely carbon damages, oil capitalgains and total factor productivity), which affectthe size of the productive base of a nation. In
Section 5 we compare the IWI to GDP and HDI,
while Section 6 serves as our conclusion.

2 These capital forms are also adjusted by environmental externalities (particularly carbon damages) andoil capital gains (see Section 2).

28

Inclusive Wealth Report2. Methodology
The Inclusive Wealth Index (IWI) offers a capital approach to sustainability. The Index seeks
to measure the social value of capital assets ofnations by going beyond the traditional economic concept of manufactured (or produced)
capital. Indeed, the Index is inclusive in thesense that it also accounts for other key inputs
as important components of the productive
base of the economy, such as natural capital(NC), human capital (HC) and, ideally, social capital (SC) (excluded here due to the lack of empirical measures).3 As it has been previously shown(see Chapter 1), the basket of assets (or productive base) is concretely measured by adding up
the social worth, which acts as a weight in the
Index, of each capital type of a country, resulting in the Inclusive Wealth Index, or wealth (seeEquation 1).

3 See Chapter 1 for a comprehensive list of different
capital forms.

CHAPTER 2 Key Findings

Figure 1

Average IWI per capita
growth rate

Key
Average percentage annual growth rates

2.0–1.5

0.5–0

1.5–1.0

0 – -1

1.0–0.5-1 – -2

Australia
BrazilCanadaChile
China
Colombia
EcuadorFranceGermany
India
Japan
Kenya
Nigeria
NorwayRussian Federation
Saudi Arabia
South Africa
United Kingdom
United States
Venezuela
29Equation 1 		Wealth = Pmc x Manufactured Capital (MC)+ Phc x Human Capital (HC) + Pnc x Natural
Capital (NC)Moreover, the Index emphasizes changes
in wealth (or per capita wealth) over the time
period studied. Thus, changes in wealth – or
inclusive investment – are directly measured byassessing the changes in the physical asset baseof a nation over time, and subsequently adjusting by population:
Equation 2

ΔWealth = Inclusive Investment = Pmc x Δ MC
+ Phc x Δ HC + Pnc x ΔNC
It is worth highlighting that changes in IWI
are solely driven by changes in the physical sideof the economy, since prices (or the weights in
the Index) are assumed to be constant and represented by the average price of the time span underevaluation. In this way, changes in wealth are
induced by real changes in the physical amountof the various capital forms, and not simply by
price fluctuations that could be subject to contingent situations (e.g., market bubbles). From anenvironmental sustainability viewpoint, assessing the physical change in natural capital tends
to provide a more meaningful indication of theecological changes. Over the long run, however,price changes may be important, and could influence inclusive wealth estimates.

2.1 Capital assets in the IWR
We measure wealth in our accounts by studying various assets that can be grouped into thefollowing four categories: human capital; manufactured capital; natural capital; and healthcapital. The later capital is treated separatelyfrom the other capital forms as modest changes
in health capital would outweigh any changes
in the other three assets. There are additionally
three adjustments made to these accounts: (1)the potential damages that climate change may
cause on the wealth of a nation; (2) the study of
how increases in oil prices may benefit (harm)
30

some countries in building other capital forms;
and (3) the role of technical progress as reflectedby the change in total factor productivity. While
the rest of this section aims at sketching theapproach used to measure each of these capitalforms and how they break down, Box 1 provides
an overview of the key variables involved in thecomputation of the IWI.
2.1.1. Human capital4
To calculate human capital, we followed the workof Arrow et al. (2012), who based their method
upon Klenow and Rodríguez-Clare (1997). In
this former study, human capital is primarily
captured by measuring the population’s educational attainment and the additional compensation over time of this training, which is assumed
to be equivalent to the interest rate (8.5 percent
in this case). As the interest rate is constant overtime, changes in human capital are basicallycaused by either the change in number of people
educated or an increase (decrease) in the yearsof education. It is additionally assumed that theamount of human capital per person increases
exponentially with the interest rate, and withthe average educational attainment per person.
The shadow price per unit of human capital is
obtained by computing the present value of thelabor compensation received by workers overan entire working life. Notice that these latter
estimates are subject to various demographic
parameters such as birth or mortality rates aswell as other parameters related to the labormarket, like the participation of the populationin the labor force by age and gender. In our case,for each nation we computed these shadow
prices for every year within the 1990–2008
time period, and then used the average of thisrental price of one unit of human capital overtime as the representative weight for entering
4 While both education and health can be considered as components of human capital, we refer here
to human capital as the contribution of education to
the productive base only, and we use the term healthcapital for the study of the progress made in the life
expectancy of the population.

Inclusive Wealth Reporthuman capital into the wealth accounting framework.

Box 1

Key variables used in the measurement of wealth2.1.2. Manufactured capital
Human capitalWith regard to manufactured capital, we
follow the method developed in King andLevine (1994), who based their calculations on the Perpetual Inventory Method(PIM) by setting an initial capital estimate.
Indeed, one of the big difficulties in the
manufactured capital computation concerns the fixing of the initial amount of
capital available at the beginning of theaccounting period. Once this departure
point is obtained, changes over time arecaptured by using the net capital formation reported every year in the system ofnational accounts. Regarding the initial
estimate, steady-state estimates are used,thus assuming that the capital-output
ratio of the economy is constant in thelong-term (for details on this method, seeKing and Levine [1994]). Once this ratio
is measured, it is subsequently multipliedby the final output (GDP in this case) of theeconomy under study, in order to obtain afirst estimate of the manufactured capitalstock. This approach can only give a roughestimation of the fixed capital assets
available in a specific period. In order tominimize errors in the time period understudy (1990–2008), we carried out our
initial estimate in 1970; as capital depreciates over time (we assumed an annual
depreciation rate of 7 percent) the initial
capital estimate retained in 1990 would
be of about 22 percent and only 5 percent
in 2008. This means that any potential
error in the departure point (year 1970)
would be minimized during the relevant
period under analysis. Subsequently, theperpetual inventory method allows capturing the dynamics in the manufactured
capital accumulation by looking at theannual changes in investment. Finally,
regarding the lifetimes of the assets, we
CHAPTER 2 Key Findings• Population by age andgender• Mortality probability by
age and gender• Discount rate
• Employment• Percentage of forest areaused for the extraction of
NTFB• Discount rate
D. Agricultural land
• Quantity of crops produced• Educational attainment• Price of crops produced• Employment compensa-• Rental ratetion
• Labour force by age andgender• Harvested area in crops• Discount rate
• Permanent cropland area
• Permanent pastureland

Produced capitalarea• Investment

E. Fisheries• Depreciation rate

• Fishery stocks• Assets lifetime• Value of capture fishery• Output growth• Quantity of capture fishery• Population• Rental rate

• Productivity
Health capital
Natural capital• Population by age

A. Fossil fuels• Probability of dying by age• Reserves• Value of statistical life

• Production• Discount rate

• Prices• Rental rate

Adjustments in IWI

B. Minerals

A. Total factor productivity• Reserves• Technological change• Production

B. Carbon damages• Prices• Carbon emission• Rental rate

• Carbon price

C. Forest resources• Climate change impacts• Forest stocks• GDP• Forest stock commercially

C. Oil capital gains

available• Reserves• Wood production• Oil production• Value of wood production• Oil consumption• Rental rate

• Prices• Forest area

• Rental rate

• Value of non-timber forest
benefits (NTFB)

31

have assumed indefinite depreciation periods(see methodological annex for further details).

changes in people’s life expectancy that translate into changes in health capital.

2.1.3. Natural capital
2.2 Adjustments to the IWI
Natural capital assets are primarily measured inthis report by the following five categories: (1)forests, represented by timber and non-timber
forest benefits (NTFB); (2) fisheries (only for four
countries); (3) fossil fuels (oil, natural gas, andcoal); (4) minerals (bauxite, copper, gold, iron,
lead, nickel, phosphate, silver, tin, and zinc);and (5) agricultural land. The way of valuingeach capital asset shares a relatively common
accounting method, where total wealth is estimated by multiplying the physical amount available of the asset under study by its corresponding resource rent. As previously mentioned, theresource rent is represented by the average market value of one unit of natural capital over theyears 1990–2008. While the key variables usedin each category are presented in Box 1, thosereaders specifically interested in natural capitalshould refer to Chapter 3 where these accounts
are elaborated in further detail.
2.1.4. Health capital
Our health capital estimates also rely on the
study of Arrow et al. (2012). In this work, positive (negative) changes in this capital form
are essentially captured by extensions (reductions) in the individual’s life expectancy. Suchchanges are basically analyzed by calculating
the years of life remaining of a given population in different time periods, with the population age distribution and the people’s probability of death being therefore the key inputs
into the model. As far as the shadow price of
health capital is concerned, it is measured
by the multiplication of discounted years ofremaining life of a person with the value ofan extra year of life (Arrow et al. 2012). The
shadow price is constant over time and takenfrom the Value of the Statistical Life estimatedby United States Environmental Protection
Agency (EPA). Therefore, it is primarily the32

We shall refer to “Adjusted Inclusive WealthIndex” (IWIadj hereafter) when countries’ capital assets are corrected for specific factors thatfurther affect the size of the productive base ofa nation. In the following, we briefly describe
the three components that we will take into
account: (1) carbon damages; (2) oil capitalgains; and (3) total factor productivity.
2.2.1. Carbon damages
Some of the adjustments needed to be done tothe countries’ wealth relate to those stemmingfrom environmental externalities. In particular, one of the issues that arises is how climatechange can affect countries’ inclusive wealth. In
these wealth accounts, we introduce this correction of the indicator by following the method
developed by Arrow et al. (2012), where in a firststep, the total annual carbon emissions are estimated and subsequently multiplied by its social
cost (US$50 per carbon tonne5 - Ct). For calculating the distribution of these social damages thateach region will suffer we refer to Nordhaus andBoyer (2000). This study presents the distribution of damages as a percentage of the regionaland global GDP. By using information on eachcountry’s GDP, we recovered the total global
damages in absolute level, and then derived
the share of each nation in this total. We used
this proportion to allocate the total social costpreviously estimated, that is US$50 per Ct multiplied by the total global annual emissions (foradditional details see Arrow et al. [2012]).

5 The damages per ton of carbon released to theatmosphere are estimated US$50 per tonne of carbon(Tol 2009).

Inclusive Wealth Report2.2.2. Oil capital gains
Rental prices have been kept constant over time
as we previously mentioned. However, in thissection we explore potential wealth gains that
may stem from continuous price increases ina particular natural resource type. Some countries with large endowments of some specificnatural resources (e.g., oil in Nigeria or copper in Chile) may also want to compute thischange in prices as one further category in theirwealth accounts, as these wealth gains may bebeneficial for building other capital forms, forexample, human capital. In this report, we concretely explore gains stemming from a changein oil prices. In line with Arrow et al. (2012), we
assume an annual increase in the rental priceof 5 percent over the period 1990–2008.6 Thesechanges in the rental price are multiplied by thestock of oil available in each subsequent period.
While some countries enjoy higher rental prices
for their oil asset, other countries, which dependon oil imports, may be negatively affected, since
their capacity to build other capital forms isdiminished by these higher prices. We therefore
redistribute those capital wealth gains obtainedby oil extractive economies to those nations that
consume this commodity. There are, of course,
some countries that extract large amounts ofoil at the world level (for example the UnitedStates, which is the second largest producer inthe world), but at the same time are an important consumer of this material. This fact leads
us to compute the “net” oil capital gains as thedifference between oil capital wealth gains andlosses. See methodological annex and Arrow etal. (2012) for additional details.
2.2.3. Total factor productivity
Total factor productivity (TFP) growth measuresthe change in aggregate output that cannot be
explained by the growth rate of observable inputs
6 This 5 percent corresponds to the annual average oil price increase during the years 1990–2008 (BP2011).

CHAPTER 2 Key Findings(Barro and Sala-i-Martin 1995). This residual in
growth accounting can be understood as a proxyvariable of technological progress, which is hardto measure directly. Given the empirical evidence
that TFP growth accounts for a substantial part ofthe overall growth rate in real GDP (see, for example, Christensen et al. [1980]), it is important
to consider this variable in wealth accounting as
well. Adjusting for TFP in this context means thatthe same productive base can lead to an increasein aggregate output over time because technicalchange renders each capital asset more productive. For further details see Arrow et al. (2012).

2.2 Data limitations
We have measured four capital forms here, plus
carbon damages, oil capital gains, and total factor productivity. There are, however, other capital stocks not accounted for yet; a clear exampleof this is social capital. Even more, within somenatural resource categories, for example fisheries
and minerals, we still lack data among the countries under study. This renders the comparison
between countries quite difficult. Other caveats
to bear in mind relate to the annual changes in
wealth; with regard to several variables, the data
points used to construct the accounts represent
points at the end of a decade. For example, someparameters in our models are obtained fromthe Life Tables (World Health Organization2012), which report information only for theyears 1990, 2000, and 2009. This implies that weneeded to fill the years in between by carrying
out linear interpolations. We therefore caution
readers about these interpolations when taking
conclusions from inter-annual variations (seemethodological annex for more details).

3. The wealth of nations
This section gives an overview of the resultsfor our country sample over the 1990–2008
period. All variables are measured at constant
U.S. dollars for the year 2000. The analysis is33

organized as follows: First, we will discuss the
Inclusive Wealth Index based on three types ofcapital assets: human, manufactured, and natural capital. Since health capital dominates thetotal capital asset base, we have treated thesecomputations separately from the other capitalforms (see Box 2).
The key variables we shall address in thischapter are: (i) the average annual growth rates
in Inclusive Wealth Index (IWI) over the time
period 1990–2008 as shown in Table 1 andFigure 2 respectively; (ii) the percentage change
in IWI and the three capital assets per capita aspresented in data annex; and (iii) the composition of the productive base of the economy inrelative and absolute terms shown in Figure 4
and Appendix 2 respectively. In addition, we
provide estimates of the IWI but adjusted for oilcapital gains, carbon damages, and total factor
productivity. In Section 5 of this chapter, weshall also provide a comparative exercise of the
IWI against GDP and the HDI to illustrate thedifferences across these three indices for the 20
countries.
Given the enormous amount of information
available, we restrict ourselves to summarizing ourmain findings. The interested reader can also findthe entire data set in data annex of this chapter.

3.1.	How has each country been doingin the last two decades from an inclusive
wealth perspective?
The desired output would be positive growth
rates for the IWI. Countries with positive growth
rates of IWI would ideally demonstrate that
their productive base is not being eroded andthey have maintained the asset base to produce
the same level of output for consumption of
future generations. Table 1 shows that all countries have positive IWI growth rates except for
Russia. China, Kenya, India, and Chile exhibit
the highest growth among all countries studied.

Figure 2

Average annual growth rates (per capita) disaggregated by capital form
2.5

Key
2

IWI
Natural capital

1.5

Human capital
Produced capital

1

.5

0

-0.5

34

Nigeria

Saudi Arabia

Russian Federation

Venezuela

Colombia

South Africa

Kenya

Australia

CanadaEcuador

NorwayUnited States

United Kingdom

Brazil

Japan

India

Chile

France-2Germany

-1.5
China

Percentage-1

Inclusive Wealth ReportHowever, the figures presented in column (1) of
Table 1 have only limited explanatory power inthe scope of an inter-temporal analysis, simply
due to the fact that population changes overtime. This has to be borne in mind when wetalk about sustainable consumption paths of acountry. An increase in total wealth does notnecessarily indicate that future generations
may consume at the same level as the present
one; as population grows, each form of capitalis more thinly spread over the society, so that
productivity growth based on capital accumulation alone might eventually cease. Therefore,
we need to extend the analysis by considering
per capita values of total wealth.
Column (2) in Table 1 shows the demographic
development of the countries under study. In
this regard, Kenya, Saudi Arabia, and Nigeria
top the list with average annual growth rates of
population of at least 2.4 percent. The status ofsome countries change drastically when population growth is taken into account. We see amajor shift of countries with respect to their IWI
growth rates when population is factored into
the analysis, as shown in Figure 3.
Kenya for example which returned a relatively high IWI rate of 2.85 only managed tohave a growth rate of 0.06 IWI per capita. This
demonstrates that the rate of return of its capital asset base per person is very low and either
it improves on its IWI or reduces its population
growth rate. The picture is worse in the caseof Saudi Arabia and Nigeria who move into a
non-sustainable position, as they depict negative IWI per capita growth rates. But these are
not the only countries switching from positive
to negative IWI growth: Colombia, South Africa,
and Venezuela also moved in the same direction
because of higher population growth rates thantheir IWI growth rates. These countries have, atleast, two options to reverse this trend. Theyeither have to reduce their population growth
rates or reinvest in the different capital asset
bases to increase the rate of IWI growth. The
question on which capital asset base to focus
will be addressed in the following section.

CHAPTER 2 Key Findings

Box 2

Health Capital
Health capital of a nation’s population reflects the
expected discounted value of years of life remaining. This is, understandably, a large number; indeed,
we find that health capital makes up more than 90%of the capital base for all countries in the study. In thenations under study, the amount of health capital thateach person owns outweighs all other forms of capital
combined. Given a population, slight changes in mortality rates result in more or less health capital eachyear. Most countries in the study experienced gains in
per capita health capital over the period 1990–2010.
The exceptions were South Africa, Russia, and Kenya,
which lost health capital; and Japan, Australia, andVenezuela, which remained stable. Most nations saw aslight but persistent increase in per capita health overthe entire period, but in some nations recent healthimprovements are accruing health capital after earlier
stagnation (Nigeria) or recovering health capital losses
suffered during the 1990s (Kenya). Differences between
the countries’ rates of change in per capita healthreflect national policy choices as well as demographic
differences. Improvements in mortality rates in an older
population (e.g., Japan) will not affect per capita healthcapital as much as those same mortality gains in ayounger population (e.g., Kenya).
Because health capital constitutes such a large portion of the capital base, its change renders insignificant
any other capital changes. It is obviously a key point toconsider that health capital is as important as it is, andto direct policy attention to reducing mortality to continue to increase that component of wealth. In theory,these gains in the productive base can substitute fordeclines elsewhere. However, policy-makers also needto know the relative rates of change in human, natural, and reproducible capital. It is to gain resolution fineenough to speak to these changes that our analysis in
this chapter omits health capital.

35

The situation is slightly reversed in Russia:
although the country’s IWI growth rate percapita is still negative, the situation has beenslightly alleviated, because population had
decreased steadily since 1993. The impact ofhigh population growth rate is again highlighted by comparing India and China. Bothcountries showed strong IWI of 2.66 and 2.92
respectively. However, after including population growth rate, the IWI per capital of India
fell to 0.91 while that of China dropped to only
2.07 because of the slower population growthrate in China. In the case of Venezuela, South
Africa, Saudi Arabia, Nigeria, and Colombia, theTable 1

Measuring countries’ progress. Averageannual growth rates, period 1990-2008.
2

36

Countries/
Indicators

3

IWI

Population
growth rate

IWI per
capitaAustralia

1.41

1.29

0.12

Brazil

2.30

1.38

0.91

Canada

1.41

1.03

0.37

Chile

2.56

1.35

1.19

China

2.92

0.83

2.07

Colombia

1.62

1.70

-0.08

Ecuador

2.14

1.76

0.37

France

1.95

0.51

1.44

Germany

2.06

0.23

1.83

India

2.66

1.74

0.91

Japan

1.10

0.19

0.91

Kenya

2.85

2.79

0.06

Nigeria

0.53

2.44

-1.87

Norway

1.33

0.67

0.66

Russia

-0.50

-0.19

-0.31

Saudi Arabia

1.57

2.72

-1.12

South Africa

1.57

1.64

-0.07

UK

1.26

0.38

0.88

United States

1.74

1.04

0.69

Venezuela

1.70

1.99

-0.29

1

population growth rates were higher than thegrowth rate of the IWI thus pushing these countries on a unsustainable trajectory.

3.2 What is the contribution of the different capital forms to per capita wealthcreation?
Figure 2, as mentioned before, illustrates theaverage contribution of the different capital types to the development of the average
Inclusive Wealth Index per capita for each of
the 20 countries. It is interesting to note thatamong the top five performing countries appear
three middle-income economies – China, India,
and Chile – where wealth changes are driven byhigh growth rates of manufactured capital. In
the case of France and Germany, the other twoof the five top countries, much of the growthin average IWI per capita came from the growthin human capital. Note also the low change innatural capital for Germany and France in comparison to the rest.
Turning to the bottom five countries inaverage annual IWI growth per capita, we seethat it is in fact the decline in natural capitalthat explains the negative wealth trend.7 The
only exception is Russia, where the negative
IWI growth is triggered by the steady declineof manufactured capital. For the bottom
three countries (Venezuela, Saudi Arabia, andNigeria), natural capital and in particular fossil
fuels represent the main component of wealthas will be shown in Chapter 3. Since the natural
capital accounts in these countries are based
to a large extent upon exhaustible resources,
these results come as no surprise. As the basis ofrenewable natural resources is too small to offset this decline, the advisable rule would be toinvest and achieve higher returns in other typesof assets, namely manufactured and/or humancapital. In this context, Norway, despite being
an important oil extracting country, depicts
7 Those readers interested in more information
about natural capital are referred to Chapter 3.

Inclusive Wealth ReportFigure 3

Inclusive wealth index

Key
Average annual growth rate (percent)

3-2.5

1.5-1

2.5-2

1-0

2-1.5

0-(-1)

Inclusive wealth index per capita

Key
Average annual growth rate (percent)2.0–1.5

0.5–0

1.5–1.00 – (-1)

1.0–0.5-1 – (-2)

CHAPTER 2 Key Findings37

positive growth of the IWI and a relatively mod- the entire time span. This approach, however,excludes details about how per capita wealthest decline in natural capital (see Figure 3).
has evolved within the reference period. The full
Health capital of a nation’s population
trend line is presented in data annex. Note thatreflects the expected discounted value of years
the relative change of each capital form overof life remaining. This is, understandably, alarge number; indeed, we find that health time relates to one common base year, that is to
say that per capita wealth of 1990 is indexed tocapital makes up more than 90 percent of thecapital base for all countries in the study. In 0 for all countries under study.8
the nations under study, the amount of healthIn general, the various capital categories havecapital that each person owns outweighs all contributed differently to the IWI growth perother forms of capital combined. Given a
capita. The highest cross-country discrepancies
population, slight changes in mortality rates
can be observed with manufactured/produced
result in more or less health capital each year. capital. As expected, most of the countries in our
Most countries in the study experienced gains
sample have increased their stocks, in particuin per capita health capital over the period
lar the more recently industrialized countries
1990–2008. The exceptions were South Africa, – China, Chile, and India – feature the highest
Russia, and Kenya, which lost health capital; rise in manufactured capital (China more or
and Japan, Australia, and Venezuela, whichless quintupled its stock of manufactured capiremained stable. Most nations saw a slight but tal while Chile and India show an increase bypersistent increase in per capita health over 183 percent and 168 percent, respectively). The
the entire period, but in some nations recent human capital on the other hand in these threehealth improvements are accruing health countries increased at a much lower rate while
capital after earlier stagnation (e.g., Nigeria) or natural capital declined. The key question werecovering health capital losses suffered during need to ask ourselves is if this trend is sustainthe 1990s (e.g., Kenya). Differences between theable? To answer this question we need to lookcountries’ rates of change in per capita health at the composition of the asset base in thesereflect national policy choices as well as demo- countries. In all three countries, the weight ofgraphic differences. Improvements in mortal- produced capital was approximately 17 percent
ity rates in an older population (e.g., Japan) will versus human and natural capital weights of 37
not affect per capita health capital as much as
percent and 46 percent respectively on average.
those same mortality gains in a younger popu- This implies that although these countries witlation (e.g., Kenya).
nessed the largest increases in produced capital,
Because health capital constitutes such a large
its overall weight within the inclusive wealthportion of the capital base, its change renders
index is the lowest. In other words, we might
insignificant any other capital changes. It is obvi- interpolate this as every single unit increase inously a key point to consider that health capital is
produced capital contributes less towards theas important as it is, and to direct policy attention IWI than a single unit decline in natural andto reducing mortality to continue to increase that human capital.
component of wealth. In theory, these gains in the
However, not all countries have increased
productive base can substitute for declines else- their produced capital. Russia, Nigeria, andwhere. However, policy-makers also need to know Venezuela actually show negative growth in
the relative rates of change in human, natural, and manufactured capital (with the stock decreasing
reproducible capital. It is to gain resolution fineenough to speak to these changes that our analy8 Notice that the IWI path cannot be simply comsis in this chapter omits health capital.
puted as the sum of each of these trajectories as they
So far, we have looked at the average annual are weighted differently within the wealth accountingchange of the Inclusive Wealth Index over framework.
38

Inclusive Wealth Reportby 37 percent, 42 percent, and 12 percent respectively). Russia was the only country in thesample of 20 countries had a decline in its IWI
caused largely by a decline in produced capital.
Most other countries witnessing decline in IWI
were caused either by declines in natural capitalor high population growth rates as in Venezuela.
Three countries, Brazil, Ecuador, and Kenya,
reported a more or less constant stock of manufactured capital until 2005.
The changes in inclusive wealth in Brazil,
Germany, and Saudi Arabia were driven primarily by rapid growth in human capital of 48
percent, 46 percent, and 43 percent respectively.
The increase in human capital was found to be
the prime factor that offsets the decline in natural capital that occurred in almost all nations.
In most cases, human capital is accumulated by
between 20 and 36 percent over the years understudy. The lowest growth in human capital since1990 was experienced by highly industrializedcountries such as Australia and the U.S. with
8 percent within 20 years, Japan with 12 percent, the United Kingdom with 14 percent, andNorway with 15 percent. All of these economies
had already accumulated a high stock of humancapital before 1990. This result was driven primarily by the variable we used in this report,
which is the years of total schooling of the
population. A key lesson to be learned from thisresult for the developing countries is the diminishing returns on human capital as the years ofschooling reaches a maximum. The continued
decline of natural capital in countries where thehuman capital has reached diminishing returns
suggests a strategy to reinvest in natural capital.
Most countries with the exception of Japansaw a decline in their natural capital asset base ata per capita level. The biggest declines occurred in
the United Kingdom and Saudi Arabia, where thedecrease was caused by a decline in the fossil fuels
asset base. The countries, which saw a fall in their
IWI because of declines in natural capital were
Colombia, Kenya, Nigeria, Saudi Arabia, and South
Africa. The precise information of which components of the natural capital played a key role in theoverall decline are presented in Chapter 3.
CHAPTER 2 Key Findings

39

Figure 5

Composition of productive base for France, Germany, Japan, Norway, United States, andUnited Kingdom,
Key
NC

DEU

FRA

GBR

JPN

NOR

USA

HC
PC
25%

24%

9%

26%

25%

16%

67%

75%

90%

73%

61%

78%

8%

1%

1%

1%

14%

7%

Figure 6

Change in productive base for China, Chile, India, and Kenya (US$, year 2000)
Key

2

2

China

Chile
13

12

Scale: 10

NC

Scale: 10

2007

2008

2007

2008

2005

2006

2005

2006

2003

2004

2003

2004

2001

2002

2001

2002

1 999

2000

1 999

2000

1 997

1 998

1 997

1 998

1 995

1 996

1 995

1 996

8

1 993

2

India

1 994

2007

2008

2005

2006

2003

2004

2001

2002

1 999

2000

1 997

1 998

1 995

1 996

1 993

1 994

1 991

1 992

1 990

Wealth

10

1 993

0

1 994

0

1 991

1

1 992

1

PC

1 990

HC

Kenya
12

11

Scale: 10

Scale: 10

6
1

Wealth4

The configuration of the capital portfolio
indicates which capital plays a predominant rolein the respective countries. Figure 4 shows thecapital composition of the 20 countries as anaverage between 1990 and 2008. Manufactured
capital represents on the average only 17 percent of the wealth portfolio, with little varianceamong countries. While it is not surprising that
manufactured capital is being overshadowedin every country by human capital, its sharein the composition of wealth is also less than
the share of natural capital; only in the highlyindustrialized countries of this sample – France,
Germany, Japan, Norway, United Kingdom, andUnited States – as shown in Figure 5 do fixed
40

1 992

1 991

0

1 990

2007

2008

2005

2006

2003

2004

2001

2002

1 999

2000

1 997

1 998

1 995

1 996

1 993

1 994

1 992

1 991

0

1 990

2

capital assets contribute more to the productive
base than natural resources.
However, among the countries with relatively low shares of produced capital, Nigeria,
Saudi Arabia, and the United Kingdom have evenlower shares of produced capital. The United
Kingdom has a particularly disproportional
share structure with human capital dominatingwith a 90 percent share with the United States
following closely with a share of 78 percent.
Natural capital, on the other hand, tends to be
more relevant in developing countries such as
Venezuela and Colombia and is the prevailingfactor in those economies whose GDP is largely
driven by oil extraction, such as Nigeria, Russia,
Inclusive Wealth ReportKey

Figure 7

Change in productive basefor Brazil, Kenya and Saudi
Arabia

NC
HC
PC

10

Brazil8

12

Scale: 10

6

Wealth4

1 9 97

1998

1999

2000

2001

2002

2003

2004

2005

2006

2 0 07

1 997

1 998

1 999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1 997

1 998

1 999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2008

1995

1996

1 995

1 996

1 995

1 996

1993

1994
1 994

1991

1992

0

1990

2

2

Kenya
11

Scale: 10

1 993

1 992

1 991

0

1 990

Wealth1

5

Saudi Arabia
4

12

Scale: 10

3

1 993

1 994

1 992

0

1 991

1

1 990

Wealth2

and Saudi Arabia. The countries with the lowest
share of natural capital as a share of the total
capital asset base were France, Japan, and theUnited Kingdom where natural resources constitute only 1 percent of total capital value.

3.4 What is the absolute wealth level of thecountry in terms of manufactured, human,and natural capital?
Again, the average capital composition over theentire time span does not give insights into the
dynamics behind wealth accumulation; for this,we need to know in which way the stock of each
CHAPTER 2 Key Findings

capital form has changed in absolute terms.
Data annex depicts the evolution of the different capital forms within the reference period,
this time without correcting scale effects due
to population growth. Thus, we are dealing
with the question of how rich a country has
performed overall in terms of manufactured,human, and natural capital. In this regard, total
wealth has been increasing for all countries
except for Russia.
India, Chile, Kenya, and China shown in
Figure 6 produce the highest rate of change
in their productive base with China increasing
its productive base by about 70 percent in thetime span under analysis, with manufactured
capital being the primary growth engine. As one
can see from the comparison of the diagrams,
human capital served as the main driver ofcapital accumulation. Conventionally defined,
developing countries starting from a low level ofhuman capital such as Kenya and Brazil shownin Figure 7, have been clearly catching up to themore industrialized economies in the sample.
Manufactured capital remained relatively stablein Brazil, Venezuela, Saudi Arabia, and the U.K.,
while for Russia and Nigeria, manufactured
capital has even declined in absolute terms. This
trend, primarily caused by falling saving/investment rates, has led to an overall decrease intotal wealth in the case of Russia. The diagramsin Appendix 2 also give a clear picture of theavailability of natural resources in the countries
under study: Nigeria, Russia, and Saudi Arabia
thereby present the highest stock in natural capital (driven by oil reserves), in comparison to theother assets, whereas the productive base of theindustrialized economies, as already mentioned,
depends on relatively few natural resources.
While this overall picture is unambiguous, weneed to be careful with interpreting the exact
numbers, since data availability concerning thedifferent subcategories of natural capital varies
highly among the countries. For example, we
do not possess data about Japan’s fishery stocks,
which is an important natural resource for thiseconomy. Improving on the value of the natural
capital asset base will provide us with a more
41

Figure 8

Adjusted IWI
6

Key

5

IWI
Carbon damage
4

Oil capital gains
TFP

3

IWIadj2

10

realistic understanding of the weight of natural
capital within the productive base of a country.
However, it should be noted that the relatively
high weighting associated with natural capital
already informs us of the relative importancenatural capital plays in a country’s sustainability tract.

4. Adjusted Inclusive Wealth Index
In this subsection we take the analysis one stepfurther, by including three determinants thatsomewhat alter a country’s productive base or
its aggregate output. These are: carbon damages, accounting for the potential damages ofclimate change in the country’s wealth; oil capital gains, capturing how changes in oil prices
may benefit (frustrate) the construction of othercapital forms; and total factor productivity(TFP), measuring the extent to which the capital
42

South Africa

Kenya

Colombia

Australia

Japan

Brazil

Chila

United States

EcuadorFranceUnited Kingdom

CanadaNorwaySaudi Arabia

India

RussiaVenezuela

Germany-3

Nigeria-2
China

Percentage-1stock, ceteris paribus, became more (less) productive in the generation of goods and services.
When these factors are taken into account theresulting indicator will be called the “Adjusted
Inclusive Wealth Index” (IWIadj).
We have added these adjustments to theaverage annual growth rates per capita presented in Figure 3. Results show that while
China and Germany still remain in the top
five countries in terms of growth rate, Nigeria,
Venezuela, and Russia appear as new membersin this group (see Figure 8). This huge jump in
the ranking from the bottom to the top fiveeconomies is primarily attributed to TFP growth
as well as oil capital gains, as Nigeria and
Venezuela have large endowments of this natural resource. After adjusting the IWI, not only
did Nigeria, Venezuela, and Russia moved awayfrom unsustainable consumption paths, so did
Saudi Arabia, another oil-based economy, due
to the steady increase in the price of crude oil
Inclusive Wealth Reportover the last decade. However, for other nations
that depend on oil imports, the reported IWI
growth was reduced by the adjustments, as in
Kenya, for example, where oil price fluctuations
severely hit the economy, reinforced by the
decline of total factor productivity. In comparison to Figure 3, Colombia and South Africa still
have negative growth rates, because oil prices
and TFP mainly accentuate the negative wealthgrowth. The impact of climate change on the
total value as measured here seems to be of considerable relevance in Kenya.

5. A comparison of IWI, GDP, and HDI
So far we have studied the composition andevolution in total wealth, taking into accountdemographic development. However, societal
progress (regress) can be also assessed fromother angles, most typically, by the relativechange in the gross domestic product (GDP)and the Human Development Index (HDI) overtime. The former measures the value of all final
goods and services, manufactured in an economy within one year, while the latter entails
a broader concept of societal development,
extending gross national income per capita byother determinants of social well-being, as evidenced by life expectancy as well as expected
years of schooling. These indicators generally
lead to different empirical findings concerning
the progress of a nation. Table 2 compares IWI,
GDP, and HDI for our sample of 20 nations for
1990–2008.9 The IWI column in this table summarizes results based on the average annual per
capita change within the reference period. The
numbers presented in column two depict therate of change of the HDI while those in column
three show the rate of change of GDP per capita.
Let us begin evaluating countries by looking attheir HDI and IWI rate of change.
9 We again revert to the unadjusted IWI, since weare interested in the role of the capital categories
under study for socio-economic development, being
aware that other factors (such as technical change)
may offset deteriorations in the productive base.

CHAPTER 2 Key Findings

If countries are purely evaluated on the HDI,
then all countries except South Africa haveseen an improvement in their HDI over thetime period. South Africa returned an average
growth rate of 1.3 percent of GDP over the sametime period, but also saw a negative growthrate in the IWI. The three low ratings for South
Africa suggest that urgent interventions should
be made that might include improving all three
types of capital, particularly human and natural
capital.
There are five other countries that had
positive growth rates in the HDI and GDP per
capita but had negative growth rates for the IWI:
Colombia, Nigeria, Russia, Saudi Arabia, andVenezuela. Most of these have large reserve offossil fuels. They have basically been drawing
down their oil reserves but yet not increasing
their produced and human capital bases as fast
as they should to ensure an overall positive
growth in IWI. Although all five would haveposted positive GDP per capita growth rates, thenegative IWI growth rates suggest an unsustainable track and most of the GDP growth has comeat the expense of the natural capital base.
India and China warrant special attention
because of the size of their populations andeconomies. Although China demonstrated
the highest IWI growth rate, earlier discussion
had already highlighted the need for China to
re-evaluate its development strategy and begin
increasing its investment in natural capital andget higher returns on its produced and humancapital. India faces a more dire situation as its
inclusive wealth has only growth by 0.9 percent
over the past 19 years compared to China’s 2.1
percent. These results might suggest that India
will need to improve its rate of build up ofhuman capital as it decreases its natural capital even further to maintain a positive inclusive
wealth growth rate. This again brings us backto the contribution to the IWI from a single
unit increase or decrease of the respective capital assets. But the question of critical levels ofnatural capital comes into play and these results
suggest a more detailed investigation of the natural capital categories in India and to the extent
43they have been destroyed and the level at which
this decline can continue.
If we use the HDI, Colombia and Nigeria arein the top five, although they are among thebottom countries from an IWI perspective. The
explanation may be largely based on the factthat HDI does not consider in its computation
the depletion of natural capital, which acts as
the main driver behind the negative growth
rates in these countries.
Turning now to GDP, the traditional tool for
judging the performance of economies, a different picture is drawn altogether. According
Table 2Comparing average growth rates perannum in IWI per capita, GDP per capita
and HDI.

Countries/
Indicators

44

IWI per
capitaHDI

GDP per
capitaAustralia

0.1

0.3

2.2

Brazil

0.9

0.9

1.6

Canada

0.4

0.3

1.6

Chile

1.2

0.7

4.1

China

2.1

1.7

9.6

Colombia

-0.1

0.9

1.7

Ecuador

0.4

0.6

1.8

France

1.4

0.7

1.3

Germany

1.8

0.7

1.5

India

0.9

1.4

4.5

Japan

0.9

0.4

1.0

Kenya

0.1

0.4

0.1

Nigeria

-1.8

1.3

2.5

Norway

0.7

0.6

2.3

Russia

-0.3

0.8

1.2

Saudi Arabia

-1.1

0.5

0.4

South Africa

-0.1

-0.1

1.3

United Kingdom

0.9

0.6

2.2

United States

0.7

0.2

1.8

Venezuela

-0.3

0.8

1.3

to this approach, all economies have enjoyedat least some progress. Let us discuss the relationship between our Inclusive Wealth Index
and the traditional income-based measure in
greater detail. In this regard we look at Chapter
4, which undertakes a very similar analysis ofinclusive wealth for 48 of 50 U.S. states from1990 to 2000 and compares the capital accumulation rate to the GDP growth rate. The
comparison gives information about whether
the respective economy is over- or under-consuming. Accordingly, if the capital stock cannot
keep pace with the growth in GDP, less and lesscapital will be available to feed the production
system. We have a situation where we consume
more than we could produce in the future(assuming no changes in technology). Revertingto our country sample, Table 2 displays large
differences between GDP and IWI growth rates
at a per capita level. In fact, in most of the cases
GDP growth rates tend to be larger than those
based on an inclusive capital approach (except
for France and Germany), casting some doubtson the sustainability of such GDP records in thelong run for the economies under analysis.

6. Conclusion
This chapter offers an analysis of the inclusive
wealth of nations and its changes over time interms of several relevant assets for 20 countries, over a time period of 19 years. We showedthat the IWI provides a different perspective forassessing the performance of an economy, by
switching the focus of attention from flows tostock metrics (contrary to GDP). The preservation of such stocks is essential for ensuringthat aggregate output can be sustained in thelong run, therefore enriching the measures bywhich economic development can be captured.
On the empirical grounding, we found that theannual average growth rates in IWI per capita in
six out of 20 nations report a decline in wealth.
This result has, in fact, been exacerbated by
rapid population change. Figures, however,improve for some countries, when considering
Inclusive Wealth Reportadjustments to the three accounted-for capitals.
For example, Saudi Arabia could move into asustainable consumption path, not because of
the building of the capital base, but due to theincrease in oil prices which in fact triggered themove in that direction.
The global picture that can be drawn fromthe discussion makes evident that natural
capital has been steadily declining in per capita
terms. Even though this development could beoffset by the accumulation of other assets, it isimportant to have in mind that whereas manufactured and human capital are reproducible
factors, natural capital has limited substitutability with respect to the other capital forms(see Chapters 3 and 11).
On a methodological level, the inclusive
wealth framework offers a comprehensive
accounting tool covering various socio-ecological aspects, which allows policy-makers to track
the changes in countries’ physical assets portfolio. In this study, we additionally accounted
for the effects of oil prices, an approach thatcan be extended to other relevant commodities
depending on the country under study. Other
adjustments considered within the tool regard
the carbon damages on the economy. This analysis could also be expanded to the study of the
impact of climate change on other capital assets,in particular natural capital. We do not yet havea way to apportion the damages across capitalforms, but this should clearly be a point of discussion when measuring countries’ wealth, inorder to keep gaining accuracy over previous
estimates.
Some of the aspects that still need to beaddressed are: the accounting for social capital that has been excluded due to the lack of amethodological and empirical framework; theabsence of shadow prices which have been here
substituted by rental prices; and the limitationof our study to the analysis of some specific natural capital components. The wealth accounts
that we have established in this study can becertainly extended to other categories such as
regulating services (see Chapter 9) or water (seeChapter 10) as well.
CHAPTER 2 Key Findings

Besides the sound theoretical foundations of
the Inclusive Wealth Index, one should bear inmind the uncertainties and restrictive assumptions inherent in these empirical calculations,which are mainly subject to data availability.
These results should therefore be understood asrough trends in wealth accumulation. However,even with this strong caveat, our findings warrant further investigation. Thus, the current
analysis represents a relevant step towards
illuminating the significance of the inclusive
wealth approach for long-term economic
development.

45

46

1995

1997

1995

Venezuela
20 07

-20
0

-60
-40
2003

1 994

1 993

1 992

1 991

1 990

201 0

2009

2008

2007

2006

2005

2004

-20

0

-40

-60
2007
2008
2009
201 0

20 07
200 8
20 0 9
2010

2007

200 8

200 9

2010

2005
2006

2005
20 0 6

200 5

200 6

2003
2004

20 03
20 0 420 03

20 0 4

2001
2002

2001
2002

2001

20 02

1 999
2000

1999
20 00

1999

200 0

1 997

20
1 998

40
1997

South Africa
1998

60

1997

1 995

20
1 996

40

1995

Nigeria

1996

1994

1993

1992

1991

1990

2010

20 09

20 08

60

1998

1996

200 5
20 06

Saudi Arabia

1993

200 3
20 04

2001
2002

1 999

201 0

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

Chile

1994

200 1
200 2

1 999
2000

1 997
1 998

-20

-60

-40

Percentage change
80

1992

1999
2000

1 997
1 998

1 995
1 996

Percentage change in IWI per capita and the
60

1991

1997
1998

1 995
1 996

1 993
1 994

100

1990

1995
1996

1 993
1 994

three capital forms: human, manufactured, and

2010

1993
1994

1 991
1 992

natural capital, 1990–2008.

20 09

20 08

20 07

20 06

20 05

20 04

200 3

200 2

200 1

20 00

1999

1998

80

1996

100

1993

80

1994

100
1 992

180

1992

160

1992

PC

1 990

HC

1 991

NC

1 990

180

1991

Percentage change

IWI

1990

Percentage change

Key

1991

1990

Percentage change

Appendix 1

Australia

40
20
0

200

China
460

160

140

120
400

100

60
80

40

20
300

-20
0

-60
-40

200

140

India

100
120

80
100

60

40

20

0

-20
0

-60
-40

Inclusive Wealth Report
-60

1995

CHAPTER 2 Key Findings
1995

United Kingdom

40

20

-20

0

-40

-60
1 999

1 997
1 9 97

20

-20

0

-60
-40

60

Kenya

40

20

-20

0

-60
-40

60

Russia

40

20

-20

0

-60
-40
1994

1993

1992

1991

1990

2010

2009

2008

2 0 07

2006

2005

2004

2003

2002

2001

2000

1999

1998

1 9 97

1996

1995

1994

1993

1992

1991

1990

2 0 07
2008
2009
2010

20 07
20 0 820 0 920 1 0

2007
2008
2009
201 0

2007
2008
2009
201 0

2007
20 08
200 9
20 10

20 07

20 08

20 09

20 10

2005
2006

20 0 520 0 6

2005
2006

2005
2006

20 05
200 6

20 05

20 06

2003
2004

20 0 320 0 4

2003
2004

2003
2004

200 3
200 4

200 3

200 4

2001
2002

20 0 1
20 0 2

2001
2002

2001
2002

20 01
20 02

20 01

1999
2000

1999
20 0 0

1 999
2000

1 999
2000

1999
20 0 0

1999

20 00

200 2

1 9 971998

1 9 97
1998

1 997
1 998

1 997
1 998

1997
1998

1997

1998

1995

40
1996

Germany

1995

60
1996

-40

1 995

-60

1 996

0

1 995

-20

1 996

20

1995

1994

1993

1992

1991

19 9 020 1 0

20 0 920 0 820 07

20 0 620 0 520 0 420 0 320 0 220 0 1

20 0 0

1999

1998

40

1996

1 994

1 993

1 992

1 991

1 990

201 0

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1 999

1 998

1995
1996

Ecuador

1995

1 994

1 993

1 992

1 991

1 990

201 0

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1 995
1 996

1994

1993

1992

60

1996

1993

USA
1994

60

1993

Norway

1994

1 997
1 998

Japan

1992

1 995
1 996

1 993
1 994

France

1991

1990

2010

20 09

20 08

20 07

20 06

200 5

20 04

200 3

200 2

200 1

2000

1999

1998

1997

1996

1 993
1 994

1 992

1991

19 9 0Colombia

1992

1993
1994

1 992

1 991

Percentage change
Brazil

1991

1990

2010

20 09

20 08

20 07

20 06

20 05

20 04

200 3

200 2

200 1

20 00

1999

1998

1997

1996

80

1993

100

1994

80

1992

80

1992

100
1 990

80

1 991

100

1 990

Percentage change
80

1991

Percentage change
100

1990

Percentage change
80

1991

Percentage change
100

1990

Percentage change

100

60

Canada

40

20

-20

0

-60
-40

47

Wealth

48

1

1

0

0

1995

2005

2008

20 07

20 0 6

Scale: 1013

10
0

Germany80Nigeria2

Scale: 10110South Africa

2

Scale: 10

12

4

2

NorwayScale: 10
12

6

4
1

2
1 992

19 9 320 0 820 07

20 0 620 0 520 0 420 0 320 0 220 0 1

20 0 01999

1998

1 9 97

1996

1995

19 9 420 0 320 0 420 0 520 0 620 07
20 0 8

2003
2004
2005
2006
2007
2008

2003
2004
2005
2006
2007
2008

20 0 32004
20 0 52006
2007
20 0 820 0 320 04

20 0 5

20 06

20 07

20 0 820 0 1
20 0 2

2001
2002

2001
2002

20 0 1
20 0 220 0 11999
20 0 0

1 999
2000

1 999
2000

1999
200 0

1999

200 0

20 0 2

1 9 97
1998

1 997
1 998

1 997
1 998

1997

13

1998

Scale: 10

1997

United Kingdom

1998

1995
1996

1 995

19 9 419 9 319 9 2

1991

1990

1 996

1

1 995

12

1 996

Scale: 10

1995

Colombia

1996

1 993

6
1 994

1

1 993

12

1 994

Scale: 10

1993

India

1994

1 992

13

1 991

Scale: 10

1 990

1
2

1 991

China

1 990

2007
2008

0

1992

2007
2008

2005
2006

0

1991

2005
2006

2003
2004

2

1990

2003
2004

2001
2002

2

1995

2003
20 0 4

2001
2002

1 999
2000

4

1996

2001
2002

1 999
2000

1 997
1 998

4

1991

8

1993

1999
20 00

1 997
1 998

1 995
1 996

6

19 9 2
12

1994

1997
1998

1 995
1 996

1 993
1 994

6

1990

Scale: 10

1992

1995
1996

1 993
1 994

1 992

1 991

1 990

Australia

1991

1993
1994

1 992

1 991

Wealth
10

1990

20 08

20 07

20 0 620 05

20 0 4

20 03

20 02

20 01

200 0

1999

1998

1997

1996

2

1993

0

1994

8

1992

10

1992

0

1 990

2

1991

0

1990

Wealth2

1991

Wealth8

1990

WealthAppendix 2

Composition of the productive base by form of capital, 1990–2008.

(US$, year 2000).

10

BrazilScale: 10

12

Inclusive Wealth ReportWealth

0

1993

1995

CHAPTER 2 Key Findings

20 0 8

20 07

20 06

20 0 520 04

20 0 320 0 220 0 1

200 0

1999

1998

1997

1996

20 0 1

20 0 82007

2006

20 0 52004

20 0 320 0 2

2007
2008

13

Scale: 101
13

0

Russian Federation
5

4

0

United States

4

14

3

0

2007
2008

Kenya

Scale: 10
11

6

4
1

2
19 9 320 0 820 07

20 0 620 0 520 0 420 0 320 0 220 0 1

20 0 01999

1998

1 9 97

1996

1995

19 9 419 9 2

1991

1990

12

2

1

20 0 520 0 620 07
20 0 8

2005
2006
2007
2008

2005
2006
2007
2008

2005
20 0 6
20 07
2008

20 05

20 0 6

20 07

20 08

20 0 320 0 4

2003
2004

2003
2004

2003
20 0 420 03

20 0 420 0 1
20 0 2

2001
2002

2001
2002

2001
2002

20 01

1999
20 0 0

1 999
2000

1 999
2000

1999
20 00

1999

200 0

20 02

1 9 97
1998

1 997
1 998

1 997
1 998

1997
1998

1997

1998

1995

Scale: 10

1996

Venezuela
1 995

1
1 996

2
1 995

3
1 996

1

1995

12

1996

Scale: 10

1995

Saudi Arabia

1996

19 9 31
19 9 4

1

1 993

13

1 994

Scale: 10

1 993

1 992

1 991

1 990

France

1 994

1 992

Scale: 10

1 991

2005
2006

2

1 990

Japan

1993

Scale: 10
0

1994

2005
2006

2003
2004

11

Scale: 10

1992

2003
2004

2001
2002

2
2

1991

2001
2002

1 999
2000

Ecuador

1990

1 999
2000

1 997
1 998

0

1993

1999
200 0

1 997
1 998

1 995
1 996

0

1991

13

1994

1997
1998

1 995
1 996

1 993
1 994

1

19 9 2

Scale: 10

1992

1995
1996

1 993
1 994

1 992

1

1990

Canada

1991

1993
1994

1 992

1 991

1 990

Wealth
2

1990

2

1994

0

1992

2

1992

0

1 991

8

1 990

0

1991

10

1990

Wealth3

1991

Wealth4

1990

WealthKey
IWINatural Capital

Human Capital

Produced Capital

2

Chile

Scale: 101249

References

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Archives. Retrieved May 2011, from http://
www.imfstatistics.org/imf/

United Nations. (2011). National accounts
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Arrow, K., Dasgupta, P., Goulder, L., Mumford, K. & Oleson, K. (2012). Sustainability
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Bolt, K., Matete, M. & Clemens, M. (2002).
Manual for calculating adjusted net savings.
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v7_doco.asp

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Ricard, D., Minto, C., Jensen, O. & Baum, J.K.
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Sumaila, U., Marsden, A., Watson, R. & Pauly,
D. (2005). Global ex-vessel fish price database:Construction, spatial and temporal applications. The University of British Columbia:
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Hertel, T., Tsigas, M. & Narayanan, B. (2007).
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Inclusive Wealth ReportChapter 3

The significance of thenatural wealth of nations
Leonie Pearson, Pablo Muñoz, and Elorm Darkey

Key Messages
This first IWR focuses on quantifying components of natural capital that are largely driven
by those resources for which markets exist. It iseasier to obtain physical inventories and dataon these stocks.
Shadow prices would be an effective tool formeasuring an asset’s contribution to well-being
because they also reflect the relative importance of the different capital forms within thewealth accounting framework. The lack of suchshadow prices presents a significant shortcoming. So instead, this analysis relies on rental
prices, meaning market prices minus production costs of the resources.
Empirical findings show that almost all theselected countries (19 out of 20) experienced
a decline in natural capital per capita over theperiod of study.

We see that in almost all countries, potential
gains in renewable resources were not enoughto compensate for the depletion of exhaustible
stocks, like fossil fuels. The fishery is a specific illustration where, although a renewable
resource, fish are being “mined” at a rate thatchallenges renewal of the stock.
The general trend is that population has been
growing in most of the countries, exacerbating
thereby the decline in natural capital growth
rates, as resources are accounted for among alarger number of people.
The growth in population explains morethan half of the changes in natural capital per
capita in 13 out of 20 countries.

51

1. Introduction

2. Methodology

The aim of this chapter is to investigate the roleand significance of natural capital in the measure of inclusive wealth. The analysis builds on
Chapter 2 using the same data set – a 20-country
analysis of wealth from 1990 to 2008. Natural
capital in this report can be classified into the following two main categories: (i) non-renewable
resources; and (ii) renewable resources. Coal,oil, natural gas, and 10 minerals are includedin the non-renewable resource group while
agricultural land, forest resources, and fisheries
are included as renewable resources. We were
not able to use the ecosystem services typology developed by the Millennium Ecosystem
Assessment (MA) in this study due to the lack ofdata and the inconsistency of the MA’s typology
with economic valuation and accounting.
The report adds to the broader understanding of national wealth accounting by focusing
on natural capital within wealth estimates, andby expanding the scope of natural capital as used
by Arrow et al. (2012). New stocks in this capitalform are fisheries in the renewable resource
category – although, data for these resources
was available for only four countries - and coalin the non-renewable resource category. In thecase of coal, the data were quite extensive andthe key role coal plays for many of the countries
in this pilot report were significant to warrant
inclusion in the wealth accounts.1 Thus, it isintended that figures in this chapter provide
a better understanding of how capital assets
contribute to the sustainability of a country
and where investment might be needed if some
capital asset is being depleted to levels that cancause the overall wealth portfolio to decrease.

This section builds upon Chapter 2 and provides further insights into the measurementof natural capital. Natural capital is defined in
Chapter 11 as “everything in nature (biotic andabiotic) capable of contributing to human wellbeing, either through the production process
or directly.” Indeed, nature supplies every year
multiple benefits to human beings that, in one
way or another, influence people’s well-being.
This continuous flow of natural resources andservices stemming from them largely justify themainstreaming of nature as a form of capital.
Within the wealth accounting framework, natural capital is defined as the sum of the worthof all natural assets in a given country (Arrowet al. 2012).
This first Inclusive Wealth Report (IWR),
focuses on quantifying components of natural
capital that are primarily (although not only)
driven by those resources for which markets
exist, since it is easier to obtain physical inventories and data on these stocks. The natural assets
considered in this work are shared in Chapter
2, Box 1, where we also explore the inclusion offishery stocks and their changes over time. Thisis a new natural resource category consideredwhen compared to previous studies in wealthaccounting, including Arrow et al. (2012); andWorld Bank (2011);. Note also that Chapters 9
and 10 of this report explore methodologicallyand empirically wealth accounts for three regulating ecosystem services and water accounting, respectively. However, the high degreeof incompleteness of the estimates which is
required for the wealth accounts made the useof presently available data problematic.
Turning the focus onto the valuation sideof the assets, a key element in this regard isshadow pricing where externalities play a particularly important role. Shadow prices not only
measure the asset’s marginal contribution tohuman well-being, but also reflect the relative
importance of the different capital forms within
the wealth account framework, acting therefore
as a “weight” within the Inclusive Wealth Index

1 The inclusion of coal in this report will allow computing the environmental and health damage causedby the use of coal in future reports.

52

Inclusive Wealth Report(Arrow et al. 2012). Constructing the Index inthis way facilitates the conversion of different
asset forms into a common measure. However,the limited availability of such shadow prices
presents a significant shortcoming. While there
seems to be a growing literature on the social
prices of the carbon emissions (e.g., Tol 2009),
applications to other assets are rather scarce.
This points to a significant gap in our knowledge
base and highlights an area where a systematicand comprehensive research effort should betaken to begin compiling these missing shadow
prices for many of the non-market ecosystemservices. Due to this important limitation, we
confine our empirical work to the use of rental
prices, meaning market prices minus production costs of the resources, assuming that they
provide a first rough guidance on the relative
contribution of the different assets to sustaining social well-being.
One important step in the computationof the Index relates to the changes in market
prices over time. As mentioned in Chapter 2,
this study takes a static approach to these prices,that is, keeping them constant over time andrepresenting them by the average price over theperiod under study, being the only exception
manufactured capital. This is similar to otherworks in wealth accounting, for example Arrowet al. (2012) and Chapter 2 in this report. Froman environmental sustainability viewpoint, estimating the indicator in this way underpins theanalysis of physical changes in natural capitalover time, and in the overall productive baseof the economy. However, this also excludes
shadow prices being used as warning systems
when critical capital assets are approaching
thresholds and tipping points. If averages areused, this important element might be lost.
This approach is taken in this study as a first
approximation primarily because of the lackof shadow prices and the use of market prices.
Fluctuations in the market prices of many components of natural capital can be caused by avariety of reasons and not purely by increasing
scarcity and externalities.

Another important methodological issue isthe ranking of countries based on the net wealthmeasures across countries. While one may tend
to rank nations according to their net wealth, it
is not in principle advisable. The reason is that
we used market exchange rates in this study,
and not international dollars based on countries’
purchasing power parity (PPP). In principle, thispoint can be resolved by using international dollars. However, this would not affect the resultsof the changes in wealth estimates on an intracountry level, as it would move up or down theestimates of wealth, reflecting an identical proportional change in wealth over time.
There is another reason that one shouldbear in mind before doing a final conclusion onthese findings, which is the lack of an accepted
uniform approach for collecting natural capitaldata, resulting in “missing data points” for somecountries. In the case of minerals for example,
where data from the U.S. Geological Survey(2011a; 2011b; 2011c) were used, some nations
report production (extraction) statistics forthese accounts, but they do not supply information on the corresponding reserves, leading
us to exclude the respective mineral item in
the accounts. Countries where we found poor
data on mineral reserves are: Ecuador, France,
Germany, Kenya, Nigeria, Norway, Saudi Arabia,
South Africa, and the United Kingdom. In contrast, information on mineral reserves is quite
comprehensive for Australia and Canada. A
similar situation exists for fisheries. For the
20 countries studied, we found data available
in the RAM Legacy Stock Assessment Database(Richard et al., in press) on biomass stocks forfour of them. Even among these four countries,
the number of species assessed varies considerably. For the United States, for example, theRAM Legacy Stock Assessment Database reports
information for 80 commercial species in the
United States, but only about 10 species in thecase of South Africa, Australia, and Canada.

CHAPTER 3 The significance of the ‘Natural Wealth’ of Nations

53

0.5

Quadrant II

Natural Capital %JPN

Quadrant I
IWI %

0

2.5

2.0

1.5

1.0

0.5

-0.5

-1.0

-1.5

-2.0

RUS

FRA

-0.5

DEU
-1.0

CHN
CAN

USA

-1.5

AUS
VEN
NGA

-2.0

COL
ZAF

NOR
BRA
IND
ECU

-2.5

KEN

SAU

GBR

Quadrant III-3.0

Figure 1

Measuring per capita
changes in natural capitaland IWI: average annual
growth rates

3. The natural wealth of nations
What is the role of natural capital in inclusive
wealth?
Natural capital represents an essential pool ofresources that can induce the building of othercapital assets, such as education, health, or manufactured capital. Trends in wealth accounting
indicate that natural capital constitutes, on
average, about 30 percent of national wealthestimates for the country sample analyzed here
(see Chapter 2), but it ranges from 1 percent forFrance, Japan, and the U.K. to 65 percent, 66
percent, and 73 percent in Saudi Arabia, Russia,
and Nigeria respectively. In this section we start
presenting the average annual growth rates in
wealth and natural capital at a per capita level.
To facilitate the understanding of these per
54

CHL

Quadrant IV

capita growth rates, we classify the countries
into four groups regarding the growth (decline)
in wealth and natural capital (see Figure 1):• Increase in wealth and natural capital(quadrant I in Figure 1).
• Decline in wealth and increase in natural capital stocks (quadrant II in Figure 1).
• Decline in wealth and natural capitalstocks (quadrant III in Figure 1).
• Increase in wealth and decline in natural
capital stocks (quadrant IV in Figure 1).
In general, the empirical findings showthat most countries (13 of 20) experienced adecline in natural capital stocks over the periodof study, while achieving a growth in wealth(see quadrant IV in Figure 1). Another group ofcountries composed of six nations (Colombia,
Nigeria, Russia, Saudi Arabia, South Africa, andVenezuela) present the least desirable situation,
as they are experiencing a decline in wealth aswell as in natural capital. It is worth highlighting that all these countries have relatively large
resource pools of fossil fuels. Most of these countries even with a high growth rate of human andproduced capital were not able to have positive
IWI rates because of the huge drawdowns of
Inclusive Wealth Reportpopulation growth rate in relation to other
their natural capital base. However it must be
noted that population growth plus the high nations. This is to a large extent supported bydrawdown of natural capital caused many the recent assessment of Japan’s ecosystem sercountries to fall into unsustainable trajectories. vices (Duraiappah et al. 2012). However, before
any final conclusions can be made, it is worth
These results highlight the need to improve thetransformation process of their natural capital – mentioning that the role of trade related to thisoil, in this case – to human, produced and even country may provide important insights into
the understanding of Japan’s nature’s demands.
renewable forms of natural capital to achieve
Some key points on trade and natural resource
sustainability.
Additionally, no country in this sample depletion are explored in Chapter 5 (for further
exhibits a decline in wealth while increasing its details on growth rates see Table 1).
The analysis changes a bit if population
natural capital (i.e. quadrant II in Figure 1). An
inference from this early result might suggest growth is taken out of the calculations. First,
that increases in natural capital will notcome at the expense of a decline in over- Table 1
all inclusive wealth. This result might Measuring Changes in Natural Capital: Average Annual Growth
therefore refute the “environment at the Rates, 1990–2008
expense of development” argument seen
Naturalcommonly in the climate change debate.
NaturalCapitalChina surprisingly experienced a
Population
Capital Per
IWI Per
GrowthCapitaGrowthCapita(Decline)
Countries/
somewhat lower decline in natural capi(%)
(%)
(%)
(%)
Indicators
tal compared to India and Chile, coun-0.49
1.29
-1.78
0.12
tries whom, together with China, experi- Australia
enced some very high GDP growth rates
-0.26
1.38
-1.64
0.91
Brazilover the time period reported. China
Canada
-0.21
1.03
-1.24
0.37
also showed a strong Inclusive Wealth
Chile
-0.36
1.35
-1.71
1.19
Index (IWI) suggesting a positive sustainChina
-0.24
0.83
-1.07
2.07
able track. However, caution should beshown as the rate of increase in human
Colombia
-0.39
1.70
-2.09
-0.08
capital and produced capital has shown
Ecuador
-0.50
1.76
-2.26
0.37
signs of slowing down, highlighting
France
0.48
0.51
-0.03
1.44
again diminishing returns of transformaGermany
-0.47
0.23
-0.70
1.83
tion and that its continued drawdown of
India
-0.34
1.74
-2.08
0.91
natural capital cannot be sustained at
the current rate. Interestingly, Russia,
Japan
0.63
0.19
0.44
0.91
which showed a decline of -0.34 in natuKenya
0.05
2.79
-2.74
0.06
ral capital in absolute terms, showed that
Nigeria
-0.07
2.44
-2.51
-1.87
the natural capital per capita decline is
-0.96
0.67
-1.63
0.66
alleviated to -0.19 because of its declin- Norway
ing population.
Russia
-0.34
-0.19
-0.15
-0.31
Japan depicts the most favorable
Saudi Arabia
-0.08
2.72
-2.80
-1.12
situation, as it is experiencing wealthSouth Africa
-0.60
1.64
-2.24
-0.07
accumulation while at the same time
United Kingdom
-2.50
0.38
-2.88
0.88
increasing its natural capital stocks. Thishas been achieved primarily through
United States
-0.21
1.04
-1.25
0.69
investment in the forest sector. This
Venezuela
-0.14
1.99
-2.13
-0.29
position is also explained by a slower
CHAPTER 3 The significance of the ‘Natural Wealth’ of Nations

55

Figure 2 (left( left))Average annual growth rates disaggregated bynatural capital and population change
Figure 3 (right( right))

Average annual growth rates disaggregatedby natural capital and population change inFrance and Kenya

capital to increase its overall inclusive wealthas the marginal contribution of a single unit
increase in natural and human capital to IWI is
greater than a single unit increase in produced
capita.
Colombia, Nigeria, Saudi Arabia, South
Africa, and Venezuela move from quadrant III
to IV due to a positive turn in inclusive wealth.
In these contexts, demographic development
plays an important role in wealth change, anissue that will be addressed in answering thefollowing questions.

Percentage

Which components explain the decline (increase)in natural capital?

Key
NC

France and Kenya movefrom quadrant IV toquadrant I. While thelatter country presents
the highest population
growth rate (2.79 percent), France, has one of
the lowest rates (0.51 percent), only after Japan(0.19 percent), Germany (0.23 percent), and theUnited Kingdom (0.38 percent). Kenya moving
into quadrant I is not surprising and it illustrates
very clearly how its high population growthrate is unsustainable and highlights the needfor population policies to address this driverof unsustainability. The situation for France isslightly different. The key message emerging
from this analysis shows that France will needto increase its investment in natural and human
Population

Other factors

56

We can further explore the growth rates in natural capital by investigating what determinants
are influencing the previous results. We start
looking at the proportion that is attributed to thefive aggregated categories of the natural capital
accounts: agricultural and pasture land; forest
resources; fisheries; fossil fuels (oil, natural gas,and coal); and minerals. By doing so, we also
take into account changes in population overtime. This is important insofar as a decrease in
per capita natural wealth can be triggered either
by depletion of the natural resources considered
here, or because population grows faster thanthe change in natural capital, or both. Per capita
measures are commonly used for comparing
economies of different scale; in our analysis,
however, the per capita index of natural capitalis used to primarily show the pace at which thenatural resource endowment of each memberof the society is changing.
These results are illustrated in Appendix 1,
which indeed identifies demographic development as the main driver behind the changes innatural capital. On the average for this country
sample, population change explains 62 percentof the changes in natural capital. Moreover, thegrowth in population explains more than halfof the changes in natural capital per capita in
13 out of 20 countries. The demographic pressure on natural capital is particularly evident
for developing countries such as Kenya, Nigeria,
Inclusive Wealth ReportFrance, forest resources contribute positively tothe changes in per capita natural capital rates(65 percent and 49 percent respectively). The
initial results would point towards learning lessons from France and Japan who have been able
to increase forest cover. Other countries where
forest resources are relatively important are
China and the United States with rates in therange of 15 percent as shown in Figure 5. The
other components play in general a minor role,with the exception of minerals in Chile (21 percent), as well as agricultural and pasture landin Japan (18 percent). Fisheries, in comparison
to the other components, are still at a very low
level (less than 1 percent). In this context, it isimportant to bear in mind at least two aspects:(1) we account only for a few species due to data
constraints, therefore, the figure could change
once additional assessments of other species areadded; and (2) despite the low contribution in
Figure 4

Figure 5

Average annual growth
rates disaggregated bynatural capital and population change, with focus on
fossil fuels

Average annual growth
rates disaggregated bynatural capital and population change with a focus onforests

1.5

1.5

1.0

1.0

JPN
FRA

0.5

RUS

DEU

NOR

0.5

GBR

0.0

0.0

-0.5

-0.5

-1.0

-1.0

-1.5

-1.5

-2.0

-2.0

-2.5

-2.5

CHN

USA

Key

-3.0

-3.5

CHAPTER 3 The significance of the ‘Natural Wealth’ of Nations

Percentage

Natural capital
Percentage

and India, accounting for more than 90 percent
of per capita wealth change. Saudi Arabia, on
the other hand, even as a high-income country
due to its high population growth rate falls into
the same category as Kenya, Nigeria, and India.
Conversely, in two high-income economies –the United Kingdom and Japan – population
growth rates in the range of 12 percent showedminor effects in the changes in natural capitalas illustrated in Figure 2. In the light of thesefigures, it is not surprising that if we accountfor inclusive wealth without population adjustments, Kenya and France move into a positive
growth rate as shown clearly in Figure 3. Thereis, however, only one nation where demographic development contributed positively(about 33 percent) to the changes in natural
capital per capita – Russia. Population growthin Russia has been decreasing over the past two
decades; nevertheless, the relative decrease inpopulation has not been enough to outweighthe overall decline in natural capital. Therefore,
these findings empirically support the view that
increasing population will place a higher burden on a decreasing natural capital asset base.
Turning to the contribution of the natural
capital components, fossil fuels constitute thesecond main driver (21 percent) of changes innatural wealth. This can be attributed to thelack of data on many ecosystem services inthis report. The proportion varies considerably
depending on the natural resource composition of the countries. Fossil fuels explain, as
shown in Figure 4, a large part of the negative
growth rates in the United Kingdom (82 percent), which has been triggered by the depletionof natural gas. Similar are the cases of Germany,
Russia, and Norway, where in the former country the decline is caused by the decrease in coal,
whereas in the two latter economies it is mainly
due to natural gas. Interestingly, as a third driverin this sample appears a renewable resource,
forests, explaining on the average about 11 percent of the changes in natural capital on a percapita basis.
Discrepancies, however, are big among
countries. In economies such as Japan and-3.0

Fossil Fuels
Forests
Other factors

-3.5

57

How have different natural capital components
been changing during the past two decades?

Figure 6

Percentage change in natural capital,
1990-2008
20

JPN
10

FRA
0

-10

NOR

Percentage

-20

-30

GBR

-40
2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

Figure 7

Percentage change in fish stocks,
1990-2008
350
280
210

ZAF

140

Percentage

70
0

USA

-35

AUS
CAN

-70
2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

relative terms to natural wealth, it is of importance to have an understanding of this sort ofwealth and how it has been changing (declining) over time. The evolution in the components of natural capital is presented in the next
subsection.

58

In this section we exclude population from ouranalysis and observe movements in the natural
capital categories. We present an overview of
how each natural capital component, as well as
the aggregated (weighted) natural capital index
has been changing with respect to 1990 levels.
This analysis, when looked at a resource component level, provides us with information on thephysical changes in the underlying assets under
examination, as we used a constant rental priceover time for weighting the Index (see methodological annex). A first over view indicatesthat the Natural Capital Index (NCI) has been
mainly declining in the United Kingdom and
Norway with a negative change of 36 percent,and 16 percent with respect to the 1990 levels respectively. On the other hand, positivechanges were experienced by Japan and France
as previously mentioned, with increases of 12
percent and 9 percent respectively (see Figure6). In Annex 2, we additionally grouped the 18
natural resource types under study in the same
categories previously presented: agriculturalland, fisheries, forest resources, fossil fuels, andminerals. This analysis is presented in the following subsection.
Agricultural landThis category comprises two land types, cropland and pasture land, as defined by the FAO(2012). The major negative changes with respect
to the base year (1990) can be observed in Japan(12 percent) and Australia (10 percent), althoughfor different reasons. In Australia, the current
trend is explained by pasture land, while forJapan it is cropland. Conversely, Brazil experienced positive changes in this asset, with agricultural land expanding by 10 percent, with abalanced increase in both cropland and pastureland. However, the way in which these changes
affect the total NCI depends on how importantthese changes are with respect to the totalchange worth of the natural assets. Agriculturalland changes in Australia, Brazil, and Japan tend
Inclusive Wealth Reportto play a similar role in the natural capital index,
contributing about 25 percent of the changes in
the Index. In the case of Kenya, although cropland cover expanded by slightly over 2 percent
which might seem small for the time span analyzed, these changes influence largely the Index
as they explain about 70 percent of the changes
in natural capital.
Fisheries
Fisheries in this report, for reasons statedearlier, are a small part of the overall natural
capital of the four countries for which we havedata. However, there are expectations that thisresource will become more critical as we collect
more data on stocks and shadow prices of thisvaluable asset. In the present computations, thescarcity of fish resources and their impacts onfood security are not captured explicitly in theaccounts. It is an area for future research bothat the methodological and empirical level. The
data available for analysis were complex andwhile extensive in many areas, were limited toonly four countries and one common fishingzone. Within each country there was enormous
variation in the type of fish stocks assessed andhow prices were provided. The final analysis,using data from 1990 to 2006, consisted ofvarying fish stocks: 12 from Australia; 9 from
Canada; 10 from South Africa; and 40 from theUnited States.
Fish stocks presented in Figure 7 show thatall jurisdictions, except South Africa, have experienced declining fish stocks. South Africa’s fishery stock is attributed primarily to the introduction of two new stocks – anchovy and sardine– which grew significantly, and then declined
in 2003. While fish stocks can be managed as arenewable resource, the analysis shows that all
countries use them as an exhaustible resource
and fish stocks are “mined” over the period.
Forest resources
These accounts are built on the basis of two subcategories: the stock of timber commerciallyavailable in the country, and non-timber forest
services provided by the proportion of forest

stocks accessed by the population. Moreover,these two forest accounts move in the same
direction as they are linked to the forest surface
available. Empirical measures in forest wealthaccounts depict an interesting evolution ofthis natural capital category over the last two
decades. The forest accounts explain on average2 about a quarter (26 percent) of the changes
in natural capital that occurred in this period,
although with big fluctuations among countries. Interestingly, 10 out of 20 countries scoredan increase in forest resources, of which six ofthem are high-income countries (see Annex 2).
Forest accounts are of particular relevance inthe case of Japan and France, as they lead an
important part of the changes in natural capital
accounts, explaining 75 percent and 81 percentof the changes, respectively. On the other hand,seven countries showed a decline in this account,five of them with the lowest performance in thisregard are: Brazil (-7 percent), Ecuador (-26 percent), Kenya (-7 percent), Nigeria (-41 percent),and Venezuela (-10 percent). These changes
have been of major relevance for understanding the changes in natural capital for Ecuador,
Japan, and Brazil, where forest resources explain
about 89 percent, 71 percent, and 66 percent
respectively of the changes in the natural capital account when comparing with the 1990 levels. Forest stocks have remained constant to theforest resources assessments in Canada, South
Africa, and Saudi Arabia.
Fossil fuels
Before moving to the analysis of the exhaustible
resources categories – fossil fuels and minerals – it is important to bear in mind that basedon the method employed for the study of thesecomponents, non-renewable resources are bydefinition depleted if used and therefore can be
expected to decline in all countries. The results
suggest fossil fuels on the average, contributeto more than half (53 percent) of the changes
in the Natural Capital Index. However, in
2 This figure represents an average across countries,
with all countries weighted equally.

CHAPTER 3 The significance of the ‘Natural Wealth’ of Nations

59

the case of Saudi Arabia, Canada, the United
Kingdom, and Russia, fossil fuels contributed
99 percent, 92 percent, 91 percent, and 90 percent of the changes in the NCI of these countries
respectively.
The decline in fossil fuels is by itself only
part of the story. For example, the decline infossil fuels in the United Kingdom accounted
for about 59 percent of the decline withrespect to the base year, while in the case of
Saudi Arabia, the decline was only 1.5 percent.
Venezuela and Nigeria show a decline of 2
percent, and Ecuador a decline of 0.5 percent.
These differences in magnitude across thecountries indicate the size of reserves they haveof the resource base. Canada and Russia, whichhave relatively large resource bases, suffered adecline of about 10 percent with respect to the1990 level. On the other hand, there are othercountries that showed large declines in fossil
fuels such as France (69 percent) and Japan (40percent) during this time span. However, theselarge declines were of minor relevance within
the indicator, as fossil fuel explains less than
7 percent of the changes in natural capital inthese countries.
Minerals
The impact of declines in minerals was greatest for Chile which experienced a decline of 30
percent over the time period causing a change
of 79 percent to its NCI. This was caused primarily by the drawdown of its copper resources.
Canada, South Africa, and Australia were also
drawing down heavily their mineral resources
by approximately 47 percent, 27 percent, and 21
percent respectively. These declines in the mineral base caused declines in the overall natural
capital accounts by about 10 percent. Although
the United States and Colombia saw relatively
large declines in minerals by about 35 percent
and 48 percent respectively, the overall changes
in natural capital were substantially less at
about 3 percent.

60

Lessons learned for policy
Inclusive wealth offers policy-makers with acomprehensive accounting tool for measuring the assets available in the economy and itschanges over time. In this chapter as well as in
Chapter 2, we have analyzed several changes
in the productive base of the economy. In thisregard, natural capital tends to mostly exhibit
negative trends even if the productive baseof the economy increases. This is somehow
expected due to the trade-offs of, for example,
across exhaustible resources and the other capital forms. Trend lines illustrating downward
and upward movements in the various capital
assets can be useful for providing an overview
of how long can the drawdown of certain assets
continue and how efficient the transformation
has been in the past. In this realm, some of thechallenges regard investigating ways of getting
higher returns on its drawdown of natural capital by improving the total factor productivity(TFP), and the building up of higher levels ofhuman capital through programs to increase
literacy and employment rates in the country.
The same goes for providing closer attention toachieving high returns to produced and humancapital. This might indicate that thresholds arebeing approached, and that countries might becoming to a state where the transformation ofnatural capital is reaching diminishing returns
to scale. This insight is useful to policy-makers
in understanding the potential role and significance that natural capital has when countries
might adopt a portfolio management approach
to wealth, which is necessary for achieving sustainable development.
Let us take Kenya as an example. Although
agricultural land expanded over the past 19
years, the amount of this expansion was insufficient to account for the population increase
Kenya had also witnessed over that same period.
This calls for larger investment in expansion ofagricultural land but also an increase in forests,
which actually declined in Kenya over the sametime period. Policies focusing on managementof population growth, expansion of cropland,
Inclusive Wealth Report8

y = 0.312x + 0.167

42

y = 0.098x + 0.177
0-2

y = 0.015x2 - 0.309x - 1.381

-4
2007

2005

2003

2001

1999

1997

1995

This chapter has focused on the significanceof natural capital in estimates of wealth using
empirical insights. Understanding the constituent parts of the wealth estimate is critical indetermining the “best” portfolio management
approach for each country to achieve sustainable development (i.e., non-declining IWI). The
analysis provides policy-makers guidance on
which of the capital asset bases are declining
and where investment is required. It does notnecessarily always have to be investment in natural capital, and there might be instances whenthe IWI might suggest investments in humanand produced capital. It must be acknowledged

6

1993

What does a focus on natural capital tell us for
wealth estimates?

United Kingdom

1991

and increased forest cover can be seen as building blocks for addressing the food security situation in the country.
In the case of the United Kingdom, as
another example, decline in its natural capitalbase, with an average negative rate of 2.5 percent per annum, reaching the largest depleting
rate in 2000 with a magnitude of 3.5 percent,suggests the need for intervention strategies toreverse this decline, as shown in Figure 8
The decline was primarily driven by drawdown of its oil and natural gas resources. The
negative Natural Capital Index illustrates thatthe rate of transformation of this drawdownof its natural capital assets, in this case its oil
and gas, to human and produced capital were
inefficient and below par. However, a promising
sign is the upward trend seen in the build up of
its natural capital base through an increase inforest stocks.
Lessons can be derived from having a closer
look at Norway, (see Figure 9) which also saw
a decline in its natural capital asset base, again
driven by its drawdown of oil and gas resources.
But in spite of a larger population growth rate,
Norway exhibits a positive IWI. This can betraced back to a larger increase in its human andmanufactured capital base illustrating a higher
rate of return on its natural capital base.

that countries must also have Figure 8
the critical levels for human Transformation rate ofand produced capital to capital assets in the Unitedimprove the well-being of all Kingdom
its citizens.
Key
Essentially, the IWI has to beacknowledged as a measure of
Natural capitalweak sustainability (Neumayer
Manufactured capital
2010) and allows for the substiHuman capitaltution between different capiLinear/Polytals stocks, such as produced
and natural capital. On theother hand, strong sustainability requires (broadly) that natural capital isnon-substitutable with the other capital stocks(Daly 1995). As shown through our analysis, few
nations achieve this very strict criterion (see). Additionally, this strict criterion does notallow investment from one capital into another,
the essence of the portfolio line of attack to
wealth management as currently practiced (seeHamilton and Clemens [1999], Arrow et al.
[2012]; Dasgupta [2008]). However, this might
be a criterion that can be invoked once criticallevels of each capital are reached beyond which
un-sustainability becomes an endogenous property of country’s development path.

CHAPTER 3 The significance of the ‘Natural Wealth’ of Nations

61

6

Norway54

y = 0.229x + 0.156

32

y = 0.100x + 0.476

1

0

-1

y = -0.095x + 0.052
-2

-3
2007

2005

62

2003

Key

2001

Transformation rate of capital assets in Norway

1999

1997

1995

1993

1991

Figure 9

What limitations and uncertainties need to be resolved?

There are two key areas oflimitation in the current
chapter.
First are concepNatural capitaltual issues related to natural
Manufactured capital
capital in the IWI; second are
Human capitalmethodological issues.
Linear
A key limitation of the
IWI framework is its inability
to address two key concepts
in natural capital: first, how
critical is a type of natural capital; and, second,
the resilience of natural capital. As for “howcritical,” there are some natural capital stocks
that are so important to human well-being thatthey defy both measurement and substitution(Ekins 2003). These capital stocks are considered critical because they either contributeconsequentially to human well-being and/or
there is a moral obligation for society to preserve them (Pearson et al. 2011). These natural
capital stocks include: climate regulation, flood
regulation, fertile soil, biodiversity, drinking
water, etc. These have not been included inthis measure of wealth. However, Chapters 9
and 10 of the report address some of complexities related to their assessment. It is therefore
important for policy-makers to understand thatwhile the stocks of natural capital measured inthis analysis are important, the IWI presented inthis report does not account for fundamental
functioning of the earth’s ecological systems
and therefore other assessments are necessary
to guide their management.
The second issue is the resilience of natural
capital, or the fact that natural capital and its
underpinning ecosystems do not always behave
in linear ways, exhibiting marginal change
responses to large shocks. Natural capital stocks
sometimes experience hysteric responses and,as such, the consequences of declining a natural capital stock past a threshold of no returnis not a small change in value (Rokstrom etal. 2009). Conceptually, work by Walker et al.
(2010) tried to bridge this gap by including resilience of two critical capital stocks within the
inclusive wealth measure for a small catchment.
However the data and knowledge requirements
are so large, it has yet to be implemented yet atthe national level.
There are large methodological limitations
to the current analysis as discussed in the methodological annex. However this chapter has
highlighted that there is a porosity in the type ofdata that are internationally comparable on natural capital stocks and ecosystem services. This
results in not only “value” being derived fromonly tradeable goods, but also that the choice of
which stocks to measure is limited, ensuring abias or that a less-than-complete set of natural
capital stocks can be accounted. For example,
protected areas are assessed by the World Bankas the value of pastureland and crop land. This
opportunity cost approach is at best a minimum
proxy of these significant land parcels that, insome instances, house the last remaining habitat for endangered species. These types of proxymeasures and their associated capital stocks
have been excluded from the wealth accounts.
Although important, it was decided that they do
not contribute directly to the productive base of
the national economy, instead producing othergoods and services that are best measured andmanaged by other means. This might be a matterthat falls outside the realm of simple economic
Inclusive Wealth Reportdecision-making, but should exist in the domainof ethics and moral value theory.

Table 2

Understanding How Change in Wealth and Natural Capitalis Different When Considered in Absolute and Per Capita
Rates

4. Conclusion
This initial investigation of natural capital
within a wealth assessment has provided some
useful insights for policy-makers trying toachieve sustainable development and researchers trying to measure it.
Key findings are grouped into three areas.
First, it was shown that most countries experienced decreasing natural capital over the assessment period, ensuring that potential gains in the
renewable resources were not enough to compensate for the depletion trend of exhaustible
resources (e.g., fossil fuels). Second, countries canbe broadly grouped into three categories – 1 out
of 20 countries is in this category: (i) those experiencing growth in wealth and natural capital;(ii) those experiencing growth in wealth while
depleting natural capital – 13 out of 20 countries
are in this category; and (iii) those experiencing adecline in both wealth and natural capital – 6 out
of 20 countries are in this category. Third, population has been growing in most of the countries,
exacerbating thereby the declining in the natural
capital growth rates, as resources are accounted
for among a larger number of people.
These findings assert that natural capitalis central to the need to understand inclusive
wealth. It is not enough for policy-makers toknow that inclusive wealth is non-declining, as
not all countries are satisfied with achieving asustainable development path if it requires thedepletion of natural capital stocks. However,for other countries, these natural capital stocks
are exhaustible in any case, and their value may
be invested into other forms of capital – forexample, human capital (education) – to ensure
a long-term sustainable future. This examination of natural capital has shown the strength ofinclusive wealth as not only a leading indicatorof national sustainability, but also for its ability
to understand wealth at the level of each category of capital stocks.

Growth in wealth andnatural capital

Changes in IWI andin natural capital

Per capita changes
in IWI and natural
capital.

France

Japan

Japan
Kenya

Growth in wealth while‘mining’ natural capital

Australia

Australia

BrazilBrazilCanadaCanadaColombia

Chile

Chile

China

China

EcuadorEcuadorFranceGermany

Germany

India

India

Nigeria

Kenya

NorwayNorwaySaudi Arabia

U.K.

South Africa

U.S.

U.K.
U.S.
Venezuela
Decline in wealth andnatural capital

CHAPTER 3 The significance of the ‘Natural Wealth’ of Nations

RussiaColombia
Nigeria
Saudi Arabia
South Africa
RussiaVenezuela

63

Appendix 1

Average annual growth rates disaggregated by natural capital type

1.5

1.0

0.5

0.0

Germany

FranceJapan-1.0

Russia-0.5

Canada

China

-1.5

Chile

Brazil

NorwayUnited States

-2.0

-2.5

Percentage

-3.0

-3.5

64

Inclusive Wealth Report

Key
Cropland and pastureland
Fossil fuels
ForestMinerals
Fisheries
Population
1.5

Natural capital per capita

1.0

0.5

0.0

-0.5

-1.0

-1.5

Australia-2.0

Ecuador
Kenya

-3.5

CHAPTER 3 The significance of the ‘Natural Wealth’ of Nations

United Kingdom

Percentage-3.0

Saudi Arabia

NigeriaSouth Africa

Venezuela

Colombia

India

-2.5

65

Percentage

66

-5

-10

-15

-15

1997

1993

1995

20 08

20 07

20 06

20 05

20 04

200 3

200 2

200 1

20 00

1999

1998

1997

1996

Germany

1994

1999

200 8

2007

200 6

200 5

20 0 4

2003

2002

2001

20 00

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

200 8

2007

200 6

200 5

20 0 4

2003

2002

2001

20 00

1 997

2008

2007

2006

2005

2004

2003

2002

2001

2000

1 999

1 998

1 997

1 996

1 995

1 994

1 993

1 992

1 991

1 990

2008

2007

2006

2005

2004

2003

2002

2001

2000

1 999

1 998

-15

-50
-20

-60
-25

-70
-30

1 993

1 995

2008

2007

2006

2005

2004

2003

2002

2001

2000

1 999

1 998

1 997

1 996

1 995

1 994

1 993

1 992

1 991

1 990

2008

2007

2006

2005

2004

2003

2002

2001

2000

1 999

1 998

1 997

1 996

-20

-25

1993

20 0 820 07

20 0 620 0 520 0 420 0 320 0 220 0 1

20 0 01999

1998

1 9 97

1996

1995

1994

1993

1992

1991

19 9 0

20 0 820 07

20 0 620 0 520 0 420 0 320 0 220 0 1

20 0 01999

1998

1 9 97

1996

1995

1994

-15

-20

-25
-10

Chile

Colombia

20
-10

10
-20

0
-30

-10
-40

-20
-50

-30
-60

France

-5

-10

-15

-20
-40

-25
-60

India

Inclusive Wealth Report
-80

15

15

10

10

5

5

0

0

Percentage

-35

-40

1991

-10

Percentage

-10

-40

1 994

-15

1992

-5

Percentage

-5

-30

1 992

-30

19 9 0BrazilPercentage

Ecuador

1992

1997
1998

1 995
1 996

China

1991

1995
1996

1 993
1 994

0

-20

1 991

Canada

1990

20 08

20 07

20 06

20 05

20 04

200 3

200 2

200 1

20 00

1999

1998

1993
1994

1 992

-10

1 990

Percentage

Australia

Percentage

-5

-10

1995

25

1996

20

1993

-30

1994

5

1992

10

1992

30

1 991

40

1 990

0

1991

10

1990

Percentage
5

1991

Percentage
01990

Percentage

Appendix 2

Annual growth rates disaggregated by natural capital type

15

10

5

0

-5

10

5

10

0

40

0
20

0

-20

25

20

1995

1997

CHAPTER 3 The significance of the ‘Natural Wealth’ of Nations

1995

1997

200 5

1 999

1 996

1 995

1 994

1 993

1 992

1 991

1 990

2008

2007

2006

2005

2004

2003

2002

2001

2000

2005
2006
2007
2008

2005
20 0 6
20 07
2008

2003
2004

20 03
20 0 4

2001
2002

2001
20 02

1 999

0
2000

50

1999

150

200 0

100
1 997

250
1 998

200

1997

United Kingdom

1998

1996

1995

1994

1993

1992

1991

1990

200 8

20 07

20 06

1 997
1 998
1 999

2008

2007

2006

2005

2004

2003

2002

2001

2000

1 999

1 998

1 997

1 996

1 995

1 994

1 993

1 992

1 991

1 990

2008

2007

2006

2005

2004

2003

2002

2001

2000

19 9 920 0 820 07

20 0 620 0 520 0 420 0 320 0 220 0 1

20 0 01999

1998

1 9 97

1996

1995

1994

1993

1992

1991

19 9 0

20 0 820 07

20 0 620 0 520 0 420 0 320 0 220 0 1

20 0 0

Kenya

20

10

-10
0

-30
-20

-40

NorwaySaudi Arabia

-2

-4

-6

-8

-10

United States

10

-20

Venezuela

0
20

-10
10

-20
0

-30
-10

-40
-20

-50
-30

-0.8

-1.0

40
30
20
10
0
-10
-20
-30
-40
-50
-60
-70

-10

-8

-10

-12

Percentage

3
2
1
0
-1
-2
-3
-4
-5
-6
-7
-8

Percentage

1 9 9719 9 8Minerals

Percentage

1 997
1 998

19 9 519 9 6

Fisheries

Percentage

1 995
1 996

Fossil fuels

Percentage

2003
20 04

1 995

19 9 319 9 4

Forests

Agriculture

200 8

200 1
200 2

-1.6

1 996

1 993
1 994

19 9 2

1991

1990

Natural capital index

2007

200 6

200 5

20 0 4

20 03

20 02

2001

200 0

1999

1998

-40

1996

-30

1993

1999
20 00

South Africa

1994

1997
1998

-1.4

-16

1 993

Russia

1992

1995
1996

-1.2

-14

1 994

1 992

Nigeria

1991

1993
1994

-12

1 992

1 991

Percentage

Japan

1990

20 08

20 07

20 06

20 05

20 04

200 3

200 2

200 1

20 00

1999

1998

20

1996

30

1993

-50

1994

350

1992

300
1 990

2

1992

0

1 991

10

1 990

20

1991

Percentage
-50

1990

Percentage
30

1991

Percentage
40

1990

Percentage

Key

40

30

0.4

0.2

0.0

-0.2

-0.4

-0.6

0

-2

0

-4

-6

67

References

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and the measurement of wealth. Forthcoming in Environment and Development
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Beacon Press.
Dasgupta, P. (2008). Nature in economics.
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K., Watanabe, M. & Nishi, M. (2012). Satoyama
and Satoumi: Socio ecological production
landscapes of Japan. Tokyo: United Nations
University Press.
Ekins, P. (2003). Identifying critical natural
capital: Conclusions about critical natural
capital. Ecological Economics, 44, 277–292.

Walker, B., Pearson, L., Harris, M., Mäler,K.G., Li, C.Z., Biggs, R. & Baynes, T. (2010).
Incorporating resilience in the assessmentof inclusive wealth: An example from South
East Australia. Environmental and Resource
Economics, 45, 183-202.
United States Geological Survey. (2011).
Mineral commodity summaries. Retrieved May
2011, from http://minerals.usgs.gov/minerals/pubs/mcs/
United States Geological Survey. (2011).
Mineral yearbook: Volume I - Metals andminerals. Retrieved May 2011, from http://
minerals.usgs.gov/minerals/pubs/commodity/myb/United States Geological Survey. (2011).
Mineral yearbook: Volume III - Area reports: International. Retrieved May 2011, from http://
minerals.usgs.gov/minerals/pubs/country/index.html#pubsWorld Bank. (2011). The changing wealth ofnations. Washington, DC: World Bank.

Food and Agriculture Organizationof the United Nations. (2012). FAOSTAT.
Retrieved May 2011, from http://faostat.fao.
org/site/291/default.aspx
Hamilton, K. & Clemens, M. (1999). Genuinesavings in developing countries. The WorldBank Economic Review, 13 (2), 333-56.
Neumayer, E. (2010). Weak versus strong
sustainability: Exploring the limits of two opposing paradigms. Cheltenham, UK: Edward
Elgar.
Ollivier, T. & Giraud, P.N. (2011). Assessing sustainability, a comprehensive wealthaccounting prospect: An application to Mozambique. Ecological Economics, 70, 503-512.
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Clarifying protected and utilitarian valuesof critical capital. Ecological Economics, 73,
206–210.
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(in press). Evaluating the knowledge baseand status of commercially exploited marine
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68

Inclusive Wealth ReportChapter 4

Measuring inclusive wealth at thestate level in the United States
Kevin J. Mumford

Key Messages
This chapter is the first attempt to construct
an accounting of the capital assets of each of
the 48 contiguous U.S. states.
The study looks at four types of capital:
exhaustible natural capital (mainly coal, oil, andnatural gas); land; physical capital (like buildings, homes, and equipment); and human capital (based on education, wages, and number ofworking years remaining).
The results show a very low level of wealthinequality across states. The Gini coefficient is
0.09, which represents a fairly equal distribution of wealth.
The study demonstrates that the rate of
economic growth as measured by inclusive
wealth can be quite different than the rate of
economic growth suggested by GDP figures.
Data show that those states with high GDP
growth rates tend to have much lower rates ofinclusive wealth growth.

It is essential that governments collect capital stock data so that inclusive wealth accounting can become increasingly accurate, comprehensive, and useful. More complete data would
enable states to measure their rate of inclusive
investment. Such data would also make it clear
to policy-makers whether current GDP growth
rates are sustainable in the long-run.
The study’s use of housing and stock market
data to value physical capital is an important
contribution to the literature on sustainability.
An important conclusion drawn here isthat if states with an inclusive wealth per capita
annual growth rate that is less than their GDP
per capita annual growth rate want to sustain
higher GDP growth rates for the long term,increased inclusive investment will be required.
This means that state governments would haveto encourage education, reduce the extractionof natural resources, and increase constructionof public infrastructure.
69

1. Introduction
Economic growth is usually defined as theincreasing capacity to produce goods and services and is often measured by the growth ingross domestic product (GDP) per capita. While
GDP measures the value of the goods and services produced, it is not a direct measure of thecapacity to produce these goods and services.
To directly measure a change in the capacity
to produce goods and services would requirea measure of the growth in a comprehensive
accounting of all forms of capital (including
human capital). GDP may still be useful as ameasure of economic growth to the extent that
it is similar to the growth in the capital stock.
However, it turns out that these two measures
are the same only if the economy is following an
optimal growth path.1 If the economy is not on
an optimal growth path, then an income-based
measure like GDP could lead to qualitatively
different conclusions about economic growththan a direct measure of the growth of the capital stock.
Consider an economy that slows the rateof investment in capital and allows the capitalstock to depreciate over time. This diminishes
the economy’s capacity to produce goods andservices. However, the reduction in investment
allows for higher levels of consumption andthus GDP growth is not immediately influenced.
A direct measure of the change in the capitalstock would reflect this reduction in the capacity to produce goods and services straight away.
As a second example in which income-based
measures and capital-based measures give different results, consider an economy in which an
exhaustible resource is an input to production.2
1 For the capital stock growth rate to be the same as
the GDP growth rate in a simple model with an optimal
growth path, the production function must also exhibit
constant returns to scale.
2 An exhaustible resource is a commodity whose
available stock cannot be increased. See Dasgupta and
Heal (1974) for the derivation of the optimal consumption path in a production economy with an exhaustible
resource.

70

If the economy increased the amount of thisexhaustible resource used in production eachperiod, this would increase GDP but decrease thecapacity to produce goods and services in the
future, all other variables remaining the same.
How different the GDP growth rate is from thecapital stock growth rate is an empirical question. The purpose of this chapter is to construct
an accounting of the capital assets of each of
the 48 contiguous U.S. states. This capital-based
measure is called “inclusive wealth” or “comprehensive wealth” and represents a complete
accounting of all capital assets. The growth rateof the measure of inclusive wealth is computedfor each U.S. state from 1990 to 2000 and compared to the GDP growth rate. This comparison
is useful as an indicator of whether a given stateis over- or under-consuming. If the rate of GDP
growth exceeds the rate of capital stock growth,
the state is consuming at a rate where it will not
be able to sustain the rate of GDP growth in thelong term.
Though appealing as a measure of economic
growth, directly measuring the capital stock
is more difficult than measuring GDP because
there is no government collection of comprehensive capital stock data.3 Even when capitalstock data are available, many forms of capitalare not traded in markets and thus there is nomarket price at which to value these assets.
Some of these empirical difficulties have beenaddressed in work by Hamilton and Clemens(1999), Dasgupta (2001), Arrow et al. (2004),
World Bank (2004), Arrow et al. (2010), WorldBank (2011), and Arrow et al. (2012). This chapter is the first effort to apply the methodology
developed in this literature to U.S. states.
As this is an initial effort to use state-level
data to calculate inclusive wealth growth rates,
the empirical work is not comprehensive. This
chapter focuses only on a few of the most
3 Wealth accounting initiatives at the OECD, theWorld Bank, and the United Nations University are
working to make inclusive wealth data available toresearchers. However, none of these efforts arefocused on measuring inclusive wealth at the statelevel within the United States.

Inclusive Wealth Reportimportant forms of capital: human capital,
physical capital, land, and exhaustible resources.
The U.S. state-level data allow the incorporationof housing valuation and stock market measures that the prior literature has been unable
to use in comparisons across countries due toa lack of data.
The results from this empirical exercise
indicate that there are large and meaningful differences between measuring economic growththrough an income-based approach, like GDP, andmeasuring economic growth through an inclusive- or comprehensive- wealth-based approach.
The wealth-based growth rates are similar inmagnitude to the income-based rates, though
the correlation between them is negative.

2. Measuring inclusive wealth
While this paper does not expand on wealthaccounting theory, it offers a new application. A
short description of the theory is helpful before
explaining the methods employed. Following
Arrow et al. (2012), inclusive wealth at time t isdefined as the value of all capital assets:
Equation 1

W(t) = ∑ p i(t) K i(t)iwhere p i(t) is the shadow price or marginal valueof asset i at time t and Ki(t) is the amount ofasset i at time t. Non-decreasing wealth meansthat the economy has the capacity to produce
at least as much as in the past and is consistent
with the definition of sustainability that has
been adopted in the wealth accounting literature (e.g. Arrow et al. 2012). Inclusive investment is defined as the change in the value of all
capital assets holding prices constant:
Equation 2

I(t) = ∑ p i (t) (K i (t+1)–K i(t))
iInclusive investment can be defined over any
time period (month, quarter, year, or decade)as the data allow. A positive value for inclusive
investment in period t implies that the productive capacity of the economy is greater in period

t+1 than it was in period t. However, this does
not mean that the economy will enjoy higher
consumption indefinitely as future declines ininclusive wealth are possible if inclusive investment is negative in the future.
Technological change can be regarded as
yet another form of capital asset. As shown inArrow et al. (2012), if the rate of saving is small,the shadow price for the usual measure oftechnological change, total factor productivity(TFP), will be approximately one. Thus, the TFP
growth rate, R(t), can be added directly to inclusive investment:
Equation 3

I(t) = R(t) + ∑ p i (t) (K i (t+1)–K i(t))
i

To calculate inclusive wealth and inclusive
investment, one would need estimates of the stockof each capital asset at the beginning and the endof the time period being considered as well as the
shadow prices for each asset. For a non-renewable
resource such as oil, the change in the stock is
simply the negative of the amount extracted during the period. Ignoring externalities associatedwith the use, the shadow price corresponds to therental value, which is the price less the marginal
cost of extraction.4 Data on physical capital (buildings, machines, equipment) and land are generally
reported in dollars making the task of finding ashadow price unnecessary.
Human capital is more difficult to measure
directly. Following Klenow and Rodríguez-Clare(1997), the amount of human capital per worker
is defined as exp(rT), where r is the appropriate rate of interest, assumed to be 8.5 percent
per annum as in Arrow et al. (2012), and T is theaverage number of years of educational attainment. The stock of human capital is the humancapital per worker multiplied by the number ofworkers. The shadow price of a unit of humancapital is calculated as the total wage bill divided
by the total stock of human capital.
Population growth is assumed to be exogenous, has no effect on prices, and enters the
4 The average cost of extraction is generally used
due to data availability.

CHAPTER 4 Measuring Comprehensive Wealth in the United States71

production function multiplicatively. Under – oil, coal, and natural gas – as these are by far
these assumptions one can account for popu- the most valuable forms of natural capital.6 The
lation growth simply by measuring all capitalstate-level data for these resources are publicly
5
assets in per capita terms. In this chapter, all available from the U.S. Energy Information
forms of capital are ultimately valued in per cap- Administration. For each resource, provenita terms by dividing by the state population for reserves and quantity extracted are reported
the appropriate year. The assumption of exoge- for every year. Proven reserves are the known
nous population growth implies an assumption quantity that is economically recoverable given
current technology. While the estimated proventhat all migration is also exogenous.
reserve is available in every year, only the mostrecent year’s data are needed. Proven reserves
tend to increase over time as new resources are
3. Data and empirical results
discovered and new methods of extraction are
In this chapter, data are used from the period developed. This is true even after subtracting
the amount extracted. However, the stock of
1990–2000 to analyze economic growth in the
U.S. 48 contiguous states. Table 1 presents real energy resources is a non-renewable resource
GDP per capita by state in 1990 and 2000 and which means that it is non-increasing bythen calculates the annual growth rate. The definition.
Thus, the stock of the exhaustible resource,
state-level real GDP data were obtained fromthe Bureau of Economic Analysis, and the K(t), in year t is defined according to:state-level population data were obtained from
Equation 4
T-1
the U.S. Census Bureau. Both data series are
K(t)=K(T)+∑ X(j)j=tpublicly available. Over this 10-year period, theannual growth rates range from 4.5 percent in where X(j) is the total extraction for the state in
New Mexico to under 1 percent in Louisiana. year j and the most recent measure of proven
Though not reported in Table 1, note that each reserves is given by K(T). The most recent provenstate experienced some population growth reserves data is for 2009, so extraction dataover this 10-year period. North Dakota had thefor each state for years 1990–2008 are needed
smallest population annual growth rate at lessfor the calculation. The extraction data for oil,than 0.1 percent and Nevada had the largest at coal, and natural gas is also obtained from the
5.2 percent.
U.S. Energy Information Administration. The
The remainder of this section focuses on the
results are presented in Table 2.
calculation of inclusive wealth. The methods
The shadow price for each of these goods
and data used for each general type of capitalshould be state-specific as the extraction cost
asset are presented separately.
for the resource differs by state. However,state-specific estimates of the extraction costwere unavailable and so a U.S. average extrac3.1 Exhaustible natural capitaltion cost estimate from the World Bank (2006)
Exhaustible forms of natural capital include
non-renewable energy and mineral resources.
This chapter focuses on three energy resources

5 See Arrow, Dasgupta, and Mäler (2003) for a complete discussion of how population growth enters thetheory and the conditions under which per capita values can be used.

72

6 Future work could investigate the availability ofstate-level reserves and extraction data for a large
number of mineral types. Recent work by the WorldBank (2011) and Arrow et al. (2012) has shown thatminerals are not nearly as valuable as energy resources,
so it is unlikely that the result would be very different,
though this is just speculation that would need to be
confirmed by a more comprehensive accounting of all
forms of exhaustible natural capital.

Inclusive Wealth Reportdata appendix is used. This is an important
limitation as the cost of extracting oil, coal, andnatural gas in some states is far greater than inothers. The World Bank (2006) extraction costestimates are an average over various types of
U.S. extraction methods, not marginal costs. Asa simplification, each resource is assumed tobe homogeneous and an average price is used
for the 1990–2000 period. This yielded shadow
prices (average resource price less the average
extraction cost) of US$2.487 per barrel for oil;$1.90 per short ton for coal; and $0.19 per thousand cubic feet for natural gas.
Another important limitation in this study isthe disregard for capital gains. As explained inArrow et al. (2012), as non-renewable resources
are extracted the shadow price should increase
for the stocks that are still underground. Thus,
future consumers of non-renewable resources
should expect to pay higher prices and future
exporters of non-renewable resources should
expect to make higher profits. However, dataon the consumption and extraction behaviorof not only every state, but also of the rest of
the world would need to be obtained in orderto calculate the capital gains. This pursuit is left
for future research.

3.2 LandLand is clearly an important capital asset and,
fortunately, high-quality data are available
for land use by state. The U.S. Department ofAgriculture’s Natural Resources Conservation
Service conducts a survey of land use by state
every five years. Developed urban land is ignoredin this section as it should be captured in thevalue of housing and the value of physical business capital considered in Section 3.3. All federal
land is excluded from the present analysis as it
is not clear that this land should be counted as

7 All monetary values in this chapter are expressedin US$.

part of the wealth of the state.8 This leaves nonfederal rural land. Table 3 reports the amount of
non-federal rural land by state in thousands ofacres for 1990 and 2000.9
Across the 48 states considered in this study,
non-federal rural land declined by about 21 million acres from 1990 to 2000. Nearly 95 percentof this reduction in non-federal rural land wasdue to urbanization. The remaining 5 percent
was due to expansion of federal land and thecreation of new water areas. New water areas
include ponds, lakes, reservoirs, and estuaries.
These new water areas are excluded from theanalysis because of the difficulty in valuation.
The average quality of rural land differs
widely across states. The U.S. Department ofAgriculture’s National Agricultural Statistics
Service provides estimates of the average priceof an acre of rural land in each state. Not all
years are available, so rather than take an average price over the 1990–2000 period, this chapter uses the 1995 values. Using the average priceof an acre of rural land as the shadow priceimplies assuming that the land market is thickand that distortions from taxes and government
subsidies are small.
The average value of an acre of rural land ineach state, as well as the value of the change in
the amount of rural land (primarily reductions
due to development), are also reported in Table
3. The loss in rural land wealth for states thatexperienced a great deal of development would
likely be offset by gains in housing wealth andphysical capital, though this depends on the
8 The inclusive wealth of a state is the wealth owned
by all inhabitants of that state. Land owned by thestate government should obviously be included, but it
is not clear how land owned by the federal government
should be treated in the accounting. One option isthat the value of federal land could be divided equally
among all inhabitants of the country and thus assigned
to the states in proportion to the population. However,this is an enormous task that would likely have little
influence on the overall results.
9 The Natural Resources Conservation Service
reports land use in 1987, 1992, 1997, and 2002. The 1990
and 2000 land use reported here are linear approximations using the two adjacent land use values.

CHAPTER 4 Measuring Comprehensive Wealth in the United States73value of the rural land and housing market
prices.
It would be interesting to disaggregate therural land measure into its various component
types such as pastureland, cultivated cropland,non-cultivated cropland, and forest. Over time,
there is a great deal of conversion of one land
type to another within the rural land category.
However, average land values by sub-type andstate were unavailable. Conducting the analysis
with this finer level of detail would likely lead tosmaller total land value losses as states convert
less valuable rural land types into more valuabletypes. This gain is likely small compared to theloss from urbanization. Another limitation inthis study is that the value of various renewable resources, such as groundwater and fisheries, is not included. Though these renewable
resources are also likely small in value comparedto the forms of capital that are included, theselimitations point to the need for additional
empirical work.

3.3 Physical capital
Physical capital is the stock of all buildings,
homes, equipment, etc. Some of the stock ofphysical capital in a state is owned by investors
outside of that state. This notion of inclusive
wealth is the productive capital stock owned
by a given state’s residents.10 So, where possible,
this chapter allocates wealth based on ownership rather than location of the physical asset.
This implies that migration from one state toanother could have an important impact on
wealth calculations.11
The Bureau of Economic Analysis (BEA) publishes an annual estimate of the stock of fixed

10 This is similar to Arrow et al. (2012) where thephysical capital wealth estimates depended on theownership of physical capital, not the location of that
capital.
11 Migration of people with higher than average
wealth increases the wealth per capita of the destination state.

74

reproducible tangible wealth. This includes
estimates of the value of housing, consumer
durable goods, and financial assets owned byhouseholds and non-profit organizations lesshome mortgages and other household debt.
Assets owned by the government are includedin the estimates. The value of assets owned byfirms is not estimated directly as this should
be captured by the value of corporate equities,
equity in non-corporate business, and corporate
bonds. The BEA constructs these estimates using
the Federal Reserve Flow of Funds Accounts.
Unfortunately, the BEA only publishes physicalcapital estimates for the nation as a whole; nodata are available at the state level.
There is a great deal of state-level data on
housing wealth. This chapter uses the statelevel housing wealth series employed in Case,
Quigley, and Shiller (2005). These estimates of
housing wealth were constructed from repeat
sales price indexes, state-level home ownership rates, and the number of households ineach state. To simplify the analysis, all homes
are assumed to be owner-occupied. This is an
important limitation as about 30 percent ofhomes and apartments are rented rather thanowned by the resident. The home value dataalso includes the value of the land.
To value the physical capital contained inbusinesses, this chapter uses the stock market
holdings of all residents of the state. This allows
for businesses in one state to be owned by residents of another state. The state-level stock
market wealth series again comes from Case,
Quigley, and Shiller (2005). These stock market
estimates were constructed from the Federal
Reserve Flow of Funds Accounts. For equities
held by pension and mutual funds, the Surveyof Consumer Finances is used to distribute thewealth to households geographically. Checking
the state-level estimates against other data
would have been preferred, but no alternative
sources were known to the author.
Table 4 reports the housing and stock market
wealth value by state in 1990 and 2000. Notethat the stock market boom in the last half of the
1990s is likely responsible for an overvaluation of
Inclusive Wealth Reportthe true value of the physical capital owned bybusinesses. Using the book value rather than themarket value of companies may be a better measure, though this would neglect real increases inthe value of a business that are not captured by
the purchase price of physical capital.
Housing and stock market wealth accountfor about 70 percent of the BEA estimate of thestock of physical capital. The remaining wealthis due to durable consumer goods, savings
deposits, equity in non-corporate businesses,
and government assets. Because there is nostate-level source for these data, these types ofphysical capital in the analysis are ignored. Thisis similar to the treatment of non-energy formsof natural capital in Section 3.1 and the treatment of water areas in Section 3.2 and implies
that the results here are underestimates.
The value of urban land used by businesses
is included in the value of the business and thus
it would be double counting to have included
urban land data in the land calculations ofSection 3.2. A potentially important limitationis the double counting of the value of someenergy companies. To the extent that the state
has transferred ownership of non-renewable
resources to firms, there should be a reductionin the valuation of the non-renewable resource
discussed in Section 3.1.
Despite the limitations, using housing andstock market data to value physical capital is an
important contribution to the literature on sustainability. In particular, the stock market data
allow for wealth accounting by ownership rather
than by location. This is not a feature of the mostwidely-used OECD international capital stock data.

3.4 Human capital
The measure of human capital used here follows
methods developed by Klenow and RodríguezClare (1997) and Arrow et al. (2010). Using thismethod requires state-level data on the level of
educational attainment and an assumed rateof return on human capital. The state-level of
educational attainment data are obtained for1990 and 2000 from the U.S. Census Bureau.
Following Klenow and Rodríguez-Clare (1997)
and Arrow et al. (2010), the rate of return of
0.085 is used for all states, though this could bemade state-specific if there was empirical evidence suggesting that the rate of return differedby state.
The stock of human capital per capita in astate is defined as exp(.085 x T), where T is theaverage number of years of educational attainment in the state. The stock of human capitalper capita is reported by state in Table 5 foryears 1990 and 2000. The change in the stock ofhuman capital over time comes only from theincrease in the average level of education. Notethat all states experienced an increase in the
average level of education.
The shadow price of a unit of human capital is equal to the discounted sum of the wages
it would receive (the rental price) over the
expected number of working years remaining.
To arrive at this shadow price, the first required
step is to calculate the state-specific averageannual wage as the total wage bill for the state
divided by the number of workers. The total
wage bill by state is obtained from the Bureau of
Economic Analysis and the number of employees comes from the Bureau of Labor Statistics.
The average annual wage reported in Table 5 isthe average annual wage per worker (not perunit of human capital) in 1990. By dividing the
average annual wage per worker by the averagestock of human capital per worker, we arrive at
the rental price for a unit of human capital.
This rental price for a unit of human capitalis received each year over the number of working
years remaining with the rental price for futureyears discounted at the same rate assumed to be
the rate of return on education. The resulting
shadow price of a unit of human capital ranges
over states from about $120,000 to $200,000.
The value of the change in the stock of humancapital per capita is obtained by multiplying
this shadow price of a unit of human capital by
the difference in the stock of human capital per
capita between 1990 and 2000. This value ofthe change in the stock of human capital is then

CHAPTER 4 Measuring Comprehensive Wealth in the United States

75

MA

.03

FL

Inclusive wealth growth rate

ND

CT
WI

.02

PA

DEMD

.01

WA KS
ME
AL
OK

LA
NJ
NV

Per capita inclusive wealthand GDP annual growth
rates

MN

NY

RI

Figure 1MI

IA

Notes: The per capita inclusive wealthgrowth rate reported in Column (2) ofCO

Table 8 is plotted against the per capita

SD

MO
ILNE
OH
MS
TN

with the linear regression line.

OR

IN
NC UT
GA

SC
VACA WVAR
KY
VT
TX

NH
ID
AZ

0

WY
GDP growth rate

multiplied by the state population to arrive at
the total change in the value of human capitalfor the state as a whole and is reported in thelast column of Table 5.

3.5 Overall changes in capital: inclusive
investment
Table 6 reports the value of aggregate changes
in each of the forms of capital considered.
Exhaustible natural capital is depleted in moststates, but there is a great deal of heterogeneity with some states extracting trillions of dollars worth of energy resources over the 10-year
period and other states extracting nothing.
There is less heterogeneity in the decline in land
capital as nearly all states experienced some lossof rural land due to development with the largest decline occurring in Florida. While there arelarge gains in human capital, the gains in physical capital are nearly an order of magnitudelarger.

.05

.04

.03

.02

.01

Table 7 reports the valuechanges in each form of capital per capita. This not only
makes it easier to compare
states of very different sizes,
but also removes the effectof population growth. Again,
physical capital gains dominate the other forms of capital.
Somewhat surprisingly, thechange in inclusive wealth per
capita is found to be negative for Wyoming. Thisis because the gains in physical and human capital were not enough to overcome the US$54,000
per capita decline in natural resources over the
10-year period.
The final column of Table 7 reports thatannual total factor productivity (TFP) growthrate over 1990-2000 from Sharma et al. (2007).
As explained in Section 2, TFP can be thoughtof as another form of capital and because it has
a shadow price of one, the TFP growth rate canbe directly added to the growth rate of all otherforms of capital in dollars.
The annual growth rate for inclusive wealthis reported in Table 8. The first column reports
the inclusive wealth annual growth rate without accounting for population growth. The
second column reports the inclusive wealth per
capita annual growth rate. The third column
adds the TFP growth rate to the inclusive wealthper capita annual growth rate reported in column (2). Finally, the fourth column reports theGDP per capita annual growth rate to serve as
NM

MT

76

GDP growth rate for each state along

Inclusive Wealth ReportFL

Inclusive wealth + TFP
growth rate

LA

Notes: The sum of the per capita inclu-

DE

MN

NY

CT

PA MO

ME

growth rate reported in Column (3) of

KS
WA
AL
VA
CA
OK
SC

Table 8 is plotted against the per capita
GDP growth rate for each state along

IL

WI

ND
IA

OH

CO

MS
NE

.02

SD

TN

RI

with the linear regression line.

MA

MI

MD

sive wealth growth rate and the TFP

.03

VT

NV
NJ

KY

GAIN
UT
WVARTX

.01

0

.05

.04

CHAPTER 4 Measuring Comprehensive Wealth in the United States

.03

.02

.01

a comparison to the wealthNCMTgrowth rates reported in colOR
umns (2) and (3).
WY
ID
AZ
NH
The relationship between
the inclusive wealth per capita
annual growth rate and theGDP per capita annual growthrate is illustrated in Figure 1.
NM
This figure shows that there isa slightly positive relationshipbut a great deal of heterogeGDP Growth Rateneity. In general, GDP growthlevel inclusive wealth Lorenz Curve is createdexceeds inclusive wealth growth for all but ahandful of states. In New Mexico, for example, (see Figure 3). In this figure, all inhabitants of
the annual growth rate for GDP per capita is 4.5 a state are assumed to have the average levelof inclusive wealth of that state. The 45-degree
percent, the fastest growth rate in the U.S., while
the annual growth rate for inclusive wealth per line represents the percentage of total inclusive
capita is less than 1 percent, one of the slowest wealth in the 48 contiguous states owned by thatgrowth rates. However, this does not necessar- percentage of the total population if all states
had the same inclusive wealth per capita. The
ily imply that states are under-investing because
darker curved line represents the actual distriFigure 1 does not include productivity growth.
bution of inclusive wealth over the population.
Figure 2 illustrates the relationship of the
Figure 3 shows a very low level of wealthsum of the TFP annual growth rate and the inclusive wealth per capita annual growth rate with inequality across states. In fact, the Gini coefthe GDP per capita annual growth rate. The rela- ficient is 0.09 which represents a quite equaltionship is quite negative, implying that those distribution of wealth. Financial wealth in thestates with the highest GDP growth rates tend to U.S. over households is estimated to have a Gini
coefficient of 0.81, a very unequal distribution
have lower inclusive wealth growth rates.
of wealth (Bover 2010). It seems likely that the
distribution of inclusive wealth would have alower Gini coefficient than 0.81, though this is
3.6 State-level inclusive wealth inequality
just speculation. Regardless, it seems that only
The results can also be used to investigate state- a small amount of inclusive wealth inequality
level wealth inequality. By ranking each state by is due to state-level differences. It is likely thatits inclusive wealth per capita in 2000, a state-

77

Inclusive wealth growth rate

Figure 2

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%
100%

90%

80%

70%

60%

State-level inclusive wealthLorenz curve

50%

40%

30%

20%

10%

Figure 3

inclusive wealth inequality
across individuals within astate is much larger.

Notes: This Lorenz curve shows the
distribution of inclusive wealth across

4. Conclusion

states but not within states. In thisThis chapter has applied theinclusive wealth framework
are assumed to have the average
to U.S. states from 1990 tolevel of inclusive wealth in that state.
2000. The purpose is to apply
Calculations by the author.
this new approach of growthaccounting to an environment
with good data availability and reliability. One
important lesson is that the rate of economic
growth as measured by inclusive wealth canbe quite different than the rate of economic
growth implied by GDP figures. The negative
slope in Figure 2 is especially meaningful as it
implies that those states with high GDP growth
rates tend to have much lower rates of inclusive
wealth growth. This does not imply that any
state is currently on an unsustainable path as
all have positive inclusive investment per capita.
However, the negative slope in Figure 2 does
figure all individuals within a state78

imply that high GDP growth states are investingat much lower rates than low GDP growth states
on average.
There are significant data challenges which
limit applying the inclusive wealth theory
empirically, even in the U.S. where data reliability and available are quite good. Data limitations, particularly in the number of capital types
considered in the analysis and in the aggregation of capital assets into broad categories, aredescribed in the paper. One important policy
recommendation is for state governments tocollect capital stock data in order to perform
this type of inclusive wealth accounting. This
would enable states to measure their rate ofinclusive investment. Easy access to this typeof data would make it clear to policy-makers if
current GDP growth rates are sustainable in thelong-run.
Despite the data challenges, this exercise
produced empirical estimates of inclusive
wealth growth rates that provide meaningful
insights. The most important implication isthat states with an inclusive wealth per capita
annual growth rate that is less than their GDP
per capita annual growth rate should increase
inclusive investment in order to sustain higher
GDP growth rates in the long-run. State governments could increase inclusive investment byencouraging education, reducing the extractionof natural resources, and increasing the construction of public infrastructure.
It is hoped that other researchers will make
improvements to the methods used here byincluding additional forms of capital, disaggregating the forms of capital considered here, andby using more micro-data with the potential
to reduce the need for broad aggregation overindividuals. That the annual growth rates using
these inclusive wealth figures are so different
from those using the GDP figures is an indication that there is great potential for important
contributions in the area of growth accounting.

Inclusive Wealth ReportTable 1
Real GDPPer Capita
2000

Alabama$24,142$29,794$5,652

2.13%

Notes: GDP is in chained 2005 dollars. Data from the BEA andArizona$24,315$34,695$10,380

3.62%

the U.S. Census Bureau. Calculations by the author.

Arkansas$22,330$28,849$6,518

2.59%

California$34,654$43,254$8,6002.24%

Colorado$31,833$45,089$13,256

3.54%

Connecticut$43,245$54,302$11,057

2.30%

Delaware$52,008$59,595$7,587

1.37%

Florida$28,377$34,198$5,821

1.88%

Georgia$30,272$40,062$9,790

2.84%

Idaho

$20,349$30,329$9,9804.07%

Illinois$33,835$43,186$9,351

2.47%

Indiana$27,309$36,429$9,119

2.92%

Iowa

$26,559$35,957$9,398

3.08%

Kansas$29,203$36,359$7,156

2.22%

Kentucky$25,253$31,691$6,438

2.30%

Louisiana$34,264$37,597$3,333

0.93%

Maine

$27,092$32,603$5,511

1.87%

Maryland$34,122$39,486$5,364

1.47%

Massachusetts$35,288$47,355$12,067

2.98%

Michigan$29,386$37,282$7,896

2.41%

Minnesota$31,403$42,801$11,397

3.14%

Mississippi$20,722$26,679$5,957

2.56%

Missouri$28,675$36,530$7,855

2.45%

Montana$24,353$28,547$4,193

1.60%

Nebraska$29,558$38,028$8,4692.55%

Nevada$37,398$43,630$6,232

1.55%

New Hampshire$26,578$39,292$12,713

3.99%

New Jersey$39,714$46,647$6,934

1.62%

New Mexico$20,669$32,144$11,475

4.51%

New York$38,207$45,438$7,231

1.75%

North Carolina$29,683$39,155$9,472

2.81%

North Dakota$24,201$33,130$8,930

3.19%

Ohio

$29,153$37,761$8,608

2.62%

Oklahoma$26,597$31,937$5,3401.85%

Oregon$23,155$35,338$12,183

4.32%

State

Real GDP
Real GDPPer Capita Per Capita
Change Growth Rate

Real GDP per capita growth rate by state

Real GDPPer Capita
1990

Pennsylvania$29,543$36,828$7,2852.23%

Rhode Island$30,905$36,504$5,5991.68%

South Carolina$26,173$32,512$6,3392.19%

South Dakota$23,817$35,533$11,716

4.08%

Tennessee$26,931$34,735$7,803

2.58%

Texas

$31,887$41,659$9,772

2.71%

Utah

$26,386$35,488$9,102

3.01%

Vermont$26,273$32,738$6,4652.22%

Virginia$34,069$41,977$7,908

2.11%

Washington$36,029$43,839$7,8101.98%West Virginia$21,455$27,422$5,966

2.48%

Wisconsin$28,088$37,061$8,973

2.81%

Wyoming$39,314$46,844$7,5301.77%

CHAPTER 4 Measuring Comprehensive Wealth in the United States

79

Table 2

Exhaustible natural capital
Notes: Data from the U.S. Energy Information Administration.
Oil is measured in millions of barrels; natural gas is measured
in billions of cubic feet; and coal is measured in millions ofshort tons. Calculations by the author.

State

1990

Oil
Extracted
1990–2000

Coal
1990

Coal
Extracted
1990–2000

Natural Gas
1990

Natural Gas
Extracted
1990–2000

Alabama

180

90

4,546

247

9,046

Arizona

0

0

327

119

0

0

Arkansas

169

79

102

1

15,280

1,819

California

8,116

2,899

50

1

7,985

2,539

Colorado

716

251

16,585

240

39,100

4,676

Florida

95

56

0

0

97

58

Georgia

0

0

50

0

0

0

Idaho

0

0

50

0

0

0

Illinois

288

134

9,967

491

0

0

Indiana

44

18

9,967

320

0

0

Iowa

0

0

2,200

0

0

0

Kansas

1,029

429

406

4

13,322

6,059

Kentucky

69

30

32,062

1,563

4,251

657

Louisiana

1,973

1,007

471

33

48,956

14,771Maryland

0

0

480

37

0

0

Michigan

206

115

50

0

6,683

1,777

Mississippi

632

202

128

1

2,869

1,016

Missouri

0

0

6,016

12

0

0

Montana755

160

119,796

394

2,427

497

3,057

Nebraska

73

41

0

0

0

0

New Mexico

1,913

636

12,532

262

43,172

13,097

North Carolina

0

0

50

0

0

0

New York

0

0

0

0

771

189

North Dakota
Ohio
Oklahoma

0

0

9,507

304

2,089

468

156

74

23,628

290

2,838

1,145

1,935

780

1,533

17

55,746

16,976

Oregon

0

0

50

0

0

0

Pennsylvania

40

13

28,329660

10,046

1,353

South Dakota

0

0

50

0

0

0

Tennessee

0

0

471

42

0

0

Texas

13,977

5,330

13,179538

184,70747,230

Utah

719

170

5,688

244

12,073

1,570

Virginia

0

0

2,167

380

4,487

433

Washington

0

0

1,383

48

0

0

West Virginia

52

19

35,140

1,627

9,679

1,709

1,750

724

68,1482,491

59,387

7,959

Wyoming80

Oil

Inclusive Wealth ReportRural Land
Area

Rural Land
Area

1990

2000

AverageValue
per AcreAlabama

29,389.5

28,705.4$1,613-$1,103.2

Arizona

40,937.2

40,778.3$1,075-$170.9

Arkansas

28,799.3

28,434.4$1,258-$459.2

Notes: Land is reported in thousands

California

48,720.5

47,415.6$282-$367.5of acres. The value of the change inColorado

41,123.1

40,820.9$666-$201.1

Connecticut

2,157.6

2,064.5$7,616-$709.0

Delaware1,030.2

980.8$3,123-$154.4

Florida27,371.5

26,008.8$2,701-$3,680.5

Georgia

31,960.9

30,619.5$1,613-$2,163.5

Idaho

18,847.4

18,567.0$1,075-$301.5

Illinois

32,049.2

31,690.2$2,330-$836.3

Indiana

20,380.9

20,066.1$2,074-$652.8

Iowa

33,731.9

33,567.1$1,728-$284.9

Kansas49,832.3

49,626.0$685-$141.3

Kentucky

22,706.8

22,175.0$1,600-$850.9

Louisiana

24,935.1

24,600.0$1,382-$463.2

Maine

18,940.7

18,751.8$1,446-$273.2

Maryland

4,967.6

4,685.1$3,968-$1,120.8

Massachusetts

3,607.4

3,273.3$6,477-$2,164.2

Michigan

29,812.5

29,102.7$1,702-$1,208.4

Minnesota

45,641.0

45,291.4$1,216-$425.1

Mississippi

26,768.1

26,304.2$1,134-$526.1

Missouri

39,596.8

39,166.0$1,126-$485.2

Montana

65,077.1

65,036.9$355-$14.3

Nebraska

47,377.0

47,270.2$742-$79.3

Nevada10,214.1

10,049.9$370-$60.8

New Hampshire

4,451.8

4,316.9$2,880-$388.5

New Jersey

3,135.1

2,825.2$8,960-$2,777.2

New Mexico

50,556.9

50,129.7$268-$114.3

New York

26,897.9

26,349.9$1,638-$897.8

North Carolina

25,582.0

24,398.2$2,240-$2,651.7

North Dakota

41,601.0

41,444.4$477-$74.8Ohio

22,486.1

21,847.6$2,240-$1,430.2

Oklahoma

41,004.2

40,701.6$700-$211.9

Oregon29,079.4

28,796.3$1,080-$305.9

Pennsylvania

24,642.7

23,753.4$2,816-$2,504.3

Rhode Island

465.6

445.1

$8,320-$170.6

South Carolina

16,483.8

15,823.5$1,715-$1,132.5

South Dakota

44,553.6

44,438.1$387-$44.6

Tennessee

22,959.3

22,218.2$1,715-$1,271.1

Texas

158,454.2

156,840.3$672-$1,084.5

Utah

17,549.4

17,618.0

$909

$62.4

Vermont

5,211.8

5,125.5$1,856-$160.2

Virginia

20,342.8

19,744.5$2,202-$1,317.2

Washington

28,791.7

28,318.7$1,370-$647.9

West Virginia

13,459.4

13,102.7$1,178-$420.0

Wisconsin

30,644.3

30,311.3$1,331-$443.3

Wyoming

32,855.9

32,784.5$246-$17.5

State

CHAPTER 4 Measuring Comprehensive Wealth in the United States

Total
Value of
ChangeTable 3

Non-federal rural landvalue

rural land is reported in millions of 2005
dollars.

81

Table 4

State

Physical capital

Alabama
Arizona

Housing Wealth Housing Wealth Stock Market
Stock Market
1990
2000
Wealth 1990
Wealth 2000
$59,507.7$84,224.8$50,004.4$133,836.4$77,664.9$130,482.6$90,729.0$262,553.1

Notes: The value is measured in mil-

Arkansas$28,330.7$37,328.6$31,520.7$71,681.1

lions of 2005 dollars.

California$1,327,167.8$1,344,377.8$742,211.8$2,010,736.0

Colorado$74,425.9$159,984.6$152,113.5$522,204.7

Connecticut$156,864.0$141,777.2$116,999.0$423,787.2

82

Delaware$20,286.8$23,382.2$27,625.1$68,840.9

Florida$285,305.0$373,479.7$351,464.3$1,613,398.7

Georgia$121,092.1$194,106.5$101,459.6$276,799.1

Idaho$14,933.9$27,518.8$22,017.6$59,188.9

Illinois$262,500.6$345,320.9$314,871.4$836,122.2

Indiana$88,394.7$130,318.2$103,464.3$240,530.4

Iowa$35,738.1$49,749.5$83,855.9$229,912.3

Kansas$37,551.2$45,737.1$90,522.1$193,811.9

Kentucky$48,844.9$74,839.6$53,536.9$96,028.2

Louisiana$60,281.6$80,441.7$59,790.1$128,326.9

Maine$25,562.8$25,689.5$25,411.6$60,588.7

Maryland$166,633.4$186,286.0$140,308.9$326,424.2

Massachusetts$219,328.2$237,960.5$226,781.6$1,023,827.5

Michigan$171,723.2$252,387.7$265,080.2$721,585.0

Minnesota$90,747.9$138,077.0$185,931.4$620,933.4

Mississippi$29,210.8$41,121.3$24,998.3$81,407.9

Missouri$86,748.6$116,565.6$176,251.2$426,377.5

Montana$10,185.0$17,180.7$22,388.0$61,556.2

Nebraska$21,758.5$31,234.9$55,940.1$129,394.9

Nevada$26,556.9$51,321.9$22,683.8$88,132.4

New Hampshire$32,676.0$34,157.9$30,355.3$77,861.0

New Jersey$318,604.7$308,545.8$577,153.3$812,277.8

New Mexico$26,209.0$42,290.3$28,859.4$77,076.2

New York$444,422.7$442,301.0$609,043.2$1,996,242.9

North Carolina$117,904.9$172,848.3$111,551.8$282,736.7

North Dakota$6,606.6$8,403.9$13,259.8$53,275.0

Ohio$205,327.7$277,324.5$287,050.9$653,173.7

Oklahoma$42,246.3$53,825.9$48,006.5$118,799.3

Oregon$51,798.4$98,752.5$74,811.3$208,450.4

Pennsylvania$273,139.5$286,023.3$314,506.8$866,540.5

Rhode Island$32,431.2$29,258.3$22,153.5$61,670.1

South Carolina$56,203.9$80,698.6$42,308.9$104,826.6

South Dakota$6,911.8$10,245.6$19,402.9$49,856.8

Tennessee$79,389.4$118,926.5$75,021.2$198,577.0

Texas$266,619.0$365,907.7$301,788.2$694,792.7

Utah$29,735.5$69,962.9$30,065.7$83,887.6

Vermont$11,600.7$11,702.0$26,638.2$37,763.1

Virginia$174,970.3$194,299.9$150,218.4$324,737.7

Washington$136,665.6$214,529.6$138,605.6$368,360.6

West Virginia$23,754.0$30,513.2$19,235.4$47,028.6

Wisconsin$81,210.5$121,490.9$140,439.7$418,154.2

Wyoming$6,315.1$10,079.6$16,364.8$29,134.4

Inclusive Wealth ReportStatePer Capita
Per Capita
Average
Value of
Table 5
Human Capital Human Capital Annual Wage Change in
US$
Human Capital Human capital
1990
2000

Alabama

2.79

2.87

$39,969$22,925.8

Notes: The value of the change in

Arizona

2.90

2.95

$43,551$17,833.9

human capital is measured in millions

Arkansas

2.76

2.84

$36,382$12,778.4

of 2005 dollars.

California

2.92

2.97

$56,101$124,622.2

Colorado

3.01

3.09

$48,326$30,984.5

Connecticut

2.99

3.07

$57,889$27,353.3

Delaware

2.91

2.98

$48,695$5,211.0

Florida

2.86

2.93

$42,837$83,482.6

Georgia

2.85

2.95

$45,166$62,943.0

Idaho

2.87

2.94

$39,480$5,776.8

Illinois

2.90

2.98

$49,681$93,822.0

Indiana

2.84

2.91

$41,514$33,641.1

Iowa

2.86

2.94

$37,268$15,957.5

Kansas2.92

3.00$40,806$15,750.7

Kentucky

2.76

2.85

$39,475$23,303.6

Louisiana

2.80

2.86

$39,758$17,258.2

Maine

2.88

2.96

$39,600$7,143.7

Maryland

2.98

3.07

$50,254$39,998.9

Massachusetts

2.99

3.10

$54,686$65,028.8

Michigan

2.86

2.94

$48,688$70,336.0

Minnesota

2.93

3.02

$45,264$41,342.2

Mississippi

2.77

2.83

$35,841$10,145.8

Missouri

2.85

2.93

$42,288$34,547.2

Montana

2.90

2.98

$35,529$4,213.8

Nebraska

2.90

2.98

$38,743$10,004.7

Nevada2.84

2.88$45,029$7,072.3

New Hampshire

2.96

3.04

$43,828$7,822.3

New Jersey

2.94

3.03

$54,963$69,080.9

New Mexico

2.89

2.95

$39,850$6,081.8

New York

2.92

3.00

$56,937$129,579.0

North Carolina

2.82

2.92

$41,916$59,764.1

North Dakota

2.86

2.93

$34,950$3,297.5

Ohio

2.85

2.93

$43,822$75,764.4

Oklahoma

2.85

2.91

$39,944$12,523.7

Oregon2.92

2.99$43,573$18,134.9

Pennsylvania

2.86

2.94

$45,092$82,707.0

Rhode Island

2.88

2.96

$44,629$6,346.2

South Carolina

2.81

2.89

$39,706$22,745.3

South Dakota

2.85

2.94

$33,436$3,942.4

Tennessee

2.79

2.88

$40,321$34,681.3

Texas

2.87

2.92

$45,492$80,703.3

Utah

2.95

3.01

$40,274$9,166.4

Vermont

2.96

3.05

$39,112$3,821.2

Virginia

2.93

3.03

$49,184$58,633.1

Washington

2.95

3.03

$50,814$37,676.8

West Virginia

2.75

2.82

$38,317$7,804.1

Wisconsin

2.87

2.95

$40,726$36,256.4

Wyoming

2.90

2.96

$39,080$2,078.0

CHAPTER 4 Measuring Comprehensive Wealth in the United States

83

Table 6

Change in comprehensive wealth (millions of 2005 dollars)
Notes: The value of the change in human capital is measured in millions of 2005 dollars.

Natural Capital
2000–1990

Land Capital
2000–1990

Physical Capital
2000–1990

Human Capital
2000–1990

Total Change
2000–1990

Annual Growth
Rate

Alabama-$1,629.8-$1,103.2$108,549.2

Arizona-$289.4-$170.9$224,641.9$22,925.8$128,742.0

1.24%$17,833.9$242,015.5

Arkansas-$695.6-$459.2

1.81%$49,158.2$12,778.4$60,781.8

1.07%

California-$9,821.3

Colorado-$2,517.6-$367.5$1,285,734.3$124,622.2$1,400,167.7

1.25%-$201.1$455,649.8$30,984.5$483,915.6

2.97%

Connecticut-$709.0$291,701.4$27,353.3$318,345.7

2.19%

Delaware-$154.4$44,311.2$5,211.0$49,367.8

1.72%-$3,680.5$1,350,109.0$83,482.6$1,429,719.3

3.19%-$2,163.5$248,353.8$62,943.0$309,133.3

1.36%

State

Florida-$191.8

Georgia
Idaho
Illinois-$1,619.4

Indiana-$835.4

Iowa-$301.5$49,756.2$5,776.8$55,231.5

1.77%-$836.3$604,071.0$93,822.0$695,437.3

1.69%-$652.8$178,989.6$33,641.1$211,142.5

1.28%-$284.9$160,067.8$15,957.5$175,740.4

2.10%

Kansas-$2,844.9-$141.3$111,475.7$15,750.7$124,240.2

1.56%

Kentucky-$4,056.2-$850.9$68,486.1$23,303.6$86,882.6

0.86%

Louisiana-$6,868.8-$463.2$88,696.9$17,258.2$98,623.1

0.97%-$273.2$35,303.9$7,143.7$42,174.4

1.22%-$90.0-$1,120.8$205,768.0$39,998.9$244,556.1

1.42%-$2,164.2$815,678.2$65,028.8$878,542.8

3.20%-797.2-$1,208.4$537,169.3$70,336.0$605,499.7

1.93%-$425.1$482,331.0$41,342.2$523,248.1

2.86%
1.39%

Maine
Maryland
Massachusetts
MichiganMinnesota
Mississippi-$890.7-$526.1$68,320.1$10,145.8$77,049.1

Missouri-$29.2-$485.2$279,943.3$34,547.2$313,976.1

1.87%

Montana-$1,586.9-$14.3$46,163.9$4,213.8$48,776.5

0.94%

Nebraska-$130.1-$79.3$82,931.1$10,004.7$92,726.4

1.77%-$60.8$90,213.6$7,072.3$97,225.1

1.68%

NevadaNew Hampshire-$388.5$48,987.6$7,822.3$56,421.4

1.46%

New Jersey-$2,777.2$225,065.7$69,080.9$291,369.4

0.87%

New Mexico-$5,841.0-$114.3$64,298.2$6,081.8$64,424.7

1.42%

New York-$46.0-$897.8$1,385,078.0$129,579.0$1,513,713.2

2.19%-$2,651.7$226,128.3$59,764.1$283,240.7

1.33%

North Carolina
North Dakota-$853.1-$74.8$41,812.3$3,297.5$44,181.9

2.18%

Ohio

-$1,218.6-$1,430.2$438,119.5$75,764.4$511,235.1

1.50%

Oklahoma-$6,645.6

OregonPennsylvania$82,372.3$12,523.7$88,038.5

1.10%$180,593.1$18,134.9$198,422.1

2.02%-$2,504.3$564,917.4$82,707.0$643,144.7

1.74%

Rhode Island-$170.6$36,343.7$6,346.2$42,519.3

1.42%South Carolina-$1,132.5$87,012.4$22,745.3$108,625.2

1.15%South Dakota-$44.6$33,787.7$3,942.4$37,685.5

1.96%

Tennessee-$1,975.4-$211.9-$305.9-$102.1-$1,271.1$163,093.0$34,681.3$196,401.1

1.37%

Texas

-$29,712.2-$1,084.5$492,293.3$80,703.3$542,199.9

0.98%

Utah

-$1,514.8

Vermont
Virginia$62.4$94,049.3$9,166.4$101,763.3

1.72%-$160.2$11,226.2$3,821.2$14,887.2

0.84%
1.09%

-$1,029.5-$1,317.2$193,848.9$58,633.1$250,135.3

Washington-116.7-$647.9$307,619.0$37,676.8$344,531.2

1.80%West Virginia-4,432.8-$420.0$34,552.5$7,804.1$37,503.8

0.82%-$443.3$317,995.0$36,256.4$353,808.1

2.18%-$17.5$16,534.2$2,078.0$8,303.0

0.26%

Wisconsin
Wyoming

84-$10,291.7

Inclusive Wealth ReportTable 7

Change in comprehensive wealth per capita (2005 dollars)
State

NaturalCapitalLand
CapitalPhysicalCapitalHuman
Capital

Total
Change2000–1990

AnnualGrowthRate

TFP
GrowthRate

2000–1990

2000–1990

2000–1990

2000–1990

Alabama-$676-$1,309$21,932$11,871$31,819

1.24%

1.45%

Arizona-$118-$3,478$30,300$7,952$34,656

0.99%

0.25%

Arkansas-$491-$2,033$15,280$11,029$23,785

0.99%

0.99%

California

-$399

-$65

$29,601$8,602$37,738

1.02%

1.56%

Colorado-$4,315-$2,007$89,052$13,996$96,726

2.04%

0.72%

Connecticut-$387$82,506$16,155$98,273

2.22%

1.08%

Delaware-$914$45,660$12,392$57,139

1.35%

2.14%

Florida-$17-$1,301$74,902$11,809$85,393

2.55%

1.52%

Georgia-$4-$1,922$23,013$15,938$37,025

1.07%

1.08%

Idaho

-$27

-$4,665$30,204$10,323$35,835

1.19%

0.06%

Illinois

-$305

-$587

$44,550$15,521$59,180

1.65%

1.13%

Indiana

-$524

-$777

$26,341$11,214$36,254

1.22%

0.96%

Iowa

-$98

-$1,160$52,484$10,794$62,020

2.07%

1.14%

Kansas-$1,294-$1,136$37,330$11,701$46,601

1.45%

1.39%

Kentucky-$2,890-$1,076$14,475$12,754$23,263

0.85%

1.00%

Louisiana-$1,793-$560$18,257$8,999$24,903

1.03%

2.54%

-$1,014$26,153$11,837$36,976

1.31%

1.84%

-$608

$32,565$16,292$48,208

1.34%

1.80%

-$550

$124,179$19,532$143,161

3.14%

0.61%

Maine
Maryland-$40

Massachusetts
Michigan-$97

Minnesota-$474$50,919$15,041$65,389

1.94%

1.74%

-$1,488$90,770$15,398$104,680

2.55%

0.93%

Mississippi-$424-$1,305$21,986$8,796$29,053

1.35%

1.26%

Missouri

-$249

-$831

$45,546$12,569$57,034

1.76%

1.42%

Montana-$43,909-$3,320$46,441$10,769$9,981

0.16%

1.37%

Nebraska-$87-$1,769$44,596$10,986$53,725

1.64%

0.90%

Nevada-$1,258$28,691$6,887$34,320

0.75%

1.35%

New Hampshire-$1,509$33,614$12,576$44,6811.30%-0.17%New Jersey
New Mexico-$8,323-$619$17,467$17,294$34,142

0.79%

1.23%

-$1,533$29,326$8,166$27,6350.94%-0.73%New York

-$3

-$175

$69,841$15,001$84,664

2.21%

1.18%

North Carolina-$3-$1,844$21,920$15,265$35,338

1.12%

0.56%

North Dakota-$1,552-$303$65,023$10,063$73,230

2.30%

1.01%

Ohio

-$346

-$331

$36,551$13,470$49,345

1.57%

1.29%

Oklahoma
OregonPennsylvania-$2,585-$872$21,301$8,460$26,304

1.04%

1.48%

-$7

-$1,922$45,249$11,210$54,5291.62%-0.15%

-$351

-$389

$44,415$14,532$58,206

1.86%

1.27%

Rhode Island-$331$32,206$13,313$45,187

1.51%

0.78%

South Carolina-$1,335$17,956$12,228$28,849

1.07%

1.44%
0.83%

South Dakota-$14-$1,990$41,760$10,432$50,189

1.83%

Tennessee-$51-$1,370$24,098$12,709$35,385

1.22%

1.15%

Texas

-$2,744-$1,215$17,292$8,557$21,889

0.68%

1.30%

Utah

-$3,200-$2,086$33,979$8,524$37,215

1.12%

0.87%

-$1,537$13,367$12,793$24,622

0.79%

1.39%

Vermont
Virginia-$273-$1,089$20,722$16,674$36,033

0.98%

1.70%

Washington-$137-$1,485$42,440$13,896$54,714

1.43%

1.34%

West Virginia-$2,847-$303$18,930$10,606$26,386

1.02%

0.92%

-$813

$55,199$12,794$67,180

2.04%

1.13%

-$1,498$29,366$8,684-$17,918-0.26%

1.55%

Wisconsin
Wyoming-$54,470

CHAPTER 4 Measuring Comprehensive Wealth in the United States

85

References

Table 8Annual growth ratesState

Inclusive Wealth
Total (1)Per Capita (2) +TFP (3)GDP Per
Capita (4)Alabama

1.24%

1.24%

2.69%

2.13%

Arizona

1.81%

0.99%

1.24%

3.62%

Arkansas

1.07%

0.99%

1.98%

2.59%

California

1.25%

1.02%

2.58%

2.24%

Colorado

2.97%

2.04%

2.76%

3.54%

Connecticut

2.19%

2.22%

3.30%

2.30%

Delaware

1.72%

1.35%

3.49%

1.37%

Florida

3.19%

2.55%

4.07%

1.88%

Georgia

1.36%

1.07%

2.15%

2.84%

Idaho

1.77%

1.19%

1.25%

4.07%

Illinois

1.69%

1.65%

2.78%

2.47%

Indiana

1.28%

1.22%

2.18%

2.92%

Iowa

2.10%

2.07%

3.21%

3.08%

Kansas

1.56%

1.45%

2.84%

2.22%

Kentucky

0.86%

0.85%

1.85%

2.30%

Louisiana

0.97%

1.03%

3.57%

0.93%

Maine

1.22%

1.31%

3.15%

1.87%

Maryland

1.42%

1.34%

3.14%

1.47%

Massachusetts

3.20%

3.14%

3.75%

2.98%

Michigan

1.93%

1.94%

3.68%

2.41%

Minnesota

2.86%

2.55%

3.48%

3.14%

Mississippi

1.39%

1.35%

2.61%

2.56%

Missouri

1.87%

1.76%

3.18%

2.45%

Montana

0.94%

0.16%

1.53%

1.60%

Nebraska

1.77%

1.64%

2.54%

2.55%

Nevada

1.68%

0.75%

2.10%

1.55%

New Hampshire

1.46%

1.30%

1.13%

3.99%

New Jersey

0.87%

0.79%

2.02%

1.62%

New Mexico

1.42%

0.94%

0.21%

4.51%

New York

2.19%

2.21%

3.39%

1.75%

North Carolina

1.33%

1.12%

1.68%

2.81%

North Dakota

2.18%

2.30%

3.31%

3.19%

Ohio

1.50%

1.57%

2.86%

2.62%

Oklahoma

1.10%

1.04%

2.52%

1.85%

Oregon

2.02%

1.62%

1.47%

4.32%

Pennsylvania

1.74%

1.86%

3.13%

2.23%

Rhode Island

1.42%

1.51%

2.29%

1.68%

South Carolina

1.15%

1.07%

2.51%

2.19%

South Dakota

1.96%

1.83%

2.66%

4.08%

Tennessee

1.37%

1.22%

2.37%

2.58%

Texas

0.98%

0.68%

1.98%

2.71%

Utah

1.72%

1.12%

1.99%

3.01%

Vermont

0.84%

0.79%

2.18%

2.22%

Virginia

1.09%

0.98%

2.68%

2.11%

Washington

1.80%

1.43%

2.77%

1.98%

West Virginia

0.82%

1.02%

1.94%

2.48%

Wisconsin

2.18%

2.04%

3.17%

2.81%

Wyoming

0.26%-0.26%

1.29%

1.77%

86

Arrow, K.J., Dasgupta, P. & Mäler, K.G. (2003).
The genuine savings criterion and the valueof population. Economic Theory, 21(2), 217-225.
Arrow, K., Dasgupta, P., Goulder, L., Daily,G., Ehrlich, P., Heal, G.,…Walker, B. (2004).
Are we consuming too much? The Journal of
Economic Perspectives, 18 (3), 147-172.
Arrow, K.J., Dasgupta, P., Goulder, L.H.,
Mumford, K. & Oleson, K. (2010). China, theU.S., and sustainability: Perspectives basedon comprehensive wealth. In G. Heal (Ed.)
Is economic growth sustainable? London:
Palgrave Macmillan.
Arrow, K.J., Dasgupta, P., Goulder, L.H.,
Mumford, K.J. & Oleson, K. (2010). Sustainability and the measurement of wealth.
NBER Working Paper No 16599.
Bover, O. (2010). Wealth inequality andhousehold structure: U.S. vs. Spain. Review ofIncome and Wealth, 56(2), 259-290.
Case, K.E., Quigley, J.M. & Shiller, R.J. (2005).
Comparing wealth effects: The stock market
versus the housing market. Advances in Macroeconomics, 5(1), 1.
Dasgupta, P. (2001). Human well-being andthe natural environment. Oxford: Oxford
University Press.
Dasgupta, P. & Heal, G. (1974). The optimal
depletion of exhaustible resources. Review of
Economic Studies, 41(1), 3-28.
Hamilton, K. & Clemens, M. (1999). Genuinesavings in developing countries. The WorldBank Economic Review, 13 (2), 333-56.
Klenow, P.J. & Rodríguez-Clare, A. (1997).
The neoclassical revival in growth economics: Has it gone too far? In B. Bernanke &J. Rotemberg (Eds.) NBER macroeconomics
annual 1997. Cambridge, MA: MIT Press.
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(2007). Decomposition of total factor productivity growth in U.S. states. Quarterly Review of Economics and Finance, 47(2), 215-241.
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World Bank. (2011). The changing wealth ofnations: Measuring sustainable development in
the new millennium. Washington, DC: WorldBank.

Inclusive Wealth ReportChapter 5

Are national economies (virtually)sustainable?: an empirical analysis ofnatural assets in international trade
Giles Atkinson, Matthew Agarwala and Pablo Muñoz

Key Messages
This chapter explores the impact of international trade on sustainable development andthe measurement of genuine (or adjusted net)savings at both the global and domestic levels.

Specifically, the chapter uses a disaggregated multi-regional input-output model (MRIO)
to measure the value of resource depletion andthe social costs of carbon emissions in the context of international trade.

The chapter draws crucial distinctions
between production- and consumption-based
approaches to measuring changes in inclusive wealth, as well as between the notions ofdomestic and global sustainability, where thelatter is defined in terms of the global genuinesavings rate.

The term “virtual sustainability” is introduced here as a way to consider the implicationsof trade and the role of consumption in understanding a country’s contribution to global
sustainability.

By looking only at per-country inclusive
wealth accounting, we potentially weaken our
understanding of global performance. The chapter addresses this by examining how changes inresource wealth are embodied in internationallytraded goods and services.

Our empirical findings indicate that themagnitudes of the (change in) natural assets
embodied in trade can be substantial, both indollar value terms and in relation to national
economies. This could challenge both the conventional thinking on sustainability and theclaims of progress made on this front by individual countries.

87

1

Introduction

The proposition that an extended net – orgenuine – saving has a central place in any
portfolio of indicators purporting to measure
the sustainability of development appears now
to be firmly established (UNECE 2007; Stiglitz,
Sen and Fitoussi 2009; World Bank 2010).
Nevertheless, a number of outstanding issues
remain. Chief among these is a question as towhether (or how) international trade affects theway in which we should think about measuring
the development prospects of individual (butopen) economies.
There are several candidate mechanisms
whereby trade might influence sustainable
development (Dupuy 2011; Oleson 2011). These
include: the capital gains (or changing termsof trade more generally) on traded extracted
natural resources (Vincent, Panayotou andHartwick 1997) as well as remaining resource
stocks (Arrow et al. 2010); and the possibilityof trade in resources at prices which are “too low”
(Oleson 2011) perhaps because trade encourages
resource depletion to be “too fast” (e.g., Klepper
and Stähler 1998). In addition, considerations
about “openness” also includes transboundary
pollution where countries impose burdens oneach other and this, in turn, has implications
for the distribution of (comprehensive) wealth(Hamilton and Atkinson 1996; Arrow et al.
2010).
Common to all of these concerns is theimpression that these interactions alter insome way the comprehensive wealth accounting problem for individual countries. Reflecting
on these implications is important for at least
two reasons. First, the sustainability prospects
for an individual country might be misjudged if
its own wealth accounting neglects these concerns. Secondly, this neglect could misrepresent
the way in which an individual country contributes to global sustainability. In the words ofthe recent authoritative report by Stiglitz et al.
(2009) in focusing exclusively on per country
measurement “… we miss the global nature ofsustainability” (p.69).
88

It is this contribution of countries and regions
to this global sustainability that is primarily the
focus of this chapter. We develop this theme
through an extension of the growing literaturethat uses input-output approaches to model theway in which (changes in) resource wealth andenvironmental liabilities are embodied in goods
and services traded across national boundaries.
Our specific contribution is two-fold:First, we investigate the value of resource
depletion (such as the extraction of sub-soil
assets) as well as the social costs of carbon dioxide emissions within a relatively disaggregatedmulti-regional input-output model (MRIO).
Previously, much of this literature has either
focused upon the quantities of carbon emissions only (or some other pollutant) (see, for areview, Wiedmann [2009]) or has resorted torelatively highly aggregated models in the caseof natural resources (Atkinson and Hamilton
2002).
Second, we use our results to comment on
the contribution of individual countries (andregions) to global sustainability, where the lattercan be estimated as the global genuine savingrate in a particular year. We argue that examining the magnitudes of the values of natural
assets that countries consume tells us something distinct about their “virtual sustainability.”
There are clear parallels between the notion ofvirtual sustainability and the recent literature(e.g., Davis and Caldeira 2010; Atkinson etal. 2011) on virtual carbon (i.e., embodied carbon). However, the links to concerns about the
influence of trade on the sustainability of development represent a useful extension of thisthinking.
Our results show that taking account ofthese trade interactions gives a rather different perspective on the “over-consumption” ofindividual countries in relation to global sustainability. Moreover, the empirical magnitudeof the natural resource flows or environmental
liabilities in international trade appears to be
substantial. We also find that the notion ofembodied – that is, virtual – (un)sustainability may shed a cautionary light on economies
Inclusive Wealth Reportclaiming to have made progress on this front,
particularly if this progress is due to changes
in trade patterns. The introduction of the term
“virtual sustainability” here, we argue, offers apotentially valuable lens through which therelationship between trade and sustainability
can be explored.
The rest of this chapter is organized as follows. The next section reviews a broad range ofliterature on which our more specific contribution is premised. Section 3 discusses virtual sustainability vis-à-vis international trade. Section 4
sets out our methodological framework, including a description of the model and the data that
we use. Section 5 presents and critically reflects
on our results. Section 6 concludes.

2	Literature review
At the heart of most definitions of sustainable
development is a common concern about theway in which the fruits of development areshared across generations. For example, Pezzey(1989) states that development is sustained along
a development path if welfare does not decreaseat any point along the path. Moreover, there isincreasing evidence of a consensus around theidea that the sustainability of development canbe understood through an emphasis on wealthand what is happening to wealth, broadly construed to include natural assets (see, for example, UNECE [2007]; Stiglitz et al. [2009]; andWorld Bank [2010]). The question of measurability has long been central to this focus. In
particular, there is concern about the degree towhich current systems of economic indicators
fail to signal clearly that the economy is on anunsustainable path. It follows that if these indicators are lacking in this vital respect, then the
result is that potentially misleading signals may
be translated into policy errors.
An integral element of this measurement
debate has been the way in which current decisions about consumption and saving have an
impact upon future welfare and, in particular,
how novel but measurable indicators (of what

is happening in the “here and now”) can shedlight on prospects for future welfare. Pearce andAtkinson (1993) were among the first to posit apractical linkage between sustainable development and a measure of national wealth that was
expanded to include natural assets. If sustainability is a matter of maintaining levels of welfare, then Pearce and Atkinson proposed that
this was in turn a question of maintaining total
wealth and this could be measured by savings
rates adjusted to reflect depletion and environmental degradation.
Subsequently, Atkinson et al. (1997) and
Hamilton and Clemens (1999) have updated
both the theoretical argument linking savingsand sustainability and the empirical estimationof adjusted net savings rates – dubbed “genuine”
saving to distinguish it from traditional national
accounting measures of net saving – for a wide
range of countries. The World Bank has been
publishing estimates of genuine saving as partof its World Development Indicators since 1999
(see, in addition, World Bank [2010]).1 As a practical matter, genuine saving is defined in thesepublications as gross saving plus investments inhuman capital (proxied by education expenditures) minus the depreciation of produced capital as well as changes in certain natural assets.
The latter specifically include natural resource
depletion and liabilities caused by emissions ofgreenhouse gases and particulate matter.
Important contributions by Dasgupta and
Mäler (2000) and Asheim and Weitzman (2001)
have also established further theoretical foundations to this focus on genuine saving and,more broadly, comprehensive wealth accounting.2 The link to sustainability here is that an
economy should avoid negative genuine saving
1 In fact, World Development Indicators (and other
World Bank publications) refers to this indicator as“adjusted net saving.” However, we retain the term
“genuine saving” throughout given that this is the predominant terminology in the broader literature.
2 Dasgupta and Mäler (2000), for example, show thatnet investment is equal to the change in social welfare in a non-optimizing framework where a resource
allocation mechanism is used to specify initial capital

CHAPTER 5 Are national economies (virtually) sustainable?

89if development is to be sustained: if future
declines in well-being are to be circumvented.
Hamilton and Hartwick (2005) and Hamilton
and Withagen (2005) establish a general policy
rule for sustainability. If genuine saving isalways positive and not growing too quickly
then a development path is sustainable.3
While the importance of this savings indicator appears now to be firmly established,
the process of getting to this point has also
been accompanied by a significant debate.
Importantly, the crucial issue of resource substitutability remains largely unanswered. Put
simply, we still know little about the extent
to which sustainability requires that a general
portfolio of assets be managed sensibly or amore specific focus on sustaining stocks ofcertain (critical) resources (although see, forexample, Krautkraemer [2005] and Markandya
and Pedroso-Galinato [2007]). In addition, avariety of extensions and caveats in measuring
genuine saving (and in wealth accounting) havebeen developed to address changing populations (Dasgupta 2001; Hamilton 2003), technological progress (Weitzman and Löfgren 1997),
and international trade. It is this last issue thatis the focus of this chapter.
A comprehensive review of the possible relationships between trade and sustainability isprovided by Dupuy (2011). While this indicates anumber of candidate linkages, the focus within
the wealth accounting literature has been far
narrower. Much of the discussion has focusedon assessment of how future capital gains
arising from resources affect the way in which
income or genuine saving should be measured
now (see, for example, Sefton and Weale[1996] and Hartwick [1994]). That is, if resource
prices are increasing (decreasing) then this has
stocks can be mapped to future stocks and flows inthis economy.
3 Specifically, this means that genuine saving mustgrow at a percentage rate less or equal to the interest rate over a development path. Thus, for example,
a constant and positive rate of genuine saving will
ensure that both current utility and the present valueof utility are increasing everywhere along the path.

90

the effect of boosting (shrinking) the genuinesaving rate of a resource exporter (Vincent,
Panayotou and Hartwick 1997) and vice versa
for importers. Hamilton and Bolt (2004) estimate these capital gains for a large cross-sectionof resource exporting countries and, in doingso, indicate that these magnitudes tend not belarge (i.e., less than 1 percent of gross national
income or GNI) although, in some part, this is
explained by the apparent lack of a statisticallysignificant price trend for oil resources. Arrowet al. (2010) add further empirical insight to thiswork by estimating the capital gains “earned” byresource stocks in the ground.
This emphasis on capital gains (or losses) isa somewhat different focus than that implicit in
the question posed by, for example, MartinezAlier (1995) in his initial observation that estimates of genuine saving tended to suggest thatunsustainable countries were located (for themost part) in the developing world. The link
to trade, in turn, arose from Martinez-Alier’s
later speculation about whether an “ecological balance of payments” analysis would showthat developed countries were actually unsustainable because those economies are relatively
dependent on the import of resources fromdeveloping nations. Proposals for adjusting thesaving rates of importing and exporting countries to take account of these international flows,
however, need to be treated with care. Atkinson
and Hamilton (2002), for example, express reservations at this interpretation in arguing thatthe onus is on resource extracting countries tomake provision for the loss of their domestic
natural assets whether for export or not.
This is not to say, however, that there is norationale for adjusting saving rates in the presence of international trade. Stiglitz et al. (2009),
for example, note the potential for a disparity
between the (market) price at which some natural resources are traded and the actual scarcity
value of these resources. What this means is that
if no such mismatch exists then the fact that a
resource is traded implies no further insights
about how depletion should be accounted
for in the genuine saving of either exporter or
Inclusive Wealth Reportimporter. The genuine saving of the exportershould be measured to reflect the fact that thevalue of an asset that it owns has declined. For
the importer, the value of resource imports
already appears as a negative entry in the country’s net foreign balance. Nevertheless, if theresource is traded at a price below its actual
scarcity value then, by implication, the importerhas not fully compensated the exporter in making this exchange.
There has been some discussion of the reasons why such disparities might occur (see, fora review, Dupuy [2011]). Explanations have been
attributed to the nature of trade itself in perhaps giving rise to incentives which quicken
the pace of resource depletion (Klepper andStähler 1998) or policy failures within, forexample, the exporting country (Arrow et al.
2004; Myers and Kent 2000) or perhaps somecombination of these two factors (see, for a
discussion, Copeland and Gulati [2006], WTO[2010], and Oleson [2011]). It is this divergencethat underpins claims that importers of (underpriced) resources are “buying sustainability” atthe expense of exporters. In such cases, there
might be arguments for imputing a liability toimporters in recognition of their consumptionof “under-valued” resources. Any such liability is, however, notional in the sense that thisdoes not correspond to an actual transaction.
Nevertheless, it seems useful to consider thenature of these international linkages in sustainability indicator construction as a supplement to existing efforts.4
4 Resource security concerns of importers reliant
on particular exporting countries or particular strategically critical resources might also motivate further
empirical examination of these trade linkages. Oleson(2011) stretches this point further by asserting that
this security of importers might also be compromised
potentially by relying on resources from countries
which have negative genuine saving. While this seems
an intriguing claim, it would be interesting to add further substance to this assertion and the nature of thelinkages it implies. If, however, importers are altruistic
then they have concern about resource depletion oreven perhaps negative genuine saving in exporting
countries (Atkinson and Hamilton 2002; Oleson 2011).
So while such findings could form the basis of policies

A handful of contributions have sought toquantify these natural resource links including
Proops et al. (1999), Bailey and Clarke (2000),
Atkinson and Hamilton (2002) and, more
recently, Oleson (2011). Of course, a growing and parallel literature has also emerged to
examine the “embodied” or “virtual carbon” ininternational trade. Under the Kyoto Protocol,
Annex B (developed) countries are committed togreenhouse gas emissions restrictions (including carbon dioxide, CO2) while in an attempt
to take account of historical responsibility anddevelopment concerns, developing countries
are not (Peters et al. 2011). Numerous authors
have noted that trade in “virtual” carbon allows
developed countries (in effect) to “offshore”
their emissions by importing carbon intensive
goods (Peters and Hertwich 2008).5
Studies that have sought to measure thevirtual carbon that are embodied in flows
of goods and services traded across nationalboundaries include Lenzen et al. (2007), Petersand Hertwich (2008), Wiedmann et al. (2010),
and Atkinson et al. (2010). Davis and Caldeira(2010) and Peters et al. (2011) find that carbon
embodied in internationally traded goods andservices accounted for 23 percent (6.2 gigatons)of total CO2 emissions in 2004, and 26 percent(7.8 gigatons) for 2008, respectively. Both studies indicate that the majority of embodied carbon flows as exports from developing countries

to assist exporters in adopting prudent resource andpublic investment policies. This suggests, once more,
the need for complementary and additional indicators
rather than say an alternative method for calculating
genuine saving.
5 For these reasons, MRIO has been employed toaddress questions such as the difference between the
production and consumption emissions of countries.
Baiocchi and Minx (2010) and Wiedmann et al. (2010),
for example, confirm the insights drawn from the morerudimentary analysis in Helm et al. (2007) and thus
recast the story of U.K. carbon emissions over the past
two decades or so. Critically, it appears, while the U.K.
has had relative success in reducing its production
emissions within its own borders, there is evidence ofan ever growing reliance on virtual carbon produced
elsewhere.

CHAPTER 5 Are national economies (virtually) sustainable?

91

to the developed world. Wiedmann (2009)and Wiedmann et al. (2007) provide extensive
reviews of this growing literature.
A key distinction here is between production
emissions (of carbon dioxide) and consumption
emissions. The former are simply those CO2
emissions generated domestically (i.e., in the
production of a country’s gross domestic product). The latter are flows of virtual carbon andspecifically the CO2 implicitly consumed in orderto satisfy a country’s domestic final demand.
Multiple techniques have been developed in
an attempt to track such emissions flows, both
direct and indirect, at the global, regional, andnational levels of analysis. This includes life
cycle assessments (Oleson 2011), material flow
analysis, ecological footprints (Wackernagel
et al. 2000), and bilateral analysis (Sato andMartin 2011). The most prominent approach,however, appears to be variants of input-output
analysis particularly utilizing multi-regionalmodels. These MRIO approaches contain considerable detail about trade links between
economic sectors across countries or regionalgroupings.6
While some of this carbon accounting literature has begun to turn to important policyquestions, there has been little if any emphasis on the links to earlier contributions which
6 The chief benefit of the MRIO approach lies in its
ability to capture the entire production process sothat the full environmental impact of a traded good orservice can be attributed to a final consumption goodor service. Life cycle approaches (LCAs) are capablealso of providing such information. Indeed, LCAs tracethese impacts for specific goods and so permit a much
more finely grained detail than in the MRIO approach.
This makes the former particularly useful for developing industry and eco-labeling standards for productlife cycle impact and attributing responsibility for theenvironmental impact of specific goods. However, thefiner detail of LCA comes at the expense of aggregative capacity, making these methods less applicableto questions concerning global trade and systemsof national accounts which involve greater productheterogeneity (Rebitzer et al. 2004; Lutter et al. 2008;
Wiedmann et al. 2009). By contrast, in measuring sectoral flows rather than tracking individual products,
MRIO permits a level of aggregation that facilitates
analysis at the global level (Wiedmann et al. 2009).

92

highlighted questions about sustainability andresource trade. However, these parallels are not
only worth making once again but also are sufficiently interesting to explore further. The caseof carbon emissions relates naturally to our previous discussion about accounting for (notional)
liabilities. That is, these emissions contribute to
the accumulation of a global liability. In this way,
CO2 emissions contribute negatively to genuinesaving. The relevant question is how individual
countries should account for this liability. This
question, however, appears to have at least twoplausible (but different) answers.
First, Arrow et al. (2010) estimate the deduction to be the climate change damage that willarise in a particular country as a result of global
emissions in a given year. Put another way, if
any economy wishes to stay on a sustainable
path then it must, other things being equal,
save enough to cover the value of damages that
occur within its national boundaries regardlessof the geographical origin of the (current) emission source that gives rise to this damage.
Second, World Bank (various years)7,
Hamilton and Atkinson (1996), and Hamilton
and Clemens (1999) estimate the deduction as
the social cost of a country’s CO2 emissions. Putanother way, this country is accounting for theliability it accumulates in the form of total damages that its own emissions cause, regardless ofthe geographical destination in which thesedamages are felt.
The critical distinction in these alternative
approaches is the assumption that these makeabout responsibility (Atkinson and Hamilton2007). If we assume that countries are individually responsible for bearing the burden ofenvironmental damages that occur within theirborders (and that polluters hold no liability
for damages caused abroad) then the former
method obviously would be the most appropriate. By contrast, the latter method involves anassumption about the suitability of extending
7 We refer here to the World Bank’s annual World
Development Indicators reports which follow the
manual produced by Bolt et al. (2002).

Inclusive Wealth Reportthe polluter pays principle to the domain ofnational accounting. This requires that some
portion of an economy’s total savings should,
at least notionally, be set aside in order to compensate the recipients of damage arising fromcarbon emissions.
Unfortunately, scrutiny of these competing
assumptions is unlikely to lead to an unequivocal answer. On the one hand, if there weremeaningful international treaties for managing emissions of a transboundary pollutant
along with suitable control measures (such as
emission taxes) that placed an explicit price on
pollution liabilities then the latter accounting
approach would unambiguously be the correctone. On the other hand, if there was little or noprospect of international action then the former accounting approach is an apt descriptionof actual future prospects. Neither case seems
to be an unequivocally satisfactory descriptionof the real world.
Arguably, therefore, both approaches havetheir place in framing thoughts about the sustainability of development and it is important toacknowledge explicitly what is being assumed
about responsibilities and liabilities in any particular approach. As a practical matter, however,data limitations may hamper empirical application in particular where detailed valuation isneeded on estimated damage within individual
countries. In addition, the recent literature on
virtual carbon8 potentially adds another twist.

We take as the motivation for our empirical analysis the proposition that in terms of accountingfor (changes in) comprehensive or inclusive
wealth, the starting point for any country should
be to account – first and foremost – for the assetsthat it owns. The reason for this is straightforward. It is the prudent management of theseassets that is likely to determine primarily thesustainability of development. Nevertheless,there are a number of reasons for considering
further how relationships between countries
might be quantified within this framework for
wealth accounting. Two such relationships areof interest in this chapter. The first concerns
trade in depletable natural resources (including a range of non-living and living resources).
The second concerns the liabilities or burdens

8 Arrow et al. (2010) estimate the putative damage that might occur in a country as a result of global
carbon emissions in an accounting year. The specificmethod calculates the global damage that will arise
from emissions of greenhouse gases in a given year:that is, the product of the quantity of (carbon-equivalent) emissions and the social cost of (a unit of) carbon.
It then allocates this global damage to each country
based on the assumed share of each country of thatburden. The issue here is the evidence base simply
does not exist and so, through necessity, practitioners
must fall back on simplifying assumptions. Nordhaus
and Boyer (2000), however, provide some disaggregation for 13 regions including five individual countries
and eight country groupings. The latter is a mixture ofgeographically (broadly) similar countries (e.g., OECD
Europe) and economic groupings. For example, thosecountries belonging to the category “Other High
Income” on average appear to benefit from a 2.5°C
degree warming, although the group is comprised ofa diverse mix of countries including Australia, Israel,and Canada. The category of “Lower Middle Income”
includes countries such as Venezuela, South Africa,
Iran, and Thailand. The point here is not a critique ofNordhaus and Boyer, which represents a useful extension of the highly aggregated single-world economy ofmuch of the literature on the social costs of carbon.
Moreover, the point made by Arrow et al. (2010) is agood one. It seems sensible to account for both thedamage that a country bears from global emissions
as well as the burden for which this same country is
responsible. However, as things stand, we arguably
lack the data to be able to do this accounting satisfactorily across a wide range of countries.

That is, the social cost approach has involved
estimating the (notional) liabilities arising fromproduction emissions and deducting that frommeasures of genuine saving. It seems interesting
to ask also what this savings analysis (in termsof the contribution of countries to global sustainability) would look like if instead we measured “responsibility” and (notional) “liabilities”
with reference additionally to the social costs ofconsumption emissions.

3
Virtual sustainability and international trade

CHAPTER 5 Are national economies (virtually) sustainable?

93that countries impose burdens on one anotherIn what follows, we define “virtual sustainbecause of transboundary pollution (specifically ability” as the quantification of aspects of these
here arising from carbon emissions).
linkages between countries where responsiWe must interpret the results of such quan- bility is defined in terms of the value of thetification with care. In particular, we do not resources and carbon that a country consumes.
consider further those trade linkages which Put another way, these linkages can be thought
may actually affect the “bottom line” of export- of as providing a somewhat different picture
ers and importers. The correct accounting for of a particular country’s contribution to global
capital gains and losses on traded resources
sustainability. That is, for a country with very
would be one example of this. Our focus, in few domestic natural resources that relies onwhat follows, is (changes in) natural assets andsignificant imports of resources from othertrade flows which might be thought of as being, countries, we say that this country’s contribuin some senses, notional liabilities. The naturetion to global sustainability is diminished byof the liability for which we must account isthis consumption of resources (relative to its
determined by the interpretation of responsibil- contribution taking into account its depletionity (for resource depletion or carbon emissions) of its own resources).
that we take.
Before we proceed to describe our method
For resource depletion, conventionally for calculating the empirical magnitudes of
we might think of the country producing thethese responsibilities, one final word of caution
resource (e.g., through its domestic extraction is needed in interpreting our results. We argue,
activities) as being responsible for this depletion. in what follows, that taking account of trade
The liability arising from the (negative) change
linkages – and distinguishing between responin the resource stock arising from this deple- sibility in terms of production and consumption should be attributed to the accounts of tion of natural assets in the way we outline here
the producing country. Alternatively, we might – is useful for thinking about contributions toconceive of responsibility as residing with theglobal sustainability. However, measures ofcountry that ultimately consumes the resource
resource consumption, for example, do not(in order to satisfy its final demand). In this case, translate directly into a prescription about how
the liability reflecting the change in resourcemuch a resource-consuming country shouldstock should be attributed to the accounts of actually save to ensure the sustainability of its
the consuming country (or countries).
own development. In other words, the emphaFor carbon emissions, assuming a case cansis on the term “virtual sustainability” here is
be made for saying that polluters should pay important.
(and thus account) for the climate change damage they cause, a question also arises about
where this liability should be charged. Typically, 4Methods and data
this has been thought of as “belonging” to thecountry that produced the emissions. However, Multi-regional input-output (MRIO) models are
responsibility (and hence liability) could instead well established as a popular tool of IO (inputbe argued to lie with the country consuming theoutput) practitioners (Isard 1951; Leontief and9goods in which these emissions are embodied.
9 There are other perspectives on this issue of
responsibility. We are grateful to an anonymous
reviewer for suggesting that “source responsibility”
might also be a candidate proposition. On this view,the responsibility for the climate liability might be said
to reside (in some part) with the country that initially94

depleted and traded, for example, fossil fuel resources.
There are certainly policy contexts where this understanding of responsibility is articulated either implicitly
or explicitly. Clearly, the debate between production,
consumption perspectives, and alternatives would
benefit greatly from the further contributions of environmental ethicists.

Inclusive Wealth ReportIntermediate demand

FD.r

FD.s

TotalsRegion r

Region s

(I)
(I)
(III)

zrr

zrs

yrr

yrs

xr

Region s

Monetary input-output table
Damages

Environment

Two region economic system

Region r

Final demand

(I)
(I)
(III)

zsr

zss

ysr

yss

ys

Labor

w Lr

w Ls

CapitalrKr

rKs

Resource rent

pRr

pRs

DCr

DCs

DCt

Agriculture
Industry
Services

Agriculture
Industry
Services

Total output

(X)

xr

xs

Carbon dioxide

(C)

dCr

dCs

Figure 1

Schematic representation ofan extended multi-regional
input-output (MRIO) table

Ford 1971). Indeed, the number of studies applying MRIO models to environmental problems
has increased substantially over the past two
decades (for a literature review, see Wiedmann[2009]). The MRIO modeling competency lies
primarily in its ability to trace environmental impacts along the entire production chain,from the consumer country back to the producer country, considering both the direct andindirect effects (or embodied resources) in thecommodity traded. Thus, by use of this technique it is possible to show how production andconsumption are interconnected across regions
and sectors. Revealing a nation’s global resource
needs provides the potential for a very different
picture of its environmental responsibilities
to emerge (Munksgaard and Pedersen 2001).
For some applications of MRIO models applied

to environmental studies see for example:
Andrew, Peters, and Lennox (2009); Atkinson
et al. (2010); Davis and Caldeira (2010); Lenzen,
Pade, and Munksgaard (2004); and Muñoz andSteininger (2010).
In this section, we describe the MRIO
method as a tool for measuring the natural asset
demands from a consumption perspective, as
opposed to conventional accounting based on a
production perspective. These two approaches,or accounting practices, are also known as theconsumption-based principle (CBP) and the
production-based principle (PBP), respectively(Munksgaard and Pedersen 2001). PBP meansthat indicators only capture the domestic environmental or resource pressures that are linked
to the production of domestic consumption
and exports within the geographical borders of

CHAPTER 5 Are national economies (virtually) sustainable?

95a country. By contrast, CBP re-allocates thesesame environmental or resource pressures associated with exports to foreign countries and, in
addition, domestic responsibilities are complemented by “responsibility” for impacts that takeplace abroad, that is those that are embodied inimports.
The two components of the genuine saving
indicator that we focus upon from a CBP perspective are natural resource depletion and thesocial costs caused by carbon production or emissions. Thus, for example, while gross saving andinvestments in human capital boost genuinesaving, natural resource depletion and liabilities
caused by emissions of greenhouse gases, as wellas the depreciation of produced capital, shrink
genuine saving. More precisely, in the current
context, natural resource depletion consideredhere comprises the following categories: fisheries; forest; energy resources (mainly oil, gas, andcoal); and mineral extraction.10
Practical steps in measuring changes in natural wealth from a consumption perspective can befound, for instance, in the works of Proops andAtkinson (1998) and Proops et al. (1999), as wellas in the study of Atkinson and Hamilton (2002).
These first efforts found in the literature sharea similar empirical level of analysis, in the sensethat both studies use an MRIO model for the
global economy at a “macro” level, representing
the regional (or national) variables in the modelby the total aggregated value of the region
under study: that is, these models assumed eachcountry, in effect, has a single economic sector
trading with the rest of the world. As concerns
the number of regions included in the model,
this has been continuously increasing: while
Proops et al. (1999) referred to 28 world regions,
Atkinson and Hamilton (2002) augmented thenumber of regions up to 95. Furthermore, both
10 A notable exception here is any robust treatmentof the value of biodiversity or ecosystem services
embodied in international trade. The reasons for thisomission are readily apparent, and include difficulties
in measurement and the reliability of data. The authors
are grateful to Dr. Zafar Adeel of UNU-INWEH for thisinsightful comment.

96

studies focus on various years between 1980
and 1990.
The ability to aggregate across resource sectors is due to the convention of tracing monetary (instead of physical) flows within the
input-output framework (Miller and Blair
2009). There are several reasons that we takethis approach in this chapter. The primaryreason is that this approach provides us witha clear link to comprehensive wealth accounting. In addition, this facilitates inter- andintra-industry comparisons (Wiedmann et al.
2009). First, outputs within a given sector are
heterogeneous (fisheries produce anchovies
and tuna), and aggregating across them is madeeasier by measuring monetary flows. Similarly,
monetary terms permit the consolidation ofdiverse resource categories into a measure ofnatural resource depletion in a more intuitive
way than one which requires adding tons of fish
to tons of coal. While physical and hybrid inputoutput models are possible, and yield different
results from monetary input-output analyses(see Hubacek and Giljum [2003]), our approach
accepts convention and makes use of monetary
input-output techniques.11 In the following
subsection we take a closer look at the multiregional accounting system that we use.

4.1 Model description
In Figure 1 we present an elaboration of a
two-region accounting system extended to

11 We accept the loss of detail and exposure to monetary phenomena that this approach entails. Miller
and Blair (2009) and Wiedmann et al. (2009) note thatthe use of monetary input-output tables can lead toskewed results when changes in price and exchange
rate do not reflect actual changes in physical tradeflows. This challenge may be especially pertinent foran analysis of resource sectors given their notoriously
volatile prices (and even more so for year-to-yearcomparisons). However, given that our study reports
on a ‘snapshot’ of trade flows in 2004, we are able
to avoid at least some of this ‘skew’. For an extensive
review of these and other methodological issues, see
Wiedmann et al. (2009).

Inclusive Wealth Reportresources and the environment, which underpins the development of the MRIO model. This
figure provides a comprehensive overview of
the consumption and production structure of
two trading regions at an industry level. Thisis constructed on the basis of the System of
National Accounts (SNA), input-output tables(IOTs), trade statistics, and the extensions of thesystem to environmental accounts such as – inthe current context – CO2 emissions. More specifically, ‘xji’ (with j= ‘r’ and ‘s’) is the vector of
outputs domestically produced by industry ‘i’(with i=1,…,n). Output production additionallyneeds primary inputs of labor (Lji), capital (Kji)and natural resources (Rji), while the monetarycompensation per unit (or the price) of those
production factors is given by ‘w j’, ‘r j’ and ‘p j’
respectively.
In addition, production of this output in thedomestic territory of region ‘j’ induces pollution
and waste although, in this chapter, this is represented only by carbon dioxide emissions, ‘C ji’,with ‘d’ being the corresponding damage caused
per ton of CO2 emitted into the atmosphere bydifferent sectors and households. Under theconventional PBP, the corresponding emissions
and natural resource depletion are purely allocated to region ‘j’ even though some part of thisproduction may be for exports to other regions.
As regards commodity trade between bothregions, exported commodities for final consumption from, for instance, region ‘r’ to region‘s’ are represented by vector ‘yrsi’, embodying
the emissions and natural resource use that
occurred in the exporting region, ‘r’. In a similarway, the vector of exported commodities fromregion ‘s’ for final demand in ‘r’ is denoted by‘ysri’. The other component of the final demands
comprises the commodities domestically produced, ‘yjji’.
Finally, domestically produced goods andservices, ‘xji’, necessarily need one or more commodities as inputs, whether these are “imported”
or produced within the economy. These intraand inter-industry intermediate products areindicated in Figure 1 by two groups of matrices: (1) ‘Z srhi’ denotes exported commodity

inputs of industry ‘h’ (with h=1,..,n ) in region‘s’ to industry ‘i’ of region ‘r’ (and vice versa for‘Z rshi’); (2) whereas ‘Z jjhi’ represents intra- andinter-industry deliveries within a region. These
intermediate transaction matrices provide thekey for understanding the relationship between
consumption and production between regions
and for assigning environmental responsibilities from a consumption-based perspective. On
the basis of the accounting system describedabove, it is possible to develop the MRIO modelwith full linkages. We do not present in detailthe equations underlying the model since they
have been already widely described in recent
years. For an explicit treatment of this, seePeters (2008), Atkinson et al. (2010), Davis andCaldeira (2010), Lenzen, Pade, and Munksgaard(2004), and Muñoz and Steininger (2010). The
model formulations primarily allow tracing all
the inputs required along the production chain,from final demand12 upstream to the extraction
phase, and the corresponding resource depletion and emissions damages.

4.2 Data description
Establishing an MRIO-model requires that avariety of data are sought. For the monetaryside, the database of the Global Trade Analysis
Project (GTAP) was used to construct an MRIO
model with full linkages. In this chapter we haveused GTAP v7 (Narayanan and Walmsley 2008)
for the year 2004. GTAP v7 provides harmonized input-output tables for 113 countries andcountry groups (multi-country regions in thiscase), representing the entire world economy.
Moreover, the GTAP database (a) presents harmonized sectoral disaggregation across regions,which consists of 57 industries per region; and(b) is already balanced at the different scalesof analysis (meso, macro and global level). For
further details regarding the construction of

12 Here defined as household, government expenditures, and investment.

CHAPTER 5 Are national economies (virtually) sustainable?

97the MRIO model using the GTAP database, see
Muñoz and Steininger (2010).
Valuing resource depletion: Consistent with
Narayanan and Walmsley (2008) we have useddata on resource rents supplied by GTAP v7.
Natural resource rent comprised in GTAP isprovided at a sectoral level for the following six
industries: forestry; fishery; coal; oil; gas; andminerals. GTAP’s resource rents are indirectly
derived by estimating the cost share of thenatural resource input in the total industrial
output (for further details see Hertel et al.).
This procedure also ensures that sectoral rents
in GTAP (or ‘p.R’ in Figure 1) are harmonizedwith the other components of the economic
system as well – regional value-added acrossindustries, intermediate inputs, and domestic
output data. However, it would be useful to
explore further the links between the valuationof resource depletion that is implied within the
GTAP vis-à-vis the more direct methodologies for
estimating resource depletion values used in
the sustainability and resource accounting literatures (see, for example, Vincent, Panayotou,
and Hartwick [1997], Atkinson and Hamilton[2007], and Hamilton and Ruta [2009]).
Carbon emissions: With regard to CO2 emissions, GTAP provides data by sector and region,
satisfying the physical data requirements presented in the previous section. It is important
to mention, however, that GTAP v7 CO2 data only
refer to CO2 emissions from fuel combustion.
We have therefore also included CO2 emissions
stemming from industrial processes of the following sectors: mineral products; chemicalindustry; and metal production for all countries
reported by UNFCCC (2009). Nevertheless, somecountries do not report industrial process emissions for the specific years under study. In thosecases, we updated the last year available by using
indicators related to the industrial process. For
mineral products and metal production we usedthe changes in cement production and steel inthe respective country as a proxy variable for
updating the CO2 emissions in these industrial
processes. Cement and steel data were obtained
from the United States Geological Survey (USGS).
98

In the case of the chemical industry, we use thesectoral value-added of the examined country.
In this chapter, in order to value these flows
of carbon, we need to make an assumption
about the social costs of carbon: that is, thepresent value of future damages resulting froman additional unit of carbon emissions in agiven year (Fankhauser 1994). Estimating thissocial cost is inherently complex and uncertain
and our selection of this parameter will have asignificant impact on our findings.
For our purposes, there are three candidate
strategies for selecting a social cost of carbon.
First, we could adopt a price as determined byan already existing carbon market, such as the
EU Emissions Trading System. While this may
be a valid approach in the future, it is at present
limited by the infancy of current carbon markets.
As Dellink et al. (2010) suggest, carbon markets
are incomplete, closed, and, for most countries,
non-existent. Furthermore, there is no guarantee that market prices would capture the fullsocial cost of carbon (SCC) and, because markets
are unlinked, there is no convergence to a common world price for us to adopt (Dellink et
al. 2010). Alternatively, we could adopt a pricewhich is already in use such as the World Bank’slong standing use of 20 $/tC13 (World Bank
2010) or Australia’s recent carbon tax of 23 $/tC
(Commonwealth of Australia 2011). The chiefvalue of this approach is that, to the extent that
one exists, it entails the use of a standard andfacilitates comparisons with existing literature.
However, this too, fails to account for Dellink’s
objections, and for various reasons, may notproperly reflect carbon’s social costs. Finally, ourthird option is to adopt an estimated value forthis parameter. This approach is in accordancewith Stern (2006), and is adopted here.
The debate that followed the Stern Review
indicated the central importance of discounting (Tol 2008; Weitzman 2007; Stern 2006).
Additionally, the estimation of the social costof current emissions is not independent of the
13 All monetary values in this chapter are expressedin USD.

Inclusive Wealth ReportTable 1

Resource depletion for selected economies
Total resource depletion
Country name(in millions, US$)GNI
(in million of US$)

Production
Value

Consumption

%GNI

Value

Ratio

%GNI

Prod/ Cons.

United States

11.687.900

35.6110.30

78,387

0.67

0.45

Japan

4.694.853

4.601

0.10

27,5220.59

0.17

Germany

2.764.179

3.735

0.14

15,5970.56

0.24

United Kingdom

2.215.020

8.444

0.38

11,2760.51

0.75

France2.077.657

2.059

0.10

9,902

0.48

0.21

China

1.928.118

34.3081.78

36,8191.91

0.93

Canada971.963

14.505

1.49

7,827

0.81

1.85

India

695.941

7.047

1.01

13,0261.87

0.54

Rest of West Asia

634.21460.593

9.55

10,347

1.63

5.86

Russian Federation

578.971

29.586

5.11

10,9481.89

2.70

Norway259.079

14.351

5.54

1,233

0.48

11.64

Indonesia

225.214

9.142

4.06

6,256

2.78

1.46

South Africa

211.700

1.936

0.91

2,058

0.97

0.94

Portugal

176.127

371

0.21

1,460

0.83

0.25

Iran

160.332

14.611

9.11

4,924

3.07

2.97

Venezuela, RB

108.779

8.424

7.74

1,421

1.31

5.93

Singapore103.199

41

0.04

1,022

0.99

0.04

Nigeria78.110

9.354

11.98

931

1.19

10.05

Nicaragua

4.266

30

0.70

93

2.17

0.32

Eastern Europe

2.935

3

0.12

93

3.17

0.04

41272071

3492940.85

349294

0.85

1.00

World

Raw data from GTAP v7. See Narayanan and Walmsley (2008) available online at
http://www.gtap.agecon.purdue.edu/databases/v7/v7_doco.asp

predicted path for future emissions, complicating further the asset valuation problem (Stern
2006). Further challenges include uncertainty
in forecasting the frequency, intensity, and location of catastrophic climate events (Newbold
et al. 2010; Pycroft et al. 2011; Lemoine andTraeger 2010; Weitzman 2007; Stern 2006).
These complexities notwithstanding, a number of empirical studies have sought to estimate
the social cost of CO2 emissions which, in turn,have been used to inform past wealth accounting work. Notably, World Bank (2010) uses avalue of $20/tC. Arrow et al. (2010) and Atkinson
et al. (2010), however, arrive at a value of $50/tC;
a magnitude that can be justified with reference
to the work of the Stern Review, market prices
for EU emissions permits, and by recognizing
the general trend in the field (Guo et al. 2006;
Tol 2008; Clarkson and Deyes 2002).

CHAPTER 5 Are national economies (virtually) sustainable?

99

Table 1

Continued
CO2 emissions

Per capita resource depletion andcomparison to global average (GA) (in US$)Country nameProduction
Value

P/GA

(in millions, US$) $50/tC

Consumption
Value

Production

C/GA

Value

Consumption

%GNI

Value

%GNI

United States

120.552.30

265.35

4.88

85,421

0.73

95,467

0.82

Japan

35.96

0.69

215.15

3.96

15,7040.34

20,1400.43

Germany

45.19

0.86

188.71

3.47

12,1310.44

14,8780.54

United Kingdom

141.96

2.71

189.58

3.49

8,336

0.38

11,891

0.54

France

34.17

0.65

164.32

3.02

5,414

0.26

7,953

0.38

China

26.23

0.50

28.15

0.52

69,055

3.58

54,093

2.81

Canada453.848.67

244.89

4.51

8,190

0.84

7,707

0.79

India

6.48

0.12

11.98

0.22

17,116

2.46

15,856

2.28

Rest of West Asia

511.76

9.78

87.39

1.61

14,4092.27

11,403

1.80

Russian Federation

205.60

3.93

76.08

1.40

23,517

4.06

18,180

3.14

Norway3,119.74

59.62

268.10

4.94

888

0.34

782

0.30

Indonesia

41.54

0.79

28.43

0.52

5,232

2.32

4,763

2.12

South Africa

41.00

0.78

43.60

0.80

5,363

2.53

3,598

1.70

Portugal

35.49

0.68

139.86

2.57

934

0.53

1,141

0.65

Iran

212.37

4.06

71.57

1.32

6,663

4.16

6,728

4.20

Venezuela, RB

320.54

6.13

54.06

1.00

2,178

2.00

1,661

1.53

Singapore

9.67

0.18

239.36

4.41

557

0.54

962

0.93

Nigeria

72.67

1.39

7.23

0.13

785

1.00

793

1.01

Nicaragua

5.54

0.11

17.21

0.32

64

1.51

80

1.88

Eastern Europe

0.83

0.02

22.04

0.41

109

3.70

158

5.37

World

54.54

1

54.54

1

3843580.93384358

0.93

An important study is Tol (2008) which offers
an extensive meta-survey of over 200 estimates,
ranging from -6.6 $/tC to 2,400 $/tC with variations due largely to differences in discount rates,
assumptions about economic growth and adaptive behavior, the degree of equity rating, scientific uncertainties, and the treatment of tipping
points (Lemoine and Traeger 2010; Guo et al.
2006; Tol 2008). Clearly, this is a wide range. In
reflecting on how to narrow this range, however, Tol (2008) argues that under conservative100

assumptions the mean value is $23/tC (and acertainty equivalent value is $25/tC) and that,furthermore, there is a 1 percent probability that the social cost of carbon exceeds $78/
tC. In a recent paper, Tol (2009) suggests that$50/tC could be used for policies such as carbon taxes under plausible assumptions about
governments’ assessment of key parameters(such as the social discount rate). This corresponds to the value used, for example, by Arrowet al. (2010) and Atkinson et al. (2010) and for
Inclusive Wealth ReportFigure 2

Figure 3

Production and consumption-based
resource depletion (millions, US$)

Average per capita resource depletion(US$)

250,000

250

200,000

200

150,000

150

100,000

100

50,00050

00
Low income

Lower middle
incomeUpper middle
incomeHigh incomeKey

Low income

Lower middle
incomeUpper middle
incomeHigh income

I Key

Production-based depletion

Average production depletion

Consumption-based depletion

Average consumption depletion

Income group classifications are consistent with World

Income group classifications are consistent with WorldBank guidelines: low income (GNI/capita < $1,005), lower

Bank guidelines: low income (GNI/capita < $1,005); lower

middle income ($1,006<GNI/capita<$3,975), upper middle

middle income ($1,006<GNI/capita<$3,975); upper middle

income ($3,976<GNI/capita<$12,275), and high income (GNI/

income ($3,976<GNI/capita<$12,275); and high income (GNI/

capita>$12,276).

capita>$12,276).

Raw data from GTAP v7. See Narayanan and Walmsley

Raw data from GTAP v7. See Narayanan and Walmsley(2008) available online at http://www.gtap.agecon.purdue.

(2008) available online at http://www.gtap.agecon.purdue.

edu/databases/v7/v7_doco.asp

edu/databases/v7/v7_doco.asp

illustrative purposes we use this value of $50/tC
in what follows (or just under $14/tCO2).
Other data: We also make use of data on
gross savings, consumption of fixed capital andeducation expenditure for the year 2004 andpublished in World Bank (2011).

emissions. Second, we explore, from the two
accounting perspectives, the virtual sustainability of individual countries (or regions), and thus
their contributions to global sustainability.

5.1 Production and consumption perspectives: comparisons and contrasts
5

Empirical results

We divide our discussion of results into twoparts. First, we discuss – using our input-output
methodology – how our analysis highlights thegap between the production and consumption
perspectives on resource depletion and carbon

Table 1 illustrates production and consumption
based resource depletion (total and per capita)
and CO2 emissions for a select group of economies. Column 7 reports the ratio of production/consumption based depletions, while columns 4 and 6 show each as a percentage of GNI.

CHAPTER 5 Are national economies (virtually) sustainable?

101

of some commentators starting with Martinez-Alier (1995).
Production - minus consumption-based resource depletion (in millions,Thus, Figures 2 and 3 groupUS$)
countries by income14 to show
the total and average per
Rest of West Asia
capita dollar value difference
U.S.
inproduction- and consumpJapantion-based resource depleRussian Federation
tion. When aggregated at thisNorwaylevel the data appear to show
Germanya clear trend. However, theIran, Islamic Rep.
question
remains as to how
Rest of North Africa
well this holds for individual
Nigeria
economies.
Italy
Figure 4 thus examines
Francethe question of country level
Korea, Rep.
resource depletion. Shown
Venezuela, RB
here are the individual econoCanada
mies with the greatest disparIndia
ity between production- andconsumption-based depletion.
Positive values (net exporters)
Depletion in millions of US$
show production based depletion in excess of consumptionFigure 4 lists the economies with the greatest difference between production- and consumption-based
based depletion, while negative
resource depletions. Definitions for regional aggregations are consistent with World Bank classifications
values (net importers) indicate
and are available in Appendix A1.
the reverse. That is, although
Raw data from GTAP v7. See Narayanan and Walmsley (2008) available online at http://www.gtap.agecon.
economic activity in the Rest
purdue.edu/databases/v7/v7_doco.asp
of West Asia entails significant
resource depletion, a large portion
of
this
is
then
traded abroad. Similarly, U.S.
Depletion ratios greater (less) than one reflect
resource depletion entails significant imports. It
net resource exporters (importers). Columns
8–11 describe per capita resource depletion. A is interesting to note that low- and high-income
comparison of each economy’s (per capita) pro- countries each appear on both sides of Figure 4.
For examining contributions to sustainabilduction and consumption based depletions to
the global average is given in columns 9 and 11, ity on a global level, it is instructive to see which
respectively. Here, values that are greater than individual economies entail the greatest resource
one indicate above average depletion while val- depletion, and how this relates to the global averues less than one indicate the reverse. All CO2 age. Figures 5 and 6 rank the top 15 economies
emissions reported here (including those used in terms of their per capita production- andto calculate genuine savings) assume an SCC of consumption-based depletions relative to theglobal average. Ratios greater than one indicate$50/tC.
Do rich economies use more resources froma production or consumption perspective? 14 Income group classifications are consistent withWorld Bank guidelines: low income (GNI/capita <Clearly, the answer to this question will start to$1,005); lower middle income ($1,006<GNI/capshed light on whether empirical thinking about ita<$3,975); upper middle income ($3,976<GNI/capvirtual sustainability confirms the assertions
ita<$12,275); and high income (GNI/capita>$12,276).
102

60,00040,00020,0000-20,000-40,000-60,000

Figure 4

Inclusive Wealth Report

15 There is an analogy here to the literature on carbon
leakage, although in other respects there are possibly
key differences between these notions.

Figure 5

Ratio of per capita production-based resource depletions
to the global average
Rest of S.E. Asia
Rest of West Asia
CanadaAustralia
Venezuela, RB
Denmark
Rest of N. Africa
Rest of EFTA
Iran, Islamic Rep.
Russian Federation
Malaysia
Rest of N. America
Kazakhstan
Ecuador

14

12

10

8

6

4

2

Hong Kong, China
0

above average per capita resource depletion,
while ratios less than one indicate the reverse.
For a complete list, please see the complete table(columns 9 and 11) in Appendix A2.
Taking stock of these findings “in the round”
leads to a number of reflections:
The ratio of production- to consumptionbased resource depletion in Table 1 shows thatin some economies (notably Norway, Nigeria,
Venezuela, and West Asia), production entails
far greater resource depletion than consumption. That is, for these economies, productionbased accounting of resource depletion overstates the value of resources required by thedomestic economy (i.e., to satisfy domestic final
demand). Though in general, lower-income,resource-rich economies have higher ratios, it
is important to note that this is not exclusively
the case: developed (Norway and Canada) as
well as developing (Nigeria and Venezuela)
countries can maintain high ratios of production- to consumption-based depletions.
Alternatively, resource depletion ratios ofless than one suggest that the economy requires
more resources to satisfy consumption than
production. This is particularly the case forseveral high-income countries such as Japan,
France, Germany, the U.S., and the U.K. One
way of interpreting this result is that developed
economies with high per capita income tend
to import resource intensive goods while theirdomestic production focuses on non-resource
intensive services.15 Though the list of countries
with depletion ratios of less than one is primarily populated by developed countries, this too, is
not exclusively the case (see, for example India,
Eastern Europe, and Nicaragua).
One of the results from Chapter 3 relates
to Japan as one of the few countries in which
natural capital has been increasing over time.
However, examining natural assets in international trade for the year 2004, it is further revealed that Japan’s domestic resource

Ratio of per capita production-based depletions to
global average
Figure 5 shows economies with the highest ratios of per capita production-based
resource depletions/global average. Definitions for regional aggregations are consistent with World Bank classifications and are available in Appendix A1.
*Note that Norway’s ratio of per capita production-based depletions to theglobal average was 59.62 and that for readability and scale it has been omitted fromthis chart as an outlier.
Raw data from GTAP v7. See Narayanan and Walmsley (2008) available online at
http://www.gtap.agecon.purdue.edu/databases/v7/v7_doco.asp

extraction during constituted only 17 percent of
the natural resource depletion induced worldwide by its consumption (see Table 1). Thisimplies that if Japan had to produce all consumed goods and services in autarky, its figureswith respect to natural capital would very likely
be different.16 Chapter 3 also reports a decrease
16 This hypothetical situation is not equivalent to(and is likely to be less than) simply adding the amountof imported resources to domestic depletion. This
result is due to variations in production technologies,
resource endowments, and efficiency of use between
countries. Moreover, in such a situation, it is likely thatsignificant substitution effects would come into play.

CHAPTER 5 Are national economies (virtually) sustainable?

103

Figure 6

Ratio of per capita consumption-based resource depletions to the global average
Rest of N. America
Luxembourg
Rest of EFTA
NorwayUnited States
BelgiumHong Kong, China
Australia
CanadaSingapore
IrelandFinlandJapan
Denmark

14

12

10

8

6

4

2

0

CyprusRatio of per capita consumption-based depletions to
global average
Figure 6 shows economies with the highest ratios of per capita consumptionbased resource depletions/global average. Definitions for regional aggregations are
consistent with World Bank classifications and are available in Appendix A1.
Raw data from GTAP v7. See Narayanan and Walmsley (2008) available online at
http://www.gtap.agecon.purdue.edu/databases/v7/v7_doco.asp

in natural capital of, for example, Nigeria thatis largely triggered by fossil fuel extractions. As
this country is a net exporter of natural resources,
with a production-consumption ratio of 10 (seeTable 1), the opposite situation with respect tonatural capital would potentially happen if thisnation had a closed economy. Thus, the analysis of natural assets in international trade offers
important insights into understanding the drivers of natural capital change presented in theprevious chapter.
Figures 2 and 3 show global trends inresource depletion by gross national income andare important for two reasons. First, our results
seem broadly consistent with the proposition
that resources tend to flow from poor to richcountries. It is worth noting that our results are
104

broadly consistent with this. Second, the figures
highlight not only the direction of these flows,
but also their magnitude. Whether in terms of
total dollar value, or average per capita value,
these figures clearly show that production
depletions exceed consumption depletions for
low-, lower-middle-, and upper-middle-income
countries. The reverse is true for high-income
economies. The results also indicate that the
disparity rises with income, suggesting that for
rich (poor) countries, production-focused indicators understate (overstate) resource demand.
Figure 4 takes the analysis to the level ofindividual economies, showing that despite
the trends implied by Figures 2 and 3, there is
no steadfast rule regarding the relationshipbetween income and production or consumption depletions. This is particularly interesting
when considering adopting production-based
versus consumption-based wealth accounting: the disparity between the two can be large
for both developed and developing countries.
The value of this difference, as we discuss infurther detail below, can be interpreted as the(virtual) change in the contribution to global
sustainability.
Figures 5 and 6 are particularly useful forassessing contributions to global sustainability
by individual economies. Interestingly, several
economies (Denmark, Canada, Australia, Hong
Kong – China, Norway, the Rest of EFTA, and theRest of North America) appear in both of thesefigures, suggesting that both their production
and consumption patterns require greater than
average resource depletions. Notably, however,both Canada and Norway also appear with positive values in Figure 4 suggesting that they arestill net exporters of resources.
Results from our MRIO model can be further
disaggregated to explore what lies beneath particular findings. For instance, our analysis indicates that the China’s CO2 responsibility is lower
from a consumption perspective than fromthe production perspective. This is consistent
with the findings elsewhere in the literature.
However, if we look instead at total resource
depletion for China, the opposite is found. That
Inclusive Wealth Reportis, China’s consumption of global resources
and its resource depletion (or production) was$36,819 million and $34,408 respectively. Thissuggests a production-consumption ratio of
0.93 (see Table 1).
This finding is largely due to Chinese importsof oil. This oil, in turn, mainly originates (interms of where it was depleted or produced)
in the Middle East which is subsumed underthe “Rest of Western Asia” region in our model.
Thus, for the Rest of Western Asia, our model
suggests that oil depletion from a consumption perspective was $15,172 million which issignificantly greater than this region’s resource
consumption (of $8,586 million).
Turning our attention back to China, important sectoral drivers of its resource consumption are: Construction, petroleum and coalproducts, public administration, and machineryand equipment. A similar finding emerges if welook only at natural gas as again China appears
to be a net importer of this resource. However,for coal, the results are different. China is a net
exporter of this resource. In consumption terms,
its responsibility amounts to $9,224 million. In
production terms, depletion of coal within
China was $12,486 million. The overall effect,

Table 2

Percentage contribution to global sustainability by region (percentage of gross world income)

Education
expenditures

Depreciationof produced
capitalGenuinesavingGross saving

Genuine saving components

Virtual sustainability
Change in natural assets:
Change in natural assets:
production perspective
consumption perspective
Carbon Naturalemissions resources

Total

Carbon Naturalemissions resources

Total

Aus./NZ/ Oceania

0.22

0.43

-0.27

0.09

-0.01

-0.02

-0.03

-0.01

-0.01

-0.02

China

1.53

2.18

-0.48

0.08

-0.17

-0.08

-0.25

-0.13

-0.09

-0.22

Japan

0.93

2.96

-2.34

0.36

-0.04

-0.01

-0.05

-0.05

-0.07

-0.12

East Asia

0.71

0.97

-0.36

0.13

-0.02

-0.01

-0.03

-0.03

-0.03

-0.06

South East Asia

0.31

0.54

-0.21

0.06

-0.03

-0.05

-0.08

-0.03

-0.04

-0.07

India

0.38

0.54

-0.17

0.07

-0.04

-0.02

-0.06

-0.04

-0.03

-0.07

South Asia

0.08

0.12

-0.04

0.01

-0.01

0.00

-0.01

-0.01

-0.01

-0.02

Canada

0.31

0.55

-0.31

0.12

-0.02

-0.03

-0.05

-0.02

-0.02

-0.04

United States

1.49

3.75

-3.32

1.35

-0.20

-0.09

-0.29

-0.23

-0.19

-0.42

Mexico

0.36

0.44

-0.16

0.10

-0.01

-0.01

-0.02

-0.02

-0.01

-0.03

South America

0.31

0.63

-0.35

0.11

-0.03

-0.05

-0.08

-0.02

-0.03

-0.05

Central America/ Caribbean

0.03

0.06

-0.03

0.01

-0.01

0.00

-0.01

-0.01

-0.01

-0.02

EU-15

3.40

6.18

-4.08

1.48

-0.12

-0.06

-0.18

-0.15

-0.17

-0.32

Russia

0.27

0.44

-0.09

0.05

-0.06

-0.07

-0.13

-0.04

-0.03

-0.07

EITs

0.16

0.45

-0.31

0.10

-0.05

-0.03

-0.08

-0.05

-0.03

-0.08

Other Europe

0.30

0.50

-0.25

0.09

-0.01

-0.03

-0.04

-0.01

-0.01

-0.02

North Africa/ Middle East

0.41

0.95

-0.41

0.16

-0.07

-0.22

-0.29

-0.06

-0.06

-0.12

Sub-Saharan Africa

0.08

0.23

-0.13

0.05

-0.02

-0.05

-0.07

-0.02

-0.02

-0.04

World

11.23

21.92

-13.32

4.41

-0.93

-0.85

-1.78

-0.93

-0.85

-1.78

Raw data from GTAP v7. See Narayanan and Walmsley (2008) available online at http://www.gtap.agecon.purdue.edu/databases/v7/v7_doco.asp

CHAPTER 5 Are national economies (virtually) sustainable?

105

Table 3

Genuine saving and “virtual sustainability” by selected
countries and regions
Change in natural assets$ million

Difference% GNI

Consumption
perspective(millions, US$)

Production
perspective

Genuine saving

Rest of North America-25.43

-407

75

163

-88

Rest of Europe-12.42-2,401

1,554

1,840

-286

Rest of South Central Africa-10.24-2,414

3,412

592

2,820

Rest of South America

-9.11

-192

62

81

-19

Former Soviet Union

-4.04

-565

4,863

3,175

1,688

Zimbabwe

-2.49

-112

203

166

37

Malawi

-2.18

-56

66

60

6

Senegal

-1.75

-139

153

282

-128

Rest of South Asia

-1.53

-224

423

593

-170

Malta

-0.67

-37

51

116

-65

Rest of EFTA

0.66

102

168

210

-42

Bulgaria

1.11

278

1,121

1,234

-113

Indonesia

2.59

5,841

14,374

11,0203,355

Cambodia

2.68

137

176

191

-15

Mozambique

2.85

159

78

144

-66

Madagascar

3.59

154

223

146

76

Portugal

3.86

6,801

1,305

2,601

-1,296South Africa

3.94

8,337

7,299

5,656

1,643

Nicaragua

4.42

188

94

173

-79

Lao PDR

4.79

115

90

109

-19

Raw data from GTAP v7. See Narayanan and Walmsley (2008) available online at
http://www.gtap.agecon.purdue.edu/databases/v7/v7_doco.asp

reported in Table 1, however, is dominated by
China’s consumption of oil.

5.2 Contribution to Global Sustainability
Table 2 describes contributions to global sustainability defined as global genuine saving:106

that is the world’s gross saving plus educational
expenditures minus produced capital depreciation and the values of natural resource depletion and carbon emissions. That is, the final row
indicates the global rate of genuine savings (i.e.,
genuine saving as a percentage of gross world
income) as well as its (global) components. To
simplify this exposition of “contribution” forthe moment, we aggregate our 113 countries andregions to a smaller group of 18 regional units.
For each of these units, the specific contribution to global sustainability overall is indicatedin the initial column of results.
This indicates that China’s genuine saving issuch that overall it increases global sustainability – that is, the global rate of genuine saving –by 1.09 percent. For the components of genuinesaving, the effect of each component is either
to boost the (global) genuine saving rate, in thecase of gross saving and education expendituresor to shrink this rate in the case of depreciationof produced capital, natural resource depletion,and (notional) liabilities arising from carbon
emissions. Again, to use the example of China,
the contribution of its gross saving rate is – otherthings being equal – to increase global sustainability by 2.18 percent while depreciation of produced capital decreases global sustainability by
0.48 percent.
We are particularly interested in how ourassessment of the contribution of these regions
to global sustainability shifts when we move toconsider virtual sustainability. That is, when we
look at the implied contributions from taking
a consumption-based rather than a production-based perspective on both climate change
liabilities and resource depletion. Column 10 ofTable 2 illustrates the total contribution for theformer approach while column 7 describes thelatter. Given that these data are defined as percentages of gross world income, the magnitudes
in the table tend to look small. Thus it should
be borne in mind that these percentages correspond to substantial monetary magnitudes as
the earlier discussion of our findings indicated.
Reference to columns 6 and 9 also make it
clear that most of these total contributions (forInclusive Wealth Reportthe changes in natural assets that we consider) the picture seems rather different. Thus, theare due to the carbon emissions component. The (negative) contribution of the average citizens
region “other Europe” (which includes Norway) to (virtual) sustainability in these countries andregions is below the global (per capita) conis the only exception, although for North Africa
and Middle East as well as Sub-Saharan Africa, sumption level, whereas the opposite is true forthe components are less far apart (in percentage Canada and Russia, for example. Put anothercontribution terms). With regards to the differ- way, while the consumption perspective meansthat contribution of both of these countries toences between columns, the effect of taking the
global sustainability is boosted, in per capita
consumption-based perspective is to decrease
terms, natural asset consumption remains well
the virtual sustainability of countries or regions
above the global (per capita) average.
such as Japan, the European Union (15), and the
Finally, Table 3 illustrates those countries or
U.S. Thus, the decrease in virtual sustainability
is 0.24 percent (of gross world income), 0.73 regions in our sample which appear to exhibit
percent, and 1.03 percent, respectively. Under negative genuine saving (in 2004). The firstthe production-based perspective, by contrast, column of data indicates this negative saving
these contributions are 0.15 percent, 0.49 per- as a percentage of that country or region’s GNI
while the second column gives the correspondcent, and 0.84 percent, respectively.
These results are not a surprise and con- ing dollar value. The two columns immediately
firm the earlier intuitions of Martinez-Alier adjacent give respectively the dollar value ofthe change in natural assets (i.e., carbon emis(1995) and subsequent commentators about thesions and resource depletion) from the produccontributions to sustainability of developed
countries. Nevertheless, it is also the case that tion and consumption perspectives. The final
column is the dollar difference between thesea number of countries and regions that are
magnitudes.
comprised of less-developed countries exhibit a
It is evident that for some of these coundecreased contribution to global sustainability
including India, East Asia, South Asia, Mexico, tries or regions, taking account of virtual sustainability (i.e., the resources that these areas
and Central America and the Caribbean. Thoseregions that receive a boost to their (virtual) implicitly consumed) worsens our assessmentof their contribution to global sustainability.
sustainability on this consumption perspective
include North Africa and Middle East, Sub- This includes Senegal, Bulgaria, and Portugal
Saharan Africa, Australia and New Zealand, as a number of composite regions (such as the“Rest of South Asia”). For a number of other
Canada, and Russia.
Again this seems to indicate that it is far areas, the opposite is true. That is, virtual susfrom straightforward to validate the view that tainability for these other countries or regions
richer countries “import sustainability” from gives a more favorable impression given that it
poorer countries. However, at least two addi- appears that significant amounts of resource
tional considerations are worth noting. The depletion or domestic carbon emissions can be
first is that our coverage of (changes in) natural attributed to satisfying final demand in otherassets here is limited. Second, there are a variety parts of the world. Notable regions or countries
in this respect appear to be Indonesia and Southways of looking at this issue of contributions
to global sustainability. An appendix to this Africa. Indeed, for the Former Soviet Union
chapter describes the results (in Table A.2) in per (which comprises Tajikistan, Turkmenistan,capita terms to take account of different popu- and Uzbekistan) and the Rest of South Central
lation levels. This indicates that although the Africa (which comprises Angola and thevirtual sustainability shrinks, for example, in Democratic Republic of the Congo), the differIndia, South Asia, and Mexico, as well as Central ence between natural asset depletion and conAmerica and the Caribbean, in per capita terms
CHAPTER 5 Are national economies (virtually) sustainable?

107

sumption is greater than the estimated negative
genuine saving level.

Conclusions
The real value of global resource trade
increased more than six-fold between 1998($613 billion) and 2008 ($3.7 trillion) (WTO 2010).
Given this context, it is perhaps not surprisingthat the way in which relationships between
trade and sustainability should guide comprehensive wealth accounting has been a pervasivequestion since the genesis of current interest in
sustainability indicators more than two decadesago. While some progress has been made inanswering this question, it is also arguable that
there has been no satisfactory resolution. While
we do not claim to have solved this conundrum
in this chapter, we hope to have provided additional empirical insights. We have done this byaugmenting an approach that has been muchused recently to examine questions about carbon footprints and carbon leakage and, specifically, the carbon emissions that are embodied
in the goods and services traded across national
economies (i.e., virtual carbon).
Our extension here has been to consider in a
fuller way how natural resources and the valueof (notional) liabilities arising from carbon emissions are embodied in international trade flows.
Furthermore, we have related this discussion toconcerns about the sustainability of development.
The key distinction here has been that of looking
at use of natural resources and carbon emissions
from a production perspective or a consumption
perspective. In the former, we are interested onlyin accounting for resources depleted or carbon
emitted by a national economy. In the latter, we
are interested in the resources or carbon that an
economy consumes to satisfy its final demand.
We have argued that moving from the former
perspective to the latter gives additional insights
concerning the contribution of national economies to global sustainability (where sustainability here has been defined in terms of genuinesaving). This can be best conceived of as telling108

us something about the virtual sustainability ofa national economy (i.e., rather than offering
concrete prescriptions about how much that
economy should actually save).
The empirical findings presented in thischapter appear to indicate that the magnitudesof the (change in) natural assets embodied in
trade are substantial, both in dollar value terms
and in relation to national economies. Moreover,
our results seem to confirm the assertions of
those who have argued that such resources flowfrom poor to rich nations. Nevertheless, there
are nuances and caveats here, and whether such
empirical patterns are sufficiently concrete as todraw strong conclusions about the virtual unsustainability of certain countries is another matter.
Of course, a large number of extensions andfurther work suggest themselves. In particular,
in the context of further development of thecurrent chapter, the following issues seem especially important:First, it would be desirable to link our valuation of natural resource depletion to discussions elsewhere about the measurement ofscarcity rents. For example, the latest estimatesof resource use published in World Bank (2010)provide a clear link to the correct valuation of
the change in natural assets in terms of comprehensive wealth accounting and sustainability.
Second, we have focused here on the total
value of (rents in) resource trade. But given thatthe clearest link to thinking about this trade in
relation to global sustainability is based on thepossible mismatch between these magnitudes
and their true scarcity values. Introducing further reflections on this into our empirical analysis seems worth considering.
Finally, our model here has focused on investigating the full links between where a resource
is depleted and where it is finally consumed.
There remain legitimate questions about where
the limits of responsibility end. Such questions
have clear relevance to thinking about virtualsustainability. Therefore, the examination ofbilateral trade flows also seems relevant fromthis perspective.

Inclusive Wealth ReportAppendix 1

World Bank Regional Classifications

Rest of South America
XSM• Faroe Islands• Niger• American Samoa

Rest of Oceania XOC• Gibraltar• Saint Helena• Cook Islands• Falkland Islands (Malvinas)• Macedonia, the former• Sierra Leone• Fiji• French Guiana• French Polynesia• Guyana• Monaco• Guam• Suriname• San Marino

Yugoslav Republic of• Serbia and Montenegro• Island of Wallis and Futuna• TogoRest of Central Africa
XCF• Marshall Islands

Rest of Central America
XCA• Belize

Rest of Former Soviet
Union• Central African Republic• Micronesia, Federated• El Salvador• Tajikistan• Congo• Honduras• Turkmenistan• Equatorial Guinea• Uzbekistan• Gabon• Kiribati

States of• Nauru• New Caledonia• Cameroon• Chad• NiueCaribbean XCB• Norfolk Island• Anguilla• Northern Mariana Islands• Antigua and Barbuda

Rest of Western Asia
XWS

• Palau• Aruba• Bahrain

Rest of South Central
Africa XAC• Papua New Guinea• Bahamas• Iraq• Angola• Samoa• Barbados• Israel• Congo, Democratic Repub-• Solomon Islands• Cayman Islands• Jordan• Tokelau• Cuba• Kuwait• Tonga• Dominica• Lebanon• Tuvalu• Dominican Republic• OmanRest of Eastern Africa
XEC• Vanuatu• Grenada• Palestinian Territory, Oc-• Burundi• Guadeloupe• Sao Tome and Principe

lic of thecupied• Comoros

Rest of East Asia XEA• Haiti• Qatar• Djibouti• Korea, Democratic Republic• Jamaica• Saudi Arabia• Eritreaof• Martinique• Syrian Arab Republic• Kenya• Macau• Montserrat• United Arab Emirates• Mayotte• Mongolia• Netherlands Antilles• Reunion• Puerto Rico

Rest of North Africa XNF• Rwanda

Rest of Southeast Asia
XSE

• Saint Kitts and Nevis• Algeria• Seychelles• Saint Lucia• Libyan Arab Jamahiriya• Somalia• Brunei Darussalam• Saint Vincent and the• Sudan• Trinidad and Tobago

Rest of Western Africa
XWF

Rest of South Asia XSA• Turks and Caicos• BeninRest of South African
Customs Union• Afghanistan• Virgin Islands, British• Burkina Faso

• Lesotho• Bhutan• Virgin Islands, U.S.

• Cape Verde• Namibia• Cote d’Ivoire• Swaziland• Timor-Leste

Grenadines• MaldivesRest of EFTA

• Gambia• Iceland• GhanaRest of North America
XNA• Liechtenstein• Guinea• Bermuda

Rest of Europe XER• Liberia• Greenland• Andorra• Mali• Saint Pierre and Miquelon• Bosnia and Herzegovina• Mauritania• Nepal• Guinea-Bissau

CHAPTER 5 Are national economies (virtually) sustainable?

109

110

Inclusive Wealth Report
707
548

356,409

Sweden1,272

626,189

Netherlands

362,908

60,593

634,214

Rest of West Asia

Belgium

4,901

647,037

Brazil974

7,047

695,941

India

387,401

1,008

724,100

Korea, Republic of

Turkey4,197

749,084

Mexico63

14,505

971,963

Canada388,8881,760

1,030,351

Spain

Switzerland

1,594

1,717,791

Italy

7,707

34,308

1,928,118

China

29,586

2,059

2,077,657

France578,9718,444

2,215,020

United Kingdom

581,527

3,735

2,764,179

Germany

Russian Federation

4,601

4,694,853

Japan

Australia

35,611

Value

0.15

0.19

0.25

0.02

5.11

1.33

0.20

9.55

0.76

1.01

0.14

0.56

1.49

0.17

0.09

1.78

0.10

0.38

0.14

0.10

0.30

(%GNI)

1,775

2,722

3,628

1,376

10,948

5,053

2,188

10,347

5,055

13,026

8,047

4,210

7,827

7,506

9,741

36,819

9,902

11,276

15,597

27,52278,387

Value

0.50

0.75

0.94

0.35

1.89

0.87

0.35

1.63

0.78

1.87

1.11

0.56

0.81

0.73

0.57

1.91

0.48

0.51

0.56

0.59

0.67

(%GNI)

Consumption(in millions, US$)

Total Resource Depletion
Production

11,687,900(in millions
of US$)

United States

Country Name

GNI
Ratio

0.31

0.26

0.27

0.05

2.70

1.53

0.58

5.86

0.97

0.54

0.13

1.00

1.85

0.23

0.16

0.93

0.21

0.75

0.24

0.17

0.45

Production/
Consumption
Value

61

68

13

9

206

386

33

512

27

6

21

40

454

41

27

26

34

142

45

36

121

1.16

1.30

0.26

0.17

3.93

7.39

0.63

9.78

0.51

0.12

0.40

0.76

8.67

0.79

0.53

0.50

0.65

2.71

0.86

0.69

2.30

(P/GA)

Production
Value

197

261

50

190

76

253

57

87

27

12

169

40

245

176

168

28

164

190

189

215

265

3.63

4.81

0.92

3.50

1.40

4.66

1.04

1.61

0.51

0.22

3.11

0.73

4.51

3.24

3.09

0.52

3.02

3.49

3.47

3.96

4.88

C/GA

Consumption(GA) (in US$)Per Capita Resource Depletion andComparison to Global Average

729

1,578

3,035

664

23,517

5,091

3,970

14,4094,374

17,116

5,474

6,140

8,190

4,748

6,419

69,055

5,414

8,336

12,131

15,70485,421

Value

0.20

0.43

0.78

0.17

4.06

0.88

0.63

2.27

0.68

2.46

0.76

0.82

0.84

0.46

0.37

3.58

0.26

0.38

0.44

0.34

0.73

% GNI

Production

1,285

2,266

3,571

1,376

18,180

5,036

3,635

11,4034129

15,856

5,717

6,533

7,707

5,862

8,336

54,093

7,953

11,891

14,87820,14095,467

Value

0.36

0.62

0.92

0.35

3.14

0.87

0.58

1.80

0.64

2.28

0.79

0.87

0.79

0.57

0.49

2.81

0.38

0.54

0.54

0.43

0.82

% GNI

Consumption(in millions, US$) $50/tC

CO 2 Emissions

Note: In some cases the sum column across countries may not add exactly to the total value of the ‘World’. This is concretely due to the rounding in several values at the regional level.
Raw data from GTAP v7. See Narayanan and Walmsley (2008) available online at http://www.gtap.agecon.purdue.edu/databases/v7/v7_doco.asp

Table A1: Resource Depletion and Carbon Emissions by Country.

Appendix 2

CHAPTER 5 Are national economies (virtually) sustainable?

111

307
14,351
1,680
1,641
560
9,142
1,936
504
371

290,517
259,079
245,851244,566
227,323
225,214
211,700
190,495
176,127

Austria

NorwayDenmark

PolandGreeceIndonesia

South Africa

Finland

Portugal

0.61
14,611
275
1,752
2,338
4,947
11,754
2,498
8,424
405
41
456
187
523
790

160,332
157,376
154,104
144,211
118,328
114,553
109,496
108,779
103,508
103,199
100,140
96,864
93,907
93,649Iran, Islamic Republic of

IrelandThailand

Argentina

Malaysia

Rest of North Africa

Colombia

Venezuela, RB

Czech RepublicSingapore

Pakistan

Hungary

New ZealandPhilippines

168,892

1,037

Hong Kong – China

590

329,838

0.84

0.56

0.19

0.46

0.04

0.39

7.74

2.28

10.26

4.18

1.62

1.14

0.17

9.11

1,769

0.21

0.26

0.91

4.06

0.25

0.67

0.68

5.54

0.11

0.18

(%GNI)

1,856

737

702

1,548

1,022

836

1,421

1,122

2,273

1,769

1,184

3,179

963

4,924

1.05

1,460

1,135

2,058

6,256

1,826

3,193

1,144

1,233

1,552

3,458

Value

1.98

0.78

0.72

1.55

0.99

0.81

1.31

1.02

1.98

1.50

0.82

2.06

0.61

3.07

0.59

0.83

0.60

0.97

2.78

0.80

1.31

0.47

0.48

0.53

1.05

(%GNI)

Consumption(in millions, US$)

Total Resource Depletion
Production
Value

TaiwanCountry Name(in millions
of US$)

GNI
Ratio

0.43

0.71

0.27

0.29

0.04

0.48

5.93

2.23

5.17

2.80

1.97

0.55

0.29

2.97

149

0.25

0.44

0.94

1.46

0.31

0.51

1.47

11.64

0.20

0.17

Production/
Consumption

38

26

10

131

18

3

10

40

321

56

308

199

61

28

67

212

2.85

35

96

41

42

50

101

310

3,120

Value

0.19

2.50

0.35

0.06

0.18

0.76

6.13

1.06

5.90

3.80

1.16

0.53

1.29

4.06

254

0.68

1.84

0.78

0.79

0.96

1.93

5.93

59.62

0.72

0.50

(P/GA)

Production

140

217

44

28

165

197

212

268

190

152

23

185

69

10

239

82

54

25

60

71

31

50

236

72

4.68

Value

0.42

3.40

1.28

0.18

4.41

1.50

1.00

0.46

1.10

1.31

0.57

0.92

4.35

1.32

806

2.57

3.99

0.80

0.52

3.03

3.62

3.89

4.94

3.50

2.80

C/GA

Consumption(GA) (in US$)Per Capita Resource Depletion andComparison to Global Average
CO 2 Emissions

1,208

527

844

2,158

557

1,734

2,178

859

2,300

2,085

2,170

3,218

668

6,663

0.48

934

950

5,363

5,232

1,377

3,051

757

888

1,085

3,370

Value

1.29

0.56

0.87

2.15

0.54

1.67

2.00

0.79

2.01

1.76

1.51

2.09

0.43

4.16

1,499

0.53

0.50

2.53

2.32

0.61

1.25

0.31

0.34

0.37

1.02

% GNI

Production

1,263

613

1,009

2,374

962

1,404

1,661

900

2,099

1,336

1,721

2,596

848

6,728

0.89

1,141

1,075

3,598

4,763

1,701

3,369

1,069

782

1,559

2,796

Value

1.35

0.65

1.04

2.37

0.93

1.36

1.53

0.82

1.83

1.13

1.19

1.69

0.54

4.20

0.65

0.56

1.70

2.12

0.75

1.38

0.43

0.30

0.54

0.85

% GNI

Consumption(in millions, US$) $50/tC

112

Inclusive Wealth Report

9392

29,59326,895

EcuadorLuxembourg

Tunisia

62

1,947

30,740Rest of Central Africa

497

2,582

31,819Slovenia

21,93773

33,334

Croatia

23,167

115

39,891

Rest of East Africa

Lithuania

1,643

39,926

Kazakhstan

Belarus

2,529

40,289Vietnam

3,258

1,897

44,554

Rest of Western Africa

23,571

1,081

50,191

Rest of Caribbean

Rest of South Central
Africa1,061

53,616

Slovak Republic

101

97

55,490Morocco23,627

270

55,961

Bangladesh

Guatemala958

59,542

Ukraine156

633

64,084

Peru

434

903

66,037

Romania

24,610505

73,910

Nigeria

24,953

9,354

78,110Egypt, Arab Republic ofRest of Central America

2,976

Bulgaria

1,046

78,757

0.28

2.14

13.82

0.43

0.63

1.74

1.46

0.03

6.33

8.12

0.22

0.29

4.11

6.28

4.26

2.15

1.98

0.18

0.48

1.61

0.99

1.37

0.68

11.98

3.78

1.19

(%GNI)

931

281

500

352

279

410

608

464

222

734

496

269

381

1,117

805

1,152

921

1,952

389

743

1,297

1,301

938

781

931

2,207

Value

1.28

2.16

1.49

1.18

1.67

2.44

1.72

0.75

2.39

1.56

0.81

0.95

2.80

2.00

2.59

1.83

3.64

0.70

1.33

2.18

2.03

1.42

1.06

1.19

2.80

1.06

(%GNI)

Consumption(in millions, US$)

Total Resource Depletion
Production
Value

87,815(in millions
of US$)

Chile

Country Name

GNI
Ratio

0.22

0.99

9.25

0.36

0.38

0.71

0.85

0.04

2.65

5.21

0.27

0.30

1.47

3.14

1.65

1.17

0.54

0.25

0.36

0.74

0.49

0.96

0.65

10.05

1.35

1.12

Production/
Consumption
Value

18

51

46

8

11

56

39

20

149

73

37

25

16

170

23

9

28

18

9

7

13

33

23

73

41

65

0.35

0.97

0.87

0.16

0.21

1.07

0.75

0.37

2.85

1.40

0.71

0.48

0.31

3.26

0.44

0.18

0.53

0.35

0.17

0.13

0.26

0.63

0.44

1.39

0.78

1.24

(P/GA)

Production
Value

82

51

5

23

29

78

46

490

56

14

137

84

11

54

14

8

51

72

24

9

28

34

36

7

30

58

1.50

0.94

0.09

0.42

0.54

1.44

0.85

9.01

1.04

0.26

2.52

1.54

0.21

1.00

0.26

0.14

0.93

1.33

0.44

0.17

0.51

0.63

0.66

0.13

0.56

1.06

C/GA

Consumption(GA) (in US$)Per Capita Resource Depletion andComparison to Global Average
CO 2 Emissions

929

188

828

154

165

213

687

355

200

324

160

233

320

381

2,447

1,197

361

2,465

473

580

541

5,021

575

1,476

785

1,977

Value

0.86

3.57

0.65

0.70

0.87

2.75

1.32

0.68

1.06

0.50

0.70

0.80

0.95

6.07

2.69

0.72

4.60

0.85

1.04

0.91

7.84

0.87

2.00

1.00

2.51

1.06

% GNI

Production

800

263

766

240

242

301

627

339

232

389

219

284

382

607

2,045

1,237

599

2,415

500

686

736

2,812

604

1,269

793

1,770

Value

1.20

3.31

1.02

1.02

1.22

2.51

1.26

0.79

1.27

0.69

0.85

0.96

1.52

5.08

2.78

1.19

4.50

0.90

1.23

1.24

4.39

0.92

1.72

1.01

2.25

0.91

% GNI

Consumption(in millions, US$) $50/tC

CHAPTER 5 Are national economies (virtually) sustainable?

113

454
41
83
13
275
1,907
51
104
20
563
49
149

19,32917,81815,551
15,135
14,605
13,98013,49913,137
13,095
11,483
11,350
11,153

Rest of Europe

Costa Rica

Rest of EFTA

CyprusRest of South Asia

Former Soviet Union

LatviaPanamaUruguay

Rest of East Asia

Estonia

Tanzania

64
211
295
233
818
425
976
23
287

349,294

9,989
8,869
8,388
8,338
8,323
8,144
7,980
1,600
-

41,272,071

Ethiopia

Botswana

Bolivia

UgandaRest of South East Asia

Rest of Oceania

Azerbaijan

Rest of North America

World

Myanmar1.53

162

10,573

Rest of SACU

187

20,4580.8463205

-

1.44

12.23

5.22

9.83

2.79

3.52

2.38

0.64

89

1.34

0.43

4.90

0.15

0.79

0.37

13.64

1.88

0.09

0.53

0.23

2.35

0.91

(%GNI)

188

84

375

300

48

98

150

68

180

0.85

225

127

458

139

168

174

844

341

165

115

152

762

495

349,294

Value

0.8463205

-

5.25

4.69

3.69

0.58

1.18

1.78

0.77

1.81

1.81

2.02

1.12

3.99

1.06

1.28

1.29

6.04

2.34

1.09

0.74

0.85

3.94

2.42

(%GNI)

Consumption(in millions, US$)

Total Resource Depletion
Production
Value

Sri Lanka

Country Name(in millions
of US$)

GNI
Ratio

1

1.53

0.27

2.60

1.42

17.03

2.37

1.97

3.10

0.35

33

0.66

0.38

1.23

0.14

0.62

0.29

2.26

0.81

0.08

0.72

0.27

0.60

0.38

Production/
Consumption

6

180

117

49

634

8

33

119

1

0.64

4

36

22

6

33

22

51

5

16

255

10

32

9

54.54

Value

1

0.11

3.44

2.23

0.93

12.12

0.16

0.63

2.27

0.02

18

0.08

0.69

0.42

0.11

0.63

0.42

0.97

0.09

0.30

4.88

0.18

0.61

0.17

(P/GA)

Production

4

656

45

34

37

4

17

38

2

0.34

6

95

18

40

53

75

23

6

199

354

36

53

24

54.54

Value

1

0.07

12.07

0.83

0.63

0.69

0.07

0.31

0.71

0.04

62

0.11

1.75

0.33

0.74

0.97

1.38

0.42

0.11

3.67

6.52

0.66

0.98

0.44

C/GA

Consumption(GA) (in US$)Per Capita Resource Depletion andComparison to Global Average
CO 2 Emissions

187

384,358

135

52

479

266

109

49

165

63

92

0.58

74

231

1,067

79

90

111

2,957

148

110

85

90

1,100

Value

0.93

-

3.27

6.00

3.27

1.31

0.58

1.97

0.71

0.92

111

0.66

2.03

9.29

0.61

0.69

0.82

21.15

1.01

0.73

0.55

0.50

5.69

0.91

% GNI

Production

271

384,358

172

80

542

286

70

69

164

108

141

1.05

127

223

817

117

133

215

2,331

252

148

95

122

1,078

Value

0.93

-

4.97

6.79

3.51

0.84

0.83

1.96

1.22

1.41

1.14

1.96

7.11

0.89

1.01

1.59

16.67

1.72

0.98

0.61

0.68

5.58

1.32

% GNI

Consumption(in millions, US$) $50/tC

114

Inclusive Wealth Report

682
9,495
3,874
402
203
133
6,983
5,207
1,702
698
341
6,247
1,250

480
2,997
2,796
223
143
86
3,834
2,060
1,342
349
156
3,440
766

China

Japan

East Asia

South East Asia

India

South Asia

CanadaUnited States

MexicoSouth America

Central America/ Caribbean

EU-15

Russia15,463
952
129
1,404

9,484
408
44
720

North Africa/ Middle East

Sub-Saharan Africa

World

Other Europe

780

281

EITs

Aus./NZ/ Oceania

5,344

Gross saving

2,539(millions, US$)Genuinesaving

-853

-71

-411

-7,682-535-261-4,121

-184

-385

-636

-4,612-3,993

-43

-66

-160

-1,446-7,492-150-3,434

282

26

157

2,905

175

141

1,492

57

127

372

1,869

1,544

9

28

42

502

1,150

26

1,069

Depreciation
Educationof produced
expenditures
capital

-59

-11

-70

-132

-94

-161

-120

-39

-31

-57

-285

-253

-8

-16

-25

-103

-121

-52

-178

Carbonemissions

-54

-29

-220

-1,070

-45

-203

-58

-19

-60

-39

-119

-447

-5

-6

-36

-31

-35

-26

-262

Naturalresources

-139

-364

-178

-58

-91

-96

-404

-700

-13

-22

-61

-134

-156

-78

-440

-113

-40

-290

-1,202

Total

Change in natural assets: production
perspective

Genuine saving components

Raw data from GTAP v7. See Narayanan and Walmsley (2008) available online at http://www.gtap.agecon.purdue.edu/databases/v7/v7_doco.asp

Table A2: Per Capita Contribution to Global Sustainability by Region

Appendix 3“Virtual sustainability”

-59

-10

-64

-181

-82

-125

-155

-42

-28

-61

-319

-239

-10

-14

-22

-104

-155

-41

-179

Carbonemissions

-54

-10

-59

-217

-53

-75

-168

-39

-31

-39

-262

-243

-10

-12

-28

-132

-212

-28

-184

Naturalresources

Total

-113

-20

-123

-398

-135

-200

-323

-81

-59

-100

-581

-482

-20

-26

-50

-236

-367

-69

-363

Change in natural assets: consumption
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CHAPTER 5 Are national economies (virtually) sustainable?

117

Part II

PART I Wealth Accounts

119

120

Inclusive Wealth ReportChapter 6

Natural capital as economic assets:a review
Partha Dasgupta

Key Messages
In calculating total wealth, depleting atype of natural capital and substituting it withanother form of natural capital or with manufactured capital is frequently uneconomical inmost countries. The assumption of absolute
substitutability is not a realistic one.
Externalities are the effects of activities
on the well-being of people who have not been
parties to the negotiations that led to those
activities. An example is the impact of upstream
deforestation on downstream farmers. Without
correction, the use of natural capital is implicitly subsidized by people who suffer from theexternalities.

The social worth of natural resources can bedivided into three parts: use value, intrinsic value,
and option value – in varying proportions.
Property rights are currently focusedon individual ownership. However, many of
nature’s services are public and therefore itis difficult to assign property rights to them.
Moreover, if those rights are assigned, they are
typically assigned without due accord to social
justice. Ill-specified or unprotected property
rights typically prevent markets from forming
or make markets function wrongly when theydo.

A large part of what nature offers is a necessity and not a luxury. There are options for somelevel of substitutability, but in consideration,caution must be taken for irreversible processes
that might cause a decrease in well-being.

121

1. Introduction
Natural capital can be consumed directly (e.g.,
fruit and honey), used indirectly as inputs into
production (e.g., fossil fuels and microbes that
regulate diseases), or used directly and indirectlyat the same time (e.g., clean air and fresh water).
The value of natural capital could be utilitarian (e.g., a source of food or a keystone species)– economists call that its use-value; it could beaesthetic (e.g., places of scenic beauty); it could
be intrinsic (e.g., primates and sacred groves); or
it could be all those things together – in a word,biodiversity.
Natural capital often possesses yet anotherkind of value. It arises from a combination of
two things: uncertainty in the future use-valueof a resource (Box 1); and irreversibility in its use.
Genetic material in tropical forests is a primeexample. The twin presence of uncertainty andirreversibility implies that preservation of its
stock has the benefit of offering society flexibility regarding the future. Future options haveadditional value because, with the passage oftime, more information should be forthcoming
about the resource’s use-value. That additional
worth is often called an option value.1
Natural capital’s worth to us could be fromthe product flows we are able to extract from it(e.g., timber, gum, honey, leaves, and bark), orfrom its presence as a stock (e.g., forest cover),or from both (e.g., watersheds). The stock could
be an index of quality (e.g., air quality) or quantity. Quantity is sometimes expressed as a pure
number (e.g., population size); in various othercases it is, respectively, (bio)mass, area, volume,or depth. But even quality indices are often
based on quantity indices, as in “parts per cubic
centimeters” for measuring atmospheric haze.
We view natural capital here in an inclusive
way. At one extreme are fossil fuels. Economists
call them “exhaustible resources” because each

1 The pioneering works on option values are
Weisbrod (1964), Arrow and Fisher (1974), and Henry(1974). Option values are discussed in Section 7.3 andBox 4.

122

unit of a fossil fuel used in production is lost forever. More broadly, economists sometimes referto natural capital as “environmental resources,”sometimes as “natural resources,” and at othertimes as “environmental natural resources,” thedouble adjective being a way to ensure that readers take their minds off dams, tarmacs, bulldozers, chain-saws, and automobiles.
However, when economists speak of environmental resources, they have regenerative
resources in mind (e.g., water, timber, pollination). Handled with care, it can be put to use
in a sustained way, but gets depleted if it isexploited at rates exceeding its ability to regenerate itself. The central problem in sustainability science is to uncover ways by which a literallyindeterminate number of interlocking naturalprocesses that shape regenerative resources canbe managed so as to enable humanity to flourish indefinitely.
The Millennium Ecosystem Assessment (MA)(2005) was a pioneering study of the services
humanity enjoys from ecosystems. Ecosystems
are a mesh of humans and natural resourcesinteracting with one another at a multitudeof speeds and across often overlapping spatial
scales. What constitutes an ecosystem is therefore dictated by the scope of the environmental
problem. A number of ecosystems have a global
reach (e.g., the deep oceans); others extend overlarge land masses (e.g., “biomes,” such as theSavannah and the tundra); some cover entire
regions (e.g., river basins); many involve clustersof villages (e.g., micro-watersheds); while others
are confined to the level of a single village (e.g.,
the village pond).
MA (2005) offered a four-way classificationof ecosystem services: (i) provisioning services(e.g., food, fiber, fuel, fresh water); (ii) regulating services (e.g., protection against natural
hazards such as storms; the climate system);(iii) supporting services (e.g., nutrient cycling,soil production); and (iv) cultural services (e.g.,recreation, cultural landscapes, aesthetic or
spiritual experiences).In Sections 6 and 7 where
we review various methods that have beendevised to value natural capital, we will observe
Inclusive Wealth Reportthat the MA classification can be unified for the
purposes of quantitative reasoning. Here it isalso useful to note that cultural services and avariety of regulating services (such as disease
regulation) contribute directly to human wellbeing, whereas others like soil production, forexample, contribute indirectly by providing themeans to grow food crops.

2.	Nature as a capital asset
Viewing natural capital in an inclusive way
allows us to develop a comprehensive language
for sustainability science. We begin by studying
five related issues that appear regularly in public discussions on the state of the environment:
pollution and conservation; economic growth
and the environment; necessities vs. luxuries;
irreversible uses; and substitution possibilities.

2.1 Pollution and conservation

The mirror symmetry between conservationand pollution is illustrated by the atmosphere,
which serves as both a source of nourishment
and a sink for pollutants. The atmosphere isa public good: if the quality of the open atmosphere is improved, we all enjoy the benefits,
and no one is excluded from enjoying thosebenefits.3 However, unless public legislation
says otherwise, the atmosphere is also a common pool for pollution. It’s a pool into which
everyone can discharge pollutants without having to pay. As the atmosphere is a public good,
the private benefit from improving air quality isless than the social benefit. It follows that in theabsence of collective action (e.g., public investment or public subsidy in cleaner technologies),
there is under-investment in air quality.
Now look at the reverse side of the coin. As
the atmosphere is a pool into which pollutants(e.g., carbon compounds) can be deposited by us
all at no charge, the private cost of pollution isless than the social cost. It follows that withoutcollective action (the imposition of a pollution
tax; quantity restriction per user; or “cap-andtrade,” which continues to be a much-discussed
social mechanism for controlling carbon emissions), there is excessive use of the pool as a sink
for pollutants. Either way, the atmosphere suffers from “the tragedy of the commons,” which
is a dramatic way of characterizing a wedge
between private incentives and collective aspirations that is created by inadequate or ineffective property rights.4

There is no conceptual difference between
pollution and conservation. Environmental
pollutants are the other side of environmental
natural resources. In some cases, the emissionof pollutants leads directly to a degradation of
ecosystems (e.g., the effect of acid rains on forests); in others (e.g., wastes from pulp and paper
mills), it means a reduction in environmental
quality (deterioration of water quality in nearby
streams), which also amounts to degradation of
ecosystems (watersheds); in still others, it meansdepreciation of manufactured capital (e.g., thecorrosion of buildings and structures). Thus, foranalytical purposes there is no reason to distinguish resource management from pollution
management. Roughly speaking, “resources”
are “goods,” while “pollutants” (the degrader ofresources) are “bads.” Pollution is the reverse ofconservation.2

3 The two characteristics of the atmosphere mentioned here define “public goods”: such goods have theproperties that (i) they are jointly consumable; and (ii)no one can be excluded from consuming them. Whatmakes public goods “public” is an extreme feature ofcommodities whose use involves externalities, which
are defined in Section X.

2 This dual structure was developed in Dasgupta(1982).

4 The metaphor is due to Hardin who coined theterm “The Tragedy of the Commons” to explain theoverexploitation of resources with no well establishedrules of use and governance (1968).

CHAPTER 6 Natural capital as economic assets

1232.2 Economic growth and the environment5aQuantity index

The theory

GDP

Pollution

Time

Incentives to protect
the environment
introduced

Cleaner and more
efficient technologies
adopted in response

B

The practice: GDP and emissions in OECD
countries
200

Index 1970=100
GDP

150

Nitrogen oxides
100

Sulfur oxides
50

Lead
Particulates

The theory and the practice: GDP and emissions inOECD countries

1988

Figure 1

1985

1980

1975

1970

0

Ecosystem services are not only intrinsicallyvaluable, they also have functional worth. But
scratch an economist and you are likely to findsomeone who regards natural capital as a luxury.
It is commonly thought that, to quote an editorial in the U.K.’s The Independent (December
4, 1999), “... (economic) growth is good for theenvironment because countries need to put
poverty behind them in order to care,” or, toquote The Economist (December 4, 1999: 17),“... trade improves the environment, because it
raises incomes, and the richer people are, themore willing they are to devote resources tocleaning up their living space.”
The idea is illustrated in the upper panelof Figure 1 and is given credence in the lower
panel, where emissions of nitrous oxides (NOx),sulfur oxides (SOx), particulates, and lead were
all found to have declined since 1970 in OECD
countries even while gross domestic product(GDP) increased. Figure 1 is taken from WorldBank (1992). Figure 2, also taken from WorldBank (1992), shows that among countries where
per capita income was under US$1,200 per year,
the less poor suffered from greater concentrations of sulfur dioxide, but that among countries
enjoying per capita income in excess of US$1,200,
those that were richer suffered from lower concentrations. In short, the relationship between
income per capita and concentration has theshape of an inverted-U. Among environmental
economists, the curve in Figure 2 was promptly
christened the “environmental Kuznets curve”
because a similar relationship between GDP per
capita and income inequality had been founddecades ago by the economist Simon Kuznets.
Figure 2 is based on inter-country data, not timeseries. Nevertheless, when taken in conjunction
with Figure 1, it was found natural to interpretthe evidence in such terms as the following:

5 This section draws heavily from Arrow et al. (1995),
which was republished, with comments by a number ofexperts, in Environment and Development Economics(1996), Vol. 1, No. 1.

124Inclusive Wealth ReportCHAPTER 6 Natural capital as economic assets

ants to other countries (transfer of dirty to dirty
technology from rich to poor countries).
And fourth, in most cases where pollution concentrations have declined with risingincome, the reductions have been due to local
institutional reforms, such as environmental
legislation and market-based incentives toreduce environmental impacts. Such reforms
may ignore their possible adverse side effects
on the poor and future generations. Wherethe environmental costs of economic activity are borne by those under-represented in
the political process, the incentives to correct
environmental problems are likely to be weak.
The upper panel of Figure 1 is something of amirage.
The solution to environmental degradation
lies in such institutional reforms as would offer
incentives to private users of resources to takeaccount of the social costs of their actions. The
inverted-U curve suggests this can happen only
in some cases. Moreover, as we have alreadydeduced, growth in GDP per capita is a wrong
objective, we should instead be studying movements in wealth, not GDP.

2.3 Necessities vs. luxuries
Contrary to the views expressed in our quotes
from newspapers, a large partof what nature offers us is a Figure 2
necessity, not a luxury. Many Concentrations of sulfur
dioxide55

Micrograms per cubic meter of air“People in poor countries can’t afford placing
a weight on the natural environment over material well-being. So, in the early stages of economic development pollution is taken to be an
acceptable, if unfortunate, side-effect of growth
in GDP per capita. However, when a country has
attained a sufficiently high standard of living,people care more about the natural environment. This leads them to pass environmental
legislation and create new institutions to protect the environment.”
The argument has been invoked in the main
for amenities. Even within this class of goods,
the environmental Kuznets curve has been
uncovered for a very limited number of pollutants. Nevertheless, because it is consistent with
the notion that as their incomes rise people
spend proportionately more on environmental
quality, it has proved tempting to believe that
Figures 1 and 2 apply to environmental quality
generally.
The temptation should be resisted. For
example, if the degradation of natural capital were irreversible, economic growth itself
would be at risk. And there are other reasons
we should reject the use of Figure 1 as a generalmetaphor for the relationship between GDP and
the state of the natural environment. Here are
four reasons:First, the inverted-U has been shown to bevalid for pollutants involving local, short-term
damages (sulfur, particulates, fecal coliforms),
not for the accumulation of waste, nor for pollutants involving long-term and more dispersed
costs, such as carbon dioxide, which typicallyhave been found to increase continuously withincome (World Bank 1992; Stern 2006).
Second, the relationship between income
per capita and environmental pollution cannot
be the inverted-U if the feedback from pollution
to the state of ecosystems is positive.
Third, the inverted-U hides system-wide
consequences of emissions. Reductions in one
pollutant in one country, for example, could
involve increases in other pollutants in thesame country or transfers of those same pollut-

45

35

1976
25

1985

15

5
1 00

1 , 000

1 0, 000

10 0 ,0 0 0

Income per capita (dollars, log scale)125

of the services we obtain from natural capitalare “basic needs.” Among the visible products
are food, fibers, fuel, and fresh water – provisioning services (MA 2005). But many are hiddenfrom view. Ecosystems, for example, maintaina genetic library, preserve and regenerate soil,
fix nitrogen and carbon, recycle nutrients, control floods, mitigate droughts, filter pollutants,
assimilate waste, pollinate crops, operate thehydrological cycle, and maintain the gaseouscomposition of the atmosphere – regulating
services (MA 2005). A number of services filter
into a global context, but many are geographically confined. Human well-being and the stateof our natural environment are closely linked(Duraiappah et al. 2005).
Natural capital offers joint products.
Circulation of material (e.g., ocean currents andthe wind system) transfers energy around theglobe (e.g., influences precipitation) and dilutes
pollutants; wetlands recycle nutrients and produce purified water; mangrove forests protect
coastal land from storms and are spawning
grounds for fish; and so on. Unhappily, social
tensions arise in those many cases where an
ecosystem has competing uses (farms versus
forests versus urban development; forests versus agro-ecosystems; coastal fisheries versus
aquaculture6). Dasgupta (1982, 1993) and Sachs,
Gallup, and Mellinger (1998) traced the locationof world poverty in part to the fact that the tropics harbor some of the most fragile ecosystems,
including those that regulate disease. Carpenter
et al. (2005) and Hassan, Scholes, and Ash(2005), which contain the first two sets of technical reports accompanying the Millennium
Ecosystem Assessment, found that 15 out of the
24 major ecosystem services that the MA examined are either already degraded or are currently
subject to unsustainable use.
A resource can be a luxury for others evenwhile it is a necessity for some. Consider
watersheds, which nurture commercial timber,
6 See Tomich et al. (2004), Tomich et al. (2005),
and Palm et al. (2005); and Hassan, Scholes, and Ash(2005), respectively, on those tensions.

126

agricultural land, recreational opportunities,
and both market and non-market products (e.g.,gums, resin, honey, fibers, fodder, fresh water,
timber, and fuelwood). Watershed forests
purify water and protect downstream farmers
and fishermen from floods, droughts, and sediments. In tropical watersheds, forests house vastquantities of carbon and are the primary homeof biodiversity. A number of products fromwatersheds are necessities for local inhabitants,
including forest dwellers, downstream farmers,
and fishermen; some are sources of revenue forcommercial firms (e.g., timber companies), whileothers are luxuries for outsiders (eco-tourists).
Some benefits accrue to nationals (agricultural
products and fibers), while others spill overgeographical boundaries (carbon sequestration).
So, while watersheds offer joint products (e.g.,protection of biodiversity, flood control, carbon
sequestration, and household necessities), theyalso provide potential services that compete
against one another (commercial timber, agricultural land, and biodiversity). Competition
for nature’s services has been a prime causeof the transformation of ecosystems. Politics
often intervenes to ensure that commercial
demand trumps local needs, especially under
non-democratic regimes. Governments in poor
countries have been known to issue timber concessions in upstream forests to private logging
firms, even while evicting forest dwellers andincreasing siltation and the risk of downstream
flooding. Nor can the international community
be depended upon to apply pressure on governments. When biodiversity is lost at a particularsite, eco-tourists go elsewhere that has richbiodiversity to offer. So, international opinion
is often at best tepid. In both examples, local
needs are outflanked by outsiders’ demands.

2.4 Irreversible uses
Ecosystems are driven by interlocking non-linear
processes that run at various speeds and operate
at different spatial scales (Steffen et al. 2004).
That is why ecosystems harbor multiple basins
Inclusive Wealth Report

of attraction. The global climate system is now
a well-known example, but small-scale ecosystems also contain multiple basins of attraction,and for similar reasons. For example, so long as
phosphorus runoff into a fresh water lake is lessthan the rate at which the nutrient settles at thebottom, the water column remains clear. But
if over a period of time the runoff exceeds that
rate, the lake collapses into a eutrophic state.
Usually the point at which the lake will collapse
is unknown. That means the system is driven by
non-linear stochastic processes (as discussed inBox 1 in Chapter 1).
When wetlands, forests, and woodlands
are destroyed (for agriculture, mining, timber
extraction, urban extension, or other uses),
traditional dwellers suffer. For them, and they
are among the poorest in society, there areno substitutes. For others, there is somethingelse, often somewhere else, which means there
are substitutes. Degradation of ecosystems islike the depreciation of roads, buildings, andmachinery – but with three big differences: (1)depreciation of natural capital is frequently
irreversible (or at best the systems take a longtime to recover); (2) except in a very limitedsense, it isn’t possible to replace a depleted ordegraded ecosystem with a new one; and (3)ecosystems can collapse abruptly, without muchprior warning. Imagine what would happen to acity’s inhabitants if the infrastructure connecting it to the outside world was to break down
without notice. Vanishing water holes, deteriorating grazing fields, barren slopes, and wasting
mangroves are spatially confined instances ofcorresponding breakdowns for the rural poor
in poor countries. In recent years we have also
seen how an ecological collapse accompanying
high population growth, such as the one thathas been experienced in recent years in theHorn of Africa and the Darfur region of Sudan,
can trigger rapid socio-economic decline(Homer-Dixon 1999; Diamond 2005; Collier2007). The range between a need and a luxury
is thus enormous and dependent on context.
Macroeconomic reasoning glosses over the heterogeneity of earth’s resources and the diverse
CHAPTER 6 Natural capital as economic assets

uses to which they are put, by people residing at
the site and those elsewhere.

2.5 Substitution possibilities
Environmental debates are often over the extent
to which people are able to substitute one thing
for another. Many believe that problems arising from the depletion of natural capital canalways be overcome by the accumulation of
manufactured capital, knowledge, and skills.7
Others argue that humanity has reached thestage where there are severe limits to further
substitution possibilities among large numbersof natural resources and among environmental resources and other forms of capital assets(Ehrlich and Goulder 2007).
Four kinds of substitution help to easeresource constraints, be they local or global.
First, there can be substitution of one thing foranother in consumption (e.g., nylon and rayon
substituting for cotton and wool; pulses substituting for meat). Second, manufactured capitalcan substitute for labor and natural capital inproduction (the wheel and double-glazing are
two extreme examples). Third, novel production techniques can substitute for old ones.8
Fourth, and most important in the context of
this chapter, natural resources themselves cansubstitute for one another (e.g., renewableenergy sources could substitute for non-renewable ones). These examples point to a general
idea: as each resource is depleted, there areclose substitutes lying in wait, either at the siteor elsewhere. The thought that follows is thateven as constraints increasingly bite on any one
resource base, humanity should be able move
7 Lomborg (2001) is an example. Macroeconomic
growth theories are mostly built on economic models
in which Nature makes no appearance.
8 For example, the discovery of effective ways toreplace the piston by the steam turbine (i.e., converting from reciprocating to rotary motion) was introduced into power plants and ships a little over 100
years ago. The innovation was an enormous energy
saver in engines.

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Box 1

Timber export and wealth transfers
An easy way for governments in countries thatare rich in forests to earn revenue is to issue timber
concessions to private firms. Often, concessions areawarded in forests in upstream watersheds. However,
deforestation gives rise to soil erosion and increases
fluctuations in water supply downstream. If the law
recognizes the rights of those who suffer damage fromdeforestation, the timber firm would be required tocompensate downstream farmers. But compensationis unlikely because (a) the cause of damage is many
miles away, (b) the concession has been awarded by
the state, and (c) the victims are scattered groups of
farmers. Problems are compounded because the damage is not uniform across farms: location matters. It
can also be that those who are harmed by deforestation don’t know the underlying cause of their deteriorating circumstances. As the timber firm isn’t required
to compensate farmers, its operating cost is less than
the social cost of deforestation (the latter, as a first
approximation, being the firm’s logging costs and thedamage suffered by all who are adversely affected). The
export therefore contains an implicit subsidy, paid forby farmers downstream. And we haven’t included forest
inhabitants, who now live under even more straightened
circumstances; or worse, are evicted without compensation. The subsidy is hidden from public scrutiny, but
it amounts to a transfer of wealth from the exporting
country to the importing country. Some of the poorest
people in a poor country subsidize the incomes of theaverage importer in what could well be a rich country.
That doesn’t feel right.
(Based on Dasgupta ([1990])

to other resource bases, either at the same siteor elsewhere. The enormous additions to thesources of industrial energy that have been realized (successively, human and animal power,
wind, timber, water, coal, oil and natural gas,and, most recently, nuclear power) are a prime
historical illustration of this possibility.9
Humanity has been substituting one thing
for another since time immemorial. Even the
final conversion of forests into agricultural land
in England in the Middle Ages was a form of substitution: large ecosystems were transformed
to produce more food.10 But both the pace andscale of substitution in recent centuries havebeen unprecedented. Landes (1969) has argued
that the discovery of vast numbers of ways of
substituting resources among one another characterized the Industrial Revolution in late eighteenth century. The extraordinary economic
progress in Western Europe and North America
since then, and in East Asia more recently, hasbeen another consequence of finding new ways
to substitute goods and services among one
another and to bring about those substitutions.
That ecosystems are spatially dispersed has
enabled this to happen. The ecological transformation of rural England in the Middle Ages
probably reduced the nation’s biodiversity, but
it increased income without any direct effect on
global productivity.
But that was then and there, and we are in
the here and now. The question is whether it
is possible for the scale of human activity toincrease substantially beyond what it is today
without placing undue stress on the major ecosystems that remain. The cost of substituting
manufactured capital for natural resources canbe high. Low-cost substitutes could turn out tobe not so “low-cost” if the true costs are used in
the accounting, rather than the costs recordedin the marketplace (see below). Depleting one
9 But these shifts have not been without unintended
consequences. Global climate change didn’t feature ineconomic calculations until very recently.
10 Forests in England had begun to be denuded earlier, by Neolithic Britons and the Romans.

128

Inclusive Wealth Report

type of natural capital and substituting it withanother form of natural capital or with a manufactured capital is frequently uneconomical.

3. Property rights
If natural capital is being degraded and depleted
at unacceptable rates, wouldn’t their market
prices have risen? Aren’t price increases the only
reliable sign of growing scarcity?
The answer is “no.” It could be that various
kinds of natural capital are becoming scarcer
even while prices in the market don’t register
that. So, in the presence of externalities – theeffects of activities on the well-being of people
who have not been parties to the negotiations
that led to those activities – markets don’t provide us with the right incentives to economize
on our use of nature’s services.
The question arises: Why don’t market
prices reflect nature’s scarcity value? A common
reason is that the institutions mediating the useof natural resources harbor externalities.
The presence of externalities in the use ofnatural capital means that their markets not
only don’t function well, they often don’t evenexist. In some cases markets don’t exist because
relevant economic interactions take place overlarge distances, making the costs of negotiation among interested parties too high (e.g., theeffects of upland deforestation on downstream
farming and fishing activities – see Box 1). In
other cases, they don’t exist because the interactions are separated by large temporal distances(the effect of carbon emissions on climate in
the distant future, in a world where forward
markets don’t exist because future generations
are not present today to negotiate with us). But
the overarching reason is that private property
rights to natural capital are frequently impossible to define, let alone enforce. And a common
reason for the latter is that many “species” ofnatural capital are mobile. Birds and insects fly,rivers flow, fish swim, the winds carry, gases andparticulates diffuse in air and water, and evenearthworms are known to travel. The migratory
CHAPTER 6 Natural capital as economic assets

character of natural resources prevents markets
from being formed because it isn’t possible forpeople acting singly to lay claim to them.11 The
atmosphere and the open seas are prominent
examples of resources whose markets don’t
exist. They are open to all, which is why they
are called “open access” resources. As people areable to “free-ride,” they collectively experience
the “tragedy of the commons” (Hardin 1968).
Admittedly, private monopoly of a self-contained ecosystem would avoid free-riding, but itwould grant far too much power to one personin the community.
That the constituents of ecosystems aremobile is related to the fact that ecosystem
dynamics are non-linear, and involve positive
feedback. And because the whole is frequently
greater than the sum of its spatial parts, ecosystems are indivisible. If you slice off a portion for some other purpose, the productivity(e.g., biomass production) per unit area of what
remains is reduced. Even if it were decreed thatno portion could be converted for another use,parceling ecosystems into private bits would be
inefficient because of the influences the mobile
components would have on the parcels.
Agricultural land, especially in densely
populated areas, is a different matter. Bothlabor and capital are critical inputs in production. Investment can increase land’s productivity enormously. If agricultural land were to
be decreed to be common property, it would
be subject to serious management problems:
temptations to free-ride on investment costs
would be immense. The lack of incentives toinvest and innovate would lead to stagnation,even decay. The fate of collective farms in theformer Soviet Union testifies to that. Thoseregions of Sub-Saharan Africa where land is, or
was until recently, held by the kinship, were
exceptions, but in that region land was plentiful
11 Aquifers and oil reserves could be thought to beprominent counter examples. But rival extracters areable to siphon the resources from one another. Unlessthe extracter is a monopoly, enforcing property rights
to mobile resources underground is a very difficult
matter.

129

in the past and poor soil quality meant that land commonly done in environmental economics,
had to be kept fallow for extended periods. Of is a mistake.
course, it may be that agricultural productivity
remained low there because land was held by
the kinship, not by individuals. As elsewhere in 4. Types of externalities
the social sciences, causation typically works in
As institutional failure with regard to the use ofboth directions.
environmental resources is commonly associEach of the above examples points to aated with the presence of externalities, let us
failure to have secure private property rights
to natural capital. We can state the problem in remind ourselves that by an externality we mean
the following way: ill-specified or unprotected the effects of human activities on people who
property rights prevent markets from forming weren’t party to the decisions that led to thoseor make markets function wrongly when they activities. Our definition relates directly to theobservation that externalities are a symptom
do form.
What about non-market institutions? In of institutional failure. Logging in the uplandorder to study these, we enlarge the notion of forests of watersheds can cause water runoff
property rights to include communal rights over and inflict damage on farmers and fishermen
resources such as coastal fisheries, local wood- downstream. If those who suffer damage are notlands, and village tanks; and public or state prop- compensated by mutual agreement, the damerty rights (over forest lands, park, and inland age is an externality. Free-riding on common
lakes, for example). At the extreme are global property resources (CPRs) is another example
property rights, a concept that is implicit in of behavior that gives rise to externalities. Two
broad types of externalities may be contrasted:current discussions on climate change. But theidea isn’t new, not even in the modern era. That unidirectional and reciprocal (Dasgupta 1982).
humanity has collective responsibility over the We discuss them here.
state of the world’s oceans used to be explicit in
the 1970s, when politicians maintained that the
4.1 Unidirectional vs. reciprocal externalities
oceans are a “common heritage of mankind.”
The reasons markets don’t function
well also apply to non-market institutions.
Environmental degradation is a consequence Unidirectional externalities are just that – uniof institutional failure. The failure could be an directional – where one agent (or a group ofabsence of markets for ecological services; but agents) inflicts or confers an externality on
another (or others). Upstream deforestation
it could be the inability of a group of nations
to agree on a common fisheries policy in the damaging downstream farmers and fishermenseas, or it could be the state and private indus- is an example. Under reciprocal externalities
try riding roughshod over forest inhabitants; it each party confers or inflicts an externality
could be the local community, whose norms of upon all others, as in the private production of
public goods or in the use of unmanaged CPRs.
behavior over the use of their local commons
The examples we have cited so far dishave collapsed; or it could be failure within theplay “external dis-benefits.” In contrast, whenhousehold, where the dominant male insists on
someone becomes literate at his own cost, hegrowing fruit trees (the fruit can be sold in themarket to which the female doesn’t have easy no doubt enjoys a benefit, but he also bestowsaccess), rather than trees that would supply benefits on those others who now are able to
the woodfuel the female is expected to gather correspond with him. This is an example of anfrom the receding woodlands. To identify envi- “external benefit.” Meade (1952) famously studied the example of the apple grower and theronmental problems as “market failure,” as is
130

Inclusive Wealth Reportneighboring beekeeper. As each person’s activity
confers a benefit on the other, the externalities
are reciprocal. If the pair were to act without
mutual consultation and negotiation, neither
would take into account the beneficial effect of
his investment on the other: the apple grower
would invest in fewer trees and the beekeeper
would keep fewer bees than would be in theirmutual interest. The private production of public goods also involves external benefits.
The present definition of externalities isrough and not absolute. In many circumstances
there would be people who would not be actual
parties to agreements, but whose interests
would be taken into account by those seeking
to reach agreements with others. Accumulating
funds in a bank for one’s children’s education isan obvious example; international agreements
on carbon emissions to protect future generations from undue harm would be another. So
we extend the notion of externalities to include
cases where the interests of some of the affectedparties were not adequately reflected in theagreements that underwrote the transactions.
Externalities are symptoms of institutional
failure. Malfunctioning institutions sustain inefficient allocations of resources among contemporaries, across contingencies, and across time.
They create a wedge between private and social
rates of discount. Humanity’s dealings withnatural capital are riddled with externalities. So,a fruitful way to evaluate institutions is to study
the extent to which they don’t harbor externalities. What kind of institutions would they be?

4.2 Eliminating externalities
In the case of the upstream firm and downstream farmers, the state could tax the firm
for felling trees (Pigou 1920). The firm in thiscase would be the “polluter,” the farmers the“pollutees.” Pigovian taxes therefore invoke thepolluter-pays-principle (PPP). The efficient rate oftaxation would be the damage suffered by farmers. What the state does with the tax revenue isa distributional matter. Here we are concerned
CHAPTER 6 Natural capital as economic assets

with the efficiency of resource allocations.
Pollution taxes are known today as green taxes.
But there is also a “market-friendly” way toeliminate externalities. The work of Lindahl(1958 [1919]) – and subsequently Meade (1953,
1972) and Coase (1960) – suggested that thestate (or the community) could introduce private property rights on natural capital, thethought being that markets would emerge toeliminate the externalities. A problem with theproposal, at least as it is presented it here, isthat it isn’t clear who should be awarded property rights. In our example of the upstream firmand downstream farmers, the sense of natural
justice might suggest that the rights should be
assigned to farmers, who can be regarded as thepollutees. Under a system of “pollutees’-rights,”
the upstream timber firm would be required tocompensate farmers for the damage it inflicts
on them. Such a property-rights regime also
invokes PPP.
Of course, the rights could be awarded tothe timber firm instead. In that case it would be
the farmers who would have to compensate thefirm for not felling trees. The latter system ofproperty rights invokes the pollutee-pays-principle (a reverse PPP, as it were), which for many
people would seem repellent. But from an efficiency point of view, it’s a matter of indifference
as to which system of private property rights is
introduced, so long, that is, as the prices thatemerge (including those in the markets forexternalities) are competitive prices (Starrett1972). Arrow (1971) pointed to a problem with
Lindahl’s proposal. Markets for externalities
would be “thin.” In our example, each market
would involve precisely two parties: the timber
firm and one farmer. It is hard to imagine thatcompetitive prices could emerge in such circumstances. Nevertheless, markets for externalities
have attracted much attention among ecologists and development experts in recent years,
under the label payment for ecosystem services, or
PES (see Pagiola et al. 2002, for a sympathetic
review of a market-based PES).
A PES system, in which the state plays anactive role, is attractive for wildlife conservation131

and habitat preservation. In poor countries
property rights to grasslands, tropical forests,
coastal wetlands, mangroves, and coral reefs
are often ambiguous. The state may lay claim to
the assets (“public” property being the customary euphemism), but if the terrain is difficult
to monitor, inhabitants will continue to residethere and live off its products. Inhabitants
are therefore key stakeholders. Without their
engagement, the ecosystems couldn’t be protected. Meanwhile flocks of tourists visit thesites on a regular basis. An obvious thing forthe state to do is to tax tourists and use therevenue to pay local inhabitants for protecting
their site from poaching and free-riding. Local
inhabitants would then have an incentive todevelop rules and regulations to protect the site.
Box 2 offers an account of recent work on PES
arrangements.

Institutional failure is a prime reason why
natural resources are underpriced in the market. Tracking time series of the market pricesof minerals and fossil fuels in order to judge
whether we face increasing resource scarcity isa bad move. Mining, smelting, and transporting minerals and ores involve the use of othertypes of natural capital (rivers, land, and theatmosphere, into which industrial effluents aredeposited) for which payment is usually not
made. So, mining, smelting, and transporting
minerals and ores create externalities (Maler
and Wyzga 1972). The social cost (or shadowcost) of those industrial operations could be
rising even while market prices for minerals
remain flat or perhaps even decline. Under suchinstitutional failure, the use of natural capital is
implicitly subsidized by people who suffer fromthe externalities.12

At the global level, what is the annual subsidy ofnatural capital use? One calculation suggested
that it is 10 percent of annual global income(Myers and Kent 2000). The margin of error inthat estimate is very large, but until recently it’s
the only global estimate we have had. A recent
study of The Economics of Ecosystems andBiodiversity (TEEB) puts the annual loss in ecosystem services at 1–2 percent of global income.
That figure, too, is subject to a large marginof error. Many of the most reliable studies arethose that look at “small” problems (households
or industries exploiting fisheries, wetlands, coral
reefs, water holes, mangroves, grazing fields,
woodlands, etc.). The most promising route toa better understanding of the socio-ecologicalprocesses that shape our macroeconomies is
to aggregate those small problems. From theglobal perspective, each of those many problems
is small, but when added up, the sum would besignificant (Repetto 1989; MA 2005).
The spatial character of unidirectional
externalities is self-evident, but getting a quantitative feel involves hard work. So the literatureis sparse. As elsewhere in sustainability science,some of the best advances have been made instudies of involving multi-disciplinary expertise. Repetto et al. (1989) and Vincent and Ali(1997) estimated the decline in forest cover inIndonesia and Malaysia, respectively, owing tologging. Their investigation was at an intermediate spatial scale. The authors found that when
deforestation is included, national accounts
look quite different: net domestic saving rates
are some 20–30 percent lower than recordedsaving rates. In their work on the depreciationof natural resources in Costa Rica, the World
Resources Institute some years ago found thatthe depreciation of three resources – forests,
soil, and fisheries – amounted to 10 percent of

12 That is why the infamous bet between Paul Ehrlichand the late Julian Simon on the future trajectory ofmineral and metal prices was a case of misplaced
theorizing. Being an ecologist, Ehrlich should not havebeen expected to know that he had shadow prices inmind, not market prices. And Simon, being an economist, should have told Ehrlich that it is shadow prices,not market prices, that reflect social scarcities. The
bet was unfair.

5. Quantifying externalities

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5.1 External harms

Inclusive Wealth ReportGDP and over a third of capital accumulation.
The findings suggest that an economy could in
principle enjoy growth in GDP per capita andimprovements in the United Nations’ Human
Development Index (HDI) for a long period evenwhile its productive base shrinks.

Box 2

Payment for ecosystem services
The ethics underlying payment for ecosystem services(PES) is seemingly attractive. If decision-makers in Brazil
believe that decimating the Amazon forests is the true
path to economic progress there, shouldn’t the rest of

5.2 External benefits

the world pay Brazil not to raze them to the ground? If
the lake on someone’s farm is a sanctuary for migratory

It was the point of Meade’s (1952) example
that in the absence of an agreement between
the apple grower and beekeeper, pollination
involves reciprocal externalities. But it is only
recently that quantitative estimates have beenmade. There are several credible estimates atthe local level. In a study in Costa Rica on pollination services, Ricketts et al. (2004) found that
forest-based pollinators increase the annual
yield in nearby coffee plantations by as much as
20 percent. Subsequently, Ricketts et al. (2008)
analyzed the results of some two dozen studies,
involving 16 crops in five continents, and discovered that the density of pollinators and therate at which a site is visited by them declines at
rapid exponential rates with the site’s distancefrom the pollinators’ habitat. At 0.6 km (resp. 1.5km) from the pollinators’ habitat, for example,
the visitation rate (resp. pollinator density)
drops to 50 percent of its maximum.
Pattanayak and Kramer (2001) reported
that the drought mitigation benefits farmers enjoy from upstream forests in a group ofIndonesian watersheds are 1–10 percent of average agricultural incomes. In another exemplary
work, Pattanayak and Butry (2005) studied theextent to which upstream forests stabilize soil
and water flow in Flores, Indonesia (see also
Pattanayak 2004). Downstream benefits were
found to be 2–3 percent of average agricultural
incomes.

birds, shouldn’t bird lovers pay the owner not to drain
it for conversion into farm land? Never mind that themarket for ecosystem services would be thin, if a system involving PES were put in place, owners of natural
capital and beneficiaries of ecological services would
be forced to negotiate. The former group would thenhave an incentive to conserve their assets (Daily andEllison 2002; Pagiola et al. 2002; Goldstein et al. 2006).
In a review of current practices, Jack et al. (2008) haveobserved that hundreds of new PES schemes are currently in operation round the globe. China, Costa Rica,
and Mexico, for example, have initiated large-scale
programs in which landowners receive payment forincreasing biodiversity conservation, expanding carbon
sequestration, and improving hydrological services.
Although PES may be good for conservation, one
can imagine situations where the system would be badfor poverty reduction and distributive justice. Many of
the rural poor in poor countries enjoy nature’s services
from assets they don’t own. Even though they may bewilling to participate in a system of property rights inwhich they are required to pay land owners for ecological services (Pagiola et al. 2008, report in their careful
study of a silvopastoral project in Nicaragua that theydo), it could be that in the world we have come to know,
the weaker among the farmers are made to pay a disproportionate amount. Some may even become worse
off than they had been previously (Dasgupta and Heal
1979: Ch. 3). One could argue that in those situations thestate should pay the land owner instead, using funds
obtained from general taxation. As Reid et al. (2003),
Bulte et al. (2008), and Zilberman et al. (2008) observe,
who should pay depends on the context.

6. Estimating shadow prices
How should shadow prices be estimated? The
term “externalities” is a catchword for a wide
CHAPTER 6 Natural capital as economic assets

133

class of institutional failures that are translated
into gaps between market prices and shadow
prices. So, if at time t, P(t) is the shadow price ofasset i, R(t) its market price, and E(t) the social
value of the net externalities its presence creates, thenEquation 1

Pi(t) = Ri(t) + Ei(t)6.1 A general formulation
There is a utopian scenario where market prices
equal shadow prices. The state of affairs prevailing utopia is called the full optimum. There
are no externalities at a full optimum (i.e., Ei(t)=0), because what externalities there could
have been have been internalized via institutional reforms and policy changes. Elsewhere,
depending on the circumstances, market prices
are reasonable approximations for some goods
and services, while for others they are not.
For public goods and bads, R i(t)=0 in
Equation 1, which means that P i(t)=E i(t).
Fisheries in the open seas, carbon concentrations in the atmosphere, and such localized
resources as mangroves, coral reefs, streams,
and ponds are examples of the latter.
Assets are stocks. Recalling Definition 2
from Chapter 1, which states: The shadow priceof a capital asset is the contribution a marginalunit of it is forecast to make to human well-being,
we have
Proposition 1 Pi(t) is the present discounted
value of the flow of benefits society enjoys from amarginal unit of i.13
By the same token as Proposition 1, we have
Proposition 2. Ei(t) is the present discounted
value of the flow of the externalities associatedwith the presence of a marginal unit of i.
In estimating shadow prices of environmental resources, it is safest to return to the formal
definition of shadow prices, which is provided
13 The discount rate to be used in estimating thepresent values are social rates of discount.

134

by Equations (1) and (2). Recalling Equation (1)from Chapter 1 where
Equation 2

V(t) = V(K(t),M,t)
V is intergenerational well-being, K are the capital assets and M is the evolving political economy(see Chapter 1 for a more detailed analysis of theseequations)
Equation 2 tells us that in order to estimate
the shadow price of any capital asset we need:(a) A descriptive model of the economy.
(b) The size and distribution of the economy’s capital assets at the date the evaluation isundertaken.
(c) A conception of intergenerational wellbeing.
Recall that natural capital can be consumed
directly (e.g., fruit and honey), used indirectly
as inputs into production (e.g., fossil fuels
and microbes that regulate diseases), or useddirectly and indirectly at the same time (e.g.,clean air and fresh water). Ingenious techniques for estimating shadow prices have beendeveloped for those types of natural capitalthat are used directly, but are public goods(e.g., amenities such as places of scenic beauty
and recreational areas, and such sites that arethought to possess intrinsic value [e.g., sacredgroves]).14 Unfortunately, ecosystem services
and other inputs in production activities havenot been studied much, so there is still no comprehensive text. The February 2011 issue of thejournal, Environmental & Resource Economics(Vol. 48, No. 2), containing a Symposium on“Conservation and Human Welfare: Economic
Analysis of Ecosystem Services,” is a rare exception in the prevailing literature on the valuationof ecosystem services (see especially, Balmford
et al. 2011; and Bateman et al. 2011).

14 Freeman (1992) and Smith (1997) are fine expositions of the methods.

Inclusive Wealth Report6.2 Asking questions and observing behavior
For environmental amenities, an appeal to
Definition 1 in Chapter 1 (By sustainable development we mean a pattern of societal development
along which (intergenerational) well-being does
not decline) directly is problematic because of theenormous quantity of information demanded
by requirements (a)–(c). So environmental andresource economists have devised two indirect
methods. In one method, investigators ask
people to place a value on ecological resources.
This is often called contingent valuation. The
other method has investigators study behavior
and the consequences of that behavior to infer
the value individuals place on those assets. Thismethod is frequently called the revealed preference approach. It has been put to wide use invaluing subtle characteristics of capital assetsthat are hard to unscramble from their overallvalue. As an example, consider an asset thathas multiple characteristics, such as land. The“hedonic price method” uses the market price ofa piece of land to uncover the shadow price of
one of its characteristics, for example, the valueof its aesthetic qualities.
The hedonic price method has been muchused to value real estate. In their work on
inland wetlands in eastern North Carolina (U.S.),
Bin and Polasky (2004) found that, other things
being equal, proximity to wetlands reduced
property values. Wetlands have many virtues,
associated with the services they provide in
decomposing waste, purifying water, and providing a sanctuary for birds and other animals.
What Bin and Polasky (2004) discovered is thatthey may also possess a negative feature, namely
bad odor!
As noted previously, the valuation methods
that have become most popular were devisedfor environmental amenities, such as places ofscenic beauty or cultural significance. The costof travel to a site takes “revealed preference”
to be the basis for valuing the site. Englin and
Mendelsohn (1991), for example, is a well-known

CHAPTER 6 Natural capital as economic assets

application of the method for estimating therecreation value of forests.
In contrast, the contingent valuation method(CVM) has proved to be extremely popular in
those cases where there is no observed behavior(see Carson [2004] for an extensive bibliography). The idea is to ask people how much theywould be willing to pay for the preservation ofan environmental amenity (e.g., flood control)
or a resource of intrinsic worth (e.g., an animalor bird species).
Each of the above methods is of limited
use for valuing the local natural resource basein the poor world. Moreover, one can question whether requirements (a)–(c) can be met
adequately by studying people’s behavior or
analyzing their responses even to well-designed
questions. One reason for being cautious about
those methods (there are many other reasons) isthat people often aren’t aware of environmental
risks. Jalan and Somanathan (2008) conducted
an experiment among residents of a suburb of
New Delhi. The aim was to determine the valueof information on the health risks that arise
from drinking water containing bacteria of fecal
origin. Without purification, the piped waterin 60 percent of the households were foundto be contaminated. Among households in thesample that had not been purifying their pipedwater, some were informed by the investigatorsthat their water was possibly contaminated,while the rest were not informed. The authors
report that the former group of households was
11 percent more likely to invest in purification
within the following eight weeks than the latter group. An additional year of schooling of themost educated male in the household was associated with a 3 percent increase in the probability that its piped water was being treated. The
finding is noteworthy because the wealth andeducation levels of households in the sample
were above the national average. If ignorance
of environmental risks is pervasive, estimates135

of the demand for environmental quality thatassume full information must be misleading.15

7. Using nature’s production functions
So we return to requirements (a)–(c) as the basis
for estimating shadow prices.

7.1 Carbon concentration
The welfare economics of climate change
requires carbon in the atmosphere to be priced.
It has been customary in that literature (e.g.,
Cline 1992; Stern 2006) to place a global pricefor carbon concentration. A figure of US$20 per
ton for carbon’s global shadow price was suggested by Fankhauser (1995) and Pearce et al.
(1996), with but scant justification. That figure
was however used in the World Bank’s work onsustainable development. But there are likely to
be enormous regional variations in the impact
of global climate change on economic activity(Rosenzweig and Hillel 1998; Mendelsohn
et al. 2006; Dinar et al. 2008). Agriculture insemi-arid tropical countries is expected to suffer from warming, while in temperate regions it
will probably benefit. If we apply distributional
weights to the losses and gains, the disparity isbigger than the nominal figures that have beensuggested, because the former group of countries are almost all poor while the latter are
middle-income to rich. Using a range of climate
models, Mendelsohn et al. (2006) have published estimates of losses and gains in year 2100.
The authors aggregated five sectors: agriculture,
water, energy, timber, and coasts. Dependingon the scenario, they found that the poorest
countries (almost all in Africa) are likely to suffer
damages from 12 percent to 23 percent of theirGDP, while the range of impacts on the richest
countries (North America and northern Europe)
15 Determining the “willingness to pay” for changes
in risk involves additional problems. See Smith and
Desvouges (1987).

136

is from damages of 0.1 percent to a gain of 0.9
percent of their GDP. Dinar et al. (2008) fear thatwith warming, the agricultural income in thesemi-arid tropics could be more than halved
in 2100 from its projected value in the casewhere there is no warming. But these estimatesare based on market prices. If distributional
weights are applied to obtain a global shadow
price of carbon, it would be a lot higher than if
we were merely to add the regional gains andlosses. It should also be noted that the effects ofclimate change on health and the environment(e.g., loss of species) were not included in thoseestimates.

7.2 Ecosystem services
Several recent valuation studies have met
requirement (a) by estimating the production
function for nature’s service (e.g., pollination as
a function of the distance to a forest; primary
productivity as a function of biodiversity; net
reproduction rate of a species), but have otherwise assumed that market data are more orless sufficient to meet the other requirements.16
Pattanayak and Kramer (2001) and Pattanayak
and Butri (2005), for example, constructed ahydrological model to measure the contribution of upland forests to farm productivity
downstream. Hassan (2002) used quantitative models of woody land resources in South
Africa to estimate the value to rural inhabitantsof (among other resources) the Fynbois Biome,
which dominates sandy soils there. Barbier(1994) and Gren et al. (1994) used formal ecological models to compile a catalogue of thevarious services that are provided by wetlands,
while Duraiappah (2003) developed a range ofdynamic optimization coupled socioeconomicecological models to capture a variety of ecosystem services including tidal flushing, water

16 See Dobson et al. (1997), Barbier (2000), Turner etal. (2000), and Tilman et al. (2005) for illustrations of
ecosystem production functions and the corresponding dynamics of the socio-ecological systems.

Inclusive Wealth Reportpurification, and biomass evolution. In theirstudy of wetlands in northern Nigeria, Acharya(2000) and Acharya and Barbier (2000) applied
models of ground water recharge to show thatthe contribution wetlands make to recharging
the basins is some 6 percent of farm incomes.

7.3 Option value
Economists as a general rule encourage decision-makers to maximize the expected value ofwell-being (Box 1) whereas environmentalists
urge them to keep future options open. Thereis a sound intuitive basis for the latter. The useof environmental resources can have effects
that are irreversible, implying that decisions
today may constrain choices in the future. Butthat alone is not a reason for concern because if
the future is known with certainty, then there
is no cost to forgoing one’s future options. It is
the twin presence of uncertainty and irreversibility that makes flexibility an attractive featureof a planned course of action. An option value
reflects the social worth of flexibility in a world
where the social evaluator evaluates on the basisof the expected value of well-being.
Nowhere has the desirability of keeping
future options open been advanced as vociferously as in discussions of the need for the on-sitepreservation of genetic diversity of plants andcrops. Tropical forests are particularly noted forproviding a habitat for a rich genetic pool, mostof which is so far untapped for direct use, butsome of which provides ingredients for pharmaceutical products. Much attention has beendrawn to the continued decay of the genetic
variability of crops resulting from an increased
reliance on a few high-yield varieties in large
parts of the world. As new varieties of crop
pests and diseases appear, the chance of locating crop varieties that are resistant to them willbe that much lower if genetic reserves are small.
The genetic pool is a public good whose value
becomes more and more sharply etched withthe passage of time. Box 3 presents a numerical

CHAPTER 6 Natural capital as economic assets

example to show how option values ought to be
determined.

7.4 Biases in estimates
What is the point of basing shadow prices solely
on one particular use value when we know thatnatural capital often possesses other values too?
The answer is that the method provides us withbiased estimates of shadow prices. That can be
useful information. For example, in a beautiful paper on the optimal rate of harvest of blue
whales, Spence (1974) took the shadow price ofwhales to be the market value of their flesh, aseemingly absurd and repugnant move. But on
estimating the population growth functionsof blue whales and the harvest-cost functions,
he found that under a wide range of plausible
parameter values it would be most profitablecommercially for the international whaling
industry to agree to a moratorium until thedesired long-run population size was reached,
and for the industry to subsequently harvest
the whales at a rate equal to the population’s
optimal sustainable yield.17 In Spence’s analysis,preservation was recommended solely on commercial grounds. But if preservation is justified
when the shadow price of blue whales is estimated from their market price, the recommendation would, obviously, be reinforced if theirintrinsic worth were to be added. This was thepoint of Spence’s exercise.

8. Conclusion
The social worth of natural resources can bedivided into three parts: use value, intrinsic value,
and option value. The proportions differ. Oiland natural gas aren’t usually thought to possess intrinsic value, nor perhaps an option value,
17 During the moratorium the whale population
grows at the fastest possible rate. In Spence’s numerical computations, the commercially most-profitable
duration of the moratorium was found to be some
10–15 years.

137

Box 3

Valuing Options
Section 7.3 introduced a component of environmental shadow prices that goes by the name“option value.” Option values arise from thetwin presence of uncertainty about an asset’s
future worth and irreversibility of decisions
in case the asset is degraded. An option value
measures the social worth of the flexibility thata society would enjoy by keeping options open
for the future, when new information about theworth of existing assets is expected to be forthcoming. Here we study the idea by means of an
extreme example.
We suppose the decision-maker is riskneutral. Because under normal circumstances
a risk-neutral decision-maker can replace random variables by their expected values, we will
be able to compute the value of flexibility relatively easily.
There are two periods, t=0 and 1. A forest, inarea K, harbors a genetic pool. We assume that
off-site preservation of the genetic material isprohibitive and that the forest land has alternative uses, say, urban development. However,
deforestation would mean a loss of genetic
diversity. That’s the trade-off: genetic diversity vs. urban development. For simplicity, it isassumed that genetic diversity is proportional
to forest size.
The social benefit from developing a marginal unit of forest land at t=0 is known to be
B(0). By definition, B(0) would be the increase inwell-being if an additional bit of the forest weredeveloped for its alternative use. At t=0 there
is uncertainty regarding the social losses fromdeforestation. In regards to that uncertainty,
there are two possibilities, s1 and s2, with probabilities π and (1- π) respectively. Following theestablished terminology of decision theory, wecall the possibilities “states of nature.” The stateof nature will be revealed at t=1 (the future). If
s1 were to prevail, net social benefit at t=1 from138

developing a marginal bit of the forest would be
B1(1); if s2 were to prevail, the net social benefit
at t=1 from developing a marginal bit of the forest would be B2(1). We assume that if the entire
forest is not developed at t=0, there will be a further option of how much of the forest to develop
at t=1, once the state of nature is revealed. In
short, the decision to develop the forest can bemade at both periods. It’s only if the entire forest is converted that future options are closed.
Let D(0) be the area that is developed at t=0.
Naturally, 0 ≤ D(0) ≤ K. Now let D1(1) and D2(1)be the areas developed at t=1 under s1 and s2,
respectively. Finally, let r be the rate at whichsocial costs and benefits are discounted. It follows that expected value of the proposed development policy is
Equation B.4.1

V = B(0)D(0) + [πB1(1) D1(1) + (1–π) B2 (1)D2(1)](1+r)
To have an interesting problem, we imagine
that B 1(1) < 0, B 2(1) > 1, and [π B 1(1) D 1(1) + (1–π)
B 2(1) D 2(1)] > 0; the latter of which says that at
t=0, it is expected that at t=1 further development will be a good thing.
To formalize option values in this example,
we begin by imagining that the loss of genetic
diversity is fully reversible, that is, the area
deforested at t=0 can be re-established without
cost at t=1 should that be desired. The social
evaluator’s problem is to maximize equation
B4.1 by choosing B(0), B 1(1), B 2(1) subject to theconstraints:
Equation B.4.2

0 ≤ D(0), D1(1), D2(1) ≤ K
The optimum decision rule is simple:

Inclusive Wealth ReportEquation B.4.3

Equation B.4.7

D(0) = K if B(0) > 0 and D(0) = 0 if B(0) < 0;1

and D1(1) = 0 and D2(1) = K
Now suppose the other extreme, that genetic
loss is irreversible. Irreversibility means that inplace of constraint (B4.2), the social evaluatorfaces the constraint

B(0) > B(0) + πB2(1)(1+r)
The difference between the two figures,
namely, the absolute value of πB1 (1+r), is theoption value. Development has to be that much
more valuable today if the forest is to be cleared
for it.

Equation B.4.4

0 ≤ D(0) ≤ D1(1), D2(1) ≤ K
The social evaluator’s problem is to maximize (B4.1) subject to constraint (B4.4). The way
to solve the problem is to work backward, fromt=1 to t=0. If, at t=1, the true state of nature isrevealed to be s1 then the social evaluator would
choose D 1(1) = D(0); if instead it turns out to bes2, the social evaluator would choose D 2(1) = K.
Thus, at t=0 the problem facing the social evaluator is to choose D(0) so as to maximize
Equation B.4.5

V = [B(0) + π B1(1) (1+r)]D(0) + (1–π)B2(1)K(1+r)
The decision rule is clear:
Equation B.4.6

D(0) = K if and only if B(0) + πB1(1) (1+r) >0
Uncertainty and irreversibility, taken
together, require a stiffer criterion for development than in their absence, because

1 If B(0) = 0, then the choice of D(0) is a matter ofindifference.

CHAPTER 6 Natural capital as economic assets

139

but they do have use value. The great apes are
intrinsically valuable; some would say theyshould have no other value, that they are an end
in themselves, not a means to anything. Option
value is the value we apportion to a natural
resource which could prove to be have a social
worth beyond its known use value or intrinsic
value. Biodiversity possesses all three typesof value. Although there are several excellent
treatises on valuation methods (e.g., Freeman
1992), they are altogether too limiting for thetask in hand. MA (2005) has drawn our attention to the plight of the world’s ecosystems. Yet,in comparison with the number of studies wecurrently have at our disposal on the valuationof environmental amenities, the size of the literature on the valuation of ecosystems is pitifully small. This paper has sketched a formulation that tells us the steps that are necessary tovalue ecosystem services. Valuation in practicerequires a multi-disciplinary effort. At a minimum, economists need to get together withenvironmental scientists to devise methods for
implementing steps (a)–(c), which provide thebasis for understanding the shadow prices and,
thereby, valuing ecological systems.
The valuation techniques we have enumerated here are built around the idea that preferences and demands, as they stand, should be
respected. There is an enormous amount to besaid for this, reflecting as it does a democratic
viewpoint. But even when commending it, weshouldn’t play down the strictures of thosesocial thinkers who have urged the rich, whether
in rich countries or in poor ones, to curb theirmaterial demands, to alter their ways so as tobetter husband earth’s limited resources. Theirthought is that we deplete resources without
trying to determine the consequences of depleting them, sometimes because we haven’t thetime to find out, but sometimes because we may
not wish to know, since the answer may prove
to be unpalatable to us. Being sensitive to ecological processes requires investment in earlyeducation on the connection between humanwell-being and the natural environment. If such
strictures as we are alluding to seem quaint140

today, it may be because we are psychologically
uncomfortable with the vocabulary. But that
isn’t an argument for not taking them seriously.

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Inclusive Wealth ReportChapter 7

The road to wealth accounting
Charles Perrings

Key Messages
It is clear that human activity has had aprofound effect on our environment, and thatthese effects, in turn, have had an impact onhuman well-being. While the importance of
this relationship is appreciated, there are still
few reliable indicators of the value to people ofbiosphere change.

The SNA provides an incomplete picture of
wealth because it includes only property thatgenerates private claims to future benefits. It
therefore excludes parts of natural capital thatis essential to human well-being but cannot be
privately held (e.g., the atmosphere or the open
oceans).

The Millennium Ecosystem Assessment
was able to quantify the physical changes inecosystem services that had occurred in the previous half century, but it was unable to assign
a value to the loss of non-marketed ecosystemservices.

Two major efforts to advance our understanding of wealth are discussed here: theWorld Bank’s idea of adjusted net savings, andthe System of Environmental and Economic
Accounts (SEEA). Both are important steps on
the road to wealth accounting, but neither
fully address the issues of what environmental
stocks should be included, and how they shouldbe measured and valued (the double counting
caused by the SEEA’s inclusion of ecosystems isparticularly problematic).

This chapter considers the issues involved
in developing metrics of the social importanceof biosphere change. What is needed is a measure of the impact of biosphere change on
wealth and wealth distribution. The chapter
discusses the welfare-theoretic foundations ofwealth accounting, and the steps taken so far tobuild wealth accounts. It then considers what
is required to evolve wealth accounts from thecurrent system of national accounts (SNA).

Ultimately, country wealth measurements
should include all natural assets that are undera country’s jurisdiction and that contribute tohuman well-being, whether those assets are privately owned or not.
143

1. Posing the problem
There is accumulating evidence that human“management” of the biosphere is having amajor effect on the abundance and diversity ofother species, on ecological functioning, and on
ecosystem processes. The most heralded impactof the conversion of land to human use is theextinction of other species, but anthropogenic
environmental change has many other dimensions. Emissions into the air, soil, and water are
affecting ecosystem processes at many different scales, extending from the global effect ofgreenhouse gas emissions on climate, to the
local effects of nitrate emissions on groundwater. Two global assessments have documented
the effect of people’s use of terrestrial andmarine resources on biodiversity change, andhave offered some evidence for why it matters(Heywood and Watson 1995; Millennium
Ecosystem Assessment 2005a). More recently,
the TEEB (The Economics of Ecosystems andBiodiversity) report has summarized what iscurrently known about the value of biodiversity
and non-marketed ecosystem services (Kumar
2010). The problem remains, however, that there
are few reliable indicators of the importance ofbiosphere change for human well-being.
The Millennium Ecosystem Assessment(MA) attempted to relate changes in biodiversity
to human well-being through the identification of a set of “ecosystem services,” defined as“the benefits that people get from ecosystems.”
These comprised provisioning services (production of foods, fuels, fibers, water, and genetic
resources); cultural services (recreation, spiritual and aesthetic satisfaction, and scientificinformation); regulating services (controllingvariability in production, pests and pathogens,environmental hazards, and many key environmental processes); and supporting services(the main ecosystem processes). The MA wasnot, however, able to do more than say whether
the physical flows of these services had beenenhanced or degraded in the previous half century. It was unable to assign a value to the lossof, for example, cultural or regulating services
144

relative to provisioning services. It was not,therefore, able to say whether the trade-offs
being made between ecosystems services were
warranted in terms of either their efficiency
or fairness. Nor was it able to say whether theinvestments people had made in the conversion of ecosystems for the production of valued goods and services left society collectively
richer or poorer – whether those investments
were sustainable. Without information on thevalue of the ecosystem services forgone throughland-use change, it is difficult for us to knowwhether land-use change is socially efficient,equitable, or sustainable. The TEEB project has
subsequently summarized at least the range ofvalue estimates reported in the economic literature (Kumar 2010). But point estimates ofthe value of specific services are of little help inmonitoring biosphere change.
This chapter considers the issues involved
in developing metrics of the social importanceof biosphere change. Whether society is concerned with inter-country comparisons, withtracking its own performance over time, or with
understanding the distributional effects of biosphere change, the informational requirements
are the same. What is needed is a measure of
the impact of biosphere change on wealth andwealth distribution. The chapter discusses theimplications of this requirement, first in termsof the welfare-theoretic foundations of wealthaccounting, and then in terms of the steps
required to evolve wealth accounts from thecurrent system of national accounts.

2. Environmental change and environmental assets
2.1 Measuring environmental assets
The weaknesses of gross domestic product (GDP)or gross national income (GNI) as a measure ofwell-being have been often rehearsed and are
well understood. Adjusting for transboundary flows and for the depreciation of assets toyield net national product (NNP) or net national
Inclusive Wealth Report

income (NNI) addresses two of the main reasons
why the measure is flawed. However, there still
remain a number of fundamental problems
including the exclusion of most non-marketed
production and consumption, externalities,
environmental deterioration and public lands,
and the inclusion of defensive or remedial
expenditures (repairing depreciation). Most
importantly, NNP or NNI remain measures of acurrent flow of production or income. It is nota measure of the sustainability of that income.
In other words, it does not test whether NNP is
greater than, less than, or equal to income inthe sense of Lindahl (1933) or Hicks (1939), andhence whether it increases, decreases, or has noeffect on wealth. While a large number of alternative indices have been proposed in the literature1 (Goossens et al. 2007), we consider only
those that address these specific weaknesses of
NNP or NNI.
The MA classified the benefits obtained
from ecosystems as belonging to one of fourtypes: provisioning, cultural, regulating, andsupporting.
• Provisioning services covered the products of renewable resources including
foods, fibers, fuels, water, biochemicals,
medicines, pharmaceuticals, and genetic
material.
• Cultural services comprised a range oflargely non-consumptive uses of the environment. In the MA they were defined toinclude the spiritual, religious, aesthetic,
and inspirational well-being that people
derive from the “natural” world; the value
to science of the opportunity to study andlearn from that world; and the market
benefits of recreation and tourism.

1 These include Nordhaus and Tobin’s Measure of
Economic Welfare (MEW); the Index of Sustainable
Economic Welfare (ISEW); the Genuine Progress
Indicator (GPI); the UNDP’s Human Development Index(HDI); the Gender-related Development Index (GDI);
the Ecological Footprint (EF); the Happy Planet Index(HPI); the Environmental Sustainability Index (ESI); andthe Environmental Performance Index (EPI) (Goossens
et al. 2007).

CHAPTER 7 The road to wealth accounting•

The regulating services included themoderation of air quality, climate, water flows, soil erosion, pests and diseases,
and natural hazards. More generally, they
comprise the benefits of biodiversity inregulating the effects of environmental
variation on the production of the provisioning and cultural services, or thehealthiness of the environment – in other words, benefits that people care about
directly. They limit the effect of stresses
and shocks to the system.
• Supporting services comprised the main
ecosystem processes that underpin allother services such as soil formation,
photosynthesis, primary production, andnutrient and water cycling (Millennium
Ecosystem Assessment 2005b).
Many provisioning services and some cultural services are supplied through well-functioning markets, and enter the national accounts
through the product accounts for agriculture,industry, and services (System of National
Accounts [SNA] 2009). The prices of many may
be distorted through the effects of government
policy such as agricultural subsidies, but they
are at least directly registered in the national
income accounts. There are, however, a number of services that are not supplied throughthe market, and that are therefore unpriced andnot currently captured in the national income
accounts.
Note that this does not include all ecosystem services for which there are no functioning
markets. Why? Consider a tract of land in private property that comprises a particular water
sub-catchment, and that is used for the production of food crops. The production of food is
one of the main MA provisioning services, but it
depends on several other MA ecosystem services
including the regulation of soil and water flows,
pest and disease regulation, pollination, nutrient cycling, and so on. These services, and thebiotic and abiotic conditions that support them,
are what determine the productivity of theland. They are therefore also what determine
its price – along with the land’s location relative145

to transport networks, markets, the characteristics that make it suitable as a place to live, andso on.
Variants of the MA classification have been
proposed to address the potential for double
counting (Boyd and Banzhaf 2007; Johnston
and Russell 2011). It may be more useful simply to identify where double counting is likely
to occur. To the extent that the regulating andsupporting ecosystem services needed for agricultural production are reflected in the price ofthe land, they will be appropriately measured in
the system of national accounts. Indeed, if allservices are contained within the catchment,
they will be fully accounted for. It is only theoff-site benefits or costs of land management
within the sub-catchment that are missing.
Off-site flows of nutrients, pests and pesticides,
siltation of rivers, and the like are externalitiesof land management that should be valued andaccounted for wherever they have significant
effects on well-being.
The task is not therefore to account for all
ecosystem services. It is to account for ecosystem services that are not already explicitly
or implicitly priced (and so reflected in thenational income accounts), and that have asignificant impact on well-being. Using thewelfare theoretic basis for wealth accounting
described in the appendix of this chapter as wellas in Chapter 1 of this report, we are interested
in changes in wealth due to changes in one
or other of the principal stocks in the system:
produced capital, K i(t), human capital, L i(t), andnatural capital, N i(t). Wealth in country i isdefined to be a function of these stocks:
Equation 1

Vi(Si(t))=Vi(Ki(t), Li(t), Ni(t))
It follows that the change in wealth in any
small interval of time is simply the net effectof changes in individual stocks. If there is nochange in total factor productivity this is precisely equal to investment:

146

Equation 2

dVi(Si(t))
dt=∂V(Si(t)) dKi(t)∂Ki(t)∂Vi(Si(t)) dLi(t)+∂Li(t)dt+

dt∂Vi(Si(t)) dNi(t)∂Ni(t)dt=Ii(t)

If there is a change in total factor productivity, and if that change depends upon the stateof some global environmental public good, G(t),then for the ith country:
Equation 3dVi(Si(t), G(t))
dtdGi(t)dt+∑j≠i= Ii(t)+∂Vi(Si(t))∂G(t)

dGj(t)dt

If Gi(t)= Gi(Ni(t)), that is to say if the contribution made by the ith country to a public goodthat influences total factor productivity, thenthere are two ways in which unpriced natural
capital might influence national wealth. One
is direct, the other indirect. The direct effect isthe discounted value of a change in ecosystemservices associated with a change in the physicalquantity or quality of the country’s natural capital. The indirect effect is the discounted value ofthe change in total factor productivity causedby the impact of a change in natural capital onenvironmental public goods.
It follows that conservation of natural capital in the ith country may confer benefits onother countries via an impact on total factor
productivity:
Equation 4n∂Vj(Sj(t))∂G(t) dGi(t)j≠i, j=1∂G(t)∂Gi(t)∑

dt

Such effects will typically show up in changes
in total factor productivity growth in othercountries, and should properly be recorded inmeasures of net national product or income.

Inclusive Wealth Report2.2 Environmental assets and total factor
productivity growth (TFPG)
Vounaki and Xepapadeas (2009) have exploredthis effect (Table 1). They found that unaccounted contributions of the environment may
be an important driver of estimates of totalfactor productivity growth (TFPG), and that
explicitly accounting for environmental contributions can reduce it by a significant margin– potentially driving it into the negative range.
In particular, they consider energy as an environmental factor of production in the aggregate
production function that is priced, but that also
generates an unpriced or uninternalized externality in the form of greenhouse gas emissions.
They ask how significant the effect of thishas been on total factor productivity in a groupof OECD countries, and what options exist tointernalize their cost and thus to use them efficiently. The correction involves adjusting traditional total factor productivity growth measuresby estimating an aggregate production function
for a panel of 23 OECD countries, and subtracting the contribution of the unpriced or uninternalized part of energy costs, the CO2 emissions,from output growth.
What is striking about their results is thenumber of cases in which total factor productivity growth has been driven into the negative
range. The reason that this may happen is that
if ecosystem services are an unpriced factor of
production, their use may not be subject to thesame discipline as priced factors, and so they
may be used inefficiently. Negative total factor
productivity growth would then be a measureof this inefficiency, its causes potentially lying
in institutional conditions that “authorize” theexternality in the first place (Baier et al. 2006).
The net effect is that the potential growth innational wealth is compromised.

2.3 Adjusted net savings
Adjusted net savings, as a measure of change in
wealth, grew out the work of Pearce, Hamilton,
CHAPTER 7 The road to wealth accounting

and Atkinson in the 1990s (Pearce andAtkinson 1993; Pearce et al. 1996; Hamilton
and Clemens 1999; Ferreira et al. 2008). It
is a direct attempt to measure net change inthe value of a country’s capital stocks, wherethat includes produced, human, and at least
some stocks of natural capital (Hamilton andClemens 1999). If wealth is the value of thestock of all assets plus net investment, then the
propositions in Section 2 imply that a necessary
Table 1

Traditional and externality-adjusted TFPG
for 23 OECD countries

Countries

Traditional ExternalityTFPG adjusted TFPG

Canada0.670-1.979U.S.A.

0.275-2.206Austria

0.635-0.779Belgium

1.079-1.039Denmark

0.321-1.289Finland1.144-1.107

France0.705-0.778Greece0.831-0.479

Italy

1.537

0.387

Luxembourg

1.699-2.580Portugal

1.690

0.649

Spain

0.415

-0.695

Sweden-0.040-2.028

Switzerland-0.059-1.122

U.K.

0.859

-0.896

Japan

1.646

0.235

Iceland0.473-2.533

Ireland1.638-0.172

Netherlands

0.489-1.414

Norway1.564-0.247Australia

0.567-1.226

Mexico0.330-0.814

Turkey

1.420

0.214

Average

0.865-0.952

Source: Vouvaki and Xepapadeas (2009)147

S o lo mo n Isla n d s

and sufficient condition for wealth to be
increasing over time is that net investment bepositive. That is, dV(S(t)) dt > 0. This in turnrequires that U’(C(t))(dC(t) dt) < net national
product. Adjusted net savings is intended to bea measure of dV(S(t)) dt.
In practice, adjusted net savings estimatesare based on a partial correction of the figuresin the SNA. The adjustments to gross savings
reported in the national income accounts
involve: (a) subtraction of the depreciation of
produced capital; (b) addition of expenditure
on education as a proxy for investment in
human capital; (c) subtraction of the rents on
depleted resource stocks; and (d) subtractionof specific pollution damages. The resource
stocks currently included comprise energy(oil, gas, and coal); minerals (non-renewablemineral resources); and forest (rent being calculated on timber extraction Figure 1: grossnational savings and adjusted net savings rates,
2008, in excess of the “natural” increment inwood volume). Pollution damages currently
recorded include carbon dioxide and particulate matter (PM-10) damages.
Even though the correction is partial – including only some exploited natural
resources, and a limited set of off-site external
environmental effects – the impact on wealthassessments is substantial. Figure 1 shows
the World Bank’s estimates of gross nationalsaving (GNS) and adjusted net savings (ANS)
rates, using this method. In almost every case,
GNS>ANS, and in many cases strongly positive
GNS are associated with strongly negative ANS
rates. Taking account of the depletion of valuable non-renewable assets and the environmental cost of industrial production in thesecases implies that the value of aggregate capital stocks is declining, not increasing.

B huta n
Kuwa it
Chin aS a ud i A ra bia
B otswa n a
B a hra in
No rway
In d ia
Ve n e zue la , R B
G uya n a
Russia n Fe d e ratio n
Mo ro c c o
T ha ila n d
Vie tn a m
B o livia
B e la rus
Austria
S love n ia
Mo n g o lia
Ja p a n
A rg e ntin a
Mexic oRo ma n ia
Chile
A n g o la
De n m a rk
Ca n a d a
G uin e a -B issa u
In d o n e sia
Z a m bia
Mo ld ova
Uk ra in e
Esto n ia
Ire la n d
P o la n d
I ta ly
Urug uay
A lba n ia
Turke yEthio p ia
Ma uritius
Ma c e d o n ia , F Y R
Co sta R ic a
Hun g a ry
Lithua n ia
Un ite d K in g d o m
G uate ma la
Jo rd a n
Ke nyaS yria n A ra b Re p ublic
P o rtug a l
Co m o ro s
S wa zila n dKeyLe ba n o n
Do m in ic a n Re p ublic

Figure 1

Gross national savings andadjusted net savings rates,
2008

Adjusted net
savings

E l S a lva d o r
Moza mbique

Gross nationalsavings

Cyp rusCha d
Ce ntra l Af ric a n Re p ublic

60

40

20

0

-20

-40

-60

148

Source: World Bank (2010)

Inclusive Wealth Report

25

20

10

5

0

-5

-10

149

-15

Adjusted Net Savings Rate (percent)

15

2003

2000

1997

1994

1991

1988

1985

1982

1979

1976

CHAPTER 7 The road to wealth accounting

1973

1970

While negative ANS in any
one year provides a test of
the sustainability of investment/consumption decisions
in that year, to see whether adevelopment program is sustainable requires evaluation
over a longer period of time.
Figure 2 reports ANS rates forfour groups of countries overthe period 1970–2005. The
groups of countries are high-,
middle- and low-income
countries, shown together
with the subset of low-incomeKeycountries in the International Figure 2
Monetary Fund’s Heavily Adjusted net savings rates:
High-income countries
Indebted Poor Country (HIPC) high-, middle- and low-inHeavily indebted poor countries
Program. Within that period come countries plus heavily
Low-income countries
all except the high-income indebted poor countries,
Middle-income countries
countries had periods during 1970–2005
which their adjusted net savings were negative – they were Sources: Data from World Bank
depleting aggregate capital Adjusted Net Savings (World Bank
stocks. However, for the most 2010), http://search.worldbank.org/data
part, the adjusted net savingsof most countries were positive. The exception is the HIPC
Nations (World Bank 2010) constitute the first
countries, largely in Sub-Saharan Africa.
The group of countries in the HIPC pro- attempts to understand the implications of suchsavings patterns for wealth and wealth creation.
gram had negative adjusted net savings rates
for most of this period. Since these countries As such, they are critical steps on the road toare also characterized by high rates of popula- global wealth accounting. They have, however,raised more questions than they have answered.
tion growth, the implication is that per capita
These relate to four of the issues raised in thewealth declined at an even faster rate.
literature on the welfare theoretic foundationsof wealth accounting:• What is the role of environmental assets
3. Steps on the road to comprehensivein the Solow residual and how does it afwealth accounting
fect changes in wealth?
• How should the off-site external envi3.1 The World Bank’s adjusted net savings
ronmental effects of resource use be reindicators
flected in asset values?
• What is the appropriate treatment of
The World Bank’s report on global wealth and its
environmental assets that are publicdistribution between countries in the year 2000,
goods?
Where is the Wealth of Nations? (World Bank
• What is the connection between environ2006), and the update The Changing Wealth of

mental wealth and poverty both within
and across generations?
In the World Bank’s approach there are twocore stocks – “produced” and “natural” capital– and a balancing stock called “intangible” capital. Produced capital was defined as the sum ofmachinery, equipment, built structures, andbuilt infrastructure together with the land on
which such structures appear. The decision as
to whether land was sufficiently modified to
be classified as produced capital was based on
existing land-use classifications. For example,
urban land was considered sufficiently modified as not to be a “natural resource,” and so was
combined with produced capital in the wealthestimates. It was valued using the perpetualinventory method – that is by the aggregate
value of gross investment less depreciation.
Natural capital was defined as the sum of nonrenewable resources occurring within the jurisdiction of a country such as oil, natural gas, coal,and minerals, together with arable lands, grazing lands, forested areas, and protected areas. It
was valued by calculating the present value ofresource rents over an arbitrary “lifetime” of 25
years at a discount rate of 4 percent.
Intangible capital was seen as a residual: thedifference between total wealth and the sumof produced and natural capital. This included
human capital (the knowledge, technical skills,
cognitive capacities, physical attributes, etc. of
the human population); the institutions of acountry, sometimes referred to as social capital; and any produced and natural capital not
explicitly accounted for in the produced andnatural capital accounts (such as groundwater,
diamonds, and fisheries), together with net foreign financial assets.
Not surprisingly, the World Bank found that
intangible capital became increasingly significant as incomes rise, accounting for 81 percent
of aggregate capital in high-income countries,
69 percent in middle-income countries, and 57
percent in low-income countries (World Bank
2010). This reflects the greater importance ofthe service sector in high-income countries. It
is partly accounted for by the fact that many
150

more services fall within the market economy
in high-income countries than in low-income
countries, and partly by the concentration ofskill-intensive services in high-income countries.
To understand the relative importance of different factors in intangible capital, the World Bank
(2006) modeled the residual in low- and middle-income countries as a function of domestic
human capital (measured by per capita years ofschooling of the working population); humancapital abroad (measured by remittances fromother countries); and governance/social capital(measured by the rule of law index). It foundthat most variation was explained by the ruleof law, but that years of schooling were also
important. While both are highly correlatedwith other things, it is a reasonable inference
that human capital and social capital are both
important components of intangible capital,
and that these increase with per capita income.
Since intangible capital also includes environmental assets not recorded under natural
capital and man-made assets not recorded
under produced capital, and since it reflects
factor prices that ignore external effects, thisshould be taken as a very rough guide only.
While human capital and social capital are both
important, is not possible to say much more. It
is certainly not possible to draw conclusions
about environmental assets beyond the traditional stocks recorded under natural capital.
One puzzle is that natural per capita wealthappears to rise with income. For example, percapita sub-soil assets were found to be an order ofmagnitude greater in high-income than in lowincome countries. Since this does not correlatewith the physical size of proven mineral reserves,
the implication is that such resources are used
more productively in high-income countries.
At the same time, natural capital accounts fora greater share of per capita wealth in low-income countries than in high-income countries.
This is frequently taken to mean that the poor
are more dependent on environmental assets
than the rich, and that they are consequently
more affected by environmental degradation.
Markandya’s (2001) review of the literature on
Inclusive Wealth Reportthe relation between poverty, environmental
change, and sustainable development suggested
that to the question, “does poverty damage theenvironment?” the answer was broadly “no.” To
the question “does environmental degradation
hurt the poor?” the answer was broadly “yes.”Hence he concluded while poverty alleviation
would not necessarily enhance environmental
quality, and may in fact increase stress on theenvironment, environmental protection would
generally benefit the poor (Markandya 2001).
This reflects the fact that a greater proportionof the labor force is employed in the resource
sectors, and that agriculture, forestry, and fisheries account for a greater share of GNP in lowincome countries than in high-income countries. But it also reflects the fact that property
rights are frequently less well-defined in lowincome countries, and that many natural assets
are exploited under either open access regimes
or as weakly regulated common pool resources.
What has not been resolved by the World
Bank, and what needs to be resolved if we are
to develop a full set of wealth accounts, is theidentification of net changes in physical stocks,
the value of ecosystem service flows that are
external to the markets, and the problem ofaccounting for the environmental drivers of
total factor productivity growth. Identificationof net investment requires specification of
net changes in both physical stocks and theirshadow values.

3.2 Subtractions from and additions tonatural resources
The first problem requires correct identificationof physical stocks, along with additions to andsubtractions from those stocks. A significant
part of the problem with existing accounts
is that the boundary between produced andnatural assets is both ill-defined and shifting. A
number of assets that deliver significant benefits are excluded. The only assets included in
the accounts are those that are subject to welldefined property rights and an associated set
CHAPTER 7 The road to wealth accountingof claims. This excludes human capital, social
capital, and many natural resources.2 Natural
resources need both to be owned and capableof generating economic benefits for their owners, under “available technology, scientificknowledge, economic infrastructure, available
resources and set of relative prices prevailing on
the dates to which the balance sheet relates or
expected to do so in the near future” (European
Communities et al. 2009). The SNA approachallows for forms of property other than strictly
private property, in other words natural
resources may be owned by groups of people,
but it excludes resources that are not the property of either individuals or groups. Examples of
excluded assets are the atmosphere, the open
oceans, and uncultivated forests.
Whether investment in natural resources
generates produced or natural capital in the SNA
depends on the degree to which the resources
are modified in the process. Natural resources
are land, water, uncultivated forests, and mineral deposits. Their modification generally creates a produced asset, and is not regarded asaffecting the value of the pre-existing natural
resource (European Communities et al. 2009).
The problem with this approach is that thesocial value of the pre-existing assets rests inthe discounted flow of the set of ecosystem services they deliver. In practice, what this meansis that increasing land modification is assumed
to build produced capital without impacting theflow of ecosystem services. Indeed, the value ofchanges in pre-existing ecosystem services isgenerally neglected. In Where is the Wealth of
Nations?, for example, urban land is regarded
as defined as produced capital – and valued
as a proportion of the value of machinery andbuildings.
This complicates the treatment of losses(depreciation) and gains (discoveries of non2 The SNA 2008 puts it as follows: “The coverageof assets is limited to those assets used in economic
activity and that are subject to ownership rights; thus
for example, consumer durables and human capital,
as well as natural resources that are not owned, areexcluded”

151renewable natural resources, regeneration parcel of land in some economic use may reflectof renewable natural resources) in natural its place within an ecosystem. If a change in theecosystem changes the productivity of the land,
resource stocks. The major innovation of theit will (in principle) appear in “other changes inWorld Bank’s adjusted net savings estimate
was the inclusion of the depletion of particu- the volume of assets.” However, if the interaclar natural resources. It was limited to mineral tions between the biotic and abiotic elementsof an ecosystem involve flows across property
deposits, forests, and water resources, and so
did not capture changes in many other ecosys- boundaries, and if these are external to the martem services. Nor did it treat gains symmetri- ket, they will not be recorded.
cally. Nevertheless, it was a significant step inthe development of wealth accounts.
At present, the SNA (2008) treats all gains and 3.3 Externalities
losses to natural resources as “other changes inthe volume of assets account.” These fall into a Calculation of the shadow value of the differnumber of categories: changes in mineral stocks, ent capital stocks effectively demands that thethe natural regeneration of biological resources, rents on assets be calculated net of externalities.
the effects of externalities and disasters, the These are not currently accounted for in the SNA,
assignment of property rights, monuments and although they may in principle be recorded in
valuables. In principle, natural regeneration “other changes in the volume of assets.” A discusis taken to be gross regeneration, but in prac- sion of the options for including externalities
tice it is recorded net. Depletion of forests, for in the accounts by Nordhaus (2006) identifies
two major issues: one being the adjustments toexample, was taken in World Bank (2006) tobe depletion in excess of regeneration rates. In the accounts necessary to accommodate nonmarket activities; the other being the boundary
general, the SNA takes biological regeneration to
be “produced” or “non-produced” depending on of non-market accounts.
For non-market activities, the real problem
the degree of control exercised by the resource
manager. Cultivation typically implies control, concerns activities that generate public exterso the value of land in the SNA is exclusive of nalities. If non-market activities do not gener“any buildings or other structures situated on it ate public externalities, they can be treated inor running through it; cultivated crops, trees, a parallel fashion to private market activities.
and animals; mineral and energy resources; If there is, for example, a parallel market activnon-cultivated biological resources and water ity producing the same or a similar product,resources below the ground. The associated the “pricing” of the non-market activity by thesurface water includes any inland waters (res- market good through the “third-party rule” isadequate. If, however, production of some marervoirs, lakes, rivers, etc.) over which ownershiprights can be exercised and that can, therefore, ket good involves co-production of non-market
be the subject of transactions between insti- effects, and there is no market analog to thetutional units” (European Communities et al. non-market effect, “pricing” that effect is more2009). By contrast, in non-cultivated systems, problematic.
Nordhaus (2006) considers two cases. One
any increment in biomass is recorded as an
is where externalities are already reflected in“economic appearance” in “other changes in thethe accounts: where, for example, pollution
volume of assets.”
It follows that ecosystems, as entities that damage inflicted by one activity on anotherspan distinct parcels of land, groundwater bod- increases the costs faced by the second activity.
ies, and the like, are not assets. Nor can they be The advantage of measuring and accounting
recorded as assets in the accounts. The natural for such externalities lies in the efficiency gains
productivity and hence the value of a particular that would occur if the costs incurred by the152

Inclusive Wealth Reportfirst activity fully reflected the damage inflictedon the second. The second case is where externalities cross the boundary between market andnon-market activity. In this case they are notalready reflected in the accounts, and estimating them would change value added in both themarket and non-market accounts. He argues
that it is more important to correct for the second case than the first.
The off-site externalities of many land uses
may be characterized as ecosystem services/disservices. While most land uses are undertaken to provide benefits from the productionof marketed goods and services – foods, fuels,
fibers, recreation, etc. – they typically generate
other benefits or costs. It is worth repeatingthat the ecosystem services we need to measure
and account for are these same off-site effects.
In the absence of off-site costs or benefits, therents to some land use should capture the net
effect of the full set of ecosystem services generated by that use. If there are off-site costs or
benefits it will not.
As a general observation, it will seldom makesense to try to estimate the value of every offsite effect of some land use. It will only makesense to address effects that are sufficiently
large that they lead to significant inefficiencies if neglected. For example, the importanceof water regulation in the Catskills – a poster
child for ecosystem services – lies in the factthat the catchment serves a city of 17 million
people. Off-site hydrological effects in manyother catchments might not warrant the same
effort. What is needed is a system of triage to
identify which ecosystem service flows would
warrant attention and where.

3.4 Productivity growth
The third major problem still to be addressed in
the development of wealth accounts concerns
the Solow residual. Total factor productivity
growth has a number of drivers, few of which
are explicitly accounted for in the national
income accounts. Among these are public sector
CHAPTER 7 The road to wealth accounting

research and development, and the efficiency of
resource allocation. The efficiency of resource
allocation in turn depends on the effectivenessof markets and regulatory institutions, the ruleof law, and the trust that people have in the ruleof law – or social capital. Knowing what drives
total factor productivity growth in an economy
is extremely important for the management of
economic growth. The World Bank’s wealthestimates found that a residual comprising
human capital along with many of the drivers of total factor productivity growth was
the primary correlate of income (World Bank
2006). Currently, the SNA recognizes the needto include research and development as capitalformation, and acknowledges that it should bevalued at expected future benefits (European
Communities et al. 2009). However, most of
the drivers of total factor productivity growth
are not directly measured in the accounts.
The reason to focus on this problem here isthat it is likely that environmental factors are
an important element of total factor productivity growth. While this is intuitive in the case ofrenewable resource-based sectors such as agriculture, forestry, fisheries, conservation, ecotourism, water supply, and so on, it also applies
to sectors in which productivity may be related
to health conditions. For renewable resourcebased sectors, improvements in ambient animaland plant health, water quality, soil loss, and thelike would be expected to lead to productivity
growth. But it is also the case that improvements in ambient human health are likely tohave positive effects on productivity growth inmany other sectors. Moreover, there are likely
to be interactions between the drivers of totalfactor productivity growth.
The very high rates of productivity growthachieved in agriculture, for example, are generally assigned to research and development, therate of return on agricultural R&D investment
being estimated to lie between 45 percent and55 percent (Alston et al. 2009; Alston et al.
2010). This depends on the impact improvements have on crop yields, but it also depends
on the rate at which the material becomes
153

available, the extent to which it is diffused –including the rate at which it is allowed to spillover into other jurisdictions – and the capacityof users to exploit it (Piesse and Thirtle 2010).
Projections of future total factor productivity
growth in agriculture are much less optimistic,
however. In the U.S., for example, total factor
productivity growth over the period 2000–2025
Table 2

SNA environmental assets
AN.1

Produced assets

AN.11

Fixed assets

AN.111

Tangible fixed assets

AN.1114
AN.11141

Livestock for breeding, dairy, draught, etc.

AN.11142

Vineyards, orchards and other plantations

AN.112
AN.1121
AN.12

Intangible fixed assets
Mineral exploration
Inventories

AN.122
AN.1221
AN.2

Work in progress
Work in progress on cultivated assets
Non-produced assets

AN.21

Tangible non-produced assets

AN.211Land

AN.2111Land underlying buildings and structures

AN.2112Land under cultivation

AN.2113

Recreational land and associated surface
water

AN.2119

Other land and associated surface water

AN.212

Subsoil assets

AN.2121

Coal, oil and natural gas reserves

AN.2122

Metallic mineral reserves

AN.2123

Non-metallic mineral reserves

AN.213

Non-cultivated biological resources

AN.214

Water resources

AN.22
AN.222
Source: SEEA (2003)

154

Cultivated assets

Intangible non-produced assets
Leases and other transferable contracts

is expected to be less than half the rate achieved
between 1975 and 2000 (Goettle et al. 2007).
One consequence of this is that the growth infood production needed to meet the needs ofthe growing world population will increase therate at which land is converted from other uses
to agriculture, with all the consequences thathas for biodiversity and ecosystem services.
The solution both to the problem of constructing wealth accounts, and to the management of interactions between assets not currently accounted for, is to quantify and value
the capital stocks that do affect total factor
productivity growth. That is the motivation foradding such stocks as explicit factors of production (Vouvaki and Xepapadeas 2009).

4. Satellite accounts and the capital accounts in the SNA
The consensus is that changes to the national
income accounts needed to address these issues
should appear first in satellite accounts. In
practice, changes in both natural capital stocks
and environmental externalities are addressed
via the satellite System of Environmental andEconomic Accounts (SEEA), still under development by the UN, the EC, the OECD, the IMF, and
the World Bank. The SEEA (2003) includes measures of the effect of environmental change on
capital stocks. Since the SEEA has a capital focus
it is, in principle, consistent with the welfaretheoretic approach adopted by Dasgupta et al.
(2000) That is, it takes changes in aggregate
capital as a test of sustainability. Development
is regarded as unsustainable if it relies on stocksof natural capital, and these are degraded tothe point where they are no longer able toadequately provide what are referred to in the
SEEA as “resource,” “service,” or “sink” functions(loosely corresponding to the MA provisioning,
cultural, and regulating/supporting services).
The SEEA comprises four accounts:• Flow accounts for pollution, energy, andmaterials, recording industry level useof energy and materials as inputs to proInclusive Wealth Reportduction along with the generation ofpollutants and solid waste.
• Environmental protection and resource
management expenditure accounts
identifying expenditures incurred by industry, government, and households toprotect the environment or to manage
natural resources (already recorded in
the SNA).
• Natural resource asset accounts recording changes in traditional natural resource stocks such as land, fish, forest,
water, and minerals.
• Valuation of non-market flow and environmentally adjusted aggregates which
adjusts aggregates for depletion anddegradation costs, and defensive expenditures.
In contrast with the definition of natural
resources in the SNA (Table 2), environmental
assets in the SEEA are defined in Table 3.
Two aspects of these assets are worth
noting.
First, aside from the intangible assets, these
are all place-based and involve the conversion
and management of, or impact on, ecosystemservices associated with a particular place. In
situ subsoil resources are not generally associated with biological activity, but their extraction involves production, processing, and waste
disposal on the surface that frequently has
extensive direct and indirect off-site impacts on
ecosystem services. Surface “land” and “landbased” or “water” resources are more immediately used to enhance the flow of particular
ecosystem services, though this may be at a cost
to other services.
Second, there may be a range of property
rights applying to environmental assets extending from private ownership (freehold), throughtime-limited use rights (leasehold), common
property (common pool resources and public
lands), to undefined rights (open access). Within
the SNA, only assets subject to well-defined property rights are included, and most changes inenvironmental assets recorded in the SNA occur
as “other changes in the volume of assets.” The
CHAPTER 7 The road to wealth accounting

Table 3

SEEA environmental assets
EA.1

Natural resources

EA.11

Mineral and energy resources (cubic meters,
tonnes, tonnes of oil equivalents, joules)

EA.12

Soil resources (cubic meters, tonnes)

EA.13

Water resources (cubic meters)

EA.14

Biological resources

EA.141

Timber resources (cubic meters)

EA.142

Crop and plant resources, other than timber(cubic meters, tonnes, number)

EA.143Aquatic resources (tonnes, number)

EA.144

Animal resources, other than aquatic (number)

EA.2

Land and surface water (hectares)

EA.21

Land underlying buildings and structures

EA.22

Agricultural land and associated surface water

EA.23

Wooded land and associated surface water

EA.24

Major water bodies

EA.25

Other land

EA.3

Ecosystems

EA.31

Terrestrial ecosystems

EA.32

Aquatic ecosystems

EA.33

Atmospheric systems

Memorandum items

Intangible assets related to environmental
issues (extended SNA codes)

AN.1121

Mineral exploration

AN.2221Transferable licenses and concessions for the
exploitation of natural resources

AN.2222

Tradable permits allowing the emission ofresiduals

AN.2223

Other intangible non-produced environmental
assets

Source: SEEA (2003)

SEEA, by contrast, focuses not on property rights
but on the physical attributes of assets, and so
includes a wider and less well-defined range ofenvironmental assets. The SEEA asset boundary
includes not just all land and natural resources,
for example, but also ecosystems.

155

The inclusion of ecosystems is the biggest
difference between the SNA and SEEA. It is alsoquite problematic. The SEEA’s ecosystem assets
deliberately introduce an element of double
counting in the interests of recording each of anumber of distinct ecosystem services.3 Threetypes of systems are recognized: terrestrial,
aquatic, and atmospheric. Each is recognized todeliver multiple services. An asset identified as
EA1 or EA2 can also appear in EA3, if it is associated with any of the services of EA3. As longas ecosystem services are recorded in physicalterms the double counting is not an issue, butwhen the assets are valued, this does not makeas much sense.
The designation of ecosystems as assets ismotivated by a desirable goal – the inclusionof valuable ecosystem services in the system ofnational income accounts. However, this may
not be the best option for capturing currently
non-marketed ecosystem services. Any pieceof land will jointly produce a number of goods
and services, some of which may generate off3 With the exception of natural resources that provide direct use benefits, the individual organisms andphysical features that make up ecosystems are notclassified as unique assets in the SEEA. This reflects
the fact that it is not generally the components ofecosystems that benefit humans, but the systems asa whole. However, because natural resources are recognized as specific assets, some elements of the environment appear twice in the SEEA asset classification,
once as natural assets and again as components ofecosystems. Thus, forests that are used as a source oftimber are classified as natural resource assets. Since
these same forests provide other benefits as well (carbon absorption for example), they are also classified
as ecosystem assets. This reflects the fact that these
forests provide more than one kind of benefit. As natural resources, they provide direct use benefits, while
as components of ecosystems they provide indirect
use benefits. It is necessary to recognize both rolesof forests and other biological resources if a complete picture of the benefits provided to humans by
the environment is to be captured in the SEEA. Note,though, that the inclusion of ecosystems as a separate
category, like that of the inclusion of soil, means that
there is an element of double counting in the SEEA
classification, deliberately introduced to enable different environmental aspects to be examined. (SEEA
2003: 7.74).

156

site benefits/costs. The social value of the landas an asset is the discounted flow of all theservices it yields, whether marketed or not andwhether on-site or not. The on-site benefits
should be captured in land prices (where these
exist), so the task of the SEEA is to identify theoff-site services. The justification provided in
SEEA (2003) for citing ecosystems as the sourceof such services is that “it is not generally thecomponents of ecosystems that benefit humans,
but the systems as a whole.” But this is simply
not correct. The value of any piece of land committed to some use derives from the marginal
impact of that use on the flow of all the goods
and services from the land. If the service providing benefits is a public good, then the marginalvalue of actions by the i th provider that change
the flow of the public good should be recordedin the accounts. The contributions of all otherproviders (the grey terms) affect the value of
their own assets. Of course, there may well be
assets (defined in terms of property rights) that
extend over whole ecosystems. The SEEA water
assets, for example, include the exclusive economic zones of countries, and so cover a number of large marine ecosystems. However, ingeneral, asset values derive from the marginalcontribution that individual properties make tothe flow of all economically relevant ecosystemservices.
The SEEA approach to estimating asset values is summarized in Table 4.
As in the SNA, multiple methods are used
including both perpetual inventory methods
and direct estimation of resource rents. For
most environmental assets, the resource rent
is derived by deducting costs from the market
price received for marketed products, the valueof the stock being calculated as the net present
value of rents. The SEEA suggests that non-market valuation techniques be used for services
that do not have a market price. To capture theeffect of non-marketed off-site ecosystem services flows, what is needed is a measure of theexternality involved, and not the addition of
ecosystems as an extra category of assets.

Inclusive Wealth ReportWhat is needed to correct the wealthaccounts in the SNA (or the National Income
and Product Accounts [NIPAs] in the U.S.) is boththe extension of the set of stocks measured tocomprise all relevant sources of wealth, and theinclusion of the non-marketed impacts of asset
use on third parties. The most important single
addition to make to the set of stocks measured
is undoubtedly human capital. The findings ofWorld Bank (2006) along with numerous studies
of total factor productivity growth indicate thatthe most important driver of wealth creationis the skills and know-how of the population.
This is excluded from both the NIPA and the SNA(Jorgenson and Landefeld 2006; European
Communities et al. 2009). The most importantenvironmental stocks to add are those currently
excluded on grounds that they lack sufficiently
well-defined property rights. These are notecosystems as such, but the many public lands,
open access resources, and sea areas within the
exclusive economic zone that are importantcomponents of national wealth, but that do notcurrently appear in the accounts.
The most important non-marketed impacts
of asset use on third parties are off-site ecosystem service flows: environmental externalities.
There are four main categories of off-site ecosystem service flows that are currently neglectedin the national accounts.
• Hydrologically mediated flows include
water pollution, siltation, soil loss, flooding, and so on.
• Atmospherically mediated flows include
emissions with local (PM-10, photochemical smog); regional (sulfur dioxide); andglobal (carbon dioxide, nitrous oxide,
methane) consequences.
• Human travel and transport-mediatedflows include the transmission of pests
and pathogens through local, regional,
and global goods transport and travel
networks.
• Access mediated flows include changes
in on-site benefits accessed by people
elsewhere. Examples include the external benefits or costs to others of on-site
CHAPTER 7 The road to wealth accounting

Table 4

Methods used to estimate asset values in the SEEA
Data needed for estimating stock values:
Resource rent
Stock of the resource
Life-length or rate of extraction of the resource
Decision on how to record renewals/discoveries
Discount rate for future income
Data needed for estimating resource rent:
1. Appropriation method
direct observation
2. PIM-based method
stock of produced capital (estimated from price decline)
net operating surplus
rate of return to produced capital
3. Capital service-based method
stock of produced capital (estimated from efficiency decline)
gross operating surplus
capital services rendered by produced capital
Source: SEEA (2003)

biodiversity conservation/loss. Suchflows may involve either information or
physical (e.g., travel) movements.
Many local flows might fall into Nordhaus’s
category of external effects whose impact on
asset values are already included in the accounts(Nordhaus 2006). However, many regional andall global flows are international, and are currently not recorded anywhere in the accounts.
Since many of these flows are non-exclusive
and non-rival in their effects (they are public
goods), whether they are significant enoughto be measured and recorded depends on theextent of the public interest affected – the percapita benefits conferred or costs imposed andthe size of the affected population. Indeed, thisis why a system of triage is needed. Capturing
important off-site ecosystem service flows is,however, critical to the correct estimation of
the value of the assets involved.
157

5. Conclusion
The capital accounts in the existing national
income accounts do a poor job of tracking
changes in wealth. This is partly because of
their focus on “tangible” assets and hence theirneglect of human and social capital, but it isalso because of the way in which environmental
assets are currently recorded. The weaknesses of
the approach to environmental assets in the SNA
have long been recognized (Repetto et al. 1989;
Pearce and Warford 1993). The World Bank’s
adjusted net savings measure is an attempt toestimate the errors involved (World Bank 2006,2010). The SEEA (2003) is an attempt to generate the environmental data needed to measureenvironmental wealth. While both move theagenda forward, neither resolves the questionsof what environmental stocks are important toinclude, how they should be measured and how
they should be valued.
A very large part of the problem lies inthe exclusions implied by the property rights
focus of the SNA. Since the only admissible
assets are those that generate claims to future
benefit streams, the SNA excludes a number ofnatural resources that are important to humanwell-being, but that cannot be privately coopted. The list of excluded resources includes
many in public ownership or that lie beyond
national jurisdiction. From a global perspective,
it is important that the set of accounts used tomeasure the growth, equity, and sustainability of resource use covers all assets on whichhuman well-being depends, including thosebeyond national jurisdiction. Three points areimportant.
First, the stocks of “environmental” assetsthat need to be recorded comprise all lands thatgenerate off-site benefits or costs as a result ofenvironmental flows, noting that “land” in thiscontext defines a surficial area associated withthe off-site ecosystem service flows describedabove, that is it comprises both terrestrial andaquatic properties. Note that this is not thesame as the “ecosystems” referred to in the SEEA.
Surficial assets should be defined by ownership.
158

They should cover the full extent of the surface
over which the country has rights, and should
include all forms of property, whether or notthey yield marketed products. If a parcel of land
genuinely makes no contribution to humanwell-being, then its shadow value will be zero.
But it should be on the list of assets.
Second, the lands that generate off-site ecosystem service flows are not restricted to thenatural resource categories in either the SNA or
the SEEA. There is an increasing appreciationthat built environments – urban and industrial
areas – create ecosystems that generate benefits
and costs to people that are sometimes similarand sometimes different from ecosystems inother areas. They also involve off-site flows that
affect well-being. For example, urban environments play a critical role in the transmissionof infectious diseases, even if the origins of
those diseases might lie elsewhere. Urban systems tend to have different thermal properties
than other systems. The heat island effect, forexample, is an urban phenomenon. They also
play a critical role in stimulating demand forecosystem services within the urban hinterland.
Whether assets are classified in the national
accounts as natural resources or something else
is not important. What is important is that if
assets in other classifications have significant
off-site environmental effects, then that should
impact their value in the accounts.
Third, it is worth repeating that the nonmarketed ecosystem services that should berecorded in the accounts are those generating costs or benefits not currently reflected in
the rents to asset holders. Specifically, off-siteexternalities that affect the value of other assets
should be recorded. Such externalities cangenerally be associated with particular types of
ecosystem services. So, for example, changes
in on-site characteristics that affect the accessthat others have will frequently be cultural services. Off-site flows, including water pollution,soil loss, siltation, disease transmission, and soon, will frequently be regulating services. Froman accounting point of view, however, it is the

Inclusive Wealth Reporteffect on the value of other assets and not theclassification of the service that matters.
The relationship between asset holdings,
externalities, and poverty is important tounravel. The dependence of many people on the
non-market exploitation of natural resourcesin open- or weakly-regulated access common
pool resources is not reflected in the national
accounts as they now exist. This is partly
because of the SNA rules on assets not subject towell-defined property rights, and partly becauseof the exclusion of environmental externalities.
The evidence from the adjusted net savings estimates suggests that the poorest countries have,on average, reduced the value of their assets
over the last four decades. In the absence ofcomprehensive wealth estimates it is, however,difficult to confirm this.

CHAPTER 7 The road to wealth accounting

159

Appendix

product at time t, to be a measure of the output achievable given the produced capital stock,
The welfare-theoretic foundations
K(t), the human capital stock, L(t), and a stockof wealth accounting“natural resources” which may be thought about
as an area of land or sea, along with the biotic
and abiotic elements that area contains, N(t),together with the technology, institutions, andFifty years ago, Samuelson (1961) suggested
that the appropriate measure for making environmental conditions that collectively
intergenerational well-being comparisons is determine total factor productivity, A(t). Total
factor productivity measures the proportion of
wealth, as distinct from the income measurescommonly reported in the system of national output not explained by the amount of inputs
income accounts. It was not until the 1990s, used in production, and captures the effect of
however, that progress was made in formal- technical progress, the efficiency with which
inputs are used, institutional conditions, andizing the notion in ways that made it possible
the impact of environmental factors such as
to begin constructing wealth accounts and toclimate. If we ignore the sensitivity of total facadjust the system of national accounts to takeaccount of the depreciation of environmental tor productivity to investment in produced andassets (Hartwick 1990; Pearce and Atkinson human capital, and to the rate at which natural
1993; Hamilton 1994; Hartwick 1994; Pearce resources are extracted, GNP can be described by
et al. 1996; Hamilton and Clemens 1999; the function:
Hartwick 2000). Much of this work was stimu- Equation A.1
lated by the Brundtland Report, published inY(t) = A(t)f (K(t)L(t)N(t))
1987, which defined sustainable development interms of intergenerational changes in wealth:
Suppose that the depreciation rate cor“Sustainable development is development that responding each type of capital stock is δK, δL,meets the needs of the present without com- and δN respectively, and that investment in eachpromising the ability of future generations totype of capital is I K, I L, and I N. In addition to themeet their own needs” (World Commission on effects of investment, natural resources may be
Environment and Development 1987). From expected to regenerate through some set of bioa welfare-theoretic standpoint, the central geochemical process according to the function
requirement of a sustainable consumption pro- g(N(t),I N(t)).
gram for the current generation is that it should
The growth rate for each of the capital stocks
not reduce the consumption possibilities avail- may be written as
able to future generations. This idea was first Equation A.2
introduced by Lindahl in the 1930s (LindahldK1933) who defined “income” to be the maximum= A(t)f (K(t)L(t)R(t))-C(t)-I L(t)-I N(t)-δ KK(t)amount that could be consumed without reducdt
ing the value of the capital stocks available toEquation A.3
future generations. Income in the Lindahl sensedL
is equivalent to the SNA concepts of net national= IL(t)-δ LL(t)dtproduct or net national income.
Equation A.4
To see what it contains, and how it relates tochanges in the value of capital stocks, considerdN= g(N(t))-δ NN(t)the simplest representation of the economy. In
dtthis we adapt an argument from Dasgupta (2009)that builds on Dasgupta and Maler (2000) and
That is, net investment in produced capital
Arrow et al. (2003). Define Y(t), or gross national is just the difference between gross national
160

Inclusive Wealth Reportproduct and the sum of consumption, investment in human and natural capital, and thedepreciation of produced capital. Net investment in human and natural capital is measured
by the difference between additions and subtractions – where additions include investment
and/or natural regeneration in the case of natural capital.
Aggregate consumption at time t is denoted
C(t). It is assumed that intergenerational wellbeing, V(t) depends on aggregate consumption
via the relation:
Equation A.5

V(t) =∫t U(C(t))e-r(t-τ)dτ
∞in which U (C(t)) is instantaneous wellbeing measured at time t, and is assumed to bea concave function – to have positive first andnegative second derivatives.
The feature of Dasgupta’s approach thatmakes it particular helpful to the implementation of wealth accounting is that no assumption
is made about the optimality of V(t), C(t), or thetime paths of the various capital stocks. Denotethe state of the system at time t by:
Equation A.6

S(t) = (K(t),L(t),N(t)An economic program is then a consumption and investment path from t onwards,{E(τ)}t∞ = {C(τ),K(τ),L(τ),N(τ),I L(τ),R(τ)}t∞ , thatsatisfies the equations of motion of the capitalstocks, (Innes et al. 1998). Dasgupta (2009)
defines a resource allocation mechanism to bea mapping from the state of the system to an
economic program: α:{S(t),t }-►{E(τ)}t∞, making
the point that there is no requirement that the
program be efficient. This is particularly relevant if some of the services associated with thecapital stocks are public goods, having benefits
or costs beyond the jurisdiction of the country
concerned. Institutions having responsibility
for the domestic allocation of international
environmental public goods have little incentive to satisfy the Samuelson condition for theefficient allocation of public goods.

CHAPTER 7 The road to wealth accounting

The intergenerational measure of wellbeing corresponding to a particular economic
program is thus:
Equation A.7

V(S(t),t) = ∫t U(C(t))e-r(t-τ)dτ∞and the shadow or accounting prices of thecapital stocks are simply the partial derivativesof this function with respect to those stocks.
For assets for which there are well-functioning
markets and few externalities, shadow prices
and market prices should be reasonably closelyaligned. For assets for which there are no markets, or for which there are significant externalities, shadow prices would be expected to deviate substantially from market prices. Dasgupta(2009) offers a number of propositions that follow from such a formulation of the problem.
1. In the special case where total factor productivity is constant, the time derivative of
V(S(t)) is simply the sum of the change in eachof the capital stocks evaluated at the shadow
price of those stocks. That is,
Equation A.8

dV(S(t))dt=∂V(S(t)) dL(t)
∂L(t)

dt

∂V(S(t)) dK(t)
∂K(t)
+

dt

+

∂V(S(t)) dN(t)
∂N(t)

dt

Since the equations of motion for eachof the capital stocks record the net effect ofinvestment and depreciation, together with theregeneration of natural capital stocks, this is ameasure of aggregate net investment – what
Dasgupta refers to as comprehensive investment. Aggregate net investment, evaluated at
the shadow or accounting prices of assets, is ameasure of the rate at which marginal intergenerational well-being changes over time.
2. Aggregate net investment is also a measure of the discounted stream of consumptionthat it induces.
3. An economic program is sustainable if
and only if aggregate net investment is positive.

161

4. Aggregate wealth is the shadow value ofthe stocks of all assets available to the economy.
5. An economic program at time t is sustainable if and only if, holding shadow prices constant, aggregate wealth is non-declining at t.
6. dV (S(t)) dt > 0 if and only if U'(C(t)) dC(t)dt < net national product. That is, Lindahl’s
condition on “income” holds. Intergenerational
well-being is growing if and only if consumption is less than net national product.
7. Intergenerational well-being in a country
is higher/lower than in another country if its
wealth, evaluated in terms of its shadow prices,is greater/less.
Note that these propositions hold whether or
not the allocation mechanism is efficient. They
imply that if we wish to understand changes inintergenerational well-being, we need to understand changes in wealth, and to do this we needto track changes in aggregate net investment.
Now consider the more general case where
total factor productivity is not constant. In aclosed economy, if all factors of production
were fully accounted for, and if all effects of newtechnical knowledge, institutions, and so on
were captured in investment in those factors of
production, then the residual would be equal tozero: (dA(t) dt ) (1 A(t)=0. In practice, not all
factors of production are fully accounted for. In
particular, many natural resources lie outside themarket and are not taken into account in production decisions. The effects of changes in technicalknowledge – especially technical knowledge due
to publicly funded R&D – are not captured in factor prices. Nor are changes in the efficiency of theallocation mechanism, or environmental conditions. So even in a closed economy, the residual
will not be zero. In an open economy there are,in addition, the effects of international technology transfers and the effects of transboundary
environmental externalities. All of these have thecapacity to change total factor productivity.
Suppose, for example, that total factor productivity depends on a global public good, G,
which is influenced by the natural resource use
decisions of all countries. To fix ideas, it might
be thought of as a public good characterized by162

an additive supply technology, such as climatechange mitigation through carbon sequestration. So the size of the public good at time twould be G(t)=∑ ni=1G(t)i, that is the sum of thecontributions of all n countries. If total factor productivity in country i is A i(t)=A i(G(t),t ),i = 1,…,n, and if dV i(S(t)) dG i(t)=[∂V i(S i(t))∂A i(t)][dA i(t) dG i(t)], the i th county is able toaffect its GDP through its own carbon sequestration efforts, G i(t), it will internalize that
impact. However, it will ignore any effects it has
on total factor productivity in other countries.
Intergenerational well-being in country i is now
a function of the allocation mechanism in thatcountry, the state of its capital assets, and theglobal public good:
Equation A.9

Vi(t)=Vi(αi ,Si(t),G(t),t)
and the rate at which it changes is given by:
Equation A.10

dVi(αi ,Si(t),G(t))
dtdGi(t)dt+∑= Ii(t)+∂Vi(Si(t))∂G(t)

dGj(t)

j≠i

dt

where
Equation A.11

I(t) =+∂Vi(Si(t)) dKi(t)∂Ki(t)

dt+∂Vi(Si(t)) dLi(t)∂Li(t)

dt∂Vi(Si(t)) dNi(t)∂Ni(t)

dt

Only the quantity [∂V i(S i(t)) ∂G(t)][dG i(t)dt ] is part of the i th country’s decision. The
contribution of all other countries to the wellbeing of country i, given by [∂V i(S i(t)) ∂G(t)][∑ j≠idG j(t) dt ] is taken as given, and the contribution of country i to all other countries, ∑ nj≠i, j=1[∂V j(S j(t)) ∂G(t)][∂G(t) ∂G i(t)][dG i(t) dt ],is ignored. But these impacts have a potentially
important effect on the performance of othercountries (positive or negative) and should be
accounted for.
Inclusive Wealth ReportReferences

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CHAPTER 7 The road to wealth accounting

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Chapter 8

Ecosystem services andwealth accounting
Edward B. Barbier

Key Messages
Ecosystems should be treated as animportant asset in an economy and, in principle, ecosystem services should be valued ina similar manner as any other form of wealth.
Quantifying these services is very challenging.
The purpose of this chapter is to review progress in economics and ecology in assessing ecosystem services and their values, and to discuss
the resulting implications for including suchservices in a wealth accounting framework.
Understanding the relationship between
ecosystems, their structure and functions,and the ecological services they generate is
essential to determining how the structure andfunctions of an ecosystem provide valuable
goods and services to humans.

Since the purpose of new investment is toincrease the quantity and quality of the economy’s total capital stock, or wealth, adjusting
gross domestic product (GDP) for depreciationin this stock would measure more accurately
whether net additions to capital are occurring.
If net domestic product (NDP) is to serve asa true measure of the changes in an economy’s
wealth, it must include any appreciation or
depreciation to human and natural capital aswell.
The approach developed here requires,first, recognizing ecosystems as a componentof natural capital, or ecological capital; and second, measuring these important assets in termsof the land area, or ecological landscape, which
defines their boundaries.

165

1.

Introduction

The growing scarcity of ecosystem goods andservices, or ecological scarcity, indicates thatan important source of economic wealth, theworld’s ecosystems, is being irreversibly lostor degraded (Barbier 2011a). Over the past 50
years, ecosystems have been modified more
rapidly and extensively than in any comparable
period in human history, largely to meet rapidly
growing demands for food, freshwater, timber,fiber, and fuel. The result has been a substantial
and largely irreversible loss in biological diversity, ecosystems, and the ecological services thatthey provide. Approximately 15 out of 24 major
global ecosystem services have been degradedor used unsustainably, including freshwater,
capture fisheries, air and water purification,and the regulation of regional and local climate,natural hazards, and pests (MA 2005). Over the
next 50 years, the rate of biodiversity loss is also
expected to accelerate, leading to the extinctionof at least 500 or the 1,192 currently threatenedbird species and 565 of the 1,137 mammal species(Dirzo and Raven 2003).
An important contribution of the Millennium
Ecosystem Assessment was to define ecosystem goods and services as valuable “benefits”
to humans and to highlight the deterioratingstate of many global ecosystems and their key
services (MA 2005). As a U.S. National ResearchCouncil Report points out, “the fundamental
challenge of valuing ecosystem services lies inproviding an explicit description and adequate
assessment of the links between the structureand functions of natural systems, the benefits(i.e., goods and services) derived by humanity,
and their subsequent values” (NRC 2005, p. 2).
The main reason for this challenge is the “lack ofmultiproduct, ecological production functions
to quantitatively map ecosystem structure andfunction to a flow of services that can then bevalued” (Polasky and Segerson 2009, p. 422).
Despite these valuation problems, the consensus in the literature is that ecosystems areassets that produce a flow of beneficial goods

166

and services over time.1 For example, as Daily etal. (2000, p. 395) state, “the world’s ecosystems
are capital assets. If properly managed, theyyield a flow of vital services, including the production of goods (such as seafood and timber),life support processes (such as pollination andwater purification), and life-fulfilling conditions (such as beauty and serenity).” Ecosystems
should therefore be treated as an important
asset in an economy and, in principle, ecosystemservices should be valued in a similar manner as
any other form of wealth. That is, regardless ofwhether there exists a market for the goods andservices produced by ecosystems, they makecontributions to current and future well-being.
The importance of this economic contribution of ecosystems has become the focal pointof recent international and national studies, such as the Economics of Ecosystems andBiodiversity (TEEB 2010) and the U.K. National
Ecosystem Assessment (2011).
As chapters in this report have stressed,
accounting for the depreciation of ecological assets is essential to any inclusive wealthaccounting framework (see, especially, 3, 6, 7,
and 9). However, a major difficulty arising intreating ecosystems as economic assets is inquantifying this form of capital and in measuring the valuable benefits that it produces(Barbier 2008, 2011a, 2011b; Mäler et al. 2008;
Polasky and Segerson 2009). The valuation
challenge is further exacerbated by the difficulty in determining the ecological productionof many ecosystem goods and services and inobserving values for the myriad economic benefits, many of which are non-marketed. The
purpose of this chapter is to review progress ineconomics and ecology in assessing ecosystemservices and their values, and to discuss theresulting implications for including such services in a wealth accounting framework.

1 See, for example, Barbier (2008) and (2011a); Dailyet al. (2000); EPA (2009); MA (2005); NRC (2005);
Polasky and Segerson (2009); TEEB (2010); and WRI(2001).

Inclusive Wealth Report

The next section provides an overview of thewealth accounting method suggested for natural
capital by Dasgupta and Perrings in this reportand by Dasgupta (2009), and discusses how ecosystem services can be incorporated into thisframework. Section 3 examines further how
ecosystems can be characterized as economic byadopting ecological landscape – or land area – as
the basic measuring unit. As Section 4 explains,
understanding the relationship between ecosystems, their structure and functions, and theecological services they generate is essential todetermining how the structure and functionsof an ecosystem provide valuable goods andservices to humans. Section 5 discusses how
the economic concept of a “benefit” should
be applied to ecosystem goods and services asa guide to their correct economic valuation
through integrating the “ecological production”
of ecosystem goods and services with “economic
valuation” of these benefits. Section 6 provides
an overview of the substantial progress that has
been made by economists working with ecologists and other natural scientists on this “fundamental challenge” to improve the applicationof environmental valuation methodologies
to non-market ecosystem services. Section 7
focuses on the specific challenges that need to
be overcome in correcting wealth accounts for
ecological capital. To illustrate, Section 8 provides an example of inclusive wealth accounting
with a case study from Thailand involving mangrove loss, based on Barbier (2007). The conclusion to this chapter offers some final remarks on
how incorporating ecosystem services in wealthaccounting can be further improved.

2. Wealth accounting and ecosystemservices
Following the framework developed by
Dasgupta (2009), previous chapters in this reportsuggest a common wealth accounting methodology for natural capital, including ecosystems(see Chapters 6 and 7). Such an accounting
framework defines the aggregate wealth as the

shadow value of the stocks of all the assets of an
economy, and suggests that ecosystems should
be included as an important form of “natural
capital” in this wealth. Moreover, the aggregate
wealth of the economy will increase over time
only if current consumption is less than the net
national (or domestic) product, provided thatthe latter correctly accounts for the economic
contributions of all capital, including ecosystems. The next section summarizes the basic
wealth accounting principles arising from thismethodology, extends it to incorporate ecosystems and their valuable goods and services,and thus constructs an adjusted measure of net
domestic product (NDP) that accounts for the
additional contributions of ecological capital.
For most economies, the standard measureof economic progress is real per capita grossdomestic product (GDP), the market value ofall final goods and services produced within
the economy.2 The problem with GDP as an
economic indicator, however, is that it does
not reflect changes in the capital stock underlying the production of goods and services. GDP
accounts for gross investment in an economy
but not for any depreciation in existing capital. Since the purpose of new investment is toincrease the quantity and quality of the economy’s total capital stock, or wealth, adjusting GDP
for depreciation in this stock would measure
more accurately whether net additions to capital are occurring. And, as has been demonstrated,economic development is sustained if and only
if such investment in overall wealth is non-negative over time (Dasgupta 2009; Dasgupta and
Mäler 2000; Hamilton and Clemens 1999).
2 The alternative measure to gross domestic product is gross national product (GNP), which is the GDPof an economy plus net income from abroad. The latter net payments consist of the income that people
and organizations resident in the domestic economy
receive from abroad on account of property and otherassets which they own in foreign countries less theincome paid to non-residents from their holdings ofproperty and assets in the domestic economy. Thus,
GDP is the total income of an economy produced
domestically, whereas GNP is the total gross income
received by the residents of an economy.

CHAPTER 8 Ecosystem services and wealth accounting

167

The idea of deducting capital depreciationfrom GDP to obtain a “net” domestic product(NDP) measure is not new. Lindahl (1933) firstprovided the justification by suggesting thatan economy’s income should exceed current
consumption, including any consumption ofexisting capital, to prevent the economy’s total
wealth from declining. However, the aggregate stock of economic assets should be muchbroader than conventional reproducible (orfixed) assets, such as roads, buildings, machinery, and factories. Investments in human capital,such as education and skills training, are alsoessential to sustaining development. Similarly,
an economy’s endowment of natural resources
is an important form of “natural wealth.” Thus,a better indicator of an economy’s progress
would be an expanded measure of NDP that is“adjusted” for real depreciation in reproducible
and natural capital, as well as any net additions
to human capital, such as through real education, health, and training expenditures in theeconomy.3
In economics, and in systems of national
accounts, “capital” is conventionally defined as
reproducible real assets, which includes roads,
railways, buildings, private dwellings, factories,
machinery, equipment, and other humanmanufactured fixed assets. Thus, investment in
the economy, or gross capital formation, is conventionally measured as outlays or additions tothese reproducible assets plus net changes in
the level of inventories and valuables. If allowance is made for any capital consumption, or
depreciation, then the net changes in reproducible assets represent net investment in theeconomy.
However, the economy does not just dependon reproducible assets, but also human and natural capital. Traditionally, investment in humancapital, which can be thought of the education,
skills, and health per person, are not included

3 See, for example, Aronsson and Löfgren (1996);
Dasgupta (2009) and (2012); Hamilton and Clemens(1999); Hartwick (1990); Mäler (1991); Pearce andBarbier (2000); and Perrings (2012).

168

in the national accounts. Similarly, additions toand depreciation of natural capital are excluded.
In a true wealth accounting framework to estimate the NDP of an economy, both of theseomissions need correcting. That is, the threebasic assets comprising the overall wealth of an
economy are reproducible, human and natural
capital.
Clearly, natural capital must include thoseconventional natural resources that are thesource of raw material, land, and energy inputs
to the economy, such as fossil fuels, minerals,
metals, forest resources, and arable land. But, in
addition, natural capital should include thoseecosystems that through their natural functioning and habitats provide important goods
and services to the economy. As suggested by
Barbier (2007), these benefits are wide-ranging,which in economics would normally be classified under three different categories:(i) “goods” (products obtained from ecosystems, such as resource harvests, water, andgenetic material),(ii) “services” (e.g., recreational and tourism
benefits or certain ecological regulatory andhabitat functions, such as water purification,
climate regulation, erosion control, and habitat
provision), and(iii) “cultural benefits” (e.g., spiritual andreligious beliefs, heritage values).
It is clear that some of these ecosystem
goods and services contribute directly to humanwell-being, for example through enhancing recreation and other direct enjoyment of the environment, augmenting our current and futurenatural heritage, or by reducing harmful pollution and assimilating waste. But some services,
either on their own or combined with human
inputs, also contribute indirectly to human welfare by supporting economic production (e.g.,
raw materials, food, and other harvested inputs;
provision of freshwater, watershed protection,and coastal habitats for off-shore fisheries) orby protecting production activities, property,
and lives (e.g., flood control, storm protection,
managing climate). In other words, “ecosystemservices are the direct or indirect contributions
Inclusive Wealth Reportthat ecosystems make to the well-being of
human populations” (EPA 2009, p. 12).
However, as noted in the introduction tothis chapter, ecosystems are under threat fromdegradation and loss globally. Global land usechange has been a major cause of the alterationand loss of terrestrial ecosystems, especiallyin developing economies and tropical regions(Barbier 2011a; Dirzo and Raven 2003; FAO
2006; MA 2005). Coastal and marine ecosystems
are also some of the most heavily used andthreatened natural systems globally, such that
50 percent of salt marshes, 35 percent of mangroves, 30 percent of coral reefs, and 29 percent
of seagrasses are either converted or degradedworldwide (FAO 2007b; MA 2005; Orth et al.
2006; UNEP 2006; Valiela et al. 2001; Waycott
et al. 2009). The major reason for this loss island conversion, such as the transformationof forests and wetlands to crop and grazing
land, expansion of aquaculture and agriculture in coastal areas, and the demand for landfor urban and commercial development. In
national accounting terms, the implication isthat the depreciation of an important natural
asset (ecosystems) is partly compensated for by
the appreciation of another asset (more landfor economic production and development). As
Hartwick (1992) has illustrated with the example of agricultural conversion of tropical forests, such changes in the stock of an economy’s
wealth must be included as capital value adjustments in an accounting framework. In effect,
the opportunity cost of holding on to ecosystems as natural capital is the foregone benefitsof economic development based on converting
ecological landscape (Barbier 2008 and 2011a).
In sum, ecosystems can be considered acomponent of natural capital – or ecologicalcapital for short – that affects current economic
well-being, either directly or indirectly throughsupporting production and protecting human
lives and property. However, ecological capitalis unlikely to be intact, as many ecosystems
continue to be converted to land for economic
development and production.

The appendix of this chapter develops aformal model to show why accounting for thewelfare contributions of reproducible humanand natural capital – including ecological capital – is essential to determining the sustainability of an economy. The key accounting result of
this model is also summarized and explained inBox 1. The model yields the following important insights concerning wealth accounting,ecosystem services, and sustainable economic
development:
First, non-declining welfare is taken as the
crucial criterion defining sustainable development of an economy.4 Using this criterion,
the model in the appendix confirms the result
obtained by Dasgupta (2009) that investmentin the aggregate capital stock of an economy,
including ecological capital, determines changes
in intergenerational well-being over time.
That is, sustainable economic development isachieved if the aggregate wealth of the economy
does not decline. Thus, the sustainability criterion that “welfare does not decline over time”
essentially “requires managing and enhancing
a portfolio of economic assets, the total capitalstock, such that its aggregate value does notdecline over time,” but only if it is recognizedthat “the total stock of the economy available tothe economy for producing goods and services,and ultimately well-being, consists not just of
human and physical capital but also of natural
capital” (Pearce and Barbier 2000, pp. 20-21).
Second, as the appendix illustrates, theappropriate indicator for measuring the contribution of aggregate wealth to an economy is net
domestic product (NDP). However, this indicator should not be conventionally defined NDP as
currently measured in most national accountsof economies, that is the gross domestic product (GDP) of the economy less any depreciation(in value terms) of previously accumulated
reproducible capital. Instead, as summarized in

4 For example, Pearce et al. (1989, p. 32) state: “thewellbeing of a defined population should be at least
constant over time and, preferably, increasing for there
to be sustainable development.”

CHAPTER 8 Ecosystem services and wealth accounting

169

Box 1, if NDP is to serve as a true measure of thechanges in an economy’s wealth, it must include
any appreciation or depreciation to humanand natural capital as well. In the case of nonrenewable resources, such as fossil fuels andminerals, depletion of these resources should
be deducted from NDP. For renewable resources,
such as forests and fisheries, NDP must include
any depreciation (appreciation) in natural
resource stocks if current extraction rates are
greater (lesser) than biological growth.
Finally, we should also adjust the NDP of theeconomy to include two contributions due toecological capital:• the value of the direct benefits provided
by the current stock of ecosystems; and• any capital revaluation as a result of conversion of ecosystems to other land uses,with the “price” of changes in ecologicalcapital reflecting the present value of the
future direct and indirect benefits of ecosystems.
As discussed previously, the direct ecosystembenefits might include the value of ecosystems
in providing recreational, educational and scientific benefits, their value in terms of natural
heritage or bequests to future generation or thevalue of ecosystems in reducing harmful pollution, assimilating waste, and managing climate.
In addition, ecological capital protects or supports economic activity, property, and human
lives. These indirect ecosystem benefits arebroad ranging, and include raw materials, food,and other harvested inputs used in production
activities, provision of freshwater, watershed
protection, coastal habitats for off-shore fisheries, flood control, storm protection, climate
stabilization, and similar services.
In the wealth accounting frameworkadopted here, the resource allocation mechanism of the economy may not be optimal oreven efficient, so it is possible that ecosystem
conversion may be taking place even though
the capitalized value, or “price,” of developed
land is actually less than the capitalized valueof ecosystems. This being the case, as we havediscussed, NDP should be adjusted for the170

depreciation in ecological capital that occurs as
it is converted to less valuable developed land.
But if ecosystems are an important componentof natural capital, and if we want to adjust NDP
to account for real depreciation in this form ofnatural wealth, then we need to find a way of,first, measuring such assets, and second, valuing the various benefit flows that they generate(Barbier 2008, 2011a, and 2011b). The purpose of
the next several sections is to discuss how best to
overcome these measurement challenges. Laterin the chapter, the example of mangrove loss inThailand is used to illustrate the practical application of correctly adjusting NDP to account forthe contributions of ecological capital.

3.

Ecosystems as natural capital

If we are to view ecosystems as economic assets,
and measure their economic depreciation in
wealth accounting, then we need a way of measuring this form of “ecological wealth” (Mäler
et al. 2008). One barrier to such an approachis that, in ecology, the concept of an ecosystem
has been difficult to define or to measure quantitatively (O’Neill 2001; Pickett and Cadenasso2002).
However, it is increasingly recognized thatmost ecological processes are influenced by thespatial extent, or landscape, that defines theboundary of the system.5 Similarly, the various
coastal and marine ecosystems that make up
the land-sea interface located between watersheds, the coast, and oceans could be designated in terms of distinct seascapes that define
the boundaries between each type of system(Moberg and Rönnbäck 2003; Shackeroff
et al. 2009). Thus, as shown by Barbier, (2008and 2011a), through adopting ecological landscape, or land area, as the basic unit, characterizing the ecosystem as a natural asset isrelatively straightforward. It also facilitates
5 See, for example, Bockstael (1996); O’Neill (2001);
Perry (2002); Pickett and Cadenasso (1995) and (2002);
Turner (2005); and Zonneveld (1989).

Inclusive Wealth Reportthe examination of human transformation of conversion, draining, or other human-induced
an ecological landscape through land use con- disturbances, the impact on the provision ofversion, leaving the residual land for ecologi- and synergies between wetland services can besubstantial. Such a landscape approach is being
cal processes and habitat for species throughincreasingly used for assessing the cumulative
relatively straightforward models of land usechange. This then facilitates measurement of effects of wetland loss and degradation, characthe physical depreciation of ecosystems, which terizing wetland boundaries and identifying restoration or mitigation opportunities (Bedford
is essential if we are to account for how stocks
1996 and 1999; Gwin et al. 1999; Mitsch andof such wealth change.
To illustrate why the landscape containing Gosselink 2000; NRC 1995; Simenstad et al.
an ecosystem might serve as the basic unit for 2006). It follows that the various goods and services provided by a wetland will also be tied to,measuring changes in this natural asset, it isand thus defined by, its landscape extent; that is,
helpful to discuss a specific example, such as
wetland ecosystems. These systems, which com- “wetland values depend on the hydrogeomorphic location in which they are found” (Mitschprise coastal wetlands, freshwater swamps andmarshes (including floodplains), and peatlands, and Gosselink 2000, p. 27).
If the hydrological services of wetlands areamount to 6–8 million km2 globally (Mitsch
related to their landscape extent, then characet al. 2009). The goods and services provided
by wetlands are uniquely related to hydrologi- terizing wetland ecosystems as natural assets
cal processes. For example, seasonal soil-water is straightforward. In other words, as there are
regimes, surface inundation, and maintenance “reciprocal interactions between spatial patternof water quality, critically determine wetland and ecological processes” (Turner 2005, p. 319),
it is the spatially heterogeneous area of a wetecosystem structure and function, and thus
influence the type ecosystem goods and ser- land landscape that is the fundamental to its
vices provided. Similarly, changes in water ability to provide various goods and services. It
follows that, if for each wetland ecosystem weregime will affect different wetland services
significantly, resulting in many possible trade- can define its corresponding landscape in terms
offs and synergies among these services within of a quantifiable “land unit,” which is defined as
different wetland scenarios and water regimes. “a tract of land that is ecologically homogeneousat the scale level concerned” (Zonneveld 1989,
The consequence is that the ecosystem servicesp.
68), then we have a representation of the wetprovided by wetlands are driven by hydrology,
and understanding how changes in hydrologi- land ecosystem as a natural asset in the form ofcal processes affect the delivery of these ser- this unit of land, or ecological landscape.
However, even with a well-defined ecologivices is critical to determining the impact onhuman welfare (Brauman et al. 2007; Bullock cal landscape one must be careful to account for
and Acreman 2003; Emerton and Boss 2008; heterogeneous units within such a landscapeand to avoid problems of double counting. For
Mitsch et al. 2009).
Because the structure and functions of many example, large-scale forested ecosystems canwetlands can be uniquely defined by hydrologi- also contain wetlands, freshwater channels andcal processes, it is possible to identify the spa- rivers. Similarly, qualitative features of the landtial unit, or natural landscape, that is distinct scape may significantly influence the ecologicalto each type of wetland. In particular, different production of benefits. For example, the timber
aspects of the hydrological system underlying benefits of a forested landscape may depend notwetlands and their services operate at different only on the overall size of the system but also
scales, for example surface inundation (flood- the spatial distribution of trees across the landscape in terms age, size and species as well asing), water quality, and biodiversity. Thus, as avariations in soil quality and nutrients (Mäler
wetland landscape varies in scale, due perhaps to
CHAPTER 8 Ecosystem services and wealth accounting

171

et al. 2008). The ability of vegetated coastal
landscapes to attenuate storm surges and protect against damages not only varies considerably at the seaward edge as opposed to further
inland but also is affected by coastal geomorphology, elevation and topography (Koch et al.
2009). Finally, in a “mixed” ecological landscape,then it may be difficult to determine how a particular ecosystem benefit arises from the landscape and to avoid problems of double counting.
For example, outdoor recreation values may beenhanced by the diverse ecological features ofa mixed landscape, including the presence of
wetlands, forests, and river channels. How toseparate out the specific contribution to thevalue of recreation provided by each ecologicalcomponent of the landscape may be problematic. Nor would it be correct to attribute the fullrecreational value to each of the wetland, forest
and river components of the landscape.

4.

Ecosystems and ecosystem services

There is much confusion over the relationship between ecosystems, their structure andfunctions, and the ecological services theygenerate that contribute to human welfare.
Understanding such a relationship is essential
in order to determine how the structure andfunctions of an ecosystem provide valuable
goods and services to humans.
An ecosystem has the characteristics of a“system,” in the sense that it includes an assemblage of organisms interacting with its associated physical environment in a specific place(O’Neill 2001; Pickett and Cadenasso 2002).
Thus, within its prescribed area or location, an
ecosystem comprises its abiotic (non-living)environment and the biotic (living) groupings ofplant and animal species, or communities. The
biotic and abiotic components, and the interactions between them, are often referred to as theecosystem structure.
Two important ecosystem functions are carried out in every ecosystem: biogeochemical
cycling; and flow of energy. Important processes
172

of biogeochemical cycling include primary production (photosynthesis), nutrient and water
cycling, and materials decomposition. The flow,
storage and transformation of materials andenergy through the system are also influenced
by processes that link organisms with eachother, such as the food web, which is made up
of interlocking food chains. These food chainsare often characterized by other importantfunctions, such as pollination, predation, andparasitism.
The structure and functions of an ecosystemprovide valuable goods and services to humans.
For example, some of the living organisms foundin an ecosystem might be harvested or hunted
for food, collected for raw materials, or simply
valued because they are aesthetically pleasing.
Some of the ecosystem functions, such as nutrient and water cycling, can also benefit humans
through purifying water, controlling floods,
recharging aquifers, reducing pollution, or simply by providing more pleasing environments forrecreation. These various benefits provided byan ecosystem via its structure and functions are
now referred to as ecosystem services. As summarized in Box 2, the structure and functionsof an ecosystem are not the same as its services.
Ecosystem structure and functions describe thecomponents of an ecosystem and its biophysical relationship regardless of whether humans
benefit from them. Only if they contribute tohuman well-being do these components andrelationships generate an “ecosystem service.”6

5.	Assessing the value of ecosystem
goods and services
The idea that ecosystems provide a rangeof “services” that have value to humans is an
important step in characterizing these systems
as “natural capital.” In order to view ecosystems as a special type of capital asset – a form
6 For more discussion, see Barbier (2011a and 2011b);
Bockstael et al. (2000); Boyd and Banzhof (2007); EPA(2009); and Polasky and Segerson (2009).

Inclusive Wealth Report

of “ecological wealth” – then just like any otherasset or investment in the economy, ecosystems must be capable of generating current andfuture flows of income or benefits. It follows
that, in principle, ecosystems can be valued justlike any other asset in an economy. Regardless ofwhether there exists a market for the goods andservices produced by ecosystems, their social
value must equal the discounted net present
value (NPV) of these flows. However, for economists, the term “benefit” has a specific meaning.
This section discusses how this concept of economic benefit should be applied to ecosystem
goods and services as a guide to their correct
economic valuation. In addition, the section
outlines the main approach that is required tointegrate the “ecological production” of ecosystem goods and services with “economic valuation” of these benefits.
As noted previously, the literature on ecological services implies that ecosystems areassets that produce a flow of beneficial goods
and services over time. For example, a common
practice in this literature is to adopt the broad
definition of the MA (2005) that “ecosystem services are the benefits people obtain from ecosystems.” However, according to Mendelsohn andOlmstead (2009, p. 326), “(t)he economic benefit
provided by an environmental good or service isthe sum of what all members of society would
be willing to pay for it.” Consequently, some
economists argue that it is misleading to characterize all ecosystem services as “benefits.” As
explained by Boyd and Banzhaf (2007, p. 619), “asend-products of nature, final ecosystem services
are not benefits nor are they necessarily the final
product consumed. For example, recreation isoften called an ecosystem service. It is more
appropriately considered a benefit produced
using both ecological services and conventional
goods and services.” To illustrate this point, they
consider recreational angling. It requires certain ecosystem services, such as “surface waters
and fish populations” but also “other goods andservices including tackle, boats, time allocation,
and access” (Boyd and Banzhaf 2007, p. 619).
But other economists still prefer the broader

perspective of the MA (2005), which equatesecosystem services with benefits. For example,
Polasky and Segerson (2009, p. 412) state: “Weadopt a broad definition of the term ecosystemservices that includes both intermediate andfinal services,” which they justify by explainingthat “supporting services, in economic terms,
are akin to the infrastructure that provides thenecessary conditions under which inputs canbe usefully combined to provide intermediate
and final goods and services of value to society.”
Thus, unlike Boyd and Banzhaf (2007), Polasky
and Segerson (2009) consider recreation to bean ecosystem service.
Economists do agree that, in order to determine society’s willingness to pay for the benefits
provided by ecosystem goods and services, one
needs to measure and account for their various
impacts on human welfare. Or, as Bockstael
et al. (2000, p. 1385) state: “In economics, valuation concepts relate to human welfare. So
the economic value of an ecosystem function
or service relates only to the contribution it
makes to human welfare, where human welfare
is measured in terms of each individual’s own
assessment of his or her well-being.” The key isdetermining how changes in ecosystem goods
and services affect an individual’s well-being,
and then determining how much the individualis either willing to pay for changes that havea positive welfare impact or, conversely, howmuch the individual is willing to accept as compensation to avoid a negative effect.
The starting point in identifying ecosystemservices and their values is the consensus economic view outlined above. As long as nature
makes a contribution to human welfare, either
entirely on its own or through joint use withother human inputs, then we can designate thiscontribution as an “ecosystem service.” In otherwords. as stated in Box 2, “ecosystem services
are the direct or indirect contributions that ecosystems make to the well-being of human populations.” Although it is acceptable to use “theterm ecosystem service to refer broadly to bothintermediate and final end services,” “in specificvaluation contexts…it is important to identify

CHAPTER 8 Ecosystem services and wealth accounting

173whether the service being valued is an intermediate or a final service” (EPA 2009, pp. 12-3).
Following this approach, for example, recreation can be considered the product of an ecosystem service. But, as pointed out by Boyd andBanzhaf (2007, p.619), the ecosystem provides
only an “intermediate service” (along with “conventional goods and services”) in the production of the final benefit of recreation and tourism. In estimating the value of this intermediate
ecosystem service in producing recreational
benefits, it is therefore important to assess only
the effects of changes in the ecosystem on recreation, and not the additional influence of any
human inputs. The same approach should betaken for those “final” ecosystem services, suchas coastal protection, erosion control, nutrient
cycling, water purification, and carbon sequestration, which may benefit human well-being
with or without any additional human-provided
goods and services. Valuation should show howchanges in these services affect human welfare,after controlling for the influence of any additional human-provided goods and services.
Although valuing ecosystem goods and services seems straightforward, in practice there
are a number of challenges to overcome. Thesedifficulties are key to understanding why there
are still a large number of ecosystem goods andservices that have yet to be valued or have very
unreliable valuation estimates.
The most significant problem is that very few
are marketed. Some of the products provided
by ecosystems, such as raw materials, food, andfish harvests, are bought and sold in markets.
Given that the price and quantities of thesemarketed products are easy to observe, there
are numerous value estimates of the contribution of the environmental input to this production. However, this valuation can be more complicated than it appears. Market conditions andregulatory policies for the commodity bought
and sold will influence the values imputed
to the environment input. For example, one
important service of many estuarine and coastal
ecosystems is that they serve as coastal breeding and nursery habitat for offshore fisheries. As
174

many fisheries are exploited commercially, theinability to control fishing access and the presence of production subsidies and other market
distortions can impact harvests, the price offish sold, and ultimately, the estimated valueof coastal habitats in supporting these fisheries(Barbier et al. 2002; Barbier 2007; Freeman
1991; Smith 2007).
However, the majority of ecosystem goods
and services are not marketed. These include
many services arising from ecosystem processes
and functions that benefit human beings largely
without any additional input from them, suchas coastal protection, nutrient cycling, erosion
control, water purification, and carbon sequestration. In recent years, substantial progresshas been made by economists working withecologists and other natural scientists in applying environmental valuation methodologies toassess the welfare contribution of these services.
The various non-market valuation methods
employed for ecosystem services are essentiallythe standard techniques that are available toeconomists.7 Later in this chapter, we discussthese issues further. Nevertheless, what makes
applying these methods to estimate the valueof a non-marketed ecosystem service especiallydifficult is that it requires three important andinterrelated, steps (Barbier 1994, 2011a, and2011b; EPA 2009; Freeman 2003; NRC 2005;
Polasky and Segerson 2009).
The first step involves determining how
best to characterize the change in ecosystem
structure, functions and processes that gives
rise to the change in the ecosystem service. For
example, the change could be in the spatial
area or quality of a particular type of ecosystem,
such as a mangrove forest, marsh vegetation orwatershed extent. It could also be a change in a
7 For example, Barbier (2007, 2011a, and 2011b);
Bateman et al. (2011); EPA (2009); Freeman (2003);
Hanley and Barbier (2009); Mendelsohn and Olmstead(2009); NRC (2005); and and Pagiola et al. (2004) discuss how these standard valuation methods are best
applied to ecosystem services, emphasizing in particular both the advantages and the shortcomings ofthe different methods and their application.

Inclusive Wealth Reportkey population, such as fish or main predator.
Alternatively, the change could be due to variation in the flow of water, energy, or nutrients
through the system, such as the variability intidal surges due to coastal storm events or the
influx of organic waste from pollution upstream
from estuarine and coastal ecosystems.
The second step requires tracing how thechanges in ecosystem structure, functions andprocesses influence the quantities and qualities
of ecosystem service flows to people. Underlying
each ecosystem service is a range of important energy flow, biogeochemical, and biotic
processes and functions. For example, water
purification by seagrass beds is linked to theecological processes of nutrient uptake and suspended particle deposition (Koch et al. 2006;
Rybicki 1997). However, the key ecological process and functions that generate an ecosystemservice are in turn controlled by certain abiotic
and biotic components that are unique to eachecosystem’s structure. The various controllingcomponents that may affect nutrient uptake
and particle deposition by seagrass ecosystems
include seagrass species and density, nutrientload, water residence time, hydrodynamic conditions, and the availability of light. Only whenthese first two steps are completed is it possible to conduct the final step, which involves
using existing economic valuation method toassess the impact on human well-being that
results from the change in ecosystem goods andservices.
Figure 1 provides a visual summary of the key
elements of this three-step approach. Humandrivers of ecosystem change affect important
ecosystem processes and functions and theircontrolling components. Assessing this change
is crucial yet difficult. However, as NRC (2005,
pp. 2-3) points out, “making the translation fromecosystem structure and function to ecosystem
goods and services (i.e., the ecological production) is even more difficult” and “probably thegreatest challenge for successful valuation of
ecosystem services is to integrate studies of theecological production function with studies ofthe economic valuation function.” Similarly,

Figure 1

Key interrelated steps in valuing ecosystem goods andservices

Ecosystem structureand functions

Human drivers of
ecosystem change

Ecologicalproduction
function

Ecosystem
goods and services

ValuesEconomic valuation

Source: Adapted from NRC (2005, Figure 1-3)

Polasky and Segerson (2009, p. 422) maintainthat “among the more practical difficulties thatarise in either predicting changes in service
flows or estimating the associated value of ecosystem services” include the “lack of multiproduct, ecological production functions to quantitatively map ecosystem structure and function
to a flow of services that can then be valued.”

6. Valuing non-market ecosystem
goods and services
One of the fundamental challenges is that many
important ecosystem goods and services are
non-marketed. These include many important
services arising from ecosystem processes andfunctions, such as coastal protection, nutrient cycling, erosion control, water purification,and carbon sequestration. In recent years substantial progress has been made by economists
working with ecologists and other naturalscientists on this “fundamental challenge” toimprove the application of environmental valuation methodologies to non-market ecosystemservices. Nevertheless, a number of important
challenges arise in applying these methods,
which are reviewed in this section.

CHAPTER 8 Ecosystem services and wealth accounting

175

Ecosystem structureand functions
Human drivers of
ecosystem change
Ecosystem
goods and services

ValuesUse values

Non-use values
e.g. existence, bequest

Consumptive use

Non-consumptive use

e.g. harvesting, water supply,
genetic material

Indirect

Directe.g. nutrient retention ande.g. recreation, transporta-

recycling, flood control,tion, scientific and educational opportunities

erosion control, storm
protection, habitat support,
carbon sequestration

Figure 2

Economic valuation of ecosystem goods
and services
Source: Adapted from NRC (2005, Figure 7-1)

In the previous section, we discussed thethree-step approach that is required to integrate the “ecological production” of ecosystem
goods and services with “economic valuation”
of these benefits, which was summarized visually by Figure 1. In recent years, substantial
progress has been made by economists working
with ecologists and other natural scientists on
this “fundamental challenge” to improve theapplication of environmental valuation methodologies to non-market ecosystem services.
Nevertheless, a number of important challenges arise in applying these methods. To help
our subsequent discussion of valuation issues, it
is useful to look at a more detailed version of176

Figure 1 that emphasizes the economic valuation component of the Figure 2.
As indicated in Figure 2, there are a numberof different ways in which humans benefit from,or value, ecosystem goods and services. The first
distinction is between the use values as opposed
to non-use values arising from these goods andservices. Typically, use values involve somehuman “interaction” with the environment
whereas non-use values do not, as they represent an individual valuing the pure “existence”
of a natural habitat or ecosystem or wanting
to “bequest it to future generations.” Direct
use values refer to both consumptive and nonconsumptive uses that involve some form of
direct physical interaction with environmental
goods and services, such as recreational activities, resource harvesting, drinking clean water,
breathing unpolluted air, and so forth. Indirect
use values refer to those ecosystem services
whose values can only be measured indirectly,
since they are derived from supporting and protecting activities that have directly measurable
values. For example, for wetlands, the indirect
use values associated with ecosystems services
include coastal protection, erosion control,
flood protection, water purification, carbon
sequestration, maintenance of temperatureand precipitation, and habitat support for fishing, hunting, and foraging activities outside thewetlands (Barbier 2007).8
Table 1 indicates the various non-market
methods that can be used for valuing ecosystem
goods and services. As shown in this table, themethods employed are essentially the standard
non-market valuation techniques that are available to economists. However, the application of
non-market valuation to ecosystem goods andservices is not without difficulties. Here, we
simply summarize some of the key issues.
8 Another component of value, option value, is commonly referred to as a non-use value in the literature.
However, option value arises from the difference
between valuation under conditions of certainty anduncertainty, and is a numerical calculation, not a value
held by people per se. See NRC (2005, ch. 6) for further discussion.

Inclusive Wealth ReportFirst, the application of some of the valua- over and above the value of mangroves’ marketable products” (Naylor and Drew 1998, p. 488).
tion methods listed in Table 1 is often limited to
specific types of ecological goods and services. Similarly, choice modeling has the potential to
For example, the travel cost method is used elicit the relative values that individuals placeprincipally for those environmental values that on different ecosystem services. A study of wetland restoration in southern Sweden revealed
enhance individuals’ enjoyment of recreationand tourism, averting behavior models are best through choice experiments that individuals’
applied to the health effects arising from envi- willingness to pay for the restoration increased
if the result enhanced overall biodiversity butronmental pollution. Similarly, hedonic wage
and property models are used primarily for decreased if the restored wetlands were usedmainly for the introduction of Swedish crayfish
assessing work-related environmental hazards
and environmental impacts on property values, for recreational fishing (Carlsson et al. 2003).
However, as emphasized by NRC (2005), to
respectively.
In contrast, stated preference methods, implement a stated-preference study two key
conditions are necessary:
which include contingent valuation methods
and choice modeling, have thepotential to be used widely Table 1
in valuing ecosystem goods Various non-market valuation methods applied to ecosystem services
and services. These valuationTypes
methods share the common
Valuationof value
Common types ofapproach of surveying individ- methoda
estimated applications
Ecosystem services valued
uals who benefit from an ecoMaintenance of beneficial
logical service or range of ser- Travel costDirect use Recreation
species, productive ecosystems and biodiversity
vices, in the hope that analysis
Environmental impacts on
Pollution control andof these responses will provide Averting
Direct use
behavior
human healthdetoxificationan accurate measure of theEnvironmental impacts on res-Storm protection; flood
individuals’ willingness to pay
Direct andidential property and human mitigation; maintenance of air
Hedonic priceindirectuse
for the service or services. In
qualitymorbidity and mortality
addition, stated preference
Maintenance of beneficial
methods can go beyond estiCommercial and recreational species; maintenance ofarable land and agricultural
fishing;mating the value to individuagricultural systems; control productivity; prevention of
Production
als of single and even multiple
Indirect use of invasive species; watershed damage from erosion and siltfunction
ation; groundwater recharge;
protection; damage costs
benefits of ecosystems and indrainage and natural irrigaavoided
some cases elicit non-use valtion; storm protection; flood
mitigation
ues that individuals attach toensuring that a preserved andDrainage and natural irrigaReplacement
Damage costs avoided; freshIndirect use
tion; storm protection; flood
well-functioning system will costwater supply
mitigation
be around for future generaRecreation; environmental
tions to enjoy. For example, a
impacts on human health andstudy of mangrove-depen- Stated
Use andresidential property; damage
All of the above
preference
non-usecosts avoided; existence anddent coastal communities
bequest values of preserving
in Micronesia demonstrated
ecosystems
through the use of contingent
valuation techniques that the Notes: ASee Barbier (2007); Bateman et al. (2011); EPA (2009); Freeman (2003); Hanley & Barbier (2009);
communities “place some Mendelsohn & Olmstead (2009); NRC (2005); and Pagiola et al. (2004) for more discussion of these varivalue on the existence and eco- ous non-market valuation methods and their application to valuing ecosystem goods and services.
system functions of mangroves Source: Adapted from NRC (2005), Table 4-2.
CHAPTER 8 Ecosystem services and wealth accounting

177

(1) the information must be available to any factor input. If changes in the structure andfunctions of ecosystems affect the marketed
describe the change in an ecosystem in termsof the goods and services that people care about, production activities of an economy, then thein order to place a value on those goods and ser- effects of these changes will be transmitted toindividuals through the price system via changes
vices; and(2) the ecosystem change must be explained in the costs and prices of final good and services.
in the survey instrument in a manner that This means that any resulting “improvementsin the resource base or environmental qualpeople will understand while not rejecting theity” as a result of enhanced ecosystem services,valuation scenario.
For many of the specific ecosystem goods “lower costs and prices and increase the quantiand services listed in Table 1, one or both of ties of marketed goods, leading to increases inthese conditions may not hold. For instance, it consumers’ and perhaps producers’ surpluses”
has proven very difficult to describe accurately (Freeman 2003, p. 259).
An adaptation of the PF methodology isthrough the hypothetical scenarios requiredby stated-preference surveys how changes in required in the case where ecological regulatory
ecosystem processes and components affect and habitat functions have a protective value,
through various ecological services such as
ecosystem regulatory and habitat functions
storm protection, flood mitigation, prevention
and thus the specific benefits arising fromof erosion and siltation, pollution control, andthese functions that individuals value. If there
maintenanceof beneficial species (Barbier 2007;
is considerable scientific uncertainty surrounding these linkages, then not only is it difficult to McConnell and Bockstael 2005). In such cases,
the environment may be thought of producing
construct such hypothetical scenarios, but also
any responses elicited from individuals from a non-marketed service, such as “protection” ofstated-preference surveys are likely to yield economic activity, property, and even humaninaccurate measures of their willingness to pay lives, which benefits individuals through limitfor ecological services (Bateman et al. 2009). ing damages. Applying PF approaches requires
Valuation workshop methods may, however, modelling the “production” of this protection
help in terms of conveying information about service and estimating its value as an environmental input in terms of the expected damages
complex ecological goods, and investigating theeffects on people’s values of scientific uncer- avoided by individuals. However, PF methods
tainty about linkages within the system (see, for have their own measurement issues and limitations when they are employed to value ecosysexample, Christie et al. 2006).
In contrast to stated preference methods, tem goods and services.
For instance, applying the PF method raises
the advantage of production function (PF)approaches is that they depend on only the first questions about how changes in the ecologicalcondition, and not both conditions, holding service should be measured, whether market(see Barbier 1994 and 2007; McConnell and distortions in the final goods market are signifiBockstael 2005). That is, for those ecological cant, and whether current changes in ecologicalservices may affect future productivity throughfunctions where there is sufficient scientificknowledge of how these functions link to spe- biological “stock effects.” A common approachcific ecological services that support or protect in the literature is to assume that an estimate of
ecosystem area may be included in the “produceconomic activities, then it may be possible
to employ the PF approach to value these ser- tion function” of marketed output as a proxy forvices. The basic modeling approach underlying the ecological service input. For example, thisPF methods – also called “valuing the environ- is the standard approach adopted in coastal
habitat-fishery PF models, as allowing wetland
ment as input” – is similar to determining theadditional value of a change in the supply of area to be a determinant of fish catch is thought
178

Inclusive Wealth ReportBox 1

Adjusting net domestic product (NDP) for the contributions of ecological capital
The formal model in the Appendix derives the fol-terms) in natural resource stocks. In the case of non-lowing expression for net domestic product (NDP),

renewable resources, such as fossil fuels and min-which illustrates the importance of measuring

erals, G(S) = 0 and so –v KAFRR measures the deduc-explicitly the economic contributions of naturaltion from NDP of resource depletion. For renewable

capital, and especially that of ecological capital.

resources, such as forests and fisheries, NDP must
include any depreciation in natural resource stocks

Equation 1

NDP = vK[Y–ωK]+vK

h(E)

h'
D
N
[G(S)–R]+UNN+(v –v )cif G(S)<R. The expression UNN(t)+[ v D(t)–v N(t)]c(t)includes both the benefits to current well-being–E + v K AFR

provided by ecosystems, UNN, and any capital revaluation that occurs as ecosystems are converted byland use change for development, (v D–v N)c, whereK

In the above expression v (t)[Y(t)–ωK(t)] isv D(t) and v N(t) are the capitalized values, or prices,conventionally defined net domestic product (NDP),of development and ecosystem land, respectively.

that is the gross domestic product of the economy,

As ecosystems are converted by land use change

Y, less any depreciation (in value terms) of previously

for development, (v D–v N)c is the capital apprecia-

accumulated reproducible capital, ωK. This is NDPtion (depreciation) in land that occurs if v D > v N (v D <as currently measured in most national accounts ofv N) . In other words, we should also adjust the NDP

economies, although of course it is usually valuedof the economy to include two contributions due toat market prices rather than in terms of the shadow

ecological capital:

price of reproducible capital, v . However, if NDP•

K

economy’s wealth, it must include any appreciation

the value of the direct benefits provided by thecurrent stock of ecosystems, UNN; andis to serve as a true measure of the changes in an•any capital revaluation as a result of conversion

or depreciation to human and natural capital as well.

of ecosystems to other land uses, (v D–v N)c, with

For instance, vK(t)(h(E(t))/h'–E(t)) is the net appreci-

the price of changes in ecological capital, v N(t),ation (in value terms) in human capital, and vK(t)A(t)reflecting the present value of the future direct

FR[G(S(t))–R(t)] represents the net changes (in value

and indirect benefits of ecosystems.

by economists and ecologists to proxy someelement of the productivity contribution ofthis important habitat function (Barbier 2000,
2007; Freeman 2003, ch. 9; McConnell andBockstael 2005). In addition, as pointed out by
Freeman (1991), market conditions and regulatory policies for the marketed output will influence the values imputed to the environmental
input. For instance, in the previous example ofcoastal wetlands supporting an offshore fishery, the fishery may be subject to open accessconditions. Under these conditions, profits
in the fishery would be dissipated, and pricewould be equated to average and not marginal

costs. As a consequence, producer values are
zero and only consumer values determine thevalue of increased wetland area. Finally, afurther measurement issue arises in the casewhere the ecological service supports a natural
resource system, such as a fishery, forestry, ora wildlife population, which is then harvested
or exploited through economic activity. In suchcases, the key issue is whether the effects on thenatural resource stock or biological populationof changes in the ecological service are sufficiently large that these stock effects need to bemodelled explicitly. In the production function
valuation literature, approaches that ignore

CHAPTER 8 Ecosystem services and wealth accounting

179

stock effects are referred to as “static models”
of environmental change on a natural resource
production system, whereas approaches thattake into account the intertemporal stock
effects of the environmental change are referred
to as “dynamic models” (Barbier 2000, 2007;
Freeman 2003, ch. 9).
Finally, measurement issues, data availability
and other limitations can prevent the application of standard non-market valuation methods
to many ecosystem services. In circumstanceswhere an ecological service is unique to a specific ecosystem and is difficult to value, theneconomists have sometimes resorted to using
the cost of replacing the service or treating thedamages arising from the loss of the service asa valuation approach. However, economists
consider that the replacement cost approachshould be used with caution (Barbier 1994 and2007; Ellis and Fisher 1987; Freeman 2003;
McConnell and Bockstael 2005; Shabman
and Batie 1978). For example, a number ofstudies that have attempted to value the storm
prevention and flood mitigation services of
the “natural” storm barrier function of mangrove and other coastal wetland systems have
employed the replacement cost method by simply estimating the costs of replacing mangroves
by constructing physical barriers to perform thesame services (Chong 2005). Shabman and Batie(1978) suggested that this method can provide
a reliable valuation estimation for an ecological service, but only if the following conditions
are met: (1) the alternative considered provides
the same services; (2) the alternative should be
the least-cost alternative; and (3) there should
be substantial evidence that the service would
be demanded by society if it were provided bythat least-cost alternative. Unfortunately, very
few replacement cost studies meet all three
conditions.
However, one study that met these criteria for valuing an ecosystem service was theanalysis of the policy choice of providing clean
drinking water by the Catskills Mountains for
New York City (Chichilinsky and Heal 1998;
NRC 2005). Rather than value all the services of180

the Catskills watershed ecosystems; instead, it
was sufficient simply to demonstrate that protecting and restoring the ecological integrity of
the Catskills was less costly than replacing thisecosystem service with a human-constructedwater filtration system. The total costs of building and operating the filtration system were in
the range of US$6–8 billion, whereas it would
cost New York City US$1–1.5 billion to protect
and restore the natural ecosystem processes in
the watershed, thus preserving the clean drinking water service provided by the Catskills. A
second case study that also met the above criteria estimates the value of using wetlands forabatement of agricultural nitrogen load on theBaltic Sea coast of Sweden (Byström 2000). In
this study, the replacement value of wetlands
was defined and estimated as the difference
between two cost-effective reductions of agricultural nitrogen pollution: one that uses wetlands for nitrogen abatement, and one that doesnot. The study showed that the use of wetlands
as nitrogen sinks can reduce by 30 percent the
total costs of abating nitrogen pollution fromagriculture in Sweden.

7. Correcting wealth accounts for ecological capital
Overcoming measurement issues and challenges to determine the value of non-market
ecosystem goods and services is an important,
but there are additional considerations in using
these values to correct wealth accounts for
ecological capital. This section focuses on two
important issues: double counting; and accounting for special properties of ecosystems, such as
ecological stability, resilience, and collapse.
Recall that, as Box 1 indicates, the net
domestic product (NDP) of the economy should
be adjusted for the value of the direct benefits
provided by the current stock of ecosystem. But
NDP should not be adjusted for any indirect benefits of this current stock through its support orprotection of production in the economy. The
reason for the latter omission is that it may
Inclusive Wealth ReportBox 2The value of ecosystem resilience in the Goulburn-Broken Catchment of southeast Australia
Using the inclusive wealth framework of Arrow et al.

the system will shift from the non-saline to saline(2003), Mäler (2008) shows that it is possible to add

regime. To demonstrate the impact of resilience ona “resilience stock” to the measure of an economy’s

the inclusive wealth of the GBC, Walker et al. assume

wealth. Resilience is interpreted as the probability ofthat all other economic assets are constant andthe system transitioning to another state (regime).

only the stock of resilience changes. Between 1991

That is, the closer to the threshold, the lower theand 2001, they calculate that the resilience stock

stock of resilience, and the higher is the probability

increased by 0.5 m due to a water table fall from 3,0that the system will flip to the alternative regime. The

to 3.5 m. They estimate the value of this change inreal value, or shadow price, of the resilience stock isresilience under two different climate regimes: nor-the expected change in future social welfare frommal versus drier rainfall and evaporation conditions.

a marginal change in resilience today. This value

The results are depicted in the table below. Underchanges as the likelihood of crossing the thresholdnormal climate conditions, the 0.5 m change in eco-

into the alternative regime increases.

system resilience is valued at about $23 million, orWalker et al. (2010) apply this approach to thearound 7% of the total wealth of the GBC in 1991.

Goulburn-Broken Catchment (GBC) in Southeast

Under drier climatic conditions, resilience is worth

Australia. The GBC includes 300,000 ha in irriga-$28 million, or 8.4% of total wealth.

tion, of which 80% is for dairy pasture. However,
the removal of native vegetation for agriculture has
led to rising water tables and increased soil salinity. Once the water table rises above 2 meters (m),however, pasture land is radically changed, and theagro-ecological system shifts to a different regime
dominated by degraded and salinized soil. Thus, theresilience of the GBC system is measured by the
distance from the water table to the 2 m threshold,Climatescenario

Change in wealth from 1991 Share of
to 2001 form 0.5 m change in 1991 incluthe resilience stock
sive wealth

Normalconditions$22,852, 650

7.0%

Dry
conditions$28,558,360

8.4%

Source: Walker et al. (2010, Table 2).

and this indicator determines the probability thatcreate problems of double counting in thewealth accounts of an economy.
As discussed in the previous section andoutlined in Table 1, the production function
method is an important non-market valuation
method of measuring the economic contribution of many ecosystem goods and services that
affect human welfare indirectly through theirsupport or protection of production activities,
property, or human lives. In other words, ecosystem services that arise from the regulatory
functions of ecosystems, such as waste management, habitat support, storm protection, flood
mitigation, and groundwater recharge, often

serve as intermediate inputs in economic production activities, which are in turn often marketed. Similarly, goods or products from ecosystems, such as harvested raw materials, watersupplies, food, fiber, and fuel, may themselves bemarketed, or in turn are processed by industries
into marketed products. But if these goods andservices produced from the current stock of ecosystems serve as intermediate inputs into marketed production, then conventionally defined
NDP will most likely already reflect their current
contribution. To add to NDP the marginal value
contribution to economic production of ecosystem goods and services that are intermediate

CHAPTER 8 Ecosystem services and wealth accounting

181

Figure 3

Estimated mangrove area, Thailand, 1961–2009
Sources: FAO (2007b) and Spalding et al. (2010).
400,000

350,000

300,000

250,000

200,000

150,000

100,000

182

2010

2005

2000

1995

1990

1985

1980

1975

1970

1965

1960

inputs would result in double counting (Mäler
1991; Mäler et al. 2008; Vincent 2012).
For example, if a coastal marsh or mangrove
serves as a nursery or breeding habitat for an
off-shore commercial fishery, then this habitat
will have an influence on current harvested
and marketed output of the fishery. However,
the harvested fish will already be included inconventional NDP of an economy, as it is a marketed product. Similarly, if the wetlands also
protect coastal property from storm damages,
the value of the latter assets already accounts
for the storm protection value of the wetlands.
In addition, if the wetlands themselves are asource of currently harvested food, fiber, andraw materials, which are in turn sold commercially, then the NDP will already include thesemarketed products. In contrast, if any harvested
wetland products are not marketed but support
the subsistence needs of harvesting households,
then the value of these ecological goods will
not appear in conventionally measured NDP.
Because they are consumed and not marketed,these products are essentially direct benefits
to households. Finally, coastal wetlands may
generate many other non-marketed ecosystemservices that also directly influence welfare, such as filtering water pollution that
affects human health, enhancing enjoyment of coastal areas and recreation, andproviding cultural benefits. Again, thesecurrent values of the wetlands are unlikely
to appear in conventional NDP.
To summarize, to avoid double counting, the NDP of an economy should not
be adjusted by including the value of any
goods and services provided currently byecosystems, if they serve as intermediate
inputs in the production of marketed final
goods and services. However, if ecosystem
goods and services affect current production activities that are not marketed, suchas raw materials, food, fiber, and water thatare consumed directly by households, thenthe value of these ecological contributions
should be assessed and added to NDP.
However, as indicated in Box 1, thisparticular double counting problem does notarise when adjusting NDP to account for any
capital revaluation in the economy that occurs
when, say, ecosystems are converted to otherland uses. In this case, the capitalized value of
converted ecosystems must reflect the present
value of all foregone future benefits of theseecosystems, whether they influence welfare
directly or indirectly through production ofmarketed final goods and services.
Landscape losses and degradation of ecosystem processes and functions can also leadto unpredictable and sudden increases in therisk of ecological collapse, due to the presenceof ecological thresholds and feedback effects.
That is, large shocks or sustained disturbances
to ecosystems lead to further interactions thatcan contravene ecological thresholds, causing
the systems to “flip” irreversibly from one functioning state to another. Thus the resilience orrobustness of an ecosystem – its ability to absorb
large shocks or sustained disturbances and still
maintain internal integrity and functioning –may be an important attribute determining theextent to which landscape conversion and ecosystem degradation affects the risk of ecological
Inclusive Wealth ReportBox 3

Valuation estimates used in accounting for mangrove wealth, Thailand
As indicated in Box 1, the net domestic product

World Bank (2011) values unit carbon dioxide dam-

(NDP) of an economy must be adjusted for the direct

age at $20 per ton of carbon (1995 US$), which

benefits to current well-being provided by ecosys-

yields an annual value (in 1995 US$) of $42 per hatems, UNN, and any capital revaluation that occurs

for carbon sequestration. Over a 20-year time hori-

as ecosystems are converted by land use change

zon and a 10% discount rate this yields a net pres-for development, (vD–vN)c . Mangrove ecosystems inent value (NPV) of $413 per ha. These values are

Thailand provide four essential goods and services.

converted to 2000 US$ using the GDP deflator for

These are the role of mangroves as natural “barriers”

Thailand (World Bank, 2011). As a result, mangrovesto periodic damaging coastal storm events, their rolein Thailand have a constant 2000 US$ capitalized

as nursery and breeding habitats for offshore fisher-value, vN, of $21,443 per ha.

ies, their ability store carbon, and the exploitation

As the main activity responsible for mangroveof mangrove forests by coastal communities for aconversion in Thailand has been shrimp aquacul-

variety of wood and non-wood products. Estimatesture, the capitalized value of this activity is used forof the value of all four benefits exist for Thailand.

vD. The net present value (NPV) per ha for the com-

For example, the value of coastal protection

mercial net returns to shrimp farming over a 20-yearfrom storms is based on a marginal value per ha oftime horizon and 10% discount rate is based ondamages avoided (in 1996 US$) of $1,879; over a(Sathirathai & Barbier, 2001), which when updated

20-year time horizon and a 10% discount rate thisto 1996 US$, amounts to a value of $9,632 per ha.

yields a net present value (NPV) of $15,997 per ha

However, many of the inputs used in shrimp pond

(Barbier, 2007). The value of habitat-fishery link-

operations are subsidized, below border-equivalentages is based on a net value per ha (in 1996 US$,

prices, thus increasing artificially the private returns

assuming a price elasticity for fish of -0.5) of man-to shrimp farming. Without these subsidies, thegrove habitat of $249; over a 20-year time horizon

resulting economic net returns to shrimp farming

and a 10% discount rate this yields a NPV of $2,117

result in a NPV of $1,220 per ha. When converted toper ha (Barbier, 2003). The value of wood and non-2000 US$ using the GDP deflator for Thailand (World

wood products is based on net income per has from

Bank, 2011), the capitalized value of mangroves con-mangrove forests to local community (updated toverted to shrimp farms is $1,351 per ha. Because

1996 US$) of $101; over a 20-year time horizon andthe capitalized value, or “price,” of mangroves con-a 10% discount rate this yields a NPV of $864 per haverted to shrimp farming is less than the capitalized(Sathirathai & Barbier, 2001). Chmura et al. (2003)

value of mangroves, or (vN–vN) < 0, then the NDP ofestimate permanent carbon sequestration by global

Thailand should be adjusted for this resulting capitalmangroves of 2.1 metric tons per ha per year, anddepreciation in mangrove land.

collapse.9 Thus, one approach to accounting
for the resilience property of ecosystems is to

9 See, for example, Dasgupta and Mäler (2003);
Elmqvist et al. (2003); Folke et al. (2004); Levin (1999);
Levin and Lubchenco (2008); Perrings (1998); Scheffer
et al. (2001); and Walker et al. (2004).

CHAPTER 8 Ecosystem services and wealth accounting

measure directly the wealth effects of resilience(Mäler 2008; Walker et al. 2010).
Box 2 summarizes the effort by Walker etal. (2010) to value ecosystem resilience for the
Goulburn-Broken Catchment (GBC) in Southeast
Australia. The GBC is prime agricultural land,
most of which is used for dairy pasture. However,
the agro-ecosystem is threatened by increased
183soil salinity due to rising water tables fromremoval of native vegetation. At the 2 meter (m)water table threshold, the system is in dangerof flipping to a different regime dominated bydegraded and salinized pasture. The authors
estimate resilience as the distance from thecurrent water table to the 2 m threshold. Under
normal climate conditions, a 0.5 m change inecosystem resilience is valued at about US$23
million, or around 7 percent of the total wealthof the GBC in 1991. Under drier climatic conditions, resilience is worth US$28 million, or 8.4
percent of the total wealth of the GBC.
This example from Australia of valuing of
ecosystem resilience suggests that this economic contribution can be considerable. In suchhighly productive ecosystems supporting economic activity, regime shift can be catastrophic.
Or to put it differently, the value of avoiding
regime shift by maintaining or enhancing theresilience of ecosystems can be a sizable com-

Figure 4

GDP and ANDP per capita, Thailand, 1970-2009
Sources: FAO (2007b) and Spalding et al. (2010).
3000

2500

2000

1500

1000

500

0

8.	A case study: adjusted NDP andmangrove loss in Thailand
Although the previous sections discuss theimportant issues and challenges that arise
when attempting to value ecosystem services
and account for their contributions to wealth,significant progress has been made in recent
years. For some major ecosystems, we may bevery close to implementing the methodology ofadjusting NDP to reflect ecological values as wellas the depreciation or appreciation in these key
natural assets.
The purpose of this section is to provide
an example of wealth accounting with a casestudy from Thailand involving mangrove loss.
Mangroves are various kinds of trees and shrubsthat grow in saline coastal and estuarine habitats in the tropics and subtropics. The
case study illustrates the two adjustments to NDP due to ecological capital:
the value of the direct benefits provided
by the current stock of ecosystems; andany capital revaluation that occurs as aresult of ecosystem conversion to otherland uses. Estimating the wealth effectsof ecosystem resilience is beyond thescope of this case study.
Thailand is estimated to have lostaround a third of its mangroves since the1960s, mainly to shrimp farming expansion and other coastal development (FAO
2007a; Spalding et al. 2010). During thisperiod, real GDP per capita in Thailand
has increased five-fold (World Bank 2011).
A measure of the adjusted NDP, taking
into account human and natural capital
loss since 1970, is constructed. Based on
estimates of four mangrove ecosystembenefits – collected products, habitatfishery linkages, storm protection, andcarbon sequestration – the methodol2010

184

2005

Adjusted NDP per capita

2000

GDP per capita

1995

1990

1985

1980

1975

1970

Key

ponent of the total economic wealth generated
by these systems.

Inclusive Wealth ReportTable 2

Wealth accounting for mangrove capital, Thailand, 1970–2009
Average annual values per capita (constant 2000 US$)
Averageannualmangroveloss (ha)Stormprotection

Habitatfisherylinkage

Wood andnon-wood
products

CarbonTotal value of Mangrove
Net value ofsequestrationmangroves depreciation mangroves

1970–79

4,676

-

0.11

0.10

0.36

0.57

2.26

-1.69

1980–89

2,980

-

0.08

0.07

0.25

0.40

1.16

-0.76

1990–99

610

-

0.06

0.06

0.20

0.32

0.21

0.11

2000–09

97

-

0.05

0.05

0.18

0.28

0.03

0.25

Notes: As storm protection value is based on expected damages to economic property, it is assumed that this benefit is already accounted for in thecurrent market values of property. Current habitat-fishery linkages benefits are based only the imputed subsistence value, which based on a survey offour Thai coastal villages, is approximately 5.3 percent of total household income (Sarntisart and Sathirathai 2004, Tables 6.3 and 6.4). Current woodand non-wood product benefits are based only the imputed subsistence value, which based on a survey of four Thai coastal villages, is approximately
12.4 percent of total household income (Sarntisart and Sathirathai 2004, Tables 6.3 and 6.4).

ogy of adjusting NDP for the value of ecosystems
is also included as an illustration.
In 1961, Thailand was estimated to havearound 368,000 hectares (ha) of mangrovesin 1961 (see Figure 3). Mangrove deforestation
proceeded swiftly in the 1970s and 1980s, butsince 2000, the area of mangroves seems tohave stabilized around 240,000 to 250,000 ha.
The main cause of mangrove loss in Thailand
is attributed to conversion to shrimp aquaculture (Aksornkoae and Tokrisna 2004). The
main reason for the slowdown in mangrove loss
is that many of the suitable sites for establishing shrimp farms in the Gulf of Thailand havebeen deforested, whereas the mangrove areas
on the Andaman Sea (Indian Ocean) coast are
too remote and less suitable for shrimp farms(Barbier and Cox 2004).
Box 3 outlines the valuation estimates thatare used for accounting for the current benefitsof mangroves as well as their capitalized values
for Thailand over 1970 to 2009. The four principal ecosystem goods and services are the role ofmangroves as natural “barriers” to periodic damaging coastal storm events, their role as nurseryand breeding habitats for offshore fisheries,
their ability store carbon, and the exploitationof mangrove forests by coastal communities fora variety of wood and non-wood products. As
outlined in Box 3, these four benefits of mangroves in Thailand have a constant 2000 US$
capitalized value of US$21,443 per ha. As the main
activity responsible for mangrove conversion in
Thailand has been shrimp aquaculture, the capitalized value (in 2000 US$) of this alternative useof mangrove ecosystems is US$1,351 per ha. Note
that, because the capitalized value, or “price,”of mangroves converted to shrimp farming isless than the capitalized value of mangroves,
the NDP of Thailand should be adjusted for thisdepreciation in mangrove capital.
However, not all the current benefits ofmangroves impact welfare directly, but may do
so only through support or protection of economic activity and property. That is certainly thecase for storm protection benefits of mangroves,which are estimated through an expected damage approach that determines their value interms of protecting economic property (Barbier
2007). As this benefit is already accounted for in
the current market values of property, to avoid
double counting, the NDP of the Thai economy
should not be adjusted to include the benefit ofstorm protection provided by the current stock

CHAPTER 8 Ecosystem services and wealth accounting185

of mangroves. Similarly, a survey of four Thai
villages from two coastal provinces indicatesthat only 12.4 percent of the value of collectedwood and non-wood products from mangroves
and 5.3 percent of the value of coastal fishery
harvests can be attributed to subsistence production (Sarntisart and Sathirathai 2004).10
Thus, the NDP should be adjusted only for thesesubsistence contributions of these two benefitsof the mangroves in Thailand.
Using the data from Box 3, Table 2 depicts
the per capita wealth accounting estimatesfor Thailand’s mangroves from 1970 to 2009.
Average annual mangrove loss has fallen steadilyin every decade since the 1970s (see also Figure3). Nevertheless, because around a third of themangrove area has been deforested from 1970 to2009, whereas Thailand’s population has nearly

10 The four villages are Ban Sam Chong Tai and
Ban Bang Pat of Phang-nga Province, and Ban Gong
Khong and Ban Bkhlong Khut in Nakhon Si Thammarat
Province.

doubled over this period, the current per capita
benefits of mangroves has halved since the1970s, from US$0.57 to US$0.28 per person.11 In
the 1970s, when mangrove loss in Thailand wasat its highest, mangrove depreciation amounted
to US$2.26 per person, whereas by the 2000s, it
had fallen to only US$0.03 per capita. The result
is that the net value of mangroves per capita in
Thailand, which is the total value less mangrove
depreciation, was actually negative in the 1970s
and 1980s, averaging -US$1.69 and -US$0.76 perperson respectively. However, in the 1990s and2000s, the net value was slightly positive, averaging US$0.11 and US$0.22 respectively.
Table 3 depicts an approximate estimate ofadjusted net domestic product (ANDP) per capita
for real changes in reproducible, human andnatural capital for Thailand over 1970 to 2009.
ANDP is GDP less consumption of fixed capital
11 According to World Bank (2011), in 1970 Thailand’s
population was 36.9 million and grew steadily to 68.7
million in 2009.

Table 3

Wealth accounting, Thailand – 1970–2009
Average annual values per capita (constant 2000 US$)

Consumption of Natural resource
fixed capital
depletion

Education
expenditure

Net value ofmangroves

13

30

-1.7

130

19

46

-0.8

1,563

296

20

86

0.1

2,041

280

79

109

0.3

GDP

ANDP

1970–79

617

544

89

1980–89956

852

1990–99

1,793

2000–09

2,291

Notes: GDP = Gross Domestic Product
ANDP = Adjusted Net Domestic Product, or GDP less consumption of fixed capital and natural resource depletion, plus education expenditure and the net value of mangroves (estimated in Table 2).
Natural resource depletion is the sum of net forest depletion, energy depletion, and mineral depletion. Net forest depletion isunit resource rents times the excess of roundwood harvest over natural growth. Energy depletion is the ratio of the value ofthe stock of energy resources to the remaining reserve lifetime (capped at 25 years). It covers coal, crude oil, and natural gas.
Mineral depletion is the ratio of the value of the stock of mineral resources to the remaining reserve lifetime (capped at 25
years). It covers tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate.
Source: World Bank (2011), except for net value of mangroves, which is from Table 2.

186

Inclusive Wealth Reportand natural resource depletion, plus education
expenditure and net values of mangrove depletion. The latter estimate is based on the net
value of mangroves from Table 2. Since the1970s, both consumption of fixed capital andnatural resource depreciation have increased
significantly in Thailand. The value of expanding human capital, as proxied by education
expenditures, has also increased, and because of
the slowdown in mangrove loss, the net value of
this ecological capital has gone from a negative
to a positive contribution to NDP. Overall, thevalue of mangroves and expanding human capital has not kept pace with reproducible capitaldepreciation and natural resource depletionin Thailand. As a consequence, adjusted net
domestic product per capita in Thailand has
remained consistently below GDP per capita
since the 1970s. As shown in Figure 4, since1990 the gap between GDP and ANDP per capita
in Thailand has widened significantly.
To summarize, because many of the benefits
provided by the current stock of mangroves inThailand arise through supporting or protecting marketed production and property, thesebenefits should already be included in the GDP
estimates for Thailand. However, any adjusted
NDP measure does need to take into account thecurrent direct benefits provided by mangrovesin the form of carbon sequestration, habitat andbreeding ground services that support any fishery harvests consumed by coastal households
and mangrove products that also comprisesubsistence consumption. On the other hand,
all future mangrove benefits are lost as a resultof mangrove conversion, which has been substantial in Thailand since the 1970s. The substantial mangrove depreciation that occurred in
the 1970s and 1980s meant that the net valueof mangroves was actually negative in these
decades. Although mangrove deforestationand thus its capital depreciation has slowed
since, the net value of mangroves per capita, as
an indicator of its contribution to the wealthof Thailand, is still extremely low. Thus, theThailand mangrove case study not only provides
an illustration of the adjusted NDP methodology

for ecological capital but also illustrates how
significant loss of this capital can influence its
net value in wealth accounts.

9.

Conclusion

This chapter has explored the methodology andthe challenges of including ecosystem goods
and services in a wealth accounting framework.
Following the approach developed by Dasgupta(2009), which is elaborated further in the chapters by Dasgupta (2012) and Perrings (2012), it
is shown how this framework can be extended
to incorporate ecosystem and their valuable
goods and services. The approach developed
here requires, first, recognizing ecosystems as
a component of natural capital, or ecologicalcapital, and second, measuring these important
assets in terms of the land area, or ecologicallandscape, which defines their boundaries.
Such an approach clarifies how we should
value and include changes in ecological capitalin wealth accounting, which can be proxied by
the net domestic product (NDP) of an economy
provided that this indicator accounts for the
depreciation of all forms of capital – reproducible, human, and natural capital. There are
two main adjustments to NDP of the economy
that result, if ecological capital is also to beconsidered.
First, we should adjust NDP to include thevalue of the various goods and services provided
by the current stock of ecosystems that derives
from direct impacts on welfare. These direct
ecosystem benefits might include the value of
ecosystems in providing non-market recreational, educational, and scientific benefits, theirvalue in terms of natural heritage or bequests
to future generation or the value of ecosystems
in reducing harmful pollution and assimilating waste that affect human welfare and healthdirectly. In addition, ecological capital protects
or supports current economic activity andproperty. These indirect ecosystem benefits arebroad ranging, and include raw materials, food,and other harvested inputs used in production

CHAPTER 8 Ecosystem services and wealth accounting187activities, provision of freshwater, watershed
protection, coastal habitats for off-shore fisheries, flood control, storm protection, and managing climate. However unlike direct benefits
to current well-being, these indirect benefits
should not be included as additional values inany measure of an economy’s NDP, as they arelikely to already be reflected in the prices of final
marketed goods and services.
Second, conversion of ecological capital toother land uses requires a further adjustment to
GDP to reflect any capital revaluation as a resultof this land use change. As the resource allocation mechanism of the economy may not be
optimal or even efficient, ecosystem conversion
may be taking place even though the capitalized
value, or “price,” of developed land is actuallyless than the capitalized value of ecosystems.
In which case, GDP should be adjusted for the
depreciation in ecological capital that occurs as
it is converted to less valuable developed land.
The capitalized value of converted ecosystems
must reflect the present value of all foregone
future benefits of these ecosystems, whether
they influence welfare directly or indirectly
through production of marketed final goods
and services.
The main challenges of applying such an
approach is that there are still a large numberof non-makreted ecosystem goods and services
that have yet to be valued or have very unreliable valuation estimates. Measurement issues,
data availability, and other limitations can prevent the application of standard non-market
valuation methods to many ecosystem services.
Fortunately, some progress is being made, due
to the growing collaboration between economists, ecologists and other natural scientists indetermining how the ecological production of
key goods and services translate into economic
valuation of these benefits.
For some major ecosystems, we may be very
close to implementing the methodology advocated in this chapter of adjusting GDP to reflectecological values as well as the depreciation orappreciation in these key natural assets. Using
the example of mangroves in Thailand, this188

chapter illustrates how such an approach might
be applied. The case study is able to show how
valuation estimates from existing studies could
be used for accounting for the current direct
benefits of mangroves as well as their capitalized values for Thailand over 1970 to 2009. The
per capita value of mangroves net of depreciation in Thailand was actually negative in the
1970s and 1980s due to mangrove conversion todevelopment activities, and principally shrimp
aquaculture. The net value of the wealth contribution of mangroves per person was positive butvery small in the 1990s and 2000s, only US$0.11
and US$0.25 respectively. In comparison, in the
2000s, reproducible capital depreciation was
US$280 per person, natural resource depletionof energy, minerals, and forest was US$79 per
capita, and human capital increased by US$109
per person. Thus, the case study demonstrates
that accounting for the economic contributions and deprecations of mangrove capital isan important, albeit relatively small, component of the key capital adjustments that occurin Thailand’s economy.
But perhaps the more important lesson
to be learned from the example of adjusting
Thailand’s wealth accounts for mangrove current benefits and depreciation is that it illustrates that the challenges of including ecosystem services in a wealth accounting framework
can be overcome.

Inclusive Wealth ReportAppendix

Formal model of wealth accounting
and ecosystem services

Assume a closed economy with a constant population that is normalized to one.1 At time t, let
K(t) be a numerical index of the economy’s stockof reproducible capital assets, and H(t) be a
numerical index of the total quantity of humancapital, that is the level of health, education andskills per person. Reproducible capital depreciates at the constant rate ω > 0, and assume that
E(t) is investment in human capital (e.g., current
education, health, and training expenditures).
Denoting the real GDP of the economy at time
t as Y(t) and aggregate consumption of goods
and services as C(t), then net accumulation of
reproducible capital is
Equation 1

K̇ = Y(t)–C(t)–ωK(t)–E(t), K̇ = dK(t) dt
Following Hamilton and Clemens (1999),
letting represent the rate at which education,
health, and training investments are transformed into human capital, then the latteraccumulates according toEquation 2

Ḣ= h(E(t)), h’ > 0, Ḣ= dH(t) dt
Along with human and reproducible capital,
the aggregate stock of natural capital available
at time t is also important as the source of raw
material, land, and energy inputs to the economy, such as fossil fuels, minerals, metals, forest
resources, and arable land. If we represent thesenatural resource stocks as S(t), thenEquation 3

Ṡ = G(S(t))–R(t), Ṡ = dS(t) dt
where the function G represents the natural
growth rate for any renewable resources, andR(t) is the use of any natural resource inputs by
the economy.
But, in addition to S(t), natural capitalshould include those ecosystems that throughtheir natural functioning and habitats provide
important goods and services to the economy.
However, ecological capital is unlikely to be
intact, as many ecosystems continue to be converted to land for economic development andproduction. It follows that the aggregate stockof developed land, D(t), increases at the expenseof ecological capital N(t)Equation 4

Ḋ = c(t) = –Ṅ, Ḋ=dD(t) dt, Ṅ=dN(t) dt
where c(t)≥0 represents any ecosystem conversion to developed land at time t.
Following Dasgupta (2009), let A(t) be a
combined index of publicly known ideas andthe effectiveness of the economies institutions,which can be interpreted as total factor productivity in the economy at time t. Given equations(1)–(4), the economy’s real GDP, denoted as Y(t),can be stated as
Equation 5

Y(t) = A(t)F(K(t),H(t),R(t),D(t),N(t))
where F is a non-decreasing and twice differentiable function, and F = 0 if any of its arguments
are zero.2 Note that the production function of
the economy should include ecological capital,
N(t), given that many ecosystem services support and protection production activities.
Letting V(t) denote intergenerational wellbeing at time t, which takes the form
Equation 6

V(t) = ∫t U(C(τ),N(τ))e–б(τ-t)dτ∞where δ > 0 is the social rate of discount. Notethat intergenerational welfare depends not only
on aggregate consumption but also on the direct
benefits of ecosystems, which are represented

2
1

As shown by Arrow et al. (2003) and Dasgupta (2009), theAs Dasgupta (2009) points out, unlike a standard neo-classical production function, F is not necessarily concave. As

following model could accommodate population growth, but it isDasgupta (2009) points out, unlike a standard neo-classicalconceptually more difficult to do so.

production function, F is not necessarily concave.

CHAPTER 8 Ecosystem services and wealth accounting189

by the inclusion of N(t) in the function for
instantaneous well-being, or “utility,” U(t). It is
assumed that the latter function is twice differentiable, additively separable and concave withrespect to its two arguments.
As Dasgupta (2009) proves, regardless ofwhether the resource allocation mechanism of
the economy is optimal or even efficient, given(1)–(6), for any such mechanism it is possible todefine a set of shadow prices at time t for thevarious assets of the economy

Equation (11) depicts NDP as the sum ofinvestment in the aggregate capital stocks ofan economy plus the value of consumption andecosystem goods and services. Following anapproach analogous to Dasgupta (2009), NDP as
defined by (11) can also be used as an indicatorfor measuring whether intergenerational wellbeing in an economy is improving over time.
Differentiating (6) with respect to timeyields dV(t) dt = бV–U (C(t),N(t)). Using thelatter expression in (10), one obtains

Equation 7

Equation 12

vi(t) = дV(t) дi(t), i = K,H,S,N,D

dV(t)Given these shadow prices, the economy’s
aggregate, or inclusive, wealth W(t) and investment I(t) at time t are, respectively

dt

Equation 8

W(t) = vK(t)K(t)+vHH(t)+vSS(t)+vNN(t)+vDD(t)and
Equation 9

I(t) = vK(t)K̇+vHḢ+vSṠ+vNṄ+vDḊ
The current-value Hamiltonian that ensuresintergenerational well-being (6) is at a maximum for any given resource allocation mechanism of the economy is therefore
Equation 10

H(t) = U(C(t),N(t))+I(t) = δV(t)The current-value Hamiltonian as specified
in (10) is therefore an indicator of the returnon intergenerational well-being, regardless ofwhether the resource allocation mechanism of
the economy is efficient or optimal.3
By expressing the utility function U(t) as
U (C(t),N(t))=UCC(t)+UN N(t), equation (10) canbe used to define aggregate or inclusive NDP ofthe economy at time t in “utils”
Equation 11= I(t)

Condition (12) states that investment in theaggregate capital stock of an economy determines changes in intergenerational well-being
over time, and as a result, NDP as defined by (11)
is an exact measure of these welfare changes.
That is, (11) and (12) yield a condition akin to
Proposition 9 in Dasgupta (2009): dV(t) dt ≥0 if and only if NDP(t)≥U CC(t)+U NN(t). As longas NDP exceeds the value of consumption andecosystem goods and services, intergenerational welfare will not decline. Given that dV(t)dt≥0 also implies I(t)≥0, then it follows from(8) that sustainable economic development will
occur at time t if the aggregate wealth of theeconomy W(t) does not decline.
To understand the importance of measuring
explicitly the contributions of natural capital,and especially that of ecological capital, it isnecessary to decompose NDP as defined by (11).
Using the first-order conditions for maximizing
the current-value Hamiltonian (10) with respect
to C(t) and E(t), (11) can be rewritten (suppressing the time arguments) as
Equation 13

NDP = vK[C+K̇+

NDP(t) = UCC(t)+UNN(t)+I(t)= vK[Y+ωK]+ vK
3

H(t)=δV(t) can be found by integrating the current-value

h(E)
h’
h(E)
h’

]+UNN+vSṠ+vNṄ+vDḊ
–E + vKAFR[G(S)–R]+UNN+(vD–vN)c

Hamiltonian H(t)=U(C(t),N(t))+I(t). See Dasgupta (2009).

190

Inclusive Wealth ReportIn (13), the expression vK(t)[Y(t)+ωK(t)] is
ecological capital v N(t) and developed land v D(t),conventionally defined net domestic product respectively.
∞(NDP), that is the GDP of the economy less any
By definition, from (10), vN(t) = ∫t (∂H ∂N )∞depreciation (in value terms) of previously accu- (τ)e–б(τ-t)dτ and vD(t) = ∫t (∂H ∂D )(τ)e–б(τ-t)dτ. It
mulated reproducible capital. This is NDP as
follows thatcurrently measured in most national accounts
Equation 14
of economies, although of course it is usually∞vD(t)–vN(t)= ∫t e–б(τ-t) vK(τ)A(t)F D(τ)dτvalued at market prices rather than in terms of
the shadow price of reproducible capital. It is –∫t∞e–б(τ-t) [UN(τ)+v K(τ)A(τ)F N (τ)]dτ
clear from (13) that, if NDP is to serve as a truemeasure of the changes in an economy’s wealth,Thus, v D(t) is the present value of any addiit must include any appreciation or deprecia- tional production resulting from any increase intion to human and natural capital as well. For land for economic development land, whereas
instance, vK(t)(h(E(t)) h’–E(t)) is the net v N(t) is the present value of any additional ecoappreciation (in value terms) in human capital, system benefits due to increases in ecosystem
and vK(t)A(t)F R[G (S(t))–R(t)] represents the net land. That is, v D(t) and v N(t) are the capitalizedchanges (in value terms) in natural resource
values, or prices, of development and ecosystem
stocks.4 In the case of non-renewable resources, land, respectively. As ecosystems are converted
by land use change for development, (v D–v N)c is
such as fossil fuels and minerals, G(S) = 0 andso –v KAF RR measures the deduction from NDP the capital appreciation (depreciation) in landof resource depletion. For renewable resources, that occurs if v D > v N(v D < v N) . As land is a durasuch as forests and fisheries, NDP must include
ble and capital good, condition (13) indicatesany depreciation in natural resource stocks if that NDP must be adjusted for any such capital
G(S)<R. The expression U NN(t)+[v D(t)–vN(t)] revaluation.
To summarize, although conditions (13) andc(t) includes both the benefits to current wellbeing provided by ecosystems, U NN, and any (14) seem complicated, they help clarify how weshould value and include changes in ecologicalcapital revaluation that occurs as ecosystems
are converted by land use change for develop- capital in wealth accounting. First, we shouldment, (v D–v N)c.5 To interpret the latter term, it adjust the NDP of the economy to include twois helpful to explore further the shadow value of contributions due to ecological capital:• the value of the direct benefits provided by thecurrent stock of ecosystems, U NN, and
4 In (13), it is assumed that vS accounts for the marginal• any capital revaluation as a result of convercost of resource extraction or harvesting. For example, supsion of ecosystems to other land uses, (v D–pose that such costs can be represented by the functionv N)c, with the price of changes in ecologicalf(R), f R>0, which are in turn paid out of an economy’s grosscapital, v N(t), reflecting the present value
domestic product, Y. It follows from the first-order condition
for maximizing the current-value Hamiltonian (10) ∂H/∂R=0
of the future direct and indirect benefits ofthat v s=v K[AFR– f r], or equivalently, v KAFR=v s+v K f r
ecosystems.6
5

In (13), it is assumed that vD accounts for the marginal costsof converting ecosystems to land for development. For example, if such costs are represented by g(c), gc>0 and deducted

6from the economy’s gross domestic product, Y, then it follows

similar to those for environmental resource stocks derived by

These adjustments to NDP for ecological capital arefrom the first-order condition of maximizing (10) ∂H/∂c=0

Mäler (1991). It appears that, although ecosystems generate athat vD=vN+vKgc, or equivalently vD-vN=vKgc. However, as will be

wide variety of complex goods and services, the actual rules

discussed presently, as the resource allocation mechanism offor determining how the direct and indirect benefits of eco-

the economy may not be optimal or even efficient, ecosystem

logical capital should be accounted for in NDP are no different

conversion may not take place so that the difference between

than for any stock that generates both affects human welfare

the price of developed land and the capitalized value of eco-directly or indirectly via supporting or protecting economic

systems is just equal to marginal cost of conversion.

production.

CHAPTER 8 Ecosystem services and wealth accounting

191

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Inclusive Wealth ReportChapter 9

Inclusive wealth accounting for
regulating ecosystem services
Heather Tallis, Stephen Polasky, Juan Sebastian Lozano, and Stacie Wolny

Key Messages
Studies that have sought to value natural
capital have typically focused on “provisioning”
services or natural resource stocks such as oiland natural gas, minerals, timber, and fisheries.
Other than the cost of CO2 emissions vis-à-vis
climate regulation, regulating services have notbeen considered in any great depth.
Due to the high degree of uncertainty in estimating the value of regulating services, it will
be useful for policy-makers to see a range of values with lower and upper bound estimates. We
provide such uncertainty analyses for climate
regulation through carbon sequestration.
The marginal net benefit of regulating services is large enough to justify undertaking
future research in identifying servicesheds,
unbundling regulatory services into explicit
benefits, and producing value estimates forinclusion in wealth accounts.

An important first step for including regulating services in an inclusive wealth framework
is to have well-defined individual services. The
present typology of regulating services does
not lend itself well to wealth accounts because
multiple services are embedded within common regulating service category. Identifying
individual services also simplifies the valuation
process.
It is important to identify servicesheds inorder to estimate the value of ecosystem services. A serviceshed is the area that provides a
specific benefit to a specific individual or groupof people. It is further characterized by threefactors: (1) ecosystem supply; (2) institutions;and (3) physical access.

195

1.

Introduction 1

Concerns over the current trajectory of the
global economy and sustainable development
have led to high-profile calls for expanding thesystem of national accounts to include measuresthat better reflect natural capital and ecosystemservices (e.g., Stiglitz et al. 2010; World Bank
2006). The current set of national accounts doesa good job of measuring the value of benefits
that flow through markets, but has done a poor
job to date of capturing the value of benefits ofmost ecosystem services that largely do not flow
through markets. Ignoring the value of natural capital and ecosystem services in national
accounts and in benefit-cost assessment of specific projects causes a systematic imbalance ineconomic accounting. Without accurate pricing of natural capital and ecosystem services,
decision-makers do not have an appropriate setof signals and decisions may result in excessive
depletion of natural capital with a consequentdecline in the flow of ecosystem services. The
Millennium Ecosystem Assessment (MA) foundthat the majority of ecosystem services had
declined over the past 50 years (MA 2005). The
pattern of decline matches closely with the setof ecosystem services without market prices(Kinzig et al. 2011).
The inclusive wealth framework provides
a theoretically grounded and comprehensive
approach for the inclusion of natural capital, along with other forms of capital assets(manufactured capital, human capital), in
assessing sustainable development (Arrow etal. 2004; Dasgupta and Mäler 2000; Pearce
and Atkinson 1995). Sustainable development,interpreted as non-declining human well-being
over time, is equivalent to non-declining valueof inclusive wealth (or under certain conditions,non-declining value of inclusive wealth per capita, [Arrow et al. 2010]). The great advantage
of valuing assets in the inclusive wealth framework is that the value of capital takes account of1	This work was supported by the Gordon and Betty
Moore Foundation.

196

the value of the present and future flow of services generated by the asset. Measures of current income like gross domestic product (GDP)
only take into account the value of the current
flow of services. This narrow accounting of thevalue of the current flow of services can give a
distorted view of sustainability. For example,
exploiting natural resources more intensively
now can increase current income but at theexpense of natural capital. These natural capital declines will lead to declines in the future
flow of ecosystem services. Such unsustainable
exploitation could register positively for current income but would register as a decline ininclusive wealth.
To implement an inclusive wealth accounting approach, we need to be able to account forthe current and future value of all ecosystemservices. Many systems have been created for
categorizing ecosystem services (e.g., de Grootet al. 2002; Boyd and Banzhaf 2007; Fisher
and Turner 2008). The most widely accepted
and applied categorization of ecosystem services is that which is laid out in the MA (2005),
which differentiates among provisioning, regulating, supporting, and cultural services. In
this chapter, we focus on regulating services.
As defined by the MA, regulating services are
benefits derived from regulating ecosystemprocesses and include: air quality regulation;
climate regulation; water regulation; erosion
regulation; water purification and waste treatment; disease regulation; pest regulation; pollination; and natural hazard regulation.
While there are a growing number of studies that compare the value of ecosystem services
for alternative scenarios at the landscape level(e.g., Nelson et al. 2009; Polasky et al. 2011),
few studies have attempted to incorporate
the value of ecosystem services into national
accounts, or to incorporate the value of natural
capital into measures of inclusive wealth. The
studies that have attempted to do this mostly
focus on the value of provisioning services or
natural resource stocks such as oil and naturalgas, minerals, timber, and fisheries (Arrow etal. 2004, 2010; World Bank 1997, 2006, 2010).
Inclusive Wealth Report

Regulating services have not been includedin these studies, with the exception of factoring in costs of CO2 emissions as part of climate
regulation (Arrow et al. 2010). There is morework on the value of particular regulating services in specific contexts such as natural hazard
regulation (e.g., Das and Vincent 2009) andpollination (e.g., Ricketts et al. 2004; Kremen
et al. 2007). A recent book on the valuation ofregulating services that provides an overview ofissues and summary of empirical work on specific services highlights just how far we remainfrom rigorous, comprehensive measures of thevalue of regulating services (Kumar and Wood2010).
In this chapter, we discuss principles forincluding regulating services in measures ofinclusive wealth, then focus on a few key services to show how we can track their provisionand value in an inclusive wealth framework.
Finally, we give examples of what is possible atthe national scale today from two developing
countries, Colombia and Ecuador.

2. 	Principles for including regulating
services in inclusive wealth
Unlike the case for provisioning services, little
progress has been made towards including
regulating ecosystem services into measures ofinclusive wealth. In large part, this stems fromthe greater conceptual difficulty in valuing regulating services and from significant data limitations. Here we review some of the challenges ofvaluing regulating services and provide principles for successful valuation and incorporation
into an inclusive wealth framework.

2.1 	Unbundling regulatory services fornational accounts
Although the MA laid out useful distinctions
among types of services (provisioning, regulating, cultural, and supporting), some regulating
services such as erosion regulation or water

regulation do not represent a single service.
Rather, these general labels bundle together
multiple services. For example, erosion control
encompasses soil fertility benefits to farmers;
extended infrastructure life benefits to reservoir
managers and hydropower producers; and fish
habitat benefits to commercial and recreational
fishers. Water quality regulation includes regulation of bacteria and other impurities in drinking water and regulation of nutrients that affecteutrophication of surface waters with potential impacts on recreation, fishing, and drinking water quality. Natural hazard regulation
includes protection of coastal property fromstorm surge and erosion, protection of inland
property from river flooding, and protection ofproperty from fire. Bundling together multiple
services in a single name confuses issues andmakes accounting for the value of services in an
inclusive wealth context difficult or impossible.
A necessary first step for inclusion of regulatory ecosystem service values into an inclusive
wealth framework is to have well-defined
individual services. This approach will help toprovide a more complete accounting of all regulating services and will simplify and clarify thevaluation process.

2.2 	Clarifying the distinction between
supply and service provision
The inclusion of regulating services in inclusive
wealth estimation has two vital components:(1) calculating how much service is provided;and (2) identifying the value of those services tosociety in the form of improvement in humanwell-being. The first step has been hindered by
the fact that most studies claiming to measure
ecosystem services measure the potential of an
ecosystem to provide the service (supply), butstop short of asking whether there is service
demand (Tallis and Polasky 2009; Tallis andPolasky 2011; Tallis et al. 2012b). Just as withother goods and services, it is the interaction of
supply and demand that determines provisionof the good or service. For example, consider

CHAPTER 9 Inclusive wealth accounting for regulating ecosystem services

197two ecosystems that each filter pollutants andimprove water quality downstream. One ecosystem lies in a watershed with cities and towns
downstream that rely on the watershed for
drinking water and recreational opportunities,
while the other ecosystem lies in an uninhabited watershed that flows into the open ocean.
Both ecosystems supply water purification,
however only the inhabited ecosystem supplies
ecosystem services related to water quality regulation. Analyzing provision requires assessing
both ecosystem service supply and demand, a
process that requires both ecological and economic approaches.

2.3 	Servicesheds
An important challenge in ecosystem services is
to identify who benefits from regulating services
and how much benefit people actually receive.
Addressing this challenge requires a clear understanding of where regulating services are produced in an area relative to people who might
benefits from these services. To simplify theaccounting of these connections, we introduce
the concept of a “serviceshed.” A serviceshed foran ecosystem service is simply the area where a
specific benefit is provided to a specific individual
or group of people. Servicesheds are characterized by three factors: (1) ecosystem service supply; (2) institutions; and 3) physical access. The
configuration of servicesheds and the importance of these three factors vary by service andbeneficiary. For example, the serviceshed for acoastal resident receiving benefits from inundation regulation is the nearshore area where
natural capital (e.g., mangroves, coral reefs, etc.)
can dampen waves and reduce flood frequency
or intensity on their property. For climate regulation, the serviceshed is the entire globe because
the atmosphere is well-mixed and there are nolaws, social norms, or forms of infrastructurethat limit the ability of anyone on the planet to
enjoy the benefits of a well-regulated climate.
For water-related regulating services, servicesheds are often closely related to watersheds.
198

The serviceshed for drinking water quality
regulation is the area upstream of a person’s or
a community’s water extraction point (Figure 1).
For a person or community to benefit from water
quality regulation, they must be downstream ofan area that has natural capital that can regulate
water quality (supply) and have physical access(pipes, foot paths, wells, etc.) and institutional
access (legal rights, informal rights) to that water.
The importance of all three factors is illustrated
aptly by water regulatory services. In cases wherewater supply is large (i.e., no physical scarcity) but
where a group’s access is limited by institutionalarrangements (e.g., a water source is in a national
protected area or poor rural farmers lack legal
water rights for irrigation) or by a lack of physicalaccess (e.g., no infrastructure), there will not bebenefits generated for the group.

2.4 	The public goods nature of regulatory
ecosystem services
Even when the provision of a regulatory ecosystem service is clear, the second task of identifying the value of those services to society canbe challenging. Many regulatory services haveelements of public goods. For example, consider
a watershed with two cities on the mainstem of
the river that each rely on the river for drinking water. If landowners upriver of both cities
undertake actions that result in more filtrationand higher quality water downstream then bothcities will benefit. Similarly, sequestering carbon and reducing atmospheric greenhouse gas
concentrations yields climate regulation that
may have global benefits. Public goods create
two distinct challenges for understanding boththe provision and value of ecosystem services:(1) it can be difficult to estimate the value of ecosystem service provision; and (2) it is not always
clear a priori who the beneficiaries are.
Since many regulatory ecosystem services
are public goods, are not traded in markets,and do not contribute directly to productionof other marketed goods, methods of nonmarket valuation are needed. The difficulties
Inclusive Wealth Report

A

B
Nitrogen retention (100 kg/year)

30

2

1

A

B
0

25
20
15
10
5
0

0

1
2
Watershed area

Total

Figure 1

service are equal (b). In watershed Area

Hypothetical depiction ofservicesheds for waterrelated regulating services.
In watershed Area “0”“2” (a), supply is lower than watershed
Area 1 (b) because the region is smaller,
and biophysical processes provide lesspotential benefit, but service is higher
than Area 1 because both City A andof non-market valuation make the translationof biophysical estimates of service provision
to human well-being impacts more challenging than it is for many provisioning services
that are directly tied to marketed commodities. There are a number of non-market valuation approaches including both stated andrevealed preference methods that can be used
to estimate the value of regulatory ecosystemservices (see NRC [2005] for a review of standard valuation methods). Regulatory services
often reduce the impact of potential harms
or damages. Therefore, estimates of harms or
damages, or estimates of the cost of alternative
methods of reducing harm or damages (avoidedcost), can be useful in valuation. For example,
the value of the regulatory services contributing to water quality for drinking water for anumber of major metropolitan areas has been(a), there is supply, but no service inCity B enjoy its benefits, doubling thethis hypothetical case because thereamount of service Area 2 delivers. Thisare no beneficiaries (black dots)

relationship and outcome will only

downstream of that region of thehold if City A enjoys the service non-watershed to enjoy its benefits (b). In

consumptively, or does not extract allwatershed Area “1” (a), City B enjoys

available water, thus making the benefit

the benefits of the area, so supply andunavailable for City B.

estimated based on avoided water treatment
costs. The value of natural hazard regulation
is often estimated based on changes in thelevel of expected damages. For example, thevalue of mangroves or coastal wetlands forstorm protection can be estimated by modeling the reduction in the probability of storm
damage with that natural capital in place. The
decision to use avoided cost or estimated damages should depend on what is actually donein each country. In developed countries, theappropriate approach for drinking water quality regulation is typically avoided costs because
these countries will supply clean drinking
water in one way or another (e.g., natural
purification, water treatment plants, bottled
water). In developing countries, it is less common for actions to be taken to avoid the damages from lost services so people will actually

CHAPTER 9 Inclusive wealth accounting for regulating ecosystem services

199suffer losses in well-being. For example, lossof drinking water quality regulation will often
lead to higher water-borne disease and loss ofworking days.
Because many regulatory services are public
goods, there can be multiple groups benefitingfrom the supply of services. For example, consider drinking water quality regulation with twocities that both rely on the same river for drinking water, one in the upper part of the watershed (City A) and one in the middle part of thewatershed (City B, Figure 1). The area upstreamof both cities (Figure 1a, watershed area 2) provides water quality regulation benefits to bothcities. The area downstream of both cities provides supply, but it does not provide any drinking water quality service, as there are no downstream beneficiaries (Figure 1b). Calculating
benefits requires accurate determination of theserviceshed for services. In this case, summarizing the amount of service to be valued in an
inclusive wealth account would show that service is higher than supply (Figure 1b, Total). As
this example illustrates, accurate delineation ofservicesheds is necessary to calculate regulating
service delivery and value.

2.5 	Providing complete accounting while
avoiding double counting
Ecosystems provide a bundle of services, making
it essential to provide as complete an accounting as possible. Leaving out important services
can lead to poor decisions and inferior outcomes. In the current system, many provisioning services lead to production of commodities
valued in markets, but most regulatory services
lead to public goods not valued in markets. Thissituation has led to the undervaluing of regulatory services by decision-makers and a decline
in most regulatory services over time (MA 2005).
The flip side, double counting of benefits,
can also be a problem with incorporating ecosystem services into national accounts. For
example, pollination services are important toimproved crop production. However, since the200

value of crops is already included in national
accounts, including an additional value forpollination in the account would result in the
double counting of benefits. The main question
to ask before including a benefit in an inclusive
account is whether the benefit is already being
captured in another part of the account. As
another example, health metrics may be used torepresent the benefits of drinking water quality
regulation. However, if health is already wellcaptured in human capital terms (it currently
is not), including an additional health metric innatural capital context would be double counting. One way to avoid double counting in thesystem of accounts is to focus on final goods
and services and not include intermediate services (Boyd and Banzhaf 2007).

2.6 	Stocks and flows: the value of ecosystem services and natural capital
Any of the valuation methods described above
has to be tailored for use in a wealth accounting
context. In addition to the issues already raised,
it is important to distinguish between valuing
stocks and flows. Much of the discussion above(and in the literature in general) focuses on
valuing ecosystem services rather than valuing
natural capital. The value of ecosystem services
is a measure of the flow of benefits and is moreakin to measuring income rather than wealth.
Natural capital is an asset (stock) and measuring the value of natural capital is an importantcomponent of measuring inclusive wealth. As
stated in the introduction, the great advantage
of measuring inclusive wealth, as compared
to measuring current income, even inclusive
income that includes the value of regulatory
ecosystem services, relates to sustainability.
Increases in the current value of services can beachieved by intensive use that degrades capital,
which will lead to lower service provision in the
future. To achieve a sustainable outcome, theproper goal for decision-makers is non-declining inclusive wealth rather than high current
value of income. The value of natural capital
Inclusive Wealth Reportand the value of ecosystem services are linked.
The value of an asset is, in principle, determinedby the flow of benefits generated by the asset.
So, one way to measure the value of natural
capital that provides regulatory services is topredict the value of the flow of services throughtime generated by the natural capital and compute a present value of these flows. In practice,
predicting the future flow of services as a function of the presence of natural capital, the likely
value of these services in the future, and how
to properly discount future values of ecosystemservices, are all problematic.

2.7 Marginal versus total value
Computing the total value of natural capitalfor inclusive wealth calculations is quite difficult and may go beyond what can currently
be achieved. A more achievable goal might beto evaluate marginal value of natural capital,
which is how a small change in natural capital will change the present value of the flow ofservices.
The general approach of capital accounts
aims to identify the total value of capital assets.
This value is usually defined as the amount ofvalue generated by the existence of the capital
asset. In other words, what would be lost interms of benefits created if the capital assets
were destroyed? In addition to reasons discussed above, this approach can be problematic
for regulating ecosystem services, especiallythose that are crucial for life-support. The total
value of some regulating services is extremely
large (perhaps infinite if it truly is necessary
for life-support). As services become scarcer
their marginal value tends to rise. Using market
prices or estimates of marginal value when theservice is abundant and assuming that this priceholds when the service is scarce can lead to serious underestimates of value.
In addition, many regulating services are
hard to observe directly, so we will often needmodels to estimate the impact of changes innatural capital on the provision of ecosystemservices and the consequent change in benefits. However, large changes in environmental conditions may lead to shifts in ecosystemprocesses that alter functional relationships. It
may be difficult to correctly forecast the future
provision of services when conditions are quite
different from current conditions. Finally, regularly collected data are often inadequate tomeasure values at larger spatial scales necessary for national accounts. For example, water
quality regulation cannot be observed throughstandard measures of water quality because
the service is the amount of pollutant retainedby the ecosystem, not the amount released(observed). Studies of actual pollutant cycling
are often done at the plot or regional scale andare seldom connected to beneficiaries (e.g.,
Crumpton et al. 2008; Deegan et al. 2010)
making it difficult to use this approach for thekind of annual, national scale observations
needed for national accounts. Similarly, thevalue of keeping contaminants out of drinking water cannot be observed through water
treatment costs or human health metrics sincecontaminant loads are only one factor of many
affecting treatment costs and health conditions.
These challenges exist for most regulating services. In these cases, we will need to identify
the marginal contribution of the ecosystem
to regulating services through modeling thecore regulating processes under conditions
with and without natural capital (Tallis andPolasky 2009; Tallis et al. 2012a).

3. 	Examples of the accounting process
for key regulating services
The principles outlined above are relevant toinclusive wealth accounting for any regulating ecosystem service. In reality, countries will
likely start such accounting with a short list ofservices to reduce assessment time and costs.
Given these probable limitations, we outline
the accounting process for a subset of services
that are likely to be critical in all countries and

CHAPTER 9 Inclusive wealth accounting for regulating ecosystem services

201

whose assessment potential is relatively welldeveloped.

3.1 	Climate regulation through carbon
sequestration
Many atmospheric constituents interact withclimate regulation including nitrous oxide,ozone, particulate matter, methane, and carbon
dioxide (Karl and Trenberth 2003). Vegetationand microbial organisms can regulate the fluxof several of these, providing a suite of climate
regulation services. The regulation of climate
through carbon sequestration is the regulating service that has garnered the most international attention and the only climate regulation
service that has any sort of market developedaround its value. To account for the wealthbenefits provided by a country’s ecosystem service flows, we first need to be able to estimate
carbon stocks and sequestration rates. We canobserve stocks and sequestration rates directly
through biomass and growth surveys, and many
countries have developed rigorous protocols formeasuring this process for the purpose of trading carbon credits in markets (Brown 2002;
Pearson et al. 2007; Petrokofsky et al. 2011).
Remote sensing protocols are rapidly developing that will continue to improve the feasibility of making annual above-ground carbon
stock and sequestration measurements at thenational scale (Asner 2009). Fully accounting
for carbon regulation will require more practical approaches for monitoring soil carbon storage and fluxes (Conant et al. 2010). In cases
where measurement at the national scale is not
feasible, models can be used to estimate stocks
and sequestration, with strong ground-truthing
and validation. Many models exist for the estimation of carbon stocks and sequestration rates,
ranging from very simple (look-up table-driven
approaches like the Intergovernmental Panelon Climate Change [IPCC] tables or the InVEST
model; Conte et al. 2011a) to complex, dynamic
process-based models (e.g., CENTURY, LPJml).

202

In the simplest approach, the value of the
carbon stock would be calculated as the sizeof the stock (metric tons C) times the value of
keeping one metric ton of carbon stored in theecosystem and out of the atmosphere. In valuing the change in carbon stocks through time,
we also need to account for how the value ofcarbon storage changes. One major issue withaccounting for the value of carbon storage isthat there is no consensus on what is the value
for storing a metric ton of carbon. The value ofthe physical asset – the carbon stock – is equal
to the value of reducing emissions as both leadto reductions in atmospheric concentrationof carbon. Economists measure the value of
reduced emissions by estimating the social costof carbon, which is the damage to society, interms of diminished economic output, healthcosts and other impacts, caused by more intenseclimate change resulting from an additional
unit of atmospheric CO2 (Tol 2009). Estimatesof the social cost of carbon range widely, fromnear zero to well over US$1,0002 per metric ton
C depending on the model used, the assumed
discount rate, atmospheric CO2 concentration,and other factors (Tol 2009).
The existence of carbon markets, most notably the European Union Emissions Trading
Scheme, has led some to advocate for using
market prices rather than the social cost ofcarbon. However, existing market prices do notaccurately reflect the social cost of carbon but
rather the stringency of the cap under which
trading in the market occurs. For example, inJanuary 2008 the price for carbon in Europe was
21.03€ metric ton-1 (or US$30.86 metric ton-1)
while the price for carbon in the United Stateson the Chicago Climate Exchange, a voluntary
program allowing commitment to very modest
emission reductions, was US$2.30 metric ton-1.
Since then, the Chicago Climate Exchange hasceased to exist so the carbon price has dropped
effectively to zero in the United States while
future society clearly remains vulnerable to2	All monetary values are expressed in US$, unlessotherwise noted.

Inclusive Wealth Reportreductions in well-being from climate change.
European emissions have the same potential
for social damage as emissions from the UnitedStates and therefore should have the same value.
The difference in market price was due to thedifference in stringency of regulation not thevalue of reductions in carbon to the atmosphere.
Given these imperfections in the market valueof carbon, we currently strongly recommend
the use of the social cost of carbon in estimatesof carbon values until carbon markets moreaccurately represent the true change in humanwell-being from climate regulation.
Using the social cost of carbon has its own
limitations. Calculations of the social cost ofcarbon represent the present value of damages
from more intense climate change from emitting a unit of CO2 into the atmosphere for thetime that the unit would likely remain in theatmosphere. Because it is calculated for the
lifetime of carbon in the atmosphere, the social
cost of carbon will undervalue the service of
permanent carbon storage in the ecosystem.
If, however, carbon will be released becauseof land-use change, fire, or other disturbances– and so is not permanently stored – then thischange in storage must be reflected as a change
in the amount of the asset similar to loss ofother forms of capital assets.

3.2 	Nutrient retention for drinking water
quality
Water quality regulation captures the effects
of natural capital on the chemical form andconcentration of many constituents that affecthuman well-being. The value of natural capitalthat provides a flow of benefits from improved
water quality over time is equal to the present
value of change in benefits over time. Nutrients,
primarily nitrogen and phosphorus, can cause
algal or cyanobacterial blooms that contaminate drinking water if not treated. These same
blooms can damage fisheries by decreasing
deeper water oxygen concentrations, leading
to “dead zones” (Diaz and Rosenburg 2008).

Vegetation and microbes in soils can transform these nutrients, turning them into gasesthat are then released to the atmosphere, orbiomass that is locked away, at least for someperiod of time. These cycling and uptake processes reduce the concentration of nutrientsin receiving waters, reducing water treatment
costs or human health risk or increasing fisheries productivity and related nutrition or income.
Other chemicals that affect human health andmay be regulated to some degree by natural
capital include agrochemicals, coliform bacteria, dissolved organic matter and many others.
Here, we only discuss nutrients, but the generalapproach can be applied to any chemical form,
with any associated benefit (see the next section
for a treatment of sediment in drinking water).
The marginal contribution of natural capital to nutrient regulation cannot be measured
directly at large enough scales for national
wealth accounting. Therefore, we must rely
on models to provide useful estimates. Many
nutrient cycle or flux models have been developed including relatively simple ones, suchas N-SPECT (NOAA 2004) and InVEST (Conte etal. 2011b), and more complex models such as
AnnAGNPS (Young et al. 1989), SWAT (Arnold etal. 1998), and many others. Any of these models
can be used to assess nutrient retention rates
but most need to be altered to some degree to
track the retention process (instead of export)
and to account for the actual delivery of regulating services to people. Including the location
and activities of beneficiaries allows the calculation of how much service is actually delivered,rather than capturing the full potential of thesystem to provide a given benefit as most of thelisted models do. InVEST accounts for demandin a simple way by using extraction points andthe watershed area contributing to each point
to estimate actual service delivery.
An additional adjustment must be made inservice estimation to represent any “allowed”
or “safe” loads of nutrients. In many countries,
drinking water quality standards establish an
acceptable level of nutrient concentrations
in drinking water. Retention of nutrients in a

CHAPTER 9 Inclusive wealth accounting for regulating ecosystem services

203system where concentrations are below thisthreshold may not actually provide a service
if there is no damage to human well-being
for concentrations below the threshold. For
example, annual phosphorous loading to Lake
Okeechobee (Florida) was 498 metric tons y-1
from 1973 to 1999 (Havens et al. 2009). The
established total maximum daily loads (TMDL)
would be achieved with an annual loading rateof 140 metric tons y-1. Therefore, improvements
in natural capital that increased phosphorous
retention could provide a maximum service rateof 358 metric tons y-1 (the difference between
the average annual load and the allowed annualload). Any further reductions in phosphorus
loading would be below the TMDL and therefore
not provide additional service value.
Nutrient regulation benefits are not commonly traded in markets. In lieu of market prices,
we can use several methods to derive a monetary
estimate of the value of changes in service provision. First, when water is treated before use inindustry, drinking water or other uses, we canuse the avoided treatment cost as an estimateof the value of nutrient retention. Avoided costhas been used to estimate the value watershed
protection to provide clean water to municipal
water systems such as in the case of New York
City (NRC 2000, 2005). In cases where no treatment occurs before consumption, we can use
non-market valuation techniques to estimate
losses in benefits that people experience withlower quality water. A large number of studies
have estimated losses in recreation, aesthetics,
and other benefits in developed countries (e.g.,
Carson and Mitchell 1993; Van Houtven etal. 2007) and some studies have estimated thelosses associated with health and productivity
consequences of poor quality water in developing countries (e.g., Choe 1996; Pattanayak2004).

204

3.3 	Erosion regulation for drinking water
quality or reservoir maintenance
The erosion regulation provided by natural capital can contribute to benefits in several ways.
Keeping soil on crop fields increases soil fertility and crop yields. In addition, keeping sediment out of rivers can increase drinking water
quality, lengthen the lifetime of infrastructure
by avoiding abrasion and damage or reducing
dredge costs, contribute to flood regulation or
help maintain commercially, recreationally, or
culturally important fish populations. Each ofthese benefits is supported by a different set ofprocesses and is experienced at different locations by different groups of people. Here, weonly address the role of erosion regulation in
improving water quality and reservoir maintenance. Other methods would be needed tocapture the many other benefits provided byerosion control.
As with water quality regulation, it is difficult
to observe erosion regulation directly. Plot scalestudies have been used extensively (Magette etal. 1989, White et al. 2007, Zhang et al. 2010)
but are difficult to replicate annually at large
enough scales to contribute to national accounting. Again, models can be a powerful tool for
assigning the marginal contribution of natural
capital to erosion regulation processes (MuñozCarpena et al. 1999). Several of the models
noted above are also widely used to model key
erosion processes (e.g., N-SPECT, InVEST, SWAT).
To estimate the two focal service flows, thesemodels need to be applied upstream of drinking water treatment facilities, direct drinking
water extraction points, or reservoirs used for
drinking water or hydropower production.
When considering the contribution of erosion
regulation to drinking water quality, the same
allowed load principle introduced above forwater quality regulation applies to sediment. If
there are drinking water quality standards for
suspended sediment loads, service is only provided by regulation of loads above that standard.
Similarly, there is an allowed load for reservoirs
equivalent to their engineered dead volume.
Inclusive Wealth ReportWhen building reservoirs, engineers plan for
erosion and sedimentation that will reduce thevolume, and therefore productive capacity of
the reservoir over time. If sediment loads areat the rate considered in engineering the deadvolume, additional erosion regulation does notprovide a benefit.
As with the value of nutrient regulation, erosion control benefits are typically not traded inmarkets so there is no market price. The value oferosion regulation can be estimated using gains
in productivity or avoided cost. For example,
preventing sediment from entering a reservoir
can enhance the productive life of the reservoir
for hydropower generation or reduce dredging
costs. The value of reduced sediment then can be
estimated by valuing the additional hydropower
generation or the costs of dredging. If erosion
regulation improves water quality linked torecreation or health benefits then methods
discussed above for nutrient regulation are also
applicable. As with other benefits, the value ofnatural capital is equal to the present value ofthe flow of benefits it creates through time.

4. 	Applying principles to national accounting in Colombia and Ecuador
Here, we attempt to apply the methodology
outlined above with readily available data in
two countries: Colombia and Ecuador. This is apreliminary effort to explore the state of scienceand key limitations for implementing inclusive
wealth accounting in each case. We emphasizethat our findings should in no way be seen as
official estimates as we conducted this work as ademonstrative, academic exercise, not as part of
an official process with either country. We also
used the most readily available data, which may
not be the best official data. In both cases, wewere not able to implement all of the principles
discussed above, and highlight these limitations
as a means of indicating where future researchand data collection should be focused.
Colombia and Ecuador are developing
countries in Latin America where inclusive

wealth reporting could dramatically change
the national view of development progress
and influence natural resource management
and poverty alleviation decisions. Their GDPs
vary (Colombia GDP = US$288.8 billion in 2010;
Departmento Nacional de Estadística, Ecuador
GDP = US$108.4 billion in 2010) but both countries have high poverty rates (percentage of
population below poverty line: Colombia = 45.5
percent in 2009, Ecuador = 33.1 percent in 2010)(CIA Factbook). The potential utility of a new
accounting approach in the region has beenrecognized by the World Bank. They have chosen Colombia as one of five pilot countries foran effort to implement Wealth Accounting andValuation of Ecosystem Services (WAVES). Here,
we attempt to apply the InVEST models, as ademonstration of the components of the methodologies described above that are feasible withreadily available data, to four regulating services
in each country.

4.1 	Colombia
4.1.1 Climate regulation through carbon sequestration
Carbon sequestration is the only regulating
service we were able to value with readily available data. We used the InVEST carbon model,
a simple look-up table of four carbon stocks
per vegetation class (Conte et al. 2011a). Thisapproach mirrors the IPCC accounting approach,and we used stocks derived by Peralvo (2008a)
via the IPCC methodology (IPCC 2006) for theland use and land cover in the country in theyear 2000 (IDEAM et al. 2007). All four standard
carbon stocks were represented (above-groundbiomass, below-ground biomass, soil, and deadorganic matter), but we did not account for the
harvested wood product pool. Carbon stocks
in 2000 were highest in primary forest regions,and heavily concentrated in the Amazon basin(Figure 2a, c), totaling 19.3 billion metric tons C
in the country. Assuming static physical assets,
the value of this stock using a US$50 metric ton

CHAPTER 9 Inclusive wealth accounting for regulating ecosystem services

205

A

Figure 2

Projected land use change,carbon stocks and sequestration from 2000 to 2030
in Colombia and Ecuador.

C

E

FOREST
OTHER VEGETATION
WATER
CROPS
PASTUREURBAN

Primary forest, especially in the Amazon
basin, in the east of both countries (a)held large carbon stocks in the year
2000 (c, e). Areas likely to be converted

26,70024,4000

0from forest to some other land use
between 2000 (a) and 2030 (b) show
climate regulation loss (gray areas, dand f) and those that will sequester
carbon over the same time period show
climate regulation gains (green areas,

B

D

F

FOREST
OTHER VEGETATION
WATER
CROPS
PASTUREURBAN

c and d). The projected net change forthe country over the 30-year period
represents a significant loss in wealth.
Pixels in Colombia are 250 m, pixels in
Ecuador are 90 m.

C-1 social cost of carbon (Tol2009) was US$964.06 billion.
However, we know land conversion is likely
to degrade this stock into the future, so we useda scenario for land use and land cover in 2030
generated using the CLUE-S model (Galindo2008) and assumed no climate change effects onvegetation distribution and no change in land
use past that year. This scenario shows land usechange patterns affecting carbon sequestration,
primarily west of the Andes (Figure 2b). The net
effect of these changes results in a national lossof carbon storage of approximately 507,308,000
metric tons over the 30-year time period. We
assumed a linear loss rate, calculated the discounted value of the carbon stock lost eachyear, and deducted that value over the 30 years
from the static asset estimate stated above. We
also bounded our value estimate to represent
the possibilities for high or low discount rates(three percent and one percent, respectively)
and high or low annual changes in the social
206

26,70014,300-26,700-20,100

cost of carbon (one percent increase and nochange, respectively). With this approach, thepresent value of Colombia’s national carbon
stocks in 2000 is estimated to be between about
US$942.1 billion and US$947.5 billion. The reduction in the value of carbon storage is the difference between these amounts and the value of
US$964.06 billion assuming permanent storage,
or US$16.6 to US$22 billion. Given the uncertainty in estimation of the social cost of carbon,
we offer two other estimates. Using a lower estimate of $20 metric ton C-1, the rate commonly
applied by the World Bank, the value of the2000 carbon stock is between US$376.8 billion
and US$379.0 billion. Using a higher estimate of
US$205 metric ton C-1 (the 95th percentile value
based on 232 published estimates of the social
cost of carbon [Tol 2009]), the value of the 2000
carbon stock was between US$3.862 trillion and
US$3.885 trillion.
This application of the InVEST carbon
sequestration model has several limitations.
Inclusive Wealth Report

The InVEST Tier 1 carbon model does not represent sequestration by aging vegetation because
carbon stocks only change if land use land covertypes change. This means we have likely underrepresented the value of carbon stocks in the
Amazon Basin and other forested regions andpossibly overestimated the net loss of carbon
nationwide over the 30-year future projection.
However, while carbon stocks are high in old
growth forests, carbon sequestration rates in old
growth forests are generally low (Pregitzer andEuskirchen 2004). Another major limitation tousing this approach for national accounting is
the lack of regularly updated national inventories of carbon stocks or national land use andland cover maps. As a case in point, the mostrecent land use and land cover map we could
find for these analyses was developed in 2000.
At least one of these data sources must be available to allow annual tracking of carbon sequestration and its value in an inclusive wealthaccounting context. The lack of such data is a
global problem and must be addressed by theremote sensing community before real progress
can be made (Tallis et al., in review). Someefforts are underway, but must become standardized, efficient, and cost-effective before
they can be applied in this context.
4.1.2 Nutrient retention for drinking water quality
We were able to estimate and map nutrient
retention for drinking water quality supply
and service delivery, but not value. We used
the InVEST water purification: nutrient retention model (Conte et al. 2011b; Tallis et al.
2012a). This model estimates supply based on
the export coefficient approach (first developed
by Reckhow et al. 1980), where each land use
and land cover class exports a certain amountof nutrient. This export is influenced by runoff(calculated by the InVEST water yield model, asimple pixel-based water balance model), andretention by downslope vegetation and soils.
Exported nutrients are routed across the landscape and each land use and land cover typeretains nutrients in a constant, non-saturating

function. The model outputs the total amountof nutrients exported by the landscape in an
average year, and the total amount of nutrients
retained. These outputs can be calculated at
the pixel scale, and summarized to any larger
unit such as political boundaries or large basins.
Summarizing retention for the whole country
gives an estimate of supply, or the full potential
for nutrient retention benefits. Summarizing
retention for servicesheds upstream of drinking water extraction points gives an estimateof service delivery because it accounts for how
much retention is actually providing benefit toa downstream user.
We applied the water purification model for
total nitrogen (TN) and summarized retention
to the national boundary (supply) and to servicesheds delineated for all population centers(Instituto Geográfico Agustín Codazzi 2007)
in the country (service). Maps of the locationsof actual water extraction points or water treatment facilities should be used to identify beneficiaries and servicesheds, but such maps are notfreely available for Colombia. For all cities, we
assumed surface water use and identified theextraction point as the closest point on a river
within five kilometers. We used a 250 m digital
elevation model (Farr et al. 2007), soil depth(IGAC 2003; Batjes 2005), plant available watercontent (Estrada et al. 2007), annual precipitation according to WorldClim (Hijmans et al.
2005), potential evapotranspiration (derived
from WORLDCLIM data using Hargreaves method[Droogers and Allen 2002]), and land use andland cover data (IDEAM et al. 2007). For eachland use and land cover class we defined a root
depth, evapotranspiration coefficient, export
coefficient (total amount of TN exported ha-1yr-1), and retention efficiency (percentage of TN
retained yr-1) based on an extensive global andregional literature review (Tallis 2012).
In the year 2000, TN retention rates werehighest in the Andean valleys, where TN exports
from agricultural and pasture lands are highand some natural vegetation remains along
flowpaths to provide retention (Figure 3a). In
general, retention is potentially higher in areas

CHAPTER 9 Inclusive wealth accounting for regulating ecosystem services

207

A

C

5,300

510

0

0

B

D

386,000

9,160

0

0

Figure 3(inset in b, d), amplifying the demand

Nutrient regulation for
drinking water quality in theyear 2000

in that region. In both countries,
maximum service delivery is higher
than maximum supply because ofoverlapping servicesheds in densely

The magnitude of nutrient regula-populated areas. Areas not included intion supply (a, c) differs from service

a serviceshed are shown in grey (b, d).

delivery (b, d) because the populations

Pixels in Colombia are 250 m, pixels inof Colombia and Ecuador are focused

Ecuador are 90 m.

in the western parts of the countries

where there are high nutrient inputs (fertilizers, fixation, etc.) because when there is more
nitrogen flowing across the landscape, there ismore potential for vegetation and soils to take208

it up and provide a reduction in pollutant load.
This is somewhat counter-intuitive, but correct.
Pristine systems generally export little TN relative to productive areas (e.g., crops, pastures), so
there is little potential for downstream vegetation and soils to retain it. At the national level,
the total supply of nitrogen retention for drinking water in the year 2000 was ~785.8 million
kg TN. Summarizing this retention within servicesheds (Figure 3b) gives us a national service
delivery estimate of ~32.7 billion kg TN. The
national population of ~45 million people is distributed throughout the country and drinking
water servicesheds cover nearly the entire country (Figure 3b). Many servicesheds are overlapping, making service delivery much higher than
supply, especially in the area with the highest
density of population centers (Figure 3b inset).
For these ecosystem service estimates toenter into an inclusive wealth account, we needto value the well-being impact of service delivery
with a standard net present value approach using
any of the methods discussed above. Estimating
the future flows of service is straightforward: we
can simply run the InVEST model on the future
landscape as predicted in the 2030 land use andland cover map (Galindo 2008). However, data
and methods for valuation were limiting. Dataon water treatment costs are not readily available for all facilities in Colombia. The alternative
approach of estimating health and productive
losses would require another modeling effort to
extract the marginal contribution of nitrogen
regulation to these components of well-being.
Neither was feasible for this study, but can be
developed in the future.
4.1.3 Erosion regulation for drinking water quality and reservoir maintenanceOf the many benefits provided by erosion regulation, we were able to map and quantify the
supply and service delivery of two services: erosion regulation for drinking water quality andfor reservoir maintenance. The supply estimation process for these services is identical (andwould apply to estimation of any other erosion
Inclusive Wealth Reportaccumulated by these two processes is simply
added together on each pixel to estimate howmuch sediment is retained by natural capital.
We applied the sediment retention model for
drinking water quality improvement as well as
avoided reservoir sedimentation. We delineatedservicesheds independently for each service
since the services are enjoyed by different groupsof people in different places. Servicesheds fordrinking water quality were drawn as they were
for nitrogen regulation (above). Servicesheds
for reservoir maintenance were delineated as
the contributing watershed area upstream ofeach known drinking water and hydropower
production reservoir in the country (Instituto
Geográfico Agustín Codazzi 2007). We used
the same digital elevation model, annual precipitation map, and land use and land cover map
noted above. An erodibility map was developedby assigning erodibility values from Stone andHilborn (2008) to textural soil classes and soilorganic content identified by the USDA (2007).
Erosivity was derived from annual WorldClim

regulation benefit). In both cases, we used the
InVEST sediment retention model (Conte et al.
2011b, Tallis et al. 2012a). This model is basedon the Universal Soil Loss Equation (USLE;
Wischmeier and Smith 1978), where soil loss
is driven by slope, rainfall (erosivity), soil type(erodibility), vegetation type, and land use practices. In the InVEST model, the USLE approachis improved and retention is calculated as the
combination of two retention processes; theregulation of erosion from a given pixel, andthe ability of the vegetation and managementon that pixel to retain sediment arriving fromupslope parts of the watershed (run-on retention). On-pixel retention is calculated by internally comparing erosion on the current landscape to a “no-natural-capital” baseline. As such,
this model does the necessary calculation tocompare the current capital asset to its absence.
Run-on retention is calculated by routing eroded
sediment down flowpaths and applying a land
use and land cover-specific retention efficiency(percentage retained) at each pixel. Sediment
Figure 4AC

B

Erosion regulation for
drinking water quality andreservoir maintenance in
2000.

326,000
0

Erosion regulation supply is focusedin the Andean valleys and foothills(a, d). Service delivery for drinking
water quality (b, e) is much higher

989,000

32,200,000

00than supply. Service delivery forreservoir maintenance (c) is focused inwatersheds (servicesheds) upstreamDEof the Colombia’s few major reservoirs.
The black outline in (b) identifies the
expanded area in (c). Outlines in (c)delineate reservoir servicesheds.
Pixels in Colombia are 250 m, pixels in
Ecuador are 90 m.

54,000350,000

00

CHAPTER 9 Inclusive wealth accounting for regulating ecosystem services

209

precipitation data using the method in Perez andMesa (2002). For each land use and land coverclass, we defined C (vegetation) and P (management) factors based on an extensive global andregional literature review (Tallis 2012).
Following a pattern similar to nutrient retention, sediment retention in the year 2000 was
highest in the Andean valleys (Figure 4a). At
the national level, the total supply of sediment
retention was ~25.9 billion tons of sediment.
Considering demand at drinking water quality
extraction points, this translated into a muchhigher service delivery estimate for drinking water
quality regulation of ~1.1 trillion tons of sediment(Figure 4b). Again, many drinking water servicesheds are overlapping, making service delivery
much higher than supply for this regulating service, especially in areas of high population density.
Given the much lower number of demand points
for major reservoirs (Figure 4c), the service delivery estimate for reservoir maintenance in 2000
was ~1.3 billion tons of sediment.
As with nutrient regulation, these ecosystemservice estimates need to be valued in terms of
their well-being impact before they can inform
national accounts. We can again estimate thefuture flow of services by running the InVEST
model on the future landscape as predicted in
the 2030 land use and land cover map (Galindo2008). But as for nutrient retention, data andmethods for valuation were limiting. For drinking water quality regulation value, data or models on water treatment costs or marginal healthimpacts are not readily available. For reservoir
maintenance, production information (production and dredge costs, production practices, etc.)
is generally proprietary. Additional systems ofdata collection or reporting must be developed
before ready calculation of values can proceed
on a regular basis.

4.2 	Ecuador
The same InVEST modeling approaches wereused in Ecuador. The land use and land covermap used in all analyses was produced by MAG
210

and others (2002) and represents the landscapein the year 2000. The land use and land cover
map for 2030 was created by Peralvo (2008b).
Other service-specific data sources and results
are described below.
4.2.1 Climate regulation through carbon sequestration
Following the same approach and data sources
described for Colombia, we estimate total carbon stock in 2000 of 3.9 billion metric tons C in
Ecuador. Stocks are again concentrated in primary forest areas, especially in the Amazon basinon the eastern side of the country (Figure 2a, e).
Using the same assumption of likely future lossof carbon from land conversion, and the estimation of that conversion by 2030 according to
Peralvo (2008b), we estimate a loss of 211,137,000
metric tons of carbon over the 30-year period.
Considering this likely future loss, we estimate
the present value of carbon in Ecuador in 2000 tobe between US$186.2 billion and US$188.5 billion.
Again, considering the uncertainty in social costof carbon estimates, we offer a lower bound estimate of US$74.5 billion to US$75.4 billion (using
US$20 metric ton C-1), and an upper bound estimate of US$763.6 billion to US$772.8 billion (using
US$205 metric ton C-1).
4.2.2 Drinking water quality regulation and erosion regulation for reservoirs
We were able to estimate supply and service fornutrient retention and erosion regulation for
drinking water quality, and supply for erosion
regulation for reservoirs in Ecuador. Data on
the location of reservoirs were not accessible in
the timeframe of this study, but can be addedin the future. We applied the InVEST water purification model for TN using a 90-meter digital
elevation model (Farr et al. 2007), soil depth(PRONAREG 1980), plant available water content(Saxton and Rawls 2006), annual precipitation from WorldClim (Hijmans et al. 2005),
and potential evapotranspiration calculated
from the WorldClim data using the Hargreaves
method (Droogers and Allen 2002). For each
Inclusive Wealth Reportland use and land cover type, we defined a root
depth, evapotranspiration coefficient, export
coefficient and retention efficiency (Tallis2012). We also applied the Sediment Retention
model with additional data on erosivity (Roose
1996) and erodibility (PRONAREG 1980; USDA
2007; Stone and Hilborn 2008). Drinking
water servicesheds were delineated as they werefor Colombia, assuming surface water use andextraction from nearby river sources.
The areas of highest TN retention are again
in the valleys and foothills of the Andes, andin the western region of the country (Figure3c). At a national level, total TN retention supply in 2000 was approximately 221.5 million kg.
Summarization to drinking water servicesheds
showed a much higher level of service delivery,
1.2 billion kg for the country. Service delivery is
focused and amplified in the heavily populated
region west of the Andes (Figure 3d). We likely
underestimated national service delivery as
there are inhabited areas in the Amazon basinthat are not captured in the population center
data we were able to access.
Sediment retention was even more strongly
focused in the Andean valleys and foothills(Figure 4d), offering a total national sediment
retention supply of ~3.8 billion tons of sediment. Summarizing this supply to servicesheds
again amplified the service estimate due to overlapping servicesheds. The national total sediment retention service in 2000 was ~24.5 billion tons of sediment. These contributions aremuch smaller than those seen in Colombia, but
Ecuador is a much smaller country (~113 million
ha vs ~25 million ha, respectively). Valuation ofthese services can be done by delineating servicesheds and following the same additional
steps noted for Colombia. However, much more
ready access to data sources is needed for this tobe a replicable process.

5.

Case studies vs. principles

The case studies provide a valuable opportunity
to assess the state of the science to meet the

principles we can define in theory. Although it
may seem disappointing that we were unable
to assign monetary value to three of the four
regulating services we explored in Colombia
and Ecuador, we were able to apply several of
the core principles. In all cases, we were able
to apply methods that allowed us to unbundle
regulating services into explicit benefits to
explicit groups. We were also able to differentiate between supply and service delivery for all
services, and the resulting numbers emphasize
how critical this step is in accurately accounting for the benefits received by people. We wereable to delineate servicesheds for all services,
but with some serious limitations. Without dataon actual extraction points, and the ability todifferentiate between users who rely on surface
or groundwater, our estimates may be largely
skewed in space, and in terms of the national
totals for nutrient regulation and erosion regulation. Regular reporting and improved accessto data such as land use and land cover maps,
ecosystem service access points, water treatment practices and costs and reservoir management will be essential before we can regularly
report on the wealth of this subset of regulating
services.

6. 	The need to continue forward
The fundamental approach for including regulating services in inclusive wealth accounts has
been detailed here and in previous works. We
have taken the first steps towards implementing the approach and find many limitations
in data availability, especially for inputs thatmust be updated annually to provide useful
information to decision-makers at the national
scale. However, the magnitude of wealth thatthese preliminary analyses demonstrate islarge enough to have significant impacts on
the national view of social status in these twocountries. This suggests that, while difficult, theapproach and principles we have proposed here
should be pursued if we are to accurately track
the real wealth of nations.

CHAPTER 9 Inclusive wealth accounting for regulating ecosystem services

211

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214

Inclusive Wealth ReportChapter 10

Accounting for water:
stocks, flows, and values
Chris Perry

Key Messages
As water becomes increasingly scarce,
as sectoral competition for water intensifies,
and as humanity increasingly interferes withnature’s hydrological cycle, the need to measureand value water flows and stocks has increased.
Such evaluation must proceed in two discrete steps: first, the construction of physicalwater accounts, designed to figure out how
much water there is, where it is, when it is available, how accessible it is, and with what reliability; and second, when the accounts are in place,the analysis can proceed towards placing a valueon these resources.

SEEAW has important strengths. It is multisectoral; it clearly distinguishes between consumptive and non-consumptive uses of water;
it is hydrologically consistent with the law ofconservation of mass; and it can be applied atvarious scales (project, sector, region, country,
and basin).
While SEEAW has been promoted for a few
years, Australia is the only country for which
detailed implementation plans and progress
seem to be available. The process has been
lengthy and detailed and has resulted in many
reports, reviews, and studies.

The UN’s System of Environmental- SEEAW accounts should be expanded to
Economic Accounting for Water (SEEAW) is an include the “unmanaged” natural landscape;important step forward in understanding the “managed” areas; and rainfed agriculture.
flows and stocks of water. The flows compriseabstraction, consumption, and return flows;
the stocks, which are harder to assess, look at
groundwater resources, lakes, snowpack, andthe like.
215

1.

Introduction

Human, animal, and plant life all depend on
water. Water is also an essential factor in mosteconomic activities – a source of energy forhydro-power; the medium in which fish grow;a coolant for thermal power stations; a dilution
agent for wastes and pollutants; and the criticalconstraint to food and fiber production in arid
and semi-arid areas.
In the early years of human intervention in
the hydrological cycle, diversions and impoundments affected a very small proportion of natural
flows. Impacts, though real, were of no concern
to the human actors. Over time, populations
expanded, living standards rose, and dependence on water increased; interest developedin measurements and predictions of whether
the year’s flow was likely to be scarce, adequate,
abundant or, indeed, dangerously overabundant. Thousands of years ago, as Egypt began
to exploit the Nile as a key economic resource,
the world’s first significant hydrological measurement and prediction system began, basedon the “Nilometer” where the depth of the Nilewas continuously recorded and interpreted as apredictor of future flow patterns.
Today, ensuring water availability for drinking, sanitation, navigation, fisheries, recreation,
irrigation, and commercial activities is accepted
as a fundamental responsibility of governments,
at least at the level of regulating resource allocation and use. Additionally, governments areseen to be responsible for ensuring that theenvironment is protected, or where necessary,
restored.
When water is scarce, these various social,commercial and environmental interests intersect in many ways. Should water be released
from dams during the summer for irrigation, or
during the winter to generate power for heating?
Should forests be replanted to sequester carbon
and mitigate climate change, thus increasing
upstream water consumption and decreasing
river flows? Are golf courses, which generate
substantial economic activity, a higher priority
than low-value grain crops for food security?
216

Should cities have unrestricted access to water
for domestic and sanitation purposes? If somegroups in society have historically been disadvantaged in access to water, should preferential
entitlements be established? “The environment”
often requires a great deal of water to remain
healthy – but to what extent is “the environment” more important than feeding people orproviding jobs? What are the relative rights of
upstream countries, where the rain falls and therivers are fed, compared to downstream countries that have depended for millennia on thewater in those rivers?
These and many other scenarios of competition and conflict can be identified acrossthe world – from high-income to the leastdeveloped countries, in countries with extreme
scarcity of water and countries with relatively
plentiful supplies. Every water situation is aunique combination of history, climate, socialand economic pressures, resource endowments,
trading opportunities, and so on. To this extent,
the solution to every problem must be uniquely
designed, and be the result of political processes that allow local preferences and priorities to contribute to the allocation of the scarce
resource.
How these conflicting demands are resolved
fundamentally affects the individual, sectoral,
and national benefits that a nation derives fromits access to water. Underpinning these processes and the decisions that must be made lies
the essential foundation of a system of wateraccounting that unambiguously reports boththe current state of water use, and the impacts
of proposed interventions that can change thatpattern of use.
The prosperity of a nation is affected by theavailability of water, and the contribution thatwater makes to national wealth and well-being– and the impact that changes in water availability might have on these parameters – appear
to be legitimate components of any assessmentof national wealth that goes beyond traditional
constructs such as gross domestic product orcapital formation.

Inclusive Wealth ReportSuch an evaluation must necessarily pro- – the input is consumed in the process. Electricalceed in two discrete steps: 1) the construction energy is generated at a power station, distributed to consumers, and used for heating, lightof physical water accounts – how much water isthere, where, when, how accessible, with what ing, or to power a motor. Once the purpose has
been achieved, the electricity has been conreliability?; and 2) with the physical accounts inplace, the analysis can proceed towards placing sumed (albeit converted into another form ofenergy), and if more is needed, more must bevalues on these resources.
generated. Certainly the electricity originallyIn the following sections, some of theissues that arise in devising meaningful water supplied is not available for re-use. The meanaccounts are described: first regarding the dif- ing of “efficiency” (providing the same amountficult distinction between stocks of water and of heat or light with less electrical energy), andflows; second, in reporting on water use. A brief “savings” (reducing transmission losses, forhistory of water accounting is presented, focus- example) are entirely clear. Using electricity is
ing finally on the UN System of Environmental- indistinguishable from consuming electricity.
With water, the picture is much more comEconomic Accounting for Water (SEEAW), andidentifying the extent to which that frame- plex. Many uses of water – domestic use, generwork helps understand the role of water in ation of hydro-power, navigation, fisheries, andthe national economy, and the limitations of industrial processes – are predominantly nonconsumptive. The quantity of water diverted forphysical water accounts – even when linked toeconomic accounts – as a basis for estimating use is almost the same as the quantity of water
returned to the hydrological system. For mostwater wealth.
In Section 5, some experiences with applying household purposes (washing, cooking, bathing,
SEEAW are presented, and the extent to which WCs, etc.) the purpose is generally achieved withsuch analyses can be interpreted as measures of only minimal conversion of water into vapour;hydro-power plants are entirely non-consumpwealth at local or national levels is discussed.
tive, unless water storage leads to extra evaporation from the reservoir; and thermal plants only
evaporate a small fraction of the vast quantities
2. Physical water accountingof water passed through the system for cooling.
Agriculture, which is often the major userof water in water-scarce countries, is differConflicting perspectives about water
ent. Water is used in agriculture (rainfed and
The purpose of accounting is to provide infor- irrigated) to ensure that crops can transpire
mation in a consistent format for further analy- freely and grow vigorously. Biomass formationsis. Any accounting system must be based on is a direct function of the rate of transpiration
through the open stomata, which simultanean agreed upon and appropriate numeraire
ously allows the plant to assimilate carbon. If(dollars, yen, barrels of oil). However, because
the water-using sectors have operated indepen- water supplies are inadequate, production isdently when water was plentiful, each sector depressed. Transpired water (as well as evapohas evolved its own perspective, and the prob- ration from wet soil and leaves) re-enters thelem of selecting a numeraire crosses disciplin- atmosphere as water vapour, and is consequently removed from the local hydrologicalary boundaries.
The most critical (and most frequently mis- cycle. In this sense, the water is “consumed”
and available supplies for downstream users areunderstood) attribute of a particular water use
is whether it is consumptive or non-consump- reduced. This linkage between upstream use
and consumption and downstream availability
tive. For most inputs into economic processes– energy, perhaps, provides a useful comparator is the basis for the accepted need to plan water
CHAPTER 10 Accounting for water: stocks, flows, and values

217

Table 1

Global water distribution
Water volume
Water sourcein cubic km

Percentage offreshwater

Percentage of
total water

Oceans, seas, and bays

1,338,000,000

--

96.5

Ice caps, glaciers, and permanent snow

24,064,000

68.6

1.74

Groundwater:

23,400,000

--

1.7

Fresh

10,530,000

30.1

0.76

Saline12,870,000

--

0.93

Soil moisture

16,500

0.05

0.001

Ground ice and permafrost

300,000

0.86

0.022

Lakes:

176,400

--

0.013

Fresh

91,000

0.26

0.007

Saline85,400--0.007

Atmosphere

12,900

0.04

0.001

Swamp water

11,4700.03

0.0008Rivers

2,120

0.006

0.0002Biological water

1,120

0.003

0.0001

Table 1 shows the distribution of the world’s total water resources. This is a statement of stocks – an instantaneous picture ofwhere all the water is at any moment. The right-hand column indicates the dominance of the oceans. From the stock perspective, total water availability is dominated by the oceans; while freshwater availability is dominated by ice and snow, andgroundwater. Rivers, from either perspective, are a tiny fraction of the water resource, amounting to only 350 m3 per capita –significantly less than Falkenmark’s (1989) water stress indicator of 1,000 m3 per capita per year.
Viewed from a flow perspective the water resource looks rather different. Annual evaporation and transpiration from theearth’s surface (land and oceans) is about 485 km3; precipitation on land is some 111,000 km3, of which 71,000 km3 evaporates
or transpires in situ, and 40,000 km3 runs off to rivers. Thus, the flow in rivers is some 20 times larger than the water in a riverat any moment, and on average the water availability per capita per year comfortably exceeds Falkenmark’s stress indicator. The
distribution of this average is of course highly skewed.
Given that some of water’s contributions to human well-being depend on flows (power generation, irrigation) while others
depend on stocks (fisheries, amenity value of lakes), and others depend on both (wetland health requires that water be present
in abundance, and that it is continuously refreshed) we already see that water is rather more difficult to describe, account for,and value than most other natural resources. Sectoral perspectives add further complications.
Source: Igor Shiklomanov’s chapter “World fresh water resources” in Peter H. Gleick (editor), 1993, Water in Crisis: A Guide to theWorld’s Fresh Water Resources (Oxford University Press, New York).

218

Inclusive Wealth Reportuse from a basin perspective – the basin being consider the quantity and continuity of water
availability as well as its scarcity.
the integrating hydrological unit of account.
Turning now to agriculture, when an irrigaPlanners wish to assess water consumption,
losses, and efficiency, and to understand how tion specialist aims to improve “efficiency,” thewater is currently allocated and how new allo- first objective – as in the domestic sector – iscations will impact on current use. Sectoral spe- to maximize the proportion of abstracted water
cialists, however, have a different understanding that is delivered to the user (ultimately, theplant). But just as leaks from water supply pipesof water consumption.
Water utilities supplying households and can contribute to aquifer recharge or to noncommercial users pay attention to “unaccount- productive evaporation, so irrigation systems
ed-for water,” meaning either leakage, or unau- are often major sources of aquifer recharge.
thorized extraction from the delivery system. “Losses” must therefore be carefully evaluated ata broader scale than the field, canal, or project
The consequences of addressing these quite
to fully understand the impact of interventions.
separate issues are likely to be different. Leakage
The second aim of improved irrigation effifrom pipes will typically contribute to recharge
ciency is to maximize the proportion of waterof any underlying aquifer if the leaking pipe isburied. If the pipe is at or near the surface, water delivered that is consumed by the plant andmay evaporate and is thus consumptively used. converted from liquid water to water vapour by
Repairing leaks may thus reduce total abstrac- crop transpiration. Broadly speaking, biomasstion (to the benefit of downstream users), but production (and hence yield) has a linear relationship with transpiration, so maximizing crop
reduce the rate of recharge of a local aquifer.
production implies maximizing transpiration.
The consequences of reducing unauthorized
abstraction, on the other hand, will be a mixture Here, and indeed in agriculture more generally, the implications of increased efficiency areof increased revenues and decreased demand as
previously unauthorized users decide whether quite different from most other sectors, directly
to continue using and paying, or reduce their implying a reduction in water availability foruse. In sum, in the simple case where water other users.
Water harvesting for rainfed agriculture
supplied to households is collected, treated, andreturned to the system for reuse downstream, provides another complex example: the objecthe impact of demand-reduction measures on tive is to minimize runoff so that local crops
can transpire more and hence increase producactual water consumption is small. The picturechanges dramatically, of course, if the domestic tion. Without knowing whether the naturalor industrial user is located close to the coast runoff would have evaporated unproductively,
where the potential for downstream use is min- or reached a possibly more productive downimal. Water supplies may not be “consumed,” stream use, it is impossible to be sure whether
the harvesting was a net benefit, neutral, or a
but are lost to further use in the system.
net loss to the economy.
The impact of thermal power stations is also
As a final example, forestry and other forms
complex: stations that draw water from a river,pass it through the cooling system, and return of catchment protection and development presit to the river use very large quantities of water ent similar complexities. A thriving healthy for– but typically only consume 2 percent or so of est will certainly transpire more water than athe water abstracted. On the other hand, closed- degraded catchment, but the reduced quantity
loop systems (where water is only abstracted of water that arrives downstream will be a more
steady flow with less silt. Timing and quantity
to “top up” leakage and evaporation) use muchless water but consume 2–3 times more water are of concern in assessing whether the impact
per unit of electricity generated. An “efficient” is positive or negative.
design for a power station would thus have to
CHAPTER 10 Accounting for water: stocks, flows, and values219

Table 2

Water supply and use statement, Denmark
Physical use table (Million cubic metres)

Ag., forestry
and fisheries

Mining,constr'n

Power

Water supply

Sewerage

Waste collection other

TOTAL

Households

TOTAL

Industries by ISIC category

1. Total abstraction (= 1.a+1.b, =1.i+1.ii)

108

115

404

429

100

2

1,158

11

1,169

1.a Abstraction for own use

108

115

404

23

100

2

752

11

763

1.b Abstraction for distribution

From theenvironment

1.i From water resources:

108

115

404

429

1.i.1 Surface water

55

80

301

5

1.i.2 Groundwater

3

35

3

423

1.i.3 Soil water

50

100

2

1,158

406
11

441
2

466

100

1

1.ii.1 Collection of precipitation
1.ii.2 Abstraction from the sea

100

2. Use of water received from othereconomic units, of which:

51

86

10

2.a Reused water

1241

3. Total use of water (=1+2)

159

201

476
50

100

201

1

202

100

100

1

101

101

1

4

1,169
441

50

1.ii From other sources

Within theeconomy

406

406

427

51

619

101
240

859

53

53
251 2,028

408

429

527

53

1,777

6

380

43

49

624

Physical supply table
4. Supply of water to other economic
units of which:Within the economy

18

4.a Reused water
4.b Wastewater to sewerage

128
10

18

118

4.c Desalinated water

To the environment

53

43
6

1

236

49

192

53
236

1

1

860

428
1

5. Total returns (=5.a+5.b)

65

29

400

47

484

1

1,026

5

1,031

5.a To water resources(=5.a.1+5.a.2+5.a.3)

65

23

300

47

228

1

664

5

669

353

1

354

311

4

315

5.a.1 Surface water
5.a.2 Groundwater

300
65

23

53
47

175

1

5.a.3 Soil water
5.b To other sources (e.g. Seawater)

220

5

100

361

256

6. Total supply of water (= 4+5)

83

157

406

427

7. Consumption (=3-6)

76

44

2

2

527

361

50

1,650

241

1,891

3

127

10

137

Inclusive Wealth Report

These stylized examples demonstrate thatlosses, savings, and efficiency are not unambiguous, having different meanings in different
sectors. None of this is to argue that reducing
household demand (and consequently reducing
the costs of water treatment, pumping, investment in capacity expansion, etc.) is not a good
idea, nor that improving the delivery of waterto crops so that yields increase is not a benefit,or that improving the forests does not stabilize catchments. Rather it is to point out thatin conditions of scarcity and competition, thehydrological context is critical, and simplistic
statements about saving water, reducing losses,
and increasing efficiency do not translate acrosssectors. Each sounds desirable, because theterms are value-laden, but within the overallbasin or aquifer context, actual physical flows
and the law of conservation of mass must be thebasis of any sound analysis.

3. Closing the inter-sectoral divide: attempts to “unify” terminology
The difficulties and contradictions surrounding the measurement of water stocks and flows
have led to a number of attempts to establish awater accounting terminology that can be uniformly applied across sectors without confusion.
The history is long. Irrigation efficiency was the
topic of research in the 1940s (Israelsen 1950),
while in the 1960s a U.S. Inter-Agency Task force
on water allocation noted that interventions
that improved irrigation efficiency should be
evaluated very carefully before assuming thatwater would actual be saved. But in the decadesthat followed, the dominant approaches towater scarcity continued to be dominated by adiscourse based on value-laden, terminology ofsavings, losses, and efficiency.
Several authors and agencies have, in recent
years, set out to address these issues. Specificallyin the agricultural sector, Jensen (1967; 1993)
and Willardson et al. (1994) led the way inaddressing the confusion around “efficiency.”
The International Water Management Institute(Molden 2007) and the Notes To Table 2
International Commission on The water supply sector illustrates the
Irrigation and Drainage (ICID) key elements of how SEEAW works. In(Perry 2007) made broadly Denmark, total water abstraction is 429
similar recommendations, the Mm3 of which 23 Mm3 are for “own use”
last after an extensive process and the rest for distribution to customof consultation across ICID’s ers. The actual quantity of water supinternational
membership. plied to customers (Item 4) is only 380
The Food and Agriculture Mm3, because 47 Mm3 are lost throughOrganization (FAO), through a leakage to groundwater (Item 5.a.2)
variety of publications related while consumption (Item 7) accounts
to agriculture in general and for the balance of 2 Mm3 – less than
irrigation in particular, has 0.5 percent of total abstraction. By
developed a wide (and par- comparison, in agriculture, forests, andticularly well documented) fisheries, total water use is 159 units,
set of terms. Most recently, of which 76 units are consumed (48the United Nations, follow- percent of the total supply) while theing a lengthy consultation household sector consumes only 4
process, has adopted a System percent of the total supplied (10 unitsof Environmental-Economic out of 251).
Accounting for Water (SEEAW), Source: based on SEEAW Table 3.3
and associated International
Recommendations for Water
Statistics.
SEEAW has important strengths. It is multisectoral; it clearly distinguishes between consumptive and non-consumptive uses; it ishydrologically consistent with the law of conservation of mass; and it can be applied at various scales (sector, region, country, and basin).
Its approach to water quality is pragmatic – first
proposing that the physical accounts (of volumes and flows) can usefully be constructedindependently of quality, while noting thatwater quality is an important issue. The difficulty with water quality accounting (as also
acknowledged in the ICID approach) is that thesignificance of any particular form of pollution
depends entirely on the proposed use. E-colibacteria have no relevance to hydro-power ornavigation, but are exceptionally important forhuman uses. Quality accounting, in the current
SEEAW document, is thus something to be further considered “at a later date.”
The nomenclature of SEEAW is not immediately transparent for most sectoral specialists, which is unsurprising as this is where

CHAPTER 10 Accounting for water: stocks, flows, and values

221compromises must be made. Four points are
critical:• “The environment” is simply the sourcefrom which water is abstracted (rivers
and aquifers), and the sink to whichsome or all of the abstracted water
returns as surface runoff or infiltration.
• In SEEAW, “the environment” has no particular connotation of a natural system
requiring protection from intervention.
• SEEAW distinguishes between water
abstracted for “own use” and water abstracted for distribution to other users –thus allowing proper analysis of utilities
that withdraw, treat, and distribute water to consumers, and collect, treat, andreturn sewerage to “the environment.”• The accounts distinguish between waterflows from and to “the environment,”
and water flows “within the economy.”Thus utilities abstract water from theenvironment and deliver the water tohouseholds (a transaction “within theeconomy”); the household then returns
the water to a sewage treatment agency(again, “within the economy”) which inturn treats the effluent and returns it to“the environment.”

than 0.5 percent of total abstraction. By comparison, in agriculture, forests, and fisheries,
total water use is 159 units, of which 76 units are
consumed (48 percent of the total supply) while
the household sector consumes only 4 percentof the total supplied (10 units out of 251).

3.2 SEEAW stock accounts

Imbalances between inflows and outflows overa given time period cause a change in stocks.
Some such changes are easily observed: riverflows (and rainfall) enter a reservoir, and arereleased for power generation, irrigation, orother uses. In high-rainfall years, the inflows
will be high, so that at the end of the hydrological reporting period the reservoir will containmore water than at the beginning. Observationof the depth of water in the reservoir allows estimation of the opening stock, the closing stock,and thus the change in stock. Such information is of great importance to water managers
who must plan in advance to protect supplies
if severe shortages are anticipated, or to guard
against downstream flooding if high inflows are
expected while the reservoir is full.
Other water stocks are much less easy tomeasure or monitor. In the case of snowpacks
it is very difficult to estimate opening and clos3.1 SEEAW flow accounts
ing stocks, because they rest on rock formations whose precise topography is hidden fromThe sample tabulation of national annual flow view, but it is possible to monitor trends overdata included in the SEEAW report is shown time that indicate whether the stock is increasing, decreasing, or stable. Similarly, aquifers
below (Table 2). The data refer to Denmark – a
are complex structures, with varying porosity
country for which comprehensive data wereavailable, though even here some estimation and poorly documented linkages between shallow and deep components – so that translatwas required to complete the tables.
The water supply sector illustrates the key ing changes in depth at sample locations intoelements of how SEEAW works. In Denmark, volumes is difficult, though the trend is a clear
total water abstraction is 429 Mm3 of which indicator of whether the aquifer is gaining or
23 Mm3 are for “own use” and the rest for dis- losing storage over time.
Table 3 presents SEEAW’s reporting format fortribution to customers. The actual quantity ofwater supplied to customers (Item 4) is only 380 stocks.
This example already has some obvious
Mm3, because 47 Mm3 are lost through leakage
to groundwater (Item 5.a.2) while consumption “round number” estimates – indeed all the
opening stock items are rounded to one or two(Item 7) accounts for the balance of 2 Mm3 – less
222

Inclusive Wealth ReportTable 3

Statement of stocks (Mm3)
Surface water

1. Opening stocks

Groundwater

Soil water

Total

5,000

100,000500

109,700

53

315

Reservoirs Lakes

Rivers

1,500

2,700

Snow, ice,
glaciers

Increases in stocks
2. Returns

300

3. Precipitation

124

246

50

4. Inflows

1,054

339

20,137

4.a From upstream territories
4.b From other resources in the territory669
23,015437

23,43521,967

17,65017,650

1,054

339

2,487

437

280

20

141

476

6. Evaporation/actual evapotranspiration 80

215

54

4,317

Decreases in stock
5. Abstraction

50

967

21,125

21,474

7. Outflows
7.a To downstream territories

9,430

9,430

7.b To the sea

10,00010,0008. Other
9. Closing stocks

1,618

2,950

4,272

100,189553

109,583

Source: based on SEEAW table 6.1

significant figures, while the changes in stock
are expressed with great precision (up to fivesignificant figures).
Soil water (SW) is of some interest, and wascontentious during the process of formulating
SEEAW (K. Frenken, personal communication,
August 15, 2011.)1 We note first that the reportedchange in stock over the reporting period (53Mm3, closing stock-opening stock in Table 3) is0.22 percent of annual flow through the soil, or
the typical flow for one day. Heavy rain the day
before, or after, the time of evaluation of thisvariable would substantially affect the actual
value of stock, but the facilities to record suchdata at the national level do not exist.
1 Karen Franken is Co-ordinator of the AQUASTATProgram and a Senior Water Resources Management
Officer with the FAO.

Technically, SW is that quantity of water
stored in the upper profile of the soil that isavailable for crop transpiration, or can evaporate directly. This apparently simple definitionis, however, complicated by several factors.
First, the quantity that can be stored depends
on the soil type and depth, so the potential for
SW storage must be mapped, and then converted to an actual level depending on previous
precipitation and/or irrigation events.
Second, a deep-rooted plant can obviously
draw on more water than a shallow-rooted
plant – so the estimate of SW obtained in thefirst step, above must be further adjusted for
actual plant cover.
Third, whether SW actually becomes evaporation, transpiration, or something else depends
on factors totally outside the control of managers – in particular, whether it rains “on top of”

CHAPTER 10 Accounting for water: stocks, flows, and values

223the existing SW. For any given combination ofcurrent SW, soil type, and plant cover, additional rainfall or irrigation will result in somecombination of: (a) additional infiltration to thegroundwater if the soil profile exceeds its waterholding capacity; (b) additional runoff if the
profile becomes saturated or the rate of deliveryof additional water exceeds the maximum rateof infiltration for the soil type/topography; (c)additional evaporation if the soil surface was
not fully wet; and/or (d) additional transpiration if the crop was water-stressed prior to thearrival of extra water.
Viewed from this perspective, SW has thecharacteristics of a contingent asset: an asset
whose value will be determined by events outside the control of the owner of the asset. A
specific volume of SW will contribute to one
or another of the above outflows depending
on subsequent rainfall events. Converting thisalready uncertain scenario from a physical toa financial indicator adds the dimension thatthe ultimate value of plant transpiration fromtoday’s soil moisture depends on future supplies to ensure that the crop reaches maturity.

3.3 SEEAW accounts: an evaluation
The SEEAW approach is an effective way to summarize hydrological flow data in a consistentformat. The framework is hydrologically sound– distinguishing between consumptive and nonconsumptive uses, and respecting the law ofconservation of mass.
The stock accounts are problematic – notbecause of conceptual limitations, but rather
because key data are unlikely ever to beavailable.
One aspect of the SEEAW accounts as presented in the manual relates directly to thequestion of valuing natural wealth: the manual
does not address the traditional construct of“the environment” (i.e., the largely unmanaged
collection of ecosystems, plant and animal life,
habitats, etc., that both enrich life for all andprovide crucial services for human well-being).
224

This issue is easily remedied by a simple
extension of SEEAW’s reporting format that does
not conflict with the principles on which SEEAW
is formulated. Additional columns for areas ofinterest (rainfed agriculture, natural forests,
rangelands, wetlands, etc.) are added to thetable, and the relevant flows are reported. The
SEEAW accounts already include “households,”
which have no ISIC classification but are essential to documenting the financial flows in theeconomy. Adding columns for the main actors
in the water economy is similarly consistent
with SEEAW’s logic.
These comments and suggested amendments to the physical accounts proposed in
the SEEAW manual do not yet tackle valuationof those elements of the “natural” economy, or
indeed deriving value-of-water estimates (financial, economic, and social) from the relationshipbetween water flows and financial flows in theeconomic sectors.

4. From physical water accounting tovaluing water
At the beginning of this chapter, some of the
problems and challenges involved in describing
physical water use consistently across sectors
were identified. Valuing water is also problematic both for “water-specific” reasons and forreasons that apply to the valuation of any input
into economic processes. The “water-specific”
reasons are outlined below.
The fundamental role of water to humanlife – we die of thirst in its absence – suggests
a near infinite value for the first few liters per
capita per day. Since plants require water togrow, our next fundamental need, for food, isalso extremely valuable and typically several
orders of magnitude greater in terms of volume:
a kilogram of grain typically involves transpiration of a metric ton of water, or one thousand
liters. Further economic activities (as clearly
set out in SEEAW) also involve water use and/or consumption, and what we can learn about
value from those accounts will be discussed
Inclusive Wealth Reportbelow. First, though, we should note that adding more water to “the economy” rather quickly
progresses from high value (as scarcity is alleviated), to no value (excess rainfall that drainsaway naturally), to negative value when floods
occur. Thus the value of water cannot be disaggregated from time, location, quantity, and theprecedent conditions: it may rain heavily in one
part of the country, causing floods and negativevalue added, while a few hundred kilometers
away an area in drought would have benefited
greatly from the incremental water supply;
heavy rains after a period of drought bring relief,
while the same quantity of rain following earlier
rainfall brings floods.
Additionally, while most components ofnatural wealth exist predominantly as stocks
that change slowly over time (forests, mineralreserves, ecosystems, etc.), water, except in thepolar icecaps, is predominantly a flow. A nation’s
water assets are predominantly the rainfall that
supports natural vegetation, and the associated river flows that can, to some extent atleast, be harnessed for economic exploitation.
The exception to this is groundwater stored inaquifers. Depletion of the aquifer occurs whenabstractions exceed recharge, which may be an
occasional aberration, or a long-term imbalance. In some countries, aquifers deposited overmillennia are (rather like a coal deposit) being
continuously depleted.
While it may be possible to estimate thevalue that can be derived from the storage in an
aquifer (one kilogram of grain per cubic meter
stored, for example), assessing the value of rainfall is a far more complicated and uncertain process – continuous rainfall for 80 percent of thecropping season will have no value at all if followed by complete drought for the final 20 percent; excess rainfall will damage crops, and soon. And to add to this complexity, when there isa widespread drought (as in 2008, for example)
the prices of grains and other agricultural commodities rise sharply so that the total value of
production may not change significantly. One
interpretation of that phenomenon might bethat the unit value of water increased while thetotal value remained constant. An alternative
view is that water is such a fundamental input
into life that it cannot be evaluated “locally”
without knowing what is happening everywhere else.
Turning now to the general difficulties of
placing a value on one input into an economic
activity, even the fullest and most accurate setof SEEAW accounts gives only the most superficial indicator of the value of water. If, forexample, we know that an industry uses X unitsof water and produces Y units of economic
activity, we still do not know whether adding
or subtracting a unit of water would proportionately impact on the economic outcome. If theuse is predominantly non-consumptive, suchas household use, where consumption is say 4
percent of water supplied, then the water could,
with suitable treatment, be recycled indefinitely
and “water use” as measured by abstractions
from the environment would fall by 96 percent
without loss of economic benefit, but at the costof investment in on-site treatment. Similarly,
industries can often recycle water, and the caseof alternative technologies for cooling thermal
power plants has already been discussed above.
Different technologies have vastly different coefficients of water use and consumption for thesame economic result.
In agriculture particularly, the productivity of water (and hence the estimate of “water
wealth”) implied by the ratio of economic output to water use depends substantially on otherfactors of production. The green revolution
effectively doubled grain yields per unit of water
consumed. Did the “water wealth” of countries
that benefited from the green revolution double
during that period? How can the incremental
production over the green revolution period
be allocated among research into high yielding
varieties, technology, management, increased
use of chemicals, and the water, soil, and sunshine that nature provided? Only for producers who are at the production frontier can webe sure that reduced supplies of one input will
impact on the economic outcome, and even
there the marginal productivity is not equal to

CHAPTER 10 Accounting for water: stocks, flows, and values

225the average productivity implied by the simple
division of output by total input.
Finally, there is the problem of aggregationin space and time. Most countries, even small,temperate ones such as the U.K., have areas thathave enough rainfall that agricultural production and ecosystem stability are rarely constrained by water (the southwest), and otherareas where precipitation is frequently excessive (Wales), or in deficit (East Anglia). In suchcircumstances, analysis at the regional/annual
level will identify whether there is a problem, and perhaps point to regional solutions.
However, aggregating the average water supply
to a national level will reduce the information
available because the surplus from Wales willoffset the scarcity in East Anglia. Such variations are far more extreme in large countries,
such as India, which includes both the wettest
location in the world and some of the driest.
These issues are recognized in SEEAW:
Regarding problems of spatial aggregation:
9.51. Water availability and demand, as
well as water quality, can vary a great deal
over time and space. It is difficult to address
sustainability on a national level when sustainability of water use is determined on a
local or regional basis.
Source: SEEAW, p.152.

And regarding temporal aggregation:
9.60. A first possibility is to reduce theduration of the accounting period: in many
countries, quarterly national accounts are
already built. Quarterly water accounts may
be useful in some countries; for example, seasonal water accounts for Spain would reveal
higher pressure on water in summer compared to winter.
Source: SEEAW, p.154.

An alternative source of information about
the value of water is evidence from financialtransactions involving water. The potential ofmarkets and water pricing to provide incentives
for better allocation of water, and indicatorsof its value have attracted substantial interest in recent years. The number of theoreticaldemonstrations of the potential benefits of226such mechanisms exceeds the examples “onthe ground” by at least one order of magnitude,and more likely by two or three. Representative
examples of the evidence from the field include
groundwater markets (e.g., Eastern India); rising
block tariffs (e.g., Israel); and the water rights
trading system in the Murray-Darling basin in
Australia.
The first of these – groundwater markets –while widely reported and studied, offer little
information about the value of water, because infact the market is in pumping services drawing
from a common pool resource. As newer, bigger,
deeper, more efficient wells are installed, the priceof water tends to be driven down towards thecosts of the most efficient pumper, while tellingus nothing about what the price of water would
be if constrained to the sustainable supply.
Rising block tariffs, which allow provision ofa basic supply at a low unit price with successive
increments being progressively more expensive,might offer more insights, but even where usedeffectively, such as in Israel, additional factors
conspire to obscure the prospect of deriving acomprehensive valuation of the water resource(S. Arlosoroff,2 personal communication,
February 25, 2003).
• The allocation of water among sectors isdetermined by government decree basedon recent hydrological data.
• A market-based system has been discussed, but resisted by politicians andfarmers. State lawyers objected strongly
against this, arguing mainly that you
cannot trade with a commodity that
does not belong to you, and to do sowould undermine the basis of the water
law and the public ownership of water.
• Within agriculture, the rising block tariff
is basically set so as to encourage water
demand at a particular level: the priceper unit is below the likely benefits ofuse up to the target demand level, and2 Saul Arlosoroff is the former Chair of the Israeli
Water Commission. Interpretations are the responsibility of the author.

Inclusive Wealth Reportsubstantially higher than that price forsupplies in excess of the target demand.
The information about the value of waterthat can be derived from these data is limited – all we know is that the marginal valueof water to a sector whose total allocation has
been administratively set is between the two
prices at the target consumption level. We learn
nothing about the average productivity of waterand nothing about the prices that would haveprevailed if trade between sectors had been
allowed, or trade within the sector (which happens, but informally), or the average benefits
derived from water use.

—— Volume of water in river channels(data available in New South Wales).
Although these items continue to beshown in the water balance it is not expectedthat any data could be shown against them.
They remain in the water balance sheet as areminder of their existence and that in someinstances they should not be overlooked. In
all water balances the data components havebeen listed even when data was not available
to highlight data availability issues and reliability of the water balances....
Key areas of water diversion and use thatare generally excluded from accounting ofwater resources [include] forestry. The afforestation of catchments has the potential to

5.	Application of SEEAW

reduce catchment runoff, to reduce recharge
to groundwater, and to extract water directly

SEEAW has been actively promoted throughworkshops and training programs for someyears, but Australia is the only country forwhich detailed implementation plans and progress seem to be available. The process has been
lengthy and detailed and has resulted in many
reports, reviews, and studies. This brief summary tries only to capture key issues that havearisen during that process, to document thecurrent implementation of SEEAW, and to summarize ongoing advances in preparing wateraccounts in Australia.
The initial step was to review data availability nationwide, and test the extent to whichwater accounts could be formulated on a standardized basis. This “discovery phase” reported
the following:3[A]s part of the Water Accounting Project,
information was sought on the availability ofthe data that, desirably, would be used to construct the water balances. It was found thatfor several items either no data or limited
data existed. These items were:—— Volume of water in soil moisture store

from groundwater. Many of the states and territories are aware of this impact, but none has
considered increased forestry development intheir water resource planning frameworks.
South Australia has introduced a systemof “water effecting permits” to account for the
impact of plantation forestry on groundwater
recharge in the south east of the state.

These observations – on the difficulty of
estimating soil moisture and other elements of
the asset accounts – and the impacts of changes
in land use on runoff – are noteworthy.
The Australian Bureau of Statistics had
already in 2006 issued guidelines referencing
the UN-SEEAW system,4 which was to be applied
to the reporting of the 2004–05 national wateraccounts.
However, the following statement fromthe introduction to Chapter 4 of the 2004–05
National Water Accounts for Australia5 isapparently at variance with one critical element of the SEEAW approach – namely thedistinction between consumptive and nonconsumptive uses:(no data);—— Volume of water in snowpack (nodata);
3

Australian National Water Commission 2005

4 Australian Bureau of Statistics (2006), Proposed
Methodology for Producing Regional Water Use
Estimates, 2004-05, cat. no. 4610.0.55.001, 1-4
5National Water Accounts for Australia (2004–05)

CHAPTER 10 Accounting for water: stocks, flows, and values

227

Table 4

1.

Water accounts for Australia, 2004–05
2.

Australian Capital

3.

Northern Territory

6.

Tasmania

Territory

4.

Queensland

7.

Victoria

New South Wales

5.

South Australia

8.

Western Australia

Water Consumption in 2004–05 (GL)
1

ACT

2

NSW

NT3

QLD4

SA5

TAS6

VIC7

WA8

Australia

Agriculture

1

4,133

47

2,916

1,020

258

3,281

535

12,191

Forestry and fishing

<1

11

<1

3

<1

4

8

25

52

Mining

<1

63

17

83

19

16

32

183

413

Manufacturing

<1

126

6

158

55

49

114

81

589

Elec and gas

-

76

1

81

3

<1

99

13

271

Water supply

5

631

8

426

71

20

793

128

2,083

Other

17

310

30

201

52

18

262

168

1,059

Household

31

573

31

493

144

69

405

362

2,108

Total

56

5,922

141

4,361

1365

434

4,993

1495

18,767

Total resource consumption %256

45,36955,784112,905

4,321

47,056

21,33249,094

336,117

This chapter examines the use of water within
the agriculture industry in Australia. Water
used by this industry includes stock drinking
water and water applied through irrigation
to crops and pastures.... Since the agricultureindustry does not use water in-stream, or
supply water to other users, total water use
is equal to water consumption. (emphasis
added)

Nevertheless, the accounts produced byAustralia are the most comprehensive available application of the SEEAW approach. Table 4,assembles data from the 2004–05 accounts.
This table shows the wide variation acrossthe country in the pattern and intensity ofresource use. The table is entirely based on
abstracted water, and thus masks the important
contribution that rainfall makes to rainfed agriculture and the natural environment.
It also demonstrates the uncertain impactof aggregating regional accounts into a national
account – which applies to many large countries
like Australia – where transfers of water between
regions are not economically feasible. While thenational picture shows that only 6 percent of
228

the annual water resource is consumed, this figure masks variations from less than 1 percent of
the available resource (Northern Territories) to
32 percent in South Australia, which is a severelywater-stressed area, and where extensive government interventions to restore ecosystem
health are underway.
Underlying these summary tables are many
more detailed reports – agriculture broken
down by crop; regions by basin; resources broken down into surface and groundwater; etc.
In many countries, rainfed agriculture isoften a much more significant water user than
irrigated agriculture; forestry may be larger still,and some countries have vast areas of rainfed
land that provide the basic resource for tourism
and recreational activities (for example, gameparks in Africa and wilderness areas in the
United States).
Efforts to translate these physical data into
financial information are quite limited. Data
from the Murray-Darling show returns fromvarious crops varying by a factor of almost 10
between rice and vegetables – confirming thedifficulty of placing a value on “water” even in a
Inclusive Wealth Reportsingle sector when divorced from the associatedrisks, management requirements, input costs,
perishability, etc.

6.

Conclusions

The terminology of the physical accounts presented by SEEAW is well defined, and allows
a country to report annual flows of water in
relation to economic sectors in a meaningful
way. Such data can assist national planning andthe formulation of approaches to scarcity andcompetition. Certainly, the availability of suchanalysis will improve inter-sectoral understanding of water issues.
In application, the SEEAW approach has
proved difficult, even in a sophisticated andhighly developed water economy such as
Australia. Especially in the stock accounts, key
data are not available – volume stored in icecaps, volume in streams, and volume in soil
moisture.
Since the SEEAW accounts are formulatedon the basis of industrial sectors for which
financial data are collected separately, it is relatively easy to link the accounts and provide firstindications of the role of water in each sector
and, by inference, the significance of water tothe economy. Already at this stage, however,
the interpretation can become problematic:
the fact that an industry generates $X of value
added and consumes $Y units of water cannot
be interpreted as indicating a value of $X/Y perunit of water for a number of reasons:• If water is plentiful for the industry inquestion, it may well be that usage could
be curtailed significantly without additional investment or reduction in value
added.
• Even where water is scarce, the relationship between the marginal value of waterand the average value is uncertain.
• Financial prices, which are generally what
we have available for this type of analysis,
will often diverge from economic prices(which adjust financial prices for distortions caused by subsidies, quota restrictions and taxes), and even more fromprices that reflect social issues and “externalities” such as damage to the environment.
Taken together, these issues suggest that
we very rarely know the precise relationshipbetween aggregate water availability and physical output; we know even less about the marginal relationship between water availability
and economic output, and we typically know
still less about the price that should properly be
assigned to the non-financial impacts of water
use and consumption.
Finally, it is clear that aggregating “water”
over time and space will entirely mask the variability that so profoundly affects the value ofwater to a country.
While these points cast significant, perhaps
insurmountable doubts on the possibility toconstruct a meaningful statement of a nation’s
water wealth, the first step of assembling dataon the sources and uses of water within theeconomy can only help move important political debates forward as competition increases,
and point to areas where interventions will bemost appropriate.
To meet this need, and also to link water tothe broader ecological and environmental status of a nation, SEEAW accounts should include
the “unmanaged” natural landscape, including forests, rainfed rangelands, and wetlands,
which are major features of the water economy
and potential components of the financial economy; “managed” areas including rainfed agriculture feature in the financial economy as wellas the water economy; and irrigated agriculture
is a dominant feature of the water economy inmany countries, as well as an important part of
the financial economy.

CHAPTER 10 Accounting for water: stocks, flows, and values229

References

Australian Bureau of Statistics. (2006).
Proposed methodology for producing
regional water use estimates, 2004-05. Retrieved from http://www.abs.gov.au/ausstats/
abs@.nsf/productsbytitle/7CD5E3C07FF926
8FCA2571EC007C9CCD?OpenDocument
Australian Bureau of Statistics & National Water Commission. (2006). Water accountAustralia, 2004-05. Retrieved from http://
www.water.gov.au/publications/ABS_Water_
Account_2004-05(complete_report).pdf
Falkenmark, M. (1989). The massive water
scarcity now threatening Africa - Why isn’t it
being addressed? AMBIO, 18, 112-118.
Israelsen, O.W. (1950). Irrigation principles
and practices. New York: John Wiley andSons, Inc.
Jensen, M.E. (1967). Evaluating irrigation
efficiency. Journal of Irrigation and Drainage
Division, American Society of Civil Engineers,93, 83–98.
Jensen, M.E. (1993). Impacts of irrigation anddrainage on the environment. 5th N.D. Gulhati
lecture. The Hague, Netherlands: ICID.
Molden, D. (2007). Water for food, water forlife: A comprehensive assessment of water management in agriculture. London: Earthscan.
National Water Commission. (2007).
Water balance assessment method. Retrieved from http://water.gov.au/WaterAvailability/Waterbalanceassessments/
WaterBalanceAssessmentMethod/index.
aspx?Menu=Level1_3_2_1
Perry, C. (2007). Efficient irrigation; inefficient communication; flawed recommendations. Irrigation and Drainage, 56(4), 367–378.
Shiklomanov, I. (1993). World fresh water
resources. In P.H. Gleick (Ed.) Water in crisis:
A guide to the world’s fresh water resources.
New York: Oxford University Press.
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un.org/unsd/statcom/doc07/SEEAW_
SC2007.pdf
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H. (1994). Eliminating irrigation efficiencies.
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org/docs/Willardson.pdf

230

Inclusive Wealth ReportChapter 11

Safeguarding the future of thewealth of nature
Sustainability, substitutability, measurement, thresholds, and aggregation issues in natural capital accounting for human well-being
Paul Ekins

Key Messages
Nature is very different from human, social,
and manufactured capital stocks in that it predates humanity and it operates through its own
complex laws and systems.
Most accounting for natural capital involves
assigning monetary values to the flows of benefits from that capital. A monetary measure suggests that one capital stock can be substituted
for another when trying to measure a country’s
total wealth in a multi-capital model. For natural capital, there is an emerging body of opinion that such substitutability is not complete,therefore accounting for it in this way could beseriously misleading.
The assumption of more or less complete
substitutability between natural capital andother capital stocks is sometimes referred to as
the “weak sustainability” assumption; while anassumption of limited substitutability is termed
the “strong sustainability” assumption.

The assumption of strong sustainability inrespect of certain important aspects of natural
capital would seem more consistent with thescientific evidence. Starting with this assumption when trying to understand the interactions between different forms of capital allows
substitutability to be considered to the extent
appropriate. Starting with an assumption ofcomplete substitutability (the weak sustainability perspective), and proceeding directly tomonetary valuation, tends to obscure thosesituations where this assumption is not valid.
While consumption is important to wellbeing, it is also affected by a number of otherimportant factors. The contribution of natural
capital to well-being has not been widely recognized in the literature, but that has started
to change in recent years as diverse contributions have been revealed through ecosystemassessments.

231

1.

Introduction

This chapter reviews a number of actual or
potentially problematic issues that have arisen
in relation to wealth accounting, which can
supplement or modify the overall picture of
wealth accounting as described in this report,
and that need to be taken into account in thepractice of it.
All the issues explored here (as is true for
wealth accounting as a whole) can be clearly
related to, and in this chapter are based on, afour-capitals model of wealth creation. The
model is described in Section 2, followed by definitions and discussions of human, social, and,in more length, natural capital – the three capitals usually given the least attention in wealthaccounting because of the emphasis given
to manufactured capital. As noted in earlier
chapters, the concept of capital is well suited
to framing a discussion of sustainability andsustainable development, and the four-capitals
framework enables these subjects to be treatedin an integrated way.
Most accounting for natural capital, including what is described in other chapters of thisreport, proceeds by assigning monetary values
to the flows of benefits from that capital andthereby inferring the value of the natural capital stock. This assumes that, in a multi-capitalmodel such as that presented here, there iscomplete substitutability between the capitalstocks1 that are being thus valued. For natural
capital, there is now a considerable amount ofliterature giving reasons as to why such substitutability is incomplete, and therefore accounting for it by this method is also likely to beincomplete. Section 3 gives a brief overview ofthese reasons and discusses in the light of themthe various methods by which natural capital

1 An assumption of substitutability between natural
capital and other capital stocks is sometimes referred
to as the “weak sustainability” assumption, while anassumption of limited substitutability is termed the“strong sustainability” assumption. This distinction isfurther explored below.

232

has been measured, and the advantages and disadvantages of these methods.
The concept of environmental sustainability has been developed largely to address issues
involving what has been called “critical natural
capital” (Ekins et al. 2003), when strong rather
than weak sustainability seems a more appropriate starting assumption. This is the subject ofSection 4, which starts by introducing the ideaof environmental functions. Environmental sustainability is then defined as the maintenance ofthe minimum thresholds of natural capital thatare required to sustain important environmental functions, and principles of environmental
sustainability as well as sustainability standards,
are articulated on this basis. This permits thedefinition of an indicator of environmental sustainability that shows the “gap” between current
uses of the environment and the sustainability
standard. The final part of this section describes
the main, recently developed method of measuring the flows of resources through the economy with a view to identifying whether they arebeing used sustainably, and relates this to theconcepts of resource efficiency and dematerialization, the achievement of which are important
if sustainable resource use is to be achieved in acontext of continuing economic growth.
If substitutability is one assumption at
the heart of most natural capital accounting,another is that wealth is the stock that provides
the flow of future consumption (the value of
which then needs to be discounted to arrive
at its present value). However, as shown in thefour-capitals model, the purpose of wealth creation is not consumption per se, but the maintenance and increase of human welfare. There is
now a considerable body of literature to showthat there are many more influences on humanwelfare than material consumption. Section 5
briefly explores this literature, in which various terms for welfare (for example, well-being),
tend to be used interchangeably. The literaturesurprisingly places very little emphasis on theinfluence of the environment on human wellbeing, despite the fact that it is intuitively obvious that environmental functions, or ecosystem
Inclusive Wealth ReportHu, SOu
Uh, UsoWes
Environmental services, ES

Esu

Welfare, utility,
U

COu

Pu
Stocks of capital, C

EesIntermediate production, M

Natural capital, EC
Ep
Human capital, HC

Wu

Goods

Hp

Investment, I

Ic

Mp
Social/organizational capital, SC

Manufactured capital, KC

Sp

Production process/national economy, P

Consumption, CO

Kp

Wastes, pollution, W

COc

Wc

Bads
Pc

Depreciation, D

Dc

Capital feedback effects

goods and services as they have also been called,
are clearly crucial for both human survival andhuman welfare. This emerges clearly from theecosystem assessments that have so far been
carried out, and the section closes with estimates of some values delivered by ecosystem
goods and services in the U.K. Section 6 concludes by briefly drawing together the various
strands of the chapter.

2.	The four-capitals model of wealthcreation
In order to treat these issues adequately, it isnecessary to be clear about the definition of
wealth that is being employed and to locate
the issues within a comprehensive theoretical framework that identifies the relationshipbetween wealth and human welfare and shows
how wealth can be created and destroyed. Sucha framework was set out in Ekins (2000, p.53),
and is illustrated here in Figure 1.

There is no space to elabo- Figure 1
rate the theory fully here, but A four-capitals model of
Figure 1 suggests that wealth wealth creation through acreation is the product of the process of production
joint application for productive purposes of different Note: In the flow descriptors, the upperkinds of capital, where capital case letters denote the source of theis a stock, or asset, that has the flow; lower case letters denote thecharacteristic of producing a destination. Those relating to the variflow of income or some other ous capital stocks have the C omitted
benefit. The four-capitals for simplicity.
model distinguishes between Source: Ekins (2000), p.53.
four different types of capital:
manufactured (or physical) capital (e.g., buildings, built infrastructure); human capital (e.g.,knowledge, skills, health); social capital (relationships and institutions); and natural (or environmental, ecological) capital.2 The four capitals

2
It may be noted that in this formulation, financial
capital is a form of social capital with the power tomobilize other forms of social capital and the otherthree capitals.

CHAPTER 11 Safeguarding the future of the wealth of nature

233

generally need to be combined in a production
process in order to generate their benefits (thisis least true of natural capital, which generates
many benefits independently of humans).
Inclusive wealth accounting requires thatthe stocks of the four capitals, and changes inthe stocks, be measured over time. This meansthat the forms of capital themselves need to be
defined in terms of indicators that are subject
to measurement. Indicators of manufactured
capital, both monetary and non-monetary, areroutinely used and need no further discussion
here. Because most attention in the rest of thischapter will be paid to natural capital, humanand social/organizational capital are discussed
briefly first, and will then not be discussed
further.

2.1

Human capital

Human capital is a well-established concept ineconomics, with a large literature (Zula andChermack [2007] provide a brief overview),
often associated with the name of Gary Becker(Becker 1993). There has been considerable
interest in the relationship between humancapital and productivity (see, for example, Stiles
and Kulvisaechana [n.d., but after 2003] fora literature review), and in how it might bemeasured.
In 2001, the OECD produced a publication
specifically on human and social capital, in
which it discusses measurement issues and theevidence that stocks of these types of capital are
related to economic performance and personal
well-being (as shown in Figure 1). Human capital was defined as “the knowledge, skills, competencies and attributes embodied in individuals that facilitate the creation of personal, socialand economic well-being” (OECD 2001a, p.18).
The key function in the creation of humancapital is learning. This may be learning within
the family and early childcare settings, formal
education and training, workplace training
and informal learning at work, or in daily life.
There is much evidence that learning is greatly
234

influenced by “cultural capital” – “the collection of family-based resources such as parental
education levels, social class, and family habits,
norms and practices which influence academic
success” (OECD 2001a, p.23). Major specificinfluences include work habits of the family;
academic aspirations and expectations and the
support and guidance to help achieve them; anda stimulating environment for thinking, imagination, and discussion of ideas and events.
Learning is negatively affected by social
disadvantage, but can be positively affected by
aspects of social capital to be discussed further
in the next section: “The potential for school,community and family partnerships to support
learning is especially relevant to families fromdisadvantaged areas and backgrounds where
they can at a treble disadvantage of poor accessto income and employment as well as social
networks” (OECD 2001a, p.92). Putnam (2000)
found that learning outcomes were strongly
and significantly correlated with a composite
measure of social capital comprised of the following indicators:• Intensity of involvement in communityand organizational life.
• Public engagement (e.g., voting).
• Community volunteering.
• Informal sociability (e.g., visiting
friends).
• Reported levels of trust.
There is substantial evidence that humancapital levels are positively related to wages,
employment, and economic growth. Indeed,
one would expect these to be the principal
economic benefits to flow from human capital.
There is also substantial evidence that humancapital is positively related to non-economic
social and personal well-being, which may inturn feed back into economic growth. In fact,“the indirect impact of education of economic
growth via social benefits may be as large as
the direct impacts” (OECD 2001a, p.33), where
the social benefits include better health, lower
crime, political and community participation, social cohesion, more volunteering andcharitable giving, and better educated children.
Inclusive Wealth Report

There is a case for regarding health itself as anelement of human capital, because it is clearly
related positively to productivity. These othersocial benefits of education may be regarded as
elements of social capital, to be discussed in thenext section, so that human and social capitalare obviously closely inter-related.
Human capital, the benefits flowing from it,or proxies for these may be measured in a number of different ways, all of them more or lessproblematic:• Education spending, or other expenditures such as on research and development. These are input measures. Thereis no guarantee that they result in human capital and corresponding output
benefits.
• Educational credentials (e.g., years ofschooling or other education at various
levels, or enrolment rates) and qualifications. These are output measures but
there is no guarantee that these outputs
are actually being put to productive use(i.e., they may be a stock of human capital in theory, but they may not be leading
to a flow of benefits).
• Various measures of training and thehigher skill levels to which they lead. It
is likely that employment-based training,although an input measure, leads to its
intended outputs and benefits because
those qualified in this way often moveinto more advanced employment in a
related field.
• Surveys of student achievements or adultskills, of which easily the most commonly investigated is various forms of literacy(e.g., prose, document, quantitative literacy).
• Health status.
• Indicators of motivation and productivity, such as absenteeism (for health orother reasons) from work.
• Employment, unemployment, and wages.
All jobs presuppose a certain level of human capital, and the level of this should
be related to wages.

•

Indicators of disadvantage, leading to
educational and learning disadvantages,
or of the outcomes of measures and policies to reduce it.
• Levels of invention or entrepreneurship,
as shown for example in numbers of patents or new business start-ups.
Some of these indicators are already measured in money terms, most obviously the firstof the bullet points above, and it is therefore notsurprising that this is the indicator most often
used in accounts of human capital creation (e.g.,
World Bank 2000). In chapter 2 of this report,
human capital estimates are mainly driven by
the years of total schooling of the population,
which is subsequently weighted by its shadow
price.3 Efforts to improve the measurement of
human capital have continued (see Le et al.
[2005] for a review) and, because of the importance of human capital to business success,many business organizations have their own
systems of indicators to measure their humancapital, although there seems to be little standardization of these (Robinson et al. 2008).
Further exploration of human capital measurement and related issues is beyond the scope of
this chapter.

2.2 Social capital
In an early treatment of social capital Coleman(1988) defined it as aspects of social structure thatfacilitate action, in terms of the importance ofobligations and expectations, information channels, and social norms to education and linked
it explicitly to human capital, writing: “Social
capital inheres in the structure of relations
between actors and among actors.” (Coleman
1988, p.S98). In essence, therefore, social capital derives from relationships. Distinctions in
the literature include those between “bonding,”

3
In this study, the human capital shadow price isrepresented by the present value of the labor compensation received by workers over an entire working
life.

CHAPTER 11 Safeguarding the future of the wealth of nature235

“bridging,” and “linking” relationships, wherebonding relationships relate to the close ties
mainly between kin and ethnic groups; bridging
relationships to those that allow individuals totranscend those groups; while linking relationships connect individuals and groups to othergroups and institutions. It should be noted
that, unlike other forms of capital, the attitudes
and activities generated by social capital may
not necessarily be in the broad social interest:
closely bonded groups may be exclusive; theactivities of some closely bonded groups may
be anti-social (e.g., criminal gangs); and othergroups may pursue their own narrow interests
at the expense of society at large (e.g., businessassociations or trade unions).
The definition of social capital in OECD
(2001a, p.41) is “networks together with sharednorms, values, and understandings that facilitate co-operation within or among groups.”
However, this seems to be an unnecessarily
narrow definition, and social capital could also
be taken to include various other social arrangements that are recognized by the OECD as being
closely related to their preferred concept:• Organizational capital, which “reflects
the shared knowledge, teamwork andnorms of behavior, and interaction within organisations” (OECD 2001a, p.19).
• Cultural capital, which are “the habits orcultural practices based on knowledge
and demeanours learned through exposure to role models in the family andother environments” (OECD 2001a, p.23).
• Political, institutional, and legal arrangements, including the financial system.
Social capital is discussed in some detail in
World Bank (1997, pp.77ff.). This publication
notes that there are broadly three views on whatforms social capital: informal and local horizontal associations; hierarchical organizations,such as firms and professional associations; andformalized national structures, such as government and its agencies and legal arrangements.
These three descriptions of social capital share
several common features:• “All link the economic, social, and political236

spheres. They share the belief that social
relationships affect economic outcomes
and are affected by them.
• All focus on relationships among economic agents and how the formal or informal organization of those can improvethe efficiency of economic activities.
• All imply that “desirable” social relationships and institutions have positive externalities. Because these cannot be appropriated by any one individual, eachagent has a tendency to under-invest insocial capital; hence, there is a role forpublic support of social capital building.
• All recognize the potential created bysocial relationships for improving development outcomes but also recognize thedanger for negative effects. Which outcome prevails depends on the nature of
the relationship (horizontal versus hierarchical) and the wider legal and politicalcontext” (World Bank 1997, p.79).
Based on these definitions of social capital,
the World Bank (1997, p.88) suggests a numberof indicators of social capital. Table 1 compares
the headings for social capital given in OECD
(2001a) and World Bank (1997).
In the intervening years, publications havefurther explored the policy implications of
the social capital concept (e.g., Productivity
Commission 2003); the health implications (e.g.,
Lochner et al. 2003); what kinds of social capital do most to increase productivity or otherbenefits (e.g., Welzel et al. 2005); as well as taking forward the discussion about appropriate
indicators (e.g., Cavaye 2004). These issues areoutside the scope of this paper, but are clearly
relevant to any comprehensive articulation of
the four-capitals framework.
As with human capital, inclusive wealthaccounting should ideally seek to computechanges in quantities of social capital in monetary terms. For human capital, as already noted,
education spending is often used. For social
capital, the obvious difficulties of expressing
relationships in monetary terms have so far
ruled out this approach.
Inclusive Wealth Report2.3 Environmental/natural capital

Table 1

Headings for indicators of social capital
From Figure 1, a broad definition of natural
capital might be everything in nature (biotic
and abiotic) capable of contributing to humanwell-being, either through the production process or directly. As is discussed further below,
because natural capital has featured regularly
in various definitions of sustainability and sustainable development (see, for an early example,
Pezzey 1992, pp.55ff.), more attention has been
paid to the concept as sustainable development
has risen up the public policy agenda. In thiscontext, considerable efforts have been invested
in developing and making environmental indicators operational. For example, EUROSTAT produced a set of environmental indicators, basedon a major expert consultation (EUROSTAT
2001a), while the European Environment
Agency regularly publishes its “Environmental
Signals” report (most recently EEA 2011).
The OECD’s main source of environmentally
relevant data is published as a compendium of
indicators (OECD 2011).4 It is structured according to a Pressure-State-Response (PSR) framework, where Pressures include both direct environmental pressures and the indirect pressureof the human activities producing the directpressures; the States refer to various environmental conditions; and the Responses relate
to societal intentions and actions in respect
to the environmental conditions, and include
general data. The compendium has been published roughly every two years since 1993 and isused as the indicator framework for the OECD’scountry environmental performance reviews.
In 2001, 10 headline indicators were selectedfrom this compendium (OECD 2001b), and theindicators were also selected or combined toform the environmental indicators of the OECDsustainable development indicator set (OECD1998, 2001c).

4 In 2011, the compendium has different chapters inseparate pdf files, with data in different chapters fromdifferent years, the latest being 2008.

OECD

World Bank(OECD, 2001a)(World Bank, 1997)

Context indicators

Horizontal associations

Self-sufficiency

Civil and political society

EquitySocial integration

HealthLegal and governanceaspects

Social cohesion

The frameworks of environmental indicators produced by EUROSTAT and the OECD arelisted in Table 2. There is substantial overlap,
but also a few differences.
A relatively early attempt to define trends inthe stock of capital through what were calledresource indicators was made by the OECD (2001c,
pp.69ff.). This was an early precursor for natural
capital of the kind of inclusive wealth accounting approaches that have been developed sincethen and that are described in this report. The
OECD indicators were:• changes in air quality (changes in emissions of CO2 or GHG, NOx, and SOx);• changes in water resources (intensity ofwater use);• changes in land and ecosystems (changes
in land use);• changes in biodiversity (protected areas);• changes in use of energy resources(growth in consumption of energy resources);• net changes in produced assets (change
in value of the net [manufactured] capital stock);• net changes in financial assets (current
account balance to GDP ratio);• technological change (multi-factor productivity growth rate);• changes in the stock of human capital(changes in the proportion of the population with upper secondary/tertiary

CHAPTER 11 Safeguarding the future of the wealth of nature

237

Table 2

Structure of the environmental indicator sets ofEUROSTAT and OECD••EUROSTATOECD

Themes (pollution)
Climate change
Ozone depletion
Air pollution
Waste
Water pollution
Dispersion of toxic substances

Pollution issues
Climate change
Ozone layer depletion
Air quality
Waste
Water quality

Themes and indicators(resource depletion)
Water consumption
Timber balance
Urbanization of land
Energy use
Fishing pressure
Loss of biodiversity
Mixed resource and pollution
themesMarine environment andcoastal zones
Urban environmental problems

Resource issues
Water resources
Forest resources
Land resources
Energy resources
Fish resources
Biodiversity (and wildlife)
Mineral resources
Key sectors
Energy, transport, industry,
agriculture
Other issues
Risks
Environmental expenditure andtaxes
Multilateral environmental
agreements

qualifications);
investment in human capital (growth in
expenditure on education); and• depreciation of human capital (standardized unemployment rates).
OECD (2001c) also defines a number of outcome indicators, which are related more to theright hand side of Figure 1, from which they may
contribute to human welfare (e.g., consumption) or feed back into the stocks of capital ina positive (e.g., health) or negative (e.g., waste
generation) way. These indicators are:• consumption (household final consumption expenditure per capita);• sustainable consumption (waste generation intensities);• income distribution (D9/D1 decile ratio/
Gini coefficient);• health (life expectancy/disability-free life
expectancy, environment-related health•238

expenditure);work status/employment (employmentto-population ratio); andeducation (enrolment rates).

3.	Sustainability and sustainable development
Conceiving of wealth creation in terms of theinteraction between different capital stocks
allows the ideas of sustainability and sustainable development to be formulated in robust
terms. Sustainability itself simply means thatwhatever is being considered has the capacity
for continuance. As discussed in Ekins (2003),
the literature on sustainable development hascome to a broad consensus that sustainable
development entails meeting human needs andincreasing quality of life now and in the future,
the multi-dimensional nature of which has led
to sustainable development being regarded ashaving economic, social, and environmental“pillars,” or dimensions.
With regard to the economic dimension (asis also true for the idea of manufactured capital),
the sustainable development concept has contributed little that is new. Economists have long
had guidelines as to whether economic growthand development should be regarded as sustainable. The rate of inflation, public sector net
credit requirement, and balance of payments,
among others, are all considered to be important indicators of economic sustainability.
The idea of social sustainability, in contrast,
is both far less developed and seems much more
intractable. It is true that social sustainability isaffected by such conditions as poverty, inequality, unemployment, social exclusion, and thecorruption or breakdown of social institutions.
But the relationship between sustainability
and these conditions is clearly very complex
and quite different between different societies. It seems unlikely that a social sustainability threshold for unemployment or inequality,
comparable for example to the target rate of
inflation for economic sustainability, will be
Inclusive Wealth Reportidentified. What seems more important in thiscase, is to ensure that the direction of change
is toward what is considered necessary for sustainability, rather than the attainment of someparticular number.
Environmental sustainability is related tonatural capital, which is the main concern of
this chapter, and this concept is discussed anddeveloped in some detail in Section 4. However,
if sustainable development entails, at a minimum, sustaining the flows of benefits that giverise to human welfare and therefore the capitalstock that produces the benefits, the issues that
immediately arise are whether there is substitutability between capitals (in the literature, thedifference between weak and strong sustainability); whether the flows from the capitals
can be valued in monetary terms (especiallyproblematic for natural capital) and, if so, how(valuation of the capital stocks depends on valuation of the flows from them); and the difference between the economic, social, and environmental dimensions of sustainability. Theseissues are explored briefly here (and in moredetail in Ekins 2000), and lead naturally into a
discussion as to how sustainable development
and progress toward it, should be measured.

3.1

Weak and strong sustainability

It has been noted above that sustainable development is intended to deliver benefits acrosseconomic, social, and environmental dimensions of human life. The first point to be madeabout this combination of objectives is that
their simultaneous achievement by an industrial economy across all major environmental
dimensions would be unprecedented. In fact,
if industrial production can be characterized
as above as the judicious combination of fourkinds of capital stock, then one of the main
discernible aspects of this process in the history
of industrialism is the systematic depletion ofnatural capital in favor of manufactured andhuman capital.

As illustrated in Figure 1, the purpose of production is to satisfy human needs and increasehuman welfare and quality of life. Sustainableproduction and, therefore, sustainable development require that the capital stocks from which
the satisfaction of human needs and increased
quality of life derive are maintained or increased
over time.
This immediately raises the question as
to whether it is the total stock of capital thatmust be maintained, with substitution allowed
between various parts of it, or whether certain
components of capital are non-substitutable,that is they contribute to welfare in a unique
way that cannot be replicated by anothercapital component. With regard to natural
capital, Turner (1993, pp.9–15) identifies four
different kinds of sustainability, ranging fromvery weak (which assumes complete substitutability between this and other capital types) tovery strong (which assumes no substitutability
so that all natural capital must be conserved).
Few would contend that all natural capital issubstitutable, while very strong sustainability
has been called “absurdly strong sustainability” (Daly 1995, p.49) in order to dismiss it frompractical consideration. Turner’s more interesting intermediate categories are:• Weak environmental sustainability,
which derives from a perception thatwelfare is not normally dependent on a
specific form of capital and can be maintained by substituting manufactured fornatural capital, though with exceptions.
• Strong environmental sustainability,
which derives from a different perception that substitutability of manufactured for natural capital is seriously
limited by such environmental characteristics as: irreversibility, uncertainty
and the existence of “critical” components of natural capital, which make aunique contribution to welfare. An evengreater importance is placed on natural
capital by those who regard it in many
instances as a complement to man-madecapital (Daly 1992, pp.27ff.).

CHAPTER 11 Safeguarding the future of the wealth of nature

239

The point at issue is which perception mostvalidly describes reality. Resolving this pointshould be an empirical rather than a theoreticalor ideological matter. However, if weak sustainability is assumed a priori, it is impossible toshow ex post whether the assumption was justified or not, for the following reason:
The assumption underlying weak sustainability is that there is no essential difference
between different forms of capital, or between
the kinds of welfare that they generate. This
enables, theoretically at least, all types of capitaland the services and welfare generated by them
to be expressed in the same monetary unit. In
practice, there may be insuperable difficulties
in performing the necessary monetization andaggregation across the range of issues involved,
but the theoretical position is clear and strenuous efforts are being made to make it operational. But the numbers that emerge from these
efforts can only show if weak sustainability has
been achieved, that is whether overall welfare
has been maintained. They cannot shed any
light on the question as to whether the assumption of commensurable and substitutable capitals was justified in the first place.
By keeping different kinds of capital distinct from each other, the strong sustainability assumption, in contrast, can examine eachtype’s particular contribution to welfare. The
examination may reveal that, in some cases, thewelfare derived from one type of capital is fullycommensurable with other welfare from production. It can be expressed in monetary form sothat, in these cases, substitutability with otherforms of capital exists, and the weak sustainability condition of a non-declining aggregate
capital stock is sufficient to maintain welfare.
In other cases, the outcome of the examination
may be different. The important point is thatstarting from a strong sustainability assumptionof non-substitutability in general, it is possible
to shift to a weak sustainability position wherethat is shown to be appropriate. But startingfrom a weak sustainability assumption permits
no such insights to enable exceptions to be
identified. In terms of scientific methodology,
240

strong sustainability is therefore greatly preferred as the a priori position.
In respect to natural capital, there are othertheoretical reasons for choosing the strong sustainability assumption, in addition to the practical reason of the sheer difficulty of carryingout the necessary weak sustainability calculations for complex environmental effects. Victor(1991, pp.210–211) notes that there is a recognition in economics going back to Marshall that
manufactured capital is fundamentally different from environmental resources. The former
is human-made and reproducible in the quantities desired, the latter is the “free gift of nature”
and in many categories is in fixed or limited supply. The destruction of manufactured capital isvery rarely irreversible (this would only occur if
the human capital, or knowledge, that createdthe manufactured capital had also been lost),
whereas irreversibility is common in the consumption of natural capital with such effects
as species extinction, climate change, or eventhe combustion of fossil fuels. Moreover, to theextent that manufactured capital requires natural capital for its production, it can never be acomplete substitute for resources.
Victor et al. (1998, p.206) identify the elements of natural capital that are essential forlife as we know it as: water, air, minerals, energy,
space, and genetic materials, to which might be
added the stratospheric ozone layer and therelationships and interactions between theseelements that sustain ecosystems and the biosphere. Some substitution of these essential elements by manufactured and human capital canbe envisaged, but their wholesale substitutability as assumed by weak sustainability, appears
improbable, certainly with present knowledge
and technologies. In fact, if the process ofindustrialization is viewed as the applicationof human, social, and manufactured capital tonatural capital to transform it into more humanand manufactured capital, as suggested above,
then it is possible to view current environmental problems as evidence that such substitutability is not complete. If our current development
is unsustainable, it is because it is depleting
Inclusive Wealth Reportsome critical, non-substitutable componentsof the capital base on which it depends. This
has important implications for how sustainable
development, and progress toward it can andshould be measured.
Summarizing this literature, Dietz and
Neumayer (2007, p.619) list four reasons why
the strong approach to sustainability may be
preferred to the weak: risk and uncertainty;
irreversibility; risk aversion; and the ethicalnon-substitutability of consumption for natural capital.

3.2 Measurement and indicators of sustainable development
Since the UN Conference on Environment andDevelopment in 1992, which established theidea of sustainable development as an overarching policy objective, there has been an explosionof activity to develop sustainable development
indicators (SDIs) in order to determine whether
sustainable development is actually being
achieved. Because the meaning of sustainable
development was not particularly clear (and is
still often the source of some confusion), thisactivity was characterized by much experimentation. Many indicator sets were put forward
by different bodies at different levels (international, national, regional, local), and substantial
efforts have since been invested in seeking torationalize these into “core” sets that can beused for comparison and benchmarking, while
the development of particular sets of indicatorsfor specific purposes has continued to flourish.
There are two main approaches to constructing indicators of sustainable development: theframework approach which sets out a range ofindicators intended the cover the main issues
and concerns related to sustainable development; and the aggregation approach, whichseeks to express development-related changes
in a common unit (normally money), so thatthey can be aggregated. A limitation of the first
approach is that unless all the indicators in theframework are moving in the same direction (i.e.,

all making development more or less sustainable), it is not possible to say whether, in total,sustainable development is being approached.
In respect to the second approach, Kumar (2010)
recently exposed the issues that arise with theeconomic valuation of the environment, while
Foster (1997) explored many of the same issues
more than 10 years earlier. While such valuation can be both meaningful and important, amajor limitation is that it is often impossible,
very difficult or very controversial to convert
all changes of interest to money values, or any
other common numeraire, and this limitation
applies most strongly to precisely the largest
environmental effects that are therefore of mostpolicy interest. With the valuation approach,therefore, the change in respect of sustainable
development may be expressed as a single number, but the number may lack credibility.
A third approach, confined to assessing environmental sustainability, involves establishingstandards of environmental sustainability andcalculating the “gap” between current environmental situations and the standards.
The first two of these approaches are now
described briefly. The third is described in
Section 4.
Frameworks of indicators for sustainable development
In 1996 the UNCSD published its first set of SDIs,
comprising 134 economic, social, and environmental indicators (UN 1996). The indicators
were structured in a matrix that related Driving
Force, State, and Response indicators to thechapters in Agenda 21.5 Because it felt that not
all the indicators were relevant for the European
Union, EUROSTAT carried out a study using a
subset of 36 of these indicators, publishing theresults of the study in 1997 (EUROSTAT 1997).
UNCSD subsequently produced a “core” set of
59 SDIs based on its original set, and EUROSTAT(2001b) did another study involving 63 indicators,
5 Agenda 21 was the ‘Plan of Action’ that was agreed
at the Rio Earth Summit in 1992

CHAPTER 11 Safeguarding the future of the wealth of nature241which related closely to the UNCSD core set andshowed the very wide range of issues that sustainable development is considered to cover.
There are many other frameworks of SDIs.
Internationally, one of the best known is that
produced by the Organisation for Economic
Co-operation and Development (OECD). The
OECD was given a mandate to work on sustainable development in 1998. Pursuant to this its
work has resulted in theoretical, methodological, and policy- and indicator-oriented publications (OECD 1998; 2000a,b; 2001c,d,e). The firstpublication in this field (OECD 1998) was largely
environmentally focused, but this was followed
by a conference on sustainable development
indicators in 1999, the proceedings of whichwere published in 2000 (OECD 2000a). This
contained a set of “possible core sustainable
development indicators,” a number of country
case studies on different aspects of sustainable
development indicators, and sectoral/environment indicators for the major environmentallysignificant sectors. It also contained a new setof social indicators, with context indicators andstructured according to the themes: promoting
autonomy (or self-sufficiency), equity, healthyliving (or just health), and social cohesion.
Within the themes the indicators were grouped
according to social status and societal response(similar to the Pressure-State-Response framework it had used for environmental indicators).
Two other indicator frameworks should also
be described:• Those related to the EU Sustainable Development Strategy, adopted in 2006 andreviewed in 2009,6 and Sixth Environmental Action Programme (6EAP), which
was adopted to run for 10 years from2002.7 The priorities of the former were:—— Combating poverty and social exclusion—— Dealing with the economic and social
implications of an ageing society
6

See http://ec.europa.eu/environment/eussd/

7 EC, 2001, also see http://ec.europa.eu/
environment/newprg/

242—— Climate change and the use of clean
energy—— Addressing threats to public health inrelation to hazardous chemicals andfood safety—— Managing natural resources more responsibly—— Improving the transport system andland-use management
The main themes of the 6EAP are:—— Climate change—— Nature and biodiversity—— Environment and human health—— Waste and resources
In December 2001 the EU Council of
Ministers agreed a set of seven headline
indicators to measure progress in relation to the 6EAP and the last four of thepriorities of the EU Sustainable Development Strategy, and an “open list” of a further 33 indicators.
• The indicators related to the U.K. Sustainable Development Strategy, which were
published as DETR (1999b). The framework contained 152 indicators, of which
15 were identified as Headline indicators.
Regional and local versions of the indicators were produced (DETR 2000a,b) for
use at the relevant levels.
Aggregations of indicators for sustainable development
An advantage of the framework approach toindicators of sustainable development is thateach of the many aspects of sustainable development can be specifically reported on in its
own terms, and trends for the separate aspects
can be identified. However, a disadvantage isthat without combining the indicators in someway, it is not possible to draw any overall conclusions about progress towards sustainable
development unless all the indicators happen
to be moving in the same direction in relation
to that progress. This is most unlikely to be thecase.

Inclusive Wealth ReportA number of methods have been developed
for the aggregation of indicators so that overall
impacts can be assessed:
Aggregation into environmental themes
This was the approach underlying theNetherlands National Environmental PolicyPlan process. It is described in Adriaanse (1993).
Aggregation across environmental themes
One method of doing this is to weight the different themes according to perceptions of environmental performance. An example of thismethod is the Ecopoints system developed by
BRE (BRE 2008). Another method depends on
the setting of sustainability standards for thethemes, and then aggregating them according
to the distance from the standard. An exampleof this approach based on the concept of the“sustainability gap” is given in Section 4.
Aggregating across environmental and otherthemesThis can be implemented by using multi-criteria analysis, or relating the themes to some concept such as quality of life or human development. The annual United Nations Development
Programme’s Human Development Index is an
example of this approach.
An innovative application of this method
was implemented by the Consultative Groupon Sustainable Development Indicators (CGSDI
2007), which was established in 1996 and is an
Internet-based working group drawing members from many different institutions and countries. Their Dashboard of Sustainability is nota specific selection of indicators as such, but a
way of presenting sustainability indicators inan aggregated form, with the aim of providing
an informative and easily grasped and communicated overview of the complex relationships
among the social, environmental, and economic dimensions of sustainable development
issues. Indicators from the three sustainability
dimensions form the basis for aggregated social,environmental, and economic indices, which
are then further aggregated into one “policy

performance index” and presented as a pie chartorganized in three concentric circles. The outercircle contains the actual indicators, the nextlevel circle contains the three sub-indices, andthe inner circle contains the overall policy performance index. Clearly, the Index is only as
good as the indicators used for it and the proponents of this methodology stress the continued need for improved and broadened indicators. However, the methodology is being quite
widely used at the local and regional as well as
the national level.
Another use of indices to measures progress
towards environmental sustainability is the calculation of the “sustainability gap,” as describedin the next section.
Expressing the different environmental impacts in monetary form
Starting from an assumption of weak sustainability, and using techniques of environmental
valuation, environmental indicators can be
expressed in monetary form and, once expressedin this form, they can be added them up according to some theoretical position. Some calculations are based on economic welfare theory(see Nordhaus and Tobin [1972] for an earlyexample), and these have been developed into
proposals for the calculation of a Green GDP (seeEkins [2001] for a discussion of the theoreticalproblems associated with this). The Index of
Sustainable Economic Welfare (ISEW) (first proposed by Daly and Cobb [1989]) starts from consumer expenditure and then adds various social
or environmental impacts (which can be positive or negative) to arrive at a supposedly more
realistic assessment of changes in human welfare than represented by changes in GDP. ISEW
has been calculated for a number of countries(see Posner and Costanza [2011, p.1973] for a listof studies), while the Friends of the Earth website called Measuring Progress enables people
to calculate their own ISEW.8 ISEW was further
developed into the Genuine Progress Indicator8

See http://www.foe.co.uk/community/tools/isew/

CHAPTER 11 Safeguarding the future of the wealth of nature

243

(GPI),9 which has been calculated for a numberof countries, U.S. states, and other sub-national
entities (again, see Posner and Costanza [2011]
for a list). All the methods based on giving monetary values to different impacts essentiallytake the weak sustainability approach in theterms discussed earlier, assuming that the different aspects of sustainable development, andthe different forms of welfare associated withthem, are commensurable and can therefore be
expressed in the same numeraire. As was noted
earlier, the implementation of this assumption
does not permit any subsequent attempt toassess whether it was justified, except in termsof the plausibility of the results and conclusions
to which it leads.
The situation is well-illustrated by the WorldBank’s genuine savings indicator (World Bank
2000), which is one of the best known methods
to express different aspects of sustainable development in monetary terms. The indicator is
explicitly based on a capitals methodology suchas that described above. It is computed from thefigure for net domestic savings (assumed to comprise net additions to, or investment in, physicalcapital), plus education expenditures (assumed
to comprise net additions to, or investment in,human capital minus depletion of energy, mineral, and forest resources, and damages fromCO2 emissions (assumed to comprise net loss ofnatural capital). All the loss of natural capitalhas been computed in money terms, to enable
the relevant calculation to be made. In addition to assuming weak sustainability, such an
approach assumes that all education expenditures are converted into productive human capital, which may not be the case, and covers only
a relatively small range of environmental issues
compared to those assessed in frameworks ofenvironmental indicators such as those presented above. Moreover, no attempt in this publication is made to incorporate changes in social
capital in this indicator. More recent work by
the World Bank (2006) incorporates a number
9 ee for some background to the GPI http://
en.wikipedia.org/wiki/Genuine_progress_indicator244

of changes to the genuine savings calculations,while preserving its essential methodology. For
example, intangible (human and social capital)
is now estimated through regression analysis ofa residual once other aspects of wealth (natural, and produced [“manufactured” in Figure
1 above] capital) have been accounted for. A
functioning justice system emerges as making
a particularly important contribution to wealthcreation (p.xviii).
According to the calculations of genuinesavings in World Bank (2000, Table A1, p.10), allOECD countries and the great majority of developing countries have positive genuine savings.
This picture is broadly confirmed in the follow
up genuine savings calculations by the WorldBank (2006, p.41), with in addition the East
Asian countries showing strongly positive genuine savings rates and Latin America and the
Caribbean also showing positive rates (except
for a brief period in the 1980s). Only North
Africa and the Middle East emerges as a region
with consistently negative genuine savings
rates “reflecting high dependence on petroleum
extraction,” with the extent of this result beingof course highly dependent on the oil price (thehigher the price, the higher the calculated costof oil depletion to be subtracted from other savings categories).
While a negative genuine savings rate isa clear sign of unsustainability, World Bank
(2006) advocates caution in the interpretationof a positive genuine savings rate (p.38). This isbecause a number of important environmental issues are not included in the calculationsof natural capital, because of a lack of data.
Notwithstanding this, if the genuine savings
rate truly is “a sustainability indicator,” as bothWorld Bank 2000 (p.2) and World Bank 2006
(p.36) appear to claim, this would seem to indicate that most countries, and all OECD countries,
are sustainable. If this is true, then the issue ofsustainability is much less important than often
seems to be supposed in policy-making (it is notclear, for example, why the EU needs a “sustainable development strategy,” if all EU countries
are already sustainable, as the genuine savings
Inclusive Wealth Reportindicator in this publication suggests). Thisappears to put in question either the weak sustainability assumption on which the indicator isbased, or the methodology by which it has been
computed.
As noted earlier, the indicator itself cannot
help to address these questions, although WorldBank (2006) does seek to address the issue at theheart of the weak/strong sustainability debate
outlined earlier: the substitutability between
natural and other kinds of capital. In Chapter
8 it uses a constant elasticity of substitution(CES) production to estimate the elasticities ofsubstitutions between land, labor, and capital.
It is encouraging to find that these appear to bequite high, suggesting that other capitals canindeed substitute for natural capital, at leastin some cases. However, it also acknowledges
that this is preliminary work which omits many
important environmental functions so that theresults are by no means definitive.
One other fairly strong conclusion fromWorld Bank (2006) is also questionable froma strong sustainability perspective, namely:“The level of natural wealth per capita actuallyrises with income. This contradicts the common assumption, that development necessarily
entails the depletion of the environment andnatural resources” (p.32). But the level of natural
wealth is the product of the quantity of natural
wealth and its value. If its value increases at afaster rate than its quantity declines, then its
level will increase even as the physical quantity
declines (which is what is normally meant by
the word “depletion”). Of course, if the natural
wealth can be completely substituted by other
wealth (as is assumed under weak sustainability
and the very act of valuation), then depletion of
it may not matter, but that is not the same assaying that depletion has not taken place.
Those who wish to start from a strong
sustainability approach will therefore wish to
go beyond the genuine savings indicator andassess sustainability separately across the different capitals to see whether the broad sustainability conclusions of the genuine saving indicator are justified. The next section describes

such an approach in respect of environmental
sustainability.
There is also one other area in which WorldBank (2006) seems to tell an incomplete story, in
its treatment of wealth, welfare and consumption. Wealth is presented as “the present valueof future consumption” (p.xiv), while undercertain conditions “wealth per capita is thecorrect measure of social welfare” (p.17). Thismeans that “current net saving should equal
the change in future well-being, specifically thepresent value of future changes in consumption”(p.xvii). This is standard economic practice,with a detailed theoretical justification given in
Box 1.1. (pp.15–17), but it is at variance with theincreasing literature on well-being that identifies many factors apart from consumption thatare important to this condition. Outlining a different perspective on human welfare and wellbeing is the purpose of Section 5.
Finally, it is clear that the methodologyof World Bank (2006) is not the last word on
comprehensive wealth accounting. Arrow et al.
(2010), building on the theoretical foundationsof Arrow et al. (2003), significantly changes
several aspects of the methodology, in the calculation of comprehensive wealth and of several components of comprehensive investment(see p.14). They also extend the methodology
to account for population growth, technological change, different aspects of human capital(including health) and environmental quality.
However, the approach remains rooted in weaksustainability. In empirical analysis of the U.S.,
China, India, Brazil, and Venezuela, all the countries except the U.S. showed net natural capital
depletion. But only with Venezuela was this notoffset by investment in other kinds of capital (inChina, in reproducible [manufactured] capital;in the other countries human capital). Only
Venezuela therefore clearly emerges as “unsustainable” by this metric. Chapter 3, which relies
methodologically on Arrow et al. (2010) reports
a decrease of natural capital for 17 out of 20

CHAPTER 11 Safeguarding the future of the wealth of nature

245

Figure 2

4.

Environmental sustainability

The relationship between
environmental functions
and human benefits

4.1 Understanding environmental sustainability

As noted at the beginning of the previous section, sustainability itself simply means that
Natural capital
whatever is being considered has the capacity for continuance. Its interpretation whenapplied to the environment must define whatneeds to be sustained for environmental susHuman
Environmental
tainability to be achieved. In line with the overbenefits
functions
all capitals approach taken here, what needs to
Economy,Ecosystem goods andhealth,be sustained from the environment conceived
services, including
welfareResources, waste
as natural capital is the flow of benefits thatabsorption
humans derive from it.
services (life-support,
The key contribution of the environment (inamenities, etc.)
Figure 2 shown in total as the biosphere, or justnatural capital) to the human economy, and tohuman life in general, can be envisaged to takeplace through the operation of a wide range ofcountries10 studied (the three exceptions are “environmental functions.” This concept was
Japan, France, and Kenya). Nonetheless, when first employed in economic analysis by Hueting,looking at the different capital forms together, who defined environmental functions as “possible uses” of the environment (Hueting 1980,
it is only Russia that has a decrease in inclusive
wealth. It is also worth remarking that another p.95). De Groot has subsequently defined them
five countries go into negative growth rates in as “the capacity of natural processes and comwealth when changes are measured at a per ponents to provide goods and services that satisfy human needs” (De Groot 1992, p.7). Linking
capita level.
with the discussion of capital above, theseThose who feel that such a result fails to“naturalprocesses and components” can in turnreflect the evidence from environmental scienceof great and increasingly threatening environ- be identified as the flows from and stocks ofnatural capital. The flows may also be called
mental dislocation will be inclined to turn to astronger notion of sustainability for conceptual ecosystem goods and services, some of which
underpinning and associated indicators. This is flow into the production process, and others ofwhich contribute directly to human welfare, as
the subject of the next section.
shown in Figure 1.
As shown in Figure 2, the functions may beseen as being of three broad kinds: the provision of resources, the absorption and neutralization of wastes, and the generation of services
ranging from life-support services (such as themaintenance of a stable climate) to amenity
10 Australia, Brazil, Canada, Chile, China, Colombia,
and recreation services (see Pearce and Turner
Ecuador, France, Germany, India, Japan, Kenya, Nigeria,[1990, pp.35ff.] for more detail on this categoriNorway, Russian Federation, Saudi Arabia, Southzation). These three sets of functions collectively
Africa, United Kingdom, United States of America, andboth maintain the biosphere itself (the positive
Venezuela.
Biosphere

246

Inclusive Wealth Reportfeedback on the left of the diagram), and contribute to the human economy, human health,and human welfare. However, the economy’s
use of the environment can impact negatively
on the biosphere, which can in turn impair its
ability to perform its environmental functions.
In terms of Figure 2, environmental sustainability requires the maintenance of important environmental functions and the natural
capital which generates them, where importantenvironmental functions may be considered
to be those that are not substitutable, those
whose loss is irreversible and is likely to leadto “immoderate” losses (i.e., those considerably
greater than the costs of maintaining the functions), and those that are crucial for the maintenance of health, for the avoidance of substantial
threats (such as climate stability), and for economic sustainability.
The interactions in Figure 2 also draw attention to a further distinction between environmental functions that needs to be emphasized,a distinction between “functions for” and “functions of” (Ekins et al. 2003). The “functions for”
are those environmental functions that provide
direct benefits for humans. These are the functions which are generally most easily perceived
and appreciated, and towards the maintenanceof which most environmental policy is directed.
The “functions of” the environment arethose which maintain the basic integrity of natural systems in general and ecosystems in particular (shown in Figure 2 as the positive feedback to the biosphere). These functions are noteasily perceived, and scientific knowledge about
them is still uncertain and incomplete. What
may be said with certainty, however, is thatwhether science understands these functions or
not, and whether people value or are ignorant
about them or not, the continued operation of
the “functions of” the environment is a pre-requisite for the continued performance of many of
the “functions for” humans. Looked at in isolation, these “functions of” the environment may
appear useless in human terms, and therefore
dispensable. Considered as part of a complex
natural system, these functions may be essential

for the continued operation of other functionsof much more obvious importance to humans.
The danger is that the isolated view, or scientificignorance about the natural complexity, may
result in “functions of” being sacrificed for economic or social benefits, without appreciationof the wider implications. It is these “functionsof” the environment that present some of thegreatest challenges for valuation, because there
is no discrete flow of benefits to humans thatcan be identified from them.
The situation is made more complex still by
the fact that there is clearly an impact from theperformance of the “functions for,” especiallywhen they are enhanced by human intervention, on the “functions of” (shown in Figure 2
by the negative feedback to the biosphere). As
an example, increases in agricultural productivity, perhaps through intensification, may haveserious negative effects on the functions of
ecosystems, as may the disposal of wastes above
ecosystems’ critical loads. Scientific uncertainty
about these effects, and about thresholds ofresilience for the “functions of,” argues for caution over activities which may threaten them.
Thus, environmental sustainability in thischaracterization entails the maintenance of theenvironmental functions at such a level thatthey will be able both to sustain their contribution to human benefits (the economy, health.
and welfare) and to maintain the biospherefrom which they derive. The requisite levelacross different environmental functions may
be estimated using both environmental science and social preferences for environmental
quality. The environmental dimension of sustainability is therefore different from both theeconomic and social dimensions, in that it ispossible to articulate principles of sustainability,
and thence to derive thresholds and standards
for environmental sustainability, as discussed
below, according to which it is possible to distinguish between sustainable and unsustainable use of the environment and the functions
which it performs for people.

CHAPTER 11 Safeguarding the future of the wealth of nature247

4.2 Principles of environmental sustainability
Considerations of environmental sustainability
must start from the recognition of the need forthe sustainable use of resources and ecosystems,
and be rooted in basic laws of physical science,
which hold that indefinite physical expansionof the human economy (in terms of its use ofmaterials and resources) on a finite planet is
impossible; and that all use of non-solar formsof energy creates disorder, and potential disruption, in the natural world. The laws of thermodynamics mean that, at a certain physical scale,further physical growth becomes uneconomic(in the sense that the marginal environmental
costs of this growth exceed the marginal benefits of the increased production), and there is
now substantial evidence that, except from avery short-term perspective (involving high discount rates), there is little doubt that this scale
has now been exceeded in respect of certain
environmental effects. Rockström et al. (2009)
characterize acceptable human impacts on
the environment across different issues, taking risks into account, as “the safe operating
space for humanity,”11 and their work suggests,
as shown in Figure 3, that human activities are
already outside this space in respect of biodiversity loss, climate change, and the nitrogen cycle,
with the phosphorus cycle also fast approaching
the limit.
In the terms set out earlier, environmental
sustainability requires that important environmental functions are sustained, which in turnrequires that the capital stock which produces
these functions, sometimes called “critical natural capital” (CNC) (Ekins et al. 2003), should
also be maintained, although it may well not be
possible to identify CNC as particular elementsof natural capital. The complexity of natural
systems is such that environmental functions
11 The concept is very similar to the concept of ‘safe
minimum standards’ related to resource conservation over 50 years ago by Ciriacy-Wantrup (1952), andsignificantly developed since. See Ekins (2000) for a
discussion.

248

may be enabled or performed by processes
resulting from the interactions between elements of natural capital as much as from theelements themselves. These interactions derivefrom certain characteristics of the natural
capital stock, and it is these characteristics thatneed to be safeguarded if the functions are to
be maintained. Thus it is important always toconsider functions in relation to the interacting
characteristics of natural capital as well as tothe natural capital itself.
The major factor in the operationalizationof this definition of environmental sustainability is the process for identifying environmental
functions as “important.” The conventional
economic approach to such a process is toassign a monetary value to the benefit accruing
from the function, which should then be maintained unless a larger monetary value would
accrue from an activity which resulted in its
necessary destruction. It may also be noted thatthe consistent application of even this conventional economic approach would result in far
less environmental degradation than at present,
because so much environmental damage is still
given no value at all.
However, given the problems entailed incomputing monetary valuations for complex
environmental functions, as briefly mentioned
above, it seems preferable instead to define
the importance of environmental functions inmore fundamental ways. De Groot et al. (2003)
put forward the following criteria:• Maintenance of human health: functions
should be maintained at a level to avoid
negative effects on human health. These
effects may be physical or psychological,
resulting from the loss of environmental
quality or amenity.
• Avoidance of threat: functions should bemaintained if there is any possibility that
their loss would entail unpredictably
large costs. This criterion is even stronger if there is any risk that the loss of thefunction would be irreversible. It is mostobviously applicable to considerationsof climate stability, biodiversity and the
Inclusive Wealth Report

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one that can be projected to continue into thelong-term future).
Brand (2009, p.608) identifies six “domains” that emerge
from the literature as relevantto the categorization of criticalnatural capital: socio-cultural;
ecological;
sustainability;
ethical; economic; and humansurvival. Clearly in the attribution of criticality to particular
manifestations of natural capital, all the domains will need
Figure 3
to be considered. Brand (2009,
A safe operating space forp.609) also develops a concept
humanityof ecological resilience to add
Source: Rockström et al. 2009
to De Groot et al. (2003)’s threecriteria above.
On the basis of theseand the development of renewable subbroad criteria, which establish in general terms
stitutes should accompany the depletion
whether an environmental function should beof non-renewable resources.
considered important, a number of principles
6. Given the great uncertainty attached toof environmental sustainability may be derived,
many environmental impacts, and therelated to current environmental issues of conpossibility that some of these may givecern. The principles spring from the perception
rise to very large costs, the Precautionthat, in order for the environment to be able toary Principle should also be used as acontinue to perform its functions, the impacts
sustainability principle, to limit environof human activities on it must be limited inmental risks.
some ways:
7. Precious landscapes and elements of the
1. At the global level it would seem imporhuman-made environment should betant not to disrupt the climate, orpreserved.
2. deplete the ozone layer or
The first five of the above principles are fairly
3. significantly reduce biodiversity.
straightforward conceptually. For one, two, and4. For pollution generally, emissions should
four, relating to pollution, quantitative stannot exceed levels at which they cause
damage to human health, or the critical dards describing the environmental states (e.g.,concentrations of pollutants) and pressures (e.g.,loads of receiving ecosystems.
5. Renewable resources should be renewed, emissions of pollutants) that are consistent with249them may be readily derived (though not without a broad range of uncertainty in some cases)from environmental science. For resources, it
is depletion (or non-renewal) of renewable
resources that is currently giving most cause forconcern. For single, discrete resources, the ideaof depletion may be unproblematic to apply, but
this will not be the case in respect of biodiversity, especially related to more complex ecosystems, and there are many aspects of biodiversity
which cannot readily be reduced to the idea of“resources” at all. Identifying sustainability standards for biodiversity is likely, therefore, to be
especially challenging.
The sixth principle, a statement of adherence to the Precautionary Principle, acknowledges that an environmentally sustainable society will choose to forgo even quite large benefits
rather than run even a very small risk of incurring potentially catastrophic costs in the future.
Again, environmental science is the best sourceof insight into the existence of such risks, andthe standards of environmental quality which
are necessary to avoid them.
The seventh principle is rooted entirely inethical, aesthetic and socio-cultural considerations, which are present to some extent too in
the other principles, but which are outside therealm of environmental science. It is not therefore possible to specify in general terms whichlandscapes should, or should not, be conserved.
On the other hand, it is also not possible toconceive, in the contemporary context, of anenvironmentally sustainable society that makes
no attempt to identify outstandingly valuable
landscapes (however value may be construed
in these contexts), or to conserve the ones that
had been identified. Most countries have now
enacted landscape designations of various kinds,
internationally, nationally, and at sub-national
levels. Standards under this principle would
assess the extent of these designations, and therigor with which they were observed.
The ideas of critical natural capital and strong
sustainability are intended to avoid the routine
trade-offs associated with weak sustainability,
yet even within this concept trade-offs need to250

be confronted and choices made. Pearson et al.
(2012), building explicitly on Brand (2009) andSpash et al. (2009), distinguish between theutilitarian (based on consequentialist reasoning) and “protected” (based on deontologicalreasoning) motivations that may be differently
reflected in the principles. They usefully differentiate between tragic decisions, which involve
trade-offs between protected values; taboodecisions, which involves a trade-off between
protected and utilitarian values; and routine
decisions, where the trade-off only involves
utilitarian values. As environmental damages
become more serious, and environmental prognoses become more threatening, trade-off decisions of all three kinds, even related to criticalnatural capital, are likely to become more frequent and unavoidable. 12

4.3 The sustainability gap
Once the standards according to these principles and criteria have been defined, then the
difference between these standards and theenvironmental state or pressure indicator showing the current situation may be described as
the “sustainability gap” (SGAP), in physical terms,
between the current and a sustainable situation (Ekins and Simon 1999). SGAP indicates thedegree of consumption of natural capital, either
in the past or present, which is in excess of what
is required for environmental sustainability. For
the state indicators, the gap indicates the extent
to which natural resource stocks are too low, or
pollution stocks are too high. For pressure indicators, the gap indicates the extent to which theflows of energy and materials which contributeto environmental depletion and degradation are
too high. SGAP indicates in physical terms theextent to which economic activity is resulting
12 A simple example related to energy is the dispute
between those who advocate low-carbon energy
sources – such as wind turbines or nuclear power – toprotect climate stability, and those who reject theseenergy sources because of their landscape impacts orgeneration of radioactive wastes.

Inclusive Wealth ReportTable 3

Various sustainability measures for the Netherlands
Environmental stress Sustainability
standard
(ES)
1980

1991

Climate change, Ceq

286

239

Ozone depletion, Oeq

20000

Acidification, Aeq

Sustainability gap

Normalized SGAP

(SGAP) (ES-SS)(100*SGAP/SS), EPeq

(SS)

Years tosustainability

1980

1991

1980

1991

10

276

229

2760
1001

2290
83

54

8721

0

20000

8721

na

na

8.5

6700

4100

400

6300

3700

1575
100

925
59

16

Eutrophication, Eeq

302

273

86

216

187

251
100

217
86

71

Dispersion, Deq

251

222

12

239

210

1992
100

1750
88

80

Waste disposal, Weq

15.3

14.1

3

12.3

11.1

410
100

370
90

102

Disturbance, Neq

46

57

9

37

48

411
100

533
130

Never

TOTAL

na

na

na

na

na

7399
100

6085
82

51

Source: Ekins and Simon 2001, Table 4, p.14
1.

The second entry in this column has converted the NSGAP to index numbers, with 1980=100.

in unsustainable impacts on important environmental functions.
The SGAP idea can be developed further togive an indication of the time that would betaken, on present trends, to reach the standardsof environmental sustainability. Thus Ekins andSimon (2001, pp.11ff.) use calculations of various stresses across seven environmental themesin the Netherlands for two years, 1980 and 1991,
measured in various “theme equivalent” units(taken from Adriaanse 1993), to derive both
SGAPs and Years-to-Sustainability indicators foreach theme.
Columns 1 and 2 of Table 3 show Adriaanse’s
environmental stresses, and Column 3 gives his
sustainability standards. The next two columns
calculate the SGAP for each theme for each year,
where SGAP is the distance in theme equivalent
units between current conditions and the sustainability standard. Thus in the SGAP columns
the standard is subtracted from the stress foreach year. The next two columns normalize

this SGAP (NSGAP) as shown. It can be seen that
the NSGAP for climate change, for example, wasreduced by 17 percent from 1980–91, while thatfor disturbance increased by 30 percent. The
total NSGAP was reduced by 18 percent overthis period. The final column gives the years
required to reach the sustainability standard (toreduce SGAP and NSGAP to zero) given the trend
established from 1980–91. It can be seen thatthe total NSGAP will be reduced to zero after 51
years, although individually climate change,
eutrophication, dispersion and waste disposal
will still not have reached their sustainability
level by then.
It may also be noted from Table 3 that thevarious measures cannot all be derived for all
the environmental themes. For ozone depletion, the sustainability standard of 0 meansthat no figure for normalized SGAP can bederived, although there is no problem computing the years to sustainability. For disturbancethe increasing trend from 1980 to 1991 means

CHAPTER 11 Safeguarding the future of the wealth of nature251

that no figure for YS can be given. However, in
this case there is no problem with normalizing
the stress, and the increasing trend is factored
into the total normalized figures, increasing
the length of time before sustainability overall
will be reached (removing disturbance from thetotal actually reduces the time before sustainability is reached to 43 years). Both the normalized SGAP (NSGAP) and Years-to-Sustainability(YS) indicators give useful information on theachievement of sustainable development. The
SGAP indicator can also be expressed as a ratio of
output to show the “unsustainability intensity”(similar to the energy intensity) of economic
activity. Ekins and Simon (1999) also show how
maintenance and restoration costs can be used
to convert the SGAP into a monetary figure,which may be directly compared with GDP.
While all such aggregate indicators have
limitations, the SGAP avoids the main ones identified by Pillarisetti and van den Bergh (2010) in
their analysis of the Genuine Savings (GS) indicator, the Ecological Sustainability Index (ESI),and the Ecological Footprint (EF)13. SGAP takes
explicit account of critical natural capital anddoes not make inappropriate assumptions of
substitutability by setting sustainability standards for each environmental theme (unlike GS)
and it is related to the carrying capacity of the
Earth (unlike ESI), but without the methodological problems of EF. If the problem of environmental unsustainability is to increase its public
profile and awareness, some way of simplifying
and presenting the complexity of the issue islikely to be necessary.

4.4 Material flows, resource efficiency,
and dematerialization
The sustainable use of resources in line with thefifth sustainability principle above will require,

13 The latter two are aggregate environmental/ecological indicators not discussed here for reasons ofspace. Further details can be found at YCELP (2005)(ESI) and WWF et al. 2006 (EF).

252

firstly, that the flow of resources (materials witheconomic value) through the economy is measured and secondly, for those resources whose
use is excessive and unsustainable, that use willneed to be reduced.
New methods for measuring material flows
have resulted in much information, organizedthrough concepts such as Domestic or Total
Material Consumption (DMC/TMC), Direct
and Total Material Input (DMI/TMI) and Total
Material Requirement (TMR), which includes
Hidden Flows.14 Through such studies as thatfor the U.K. by Bringezu and Schütz (2001),
which utilize these concepts, it is increasingly
possible to characterize material flows, making
it possible for the first time to assess whether
or not any reduction in resource use, or dematerialization, is taking or has taken place. For
example, Bringezu et al. 2004 (p.120) foundthat for 26 countries, with the exception onlyof the Czech Republic, “no significant absolutedecline of direct material input per capita has
been observed so far in the course of economic
growth.” If incomes are to be simultaneously
increased as resource use is reduced, the efficiency of resource use will have to increase.
There are a number of related efficiency concepts, which need to be distinguished: material
efficiency (which is some ratio of useful material
output to material resource input and which
may argue, for example, for increased recycling
over the economy as a whole); and economic
efficiency (which would argue for recycling to
the extent that the marginal cost of recycling
equaled its marginal benefit). The term resource
efficiency may be applied to either of theseconcepts. Distinct is the more rigorous idea of
resource productivity, which is some measure of
economic output or value added per some unitof resources.
Resource efficiency is also important for
reducing environmental impacts. The use ofsuch indicators as TMR and TMO as sustainability indicators by themselves is obviously
14 For definitions of these and other terms used inmaterial flow analysis (MFA), see EC/EUROSTAT 2001

Inclusive Wealth Reportproblematic, because differ- Table 4
ent materials have such dif- A classification of resources and their indicators
ferent environmental impacts
Indicator
per unit of weight (Dietz
and Neumayer 2007, p.623).
Resources
Unit
Home
AbroadHowever, as Bringezu et al.
Materials: abiotic (inc.
Components of DMC/ Components of TMC/
fossil fuels), biotic (land,
Tonnes(2009, p.30) point out, there
TMR (inc. HF2)
DMI/TMI (inc. HF2)
freshwater, marine)
is an intrinsic relationship
Water exploitation
Embodied water in EU
between material flows and
Water
Litersindex (WEI)
imports
environmental impacts. It isin fact hard to think of an
Land: not built up1
Hectares Protected areas
Protected areas
environmental impact that isLand use from EU
not in some way or anotherLand: built up
Hectares Built-up area
imports
linked to the flow of materials
through the socio-industrial
Marine area
Hectares MPAs
MPAs
metabolism. Greater efficiency
Energy productivity
in the production and use of
Embodied energy in EU
Energy
MJ/MWh Absolute energy use
imports
materials therefore helps toRenewable energy use
reduce environmental impacts.
Environment
Environmental impacts may
also be reduced by reducing
TonnesGreenhouse gases
Emissions
Emissionsmost of those materials andCO2eresources with high negative
Air: non-GHG emissions,
Tonnes
impacts, or by replacing themWater: emissions, Land:
Emissions
Emissionsvariouswith those with a lower envi- emissionsronmental impact.
1. This could be broken down by habitat (e.g., from the U.K. National Ecosystem Assessment, referred toThis is the thinking behind
below: Mountains, Moorlands and Heaths, Semi-natural Grasslands, Enclosed Farmland, Woodlands,
the European Commission’s
Freshwaters [Openwaters, Wetlands and Floodplains], Coastal Margins; Urban included in Built up,“Resource Efficiency Roadmap”
Marine included separately)(EC 2011), using a classification 2. Hidden flowsof resources and environmental impacts as set out in Table
4. Policy analysis must find ways of evaluating means that productivity/efficiency improvements have been realized, but total inputs, or
any trade off between the different resourcesand environmental impacts in Table 4 (e.g., pollution outputs, continue to increase as ecorecycling may entail greater energy use, trans- nomic output increases. Absolute decoupling
port emissions) throughout supply chains and refers to the situation in which there is an overall reduction in required material inputs or polproduct life-cycles.
lution outputs, even while the economy grows,
Dematerialization is an absolute decrease in
the quantity of resources, measured by mass, whether through productivity improvements orbeing used by an economy. It is clearly related through a decrease in pollution, or a combinato but is distinct from the concept of decoupling, tion of the two.
If dematerialization occurs in a growing
which is a decline in the ratio of the amountused of a certain resource, or of the environmen- economy, then it is indicative of absolute decoupling. If it occurs in a shrinking economy, its relatal impact, to the value generated or otherwise
tionship to decoupling is unclear. Decoupling
involved. The unit of decoupling is therefore
a weight per unit of value. Relative decoupling may be defined in terms of emissions and other
CHAPTER 11 Safeguarding the future of the wealth of nature

253

environmental impacts as well as resource use.
Dematerialization is usually only defined interms of resource use, although, especially inmass balance studies, there is no over-riding
reason why this should be so. Obviously bothresource use and emissions may lead to environmental impacts, although these impacts arenormally considered as an extension to, rather
than as part of, the dematerialization concept.
Three kinds of materials may be defined inan economy. There are virgin resources, thosewhich enter the economy for the first timeafter their extraction from the natural environment; recycled resources, which circulate in theeconomy through multiple uses; and materials
for disposal (not resources at this stage because
they have no economic value). The dematerialization concept may be applied to any or allof these stages of resource and material use,
depending on whether it is the use of virginresources, the circulation of resources in theeconomy, or the disposal of materials, that has
been reduced. The distinction between thesestages of resource and material use is important,because the policies to affect the different stages
may be very different.
Dematerialization, as opposed to decoupling, is not a concept that has received much
explicit policy attention. In fact it is not easy tothink of any policies that have been introducedwith the explicit purpose of “dematerialization.”
It is therefore important, in thinking about policies that might achieve dematerialization, to beclear about the purpose of dematerialization.
This may include one or more of the following
objectives, associated with the different stagesof resource and material use:
1. To reduce the depletion, and therefore
extend the period of availability, of ascarce resource;
2. To reduce the environmental impacts associated with the extraction, transport,
processing or use of the resource;
3. To reduce the environmental impacts ofthe disposal of the material at the end ofits useful life.

254

Most economists would suggest that themain policy used to achieve dematerialization
should be an economic instrument that explicitly increases the prices associated with resource
use and environmental impacts.
Clearly different materials have very different environmental impacts (Van der Voet etal. 2003). In order to reduce environmental
impacts, dematerialization needs to focus on
the materials producing the greatest impacts,
as well as reducing their quantity mobilized by
the economy. However, the mobilization of any
material by the economy is the source of someenvironmental impact, especially its mobilization in bulk, and if the related energy use andthe whole life cycle of the material is taken into
account. For example, bulk aggregates may beinert in environmental terms, but their mining
and transport can be energy intensive and resultin very great environmental disturbance in thelocation of the mine. This is the rationale forcalling for the dematerialization of the economy
in general, as well as seeking special control ofsubstances with particularly harmful impacts.
Moll et al. (2003) provide a limited disaggregation of material flows into the four mainmaterials by mass to flow through the economy(excluding water): biomass, construction minerals, industrial minerals and ores, and fossil
fuels. The flow of these materials through theeconomies of the EU-15 countries since 1980 has
been remarkably constant (Moll et al. 2003,
Fig.4-4, p.35). This confirms that, while technical progress tends continuously to improve theefficiency or productivity with which resources
are employed, the decoupling has mainly been
relative rather than absolute. The productivity or efficiency gains have overall been outweighed by growth in the scale of the economy,
and there has been a small absolute increase ina number of both resource inputs and emission
and waste outputs. It is clear that if absolute
decoupling (dematerialization) is required toreduce the physical scale of the economy suchthat it becomes environmentally sustainable,
then either current environmental policies
will have to be applied much more stringently,
Inclusive Wealth Reportor new, more effective, policies will have to befound.

5.	The environment, the economy, andhuman well-being15
5.1 Influences on human well-being
Figure 1 shows that the purpose of economic
activity is to contribute to human welfare or
well-being, and that human welfare derives
from a number of sources. It is obvious fromany consideration of the issue that some levelof output/income is clearly vital for well-being,
and for prosperity, but the declining marginalutility of income is a well accepted notion ineconomics, and this means that, at some (high)level of income, economic growth may not be
important for well-being and may, indeed, add
a rather small increment to it. Notwithstanding,
it is conventional to assume that the level of
economic output is positively related to humanwell-being and that therefore the growth in that
output, called economic growth and measured
in money terms, will increase human well-being. Figures 1 and 2 already cast some doubt on
the general validity of this assumption, because
if economic growth results in the depletion ofenvironmental resources and negative environmental impacts, as is the case in the absenceof absolute decoupling, then any well-being
increase from increased incomes may be offset
by reductions in well-being from environmental damage. In economic parlance, if the generation of economic output has had a negative
impact on some of the other arguments in theutility function (for example, work-life balance,or relationships, or income distribution, or theenvironment), which is entirely possible, theneconomic growth at high levels of income may
actually reduce well-being.
Substantial recent empirical research on
human happiness has in fact cast doubt on the
15 This section draws substantially on Ekins and Venn
2009presumed positive relationship between economic growth beyond a certain level of output
and human well-being for reasons apart fromenvironmental impacts. The issue has recently
entered the mainstream, exemplified by the
Stiglitz-Sen report (2009) commissioned by the
French Government, the “Beyond GDP” conference (2007) and Communication16 (2009) of theEuropean Commission, and the ongoing initiative that also involves the OECD, Club of Rome,and WWF.17 In the U.K., at the Prime Minister’s
request, the Office for National Statistics has
produced a discussion paper on measuringwell-being (Beaumont 2011). This section willvery briefly review this research and its implications for accounting for natural capital.
The notion that human happiness is an
important objective of human life goes back considerably further than the 1776 U.S. Declarationof Independence which famously identified
its pursuit as one of “inalienable rights” given
to human by their Creator. As Nettle (2005)
notes, the ancient Greek philosopher Aristippus
argued in the fourth century B.C. that the goalof life is to maximize the totality of one’s pleasures. However it was not until the 1960s thatpsychologists began to investigate happiness ina scientific manner. Further, it was not until the
1970s that economists looked into the notion ofhappiness and its relationship with economic
growth.
One of the first conclusions from this workis that the concept of well-being/happinessis not easy to define. Often different words
are used to try to explain the concept. Indeed
Easterlin (2003:11176) states that he takes theterms “happiness, utility, well-being, life satisfaction, and welfare to be interchangeable.”
However, despite different definitions of wellbeing, McAllister (2005) argues that there does
appear to be common ground between the
different descriptions and resulting measurements of well-being, although these may be
16 http://eur-lex.europa.eu/LexUriServ/LexUriServ.
do?uri=COM:2009:0433:FIN:EN:PDF
17 http://www.beyond-gdp.eu/

CHAPTER 11 Safeguarding the future of the wealth of nature

255

90
80
70

Real income per head
60
50
40
30

% very happy

20
10

2000

1995

1990

1985

1980

1 975

1 970

1965

1960

1955

1950

1945

0

Figure 4

Income and happiness in
the United States
Source: Layard 2005, p.30

differentiated as to whether the measurements
are subjective or objective. Most researchers
agree about the elements that make up wellbeing: physical well-being; material well-being;social well-being; development and activity;and emotional well-being. The elements canbe paraphrased as physical health, income andwealth, relationships, meaningful work and leisure, personal stability and (lack of) depression.
Mental health is increasingly seen as fundamental to overall health and well-being. Theseelements are sometimes viewed as “drivers” ofwell-being. As is discussed further below, it isinteresting and remarkable that the naturalenvironment per se is absent from this list.
With regard to the influence on well-beingof economic growth, one of the earliest andmost influential papers was by Easterlin (1974),
who found that, firstly, individual happinessappears to be the same across poor countries
and rich countries, and secondly, economic
growth does not appear to raise well-being.
Rather Easterlin proposed that people compare
themselves to their peers, and it is their relative income in respect of this group that delivers well-being, rather than its absolute level.
Therefore, raising the income of all does not
256

increase the well-being of all (Easterlin 1995).
Similar lines of investigation were taken up by
Hirsch (1976), Scitvosky (1976), and Frank (1985),
with similar conclusions, and although a later
study (Oswald 1997) criticized the approachtaken, it also found that “it seems extra income
is not contributing dramatically to the qualityof people’s lives” (Oswald 1997:1818).
Income, relative or absolute, is however
usually included in lists of factors which affectwell-being. For example, Dolan et al. (2007, p.33)
reviewed 150 peer reviewed papers and grouped
their contributory factors to well-being underseven broad headings: 1) income; 2) personal
characteristics: who we are, our genetic makeup;3) socially developed characteristics: our healthand education; 4) how we spend our time: thework we do, and activities we engage in; 5) attitudes and beliefs towards self/others/life: how
we interpret the world; 6) relationships: theway we connect with others; and 7) the wider
economic, social and political environment: theplace we live. Again, the natural environment is
at best implicit in this list.
Although measurements of well-being tend
to be one of two types, subjective or objective, empirical work has shown that economic
conditions, like unemployment, inflation andincome, have a strong impact on people’s subjective well-being. Clark and Oswald (1994)
showed that unemployed people are significantly less happy than those with a job (see also
Winkelmann and Winkelmann 1998; Di Tella
et al. 2001; Ouweneel 2002).
At best, the relationship between happinessand income seems to be nonlinear. Over time,happiness appears to be relatively unrelated toincome. Research by Diener and Seligman (2012forthcoming) and Layard (2005) has found, as
shown for the U.S. in Figure 4, that substantial
real per capita income growth in developed
countries over the last decades has led to no
significant increases in subjective well-being –despite massive increases in purchasing power,
people in developed nations seem no happierthan they were fifty years ago. Figure 4 shows

Inclusive Wealth Reportcomprehensive assessments to date, at theconceptual level, of the multiple inter-linkages
between the environment and human well-being. Ecosystem services as defined by MA comprise provisioning services such as food, water,
timber and genetic resources; regulating services
that affect climate, floods, disease, wastes andwater quality; cultural services that provide recreational, aesthetic, and spiritual benefits; andsupporting services such as soil formation, pollination, and nutrient cycling. Supporting services
are included as an overarching category as it isperceived that they are essential for sustaining
each of the other three ecosystem services. The
link between supporting services and humanwell-being is therefore crucial but indirect.
Human well-being is assumed to have multiple constituents (MA 2005, p.v), including thebasic material for a good life, such as secureand adequate livelihoods, enough food at all
times, shelter, clothing, and access to goods;
health, including feeling well and having a
100
95
90
85
80
75
70
65
60

Georgia

Estonia

Romania
Lithuania
Armenia
Bulgaria

55
50

RussiaUkraineBelarus
Moldova

45
40
35

17000

13000

30
1000

Notwithstanding the near total absence of theenvironment from the well-being literature, as
noted above, the landmark study of the natural environment, the Millennium Ecosystem
Assessment (MA 2005) is in no doubt of the(intuitively fairly obvious) fact that human wellbeing is fundamentally dependent on the “ecosystem goods and services” (the same concept as
the environmental “functions for” humans discussed above), the production of which depends
on the continued functioning of basic environmental processes.
Carried out between 2001 and 2005, the MA
sought to assess the consequences of ecosystemchange for human well-being and to establish the scientific basis for actions needed toenhance the conservation and sustainable useof ecosystems. It resulted in one of the most

9000

5.2 Human well-being and the environment

IcelandN. IrelandNetherSwitzerland
lands
Denmark
IrelandFinland Sweden Norway
Puerto New Australia Belgium
USA
Rico Zealand Britain Canada
Colombia
Italy
TaiwanFranceSouth Korea
Phillippines
W. Germany
Venezuela
Japan
BrazilAustria
Uruguay
Ghana
MexicoSpain
Nigeria
Chile
China
Dom.Venezuela
Rep
E. Germany
BanglaPoland Czech Portugal
desh Pakistan
India
TurkeySlovenia
S. Africa
Croatia
Slovakia
Hungary
Macedonia Yugoslavia
Peru
Azerbaijan
Latvia5000

very much the same relationship between
income and “mean life satisfaction” in the U.S.
Figure 5 shows that once average income ina country exceeds $20,000 per head, increases
in income are no longer associated strongly, if
at all, with increases in happiness.
Along with Easterlin, Layard (2005) argues
that relative income is more important in
explaining well-being than absolute wealth,explaining this through a process known as the“hedonic treadmill.” As individuals and societies
grow wealthier, they adapt to new and higher living standards and adjust expectations upwards.
This means that aspirations are never satisfied,
and that at higher income levels increases inincome make less difference, as basic needs are
satisfied but consumption desires remain. On
the basis of his research, Layard also identifies
seven main factors that influence the wellbeing of people: family relationships, financial
situation, work, community and friends, health,personal freedom and personal values (Layard
2005, p.63). Again, the natural environment isconspicuous by its absence from this list.

Figure 5

Income and happiness fordifferent countries
Source: Layard 2005, p.32

CHAPTER 11 Safeguarding the future of the wealth of nature

257

Life on Earth - biodiversity
Ecosystem services
Provisioning
Food
Freshwater
Wood and fiber
Fuel
...

Supporting
Nutrient cycling
Soil formation
Primary production...

Regulating
Climate regulation
Flood regulation
Disease regulation
Water purification...

Cultural
Aesthetic
Spiritual
Educational
Recreational...

Constituents of well-being
Security
Personal safety
Secure resource access
Security from disasters

Basic material forgood life
Adequate livelihoods
Sufficient nutritious food
Shelter
Access to goods
HealthStrength
Feeling wellAccess to clean air andand water

Freedom of choice
and action
Opportunity to be
ale to achieve what
an individual values
doing and being

Good social relations
Social cohesion
Mutual respect
Ability to help others

healthy physical environment, such as clean air analysis because of its correlation with bothand access to clean water; good social relations, HDI and ESP. Regressing life satisfaction against
including social cohesion, mutual respect, and HDI and ESP for 56 countries found a significant
the ability to help others and provide for chil- relationship for both variables, with HDI having
dren; security, including secure access to natural the stronger effect. Excluding six outlier counand other resources, personal safety, and secu- tries (which, included both China and India)
rity from natural and human-made disasters; greatly improved the fit of the regression. They
conclude that natural capital has a “significant
and freedom of choice and action, including theopportunity to achieve what an individual val- impact” (Vemuri and Costanza 2006, p.131) onlife satisfaction, although the paper earlier saidues doing and being.
One of the rare studies to have investigated “we cannot conclude causal implications fromexplicitly the relationship between natural capi- this type of model” (ibid., p.128). However, it istal (and manufactured, social and human capi- at least intuitively plausible that natural capitaltal) and human life satisfaction is Vemuri and and life satisfaction have a positive relationship.
It is clear that the MA approach to human
Costanza (2006). They computed an “ecosystemservices product (ESP)” from the land-cover well-being is close to those discussed above.
dataset of the International Geosphere and Building on its classifications the MA (2005)
Biosphere Programme (IGBP) and unit ecosys- maps ecosystem services onto human wellbeing as in Figure 6, with the arrows indicating
tem service values from Costanza et al. (1997). To
represent manufactured and human capital they the strength as well as the nature of the linkused the Human Development Index (which ages, and their colors indicating of the extent
combines measures of income, health, and edu- to which it is possible for socioeconomic factors to mediate the linkage (for example, if it iscation). Social capital was represented by a press
possible to purchase a substitute for a degraded
freedom rating but was then excluded from the258

Inclusive Wealth Report•Figure 6

Illustration of linkages
between ecosystemservices and human wellbeing
Source MA (2005, p.50)

Key
Color

Width

Potential for mediation by socioeconomic factors

Intensity of linkages
between ecosystemservices and humanwell-being

low

weak

mediummediumhighstrongecosystem service, then there is a high potential
for mediation).
The MA argues that both the strength of thelinkages and the potential for mediation differ
in different ecosystems and regions. The MA
additionally identifies non-ecosystem factors
which have the potential to influence humanwell-being (classified into economic, social,technological, and cultural factors), and notes
that, as in Figure 2, these can feed back into theenvironment and affect ecosystem services, butthese interactions are not shown in Figure 6.
All this suggests that well-being is the product of a range of different factors or conditions
that include the environment. Two lists of thesefactors or conditions from the economics literature, to complement those above, but which incontrast do include environmental resources,are:• Real income per capita; health and nutritional status; educational achievement;
access to resources; income distribution; basic freedoms (Pearce et al. 1990,
pp.2–3)

Income; income distribution; employment; working conditions; leisure[“work-life balance”]; environment; relationships; safety of the future/security(Hueting 1986, pp.243ff.)
While it is clear from the review of Dolan etal. (2007) that there are remarkably few studies that investigate environment-well-being
relationships, or seek empirically to assess thestrength of the linkages identified in Figure
6; and while both Dolan et al. (2007) andMA (2005:6) also note there is also a limited
amount of information available to assess theconsequences of changes in ecosystem services
for human well-being; more recent research,
including The Economics of Ecosystems andBiodiversity (TEEB 2010) and the U.K.’s recent
National Ecosystem Assessment (UKNEA 2011)
have produced clearer evidence that ecosystems,
and the services they produce for humans, arevaluable. Some of their value appears directly inmarketed products. Some of it is not marketed,but can, with some difficulty and reservations,be expressed in monetary terms. The MA and
UKNEA in particular have also shown that in past
years pressure on many ecosystems has grown,
a number of them have been lost or degraded,
and the flow of ecosystem services has declined.
In some cases this decline continues, with probable negative consequences for social well-being
in the future. Figures from the economic analysis in UKNEA illustrate the possible scale of these
consequences.
Natural capital in the UKNEA includes theeight kinds of ecosystems that are explored indetail in the UKNEA (Mountains, Moorlands
and Heaths, Semi-natural Grasslands, Enclosed
Farmland, Woodlands, Freshwaters [Openwaters,
Wetlands and Floodplains], Urban, Coastal
Margins, Marine). These ecosystems produce
services which are involved in the productionof both monetary and non-monetary output,
and which contribute directly to human wellbeing. When ecosystems decline, so normallydoes their level of service production, thereby
reducing their level of contribution to monetary and non-monetary output and their direct

CHAPTER 11 Safeguarding the future of the wealth of nature259

contribution to human well-being. Where theirdecline has been the result of other economic
activity, then the value of the production attributed to this activity should be reduced by thevalue of the ecosystem service decline. In theextreme it may be that the value of the lost ecosystem services exceeds the value created by theso-called economic activity, so-called becausesuch activity is not really economic activity atall, but wealth destroying activity. An example
of such a wealth destroying activity might be aforestry business that clear fells a productive forest ecosystem for its timber, where the lost ecosystem services from the forest (many of whichmight have been non-monetary and therefore
not taken properly into account) were morevaluable than the timber that was produced.
The valuation work on the scenarios constructed for the UKNEA (see UKNEA 2011, p.14
Figure 8; the scenarios are called Green andPleasant Land [GPL], Nature at Work [NW],
Local Stewardship [LS], Go with the Flow [GF],
National Security [NS] and World Markets[WM]) explored precisely such trade-offs asthese, where developments in (High and Low)
marketed agricultural output and in the valueof three non-marketed ecosystem services (GHG
emissions, recreation, and urban greenspace)were compared. Table 5 shows a summary ofthese values.
The three non-marketed ecosystem services
are explicitly represented in the categories ofHueting’s utility function above: GHG emissions (safety of the future); recreation (leisure),
urban greenspace (environment), and of course
it is their presence in people’s utility functions
that causes people to value them. At the sametime, these values are highly dependent on context and circumstance, and it is not difficult toimagine situations in which they would change
markedly, so that any estimated values should betaken as a snapshot from present perspectives,and are most unlikely to be the same in 2060,
which is the year of the scenarios’ projections.
In the scenarios with both high and low climate change, on the basis of the issues considered, the two scenarios (NS, WM) that give the260most emphasis to marketed agricultural output
have the highest increase over the Baseline interms of marketed money values, but these
two scenarios represent the worst social value
in terms of total output. It might be surmised
from this that NS would have the highest GDP
of all the scenarios, followed by WM, but thiswould be wrong for two reasons.
First, agriculture is a relatively small sectorof the monetized economy, and the scenarios
could be expected to show very different outcomes for other sectors. For example, WM fromits description would probably have the highest
growth in other industries. Second, and more
importantly here, there is no allowance madefor the possible contribution of the increased
natural capital in other scenarios to other sectors. For example, those scenarios with better
protected ecosystems might have more developed U.K. tourism and leisure sectors, whichhave not been evaluated here. Third, there is
no assessment of possible feedback between
natural capital and other forms of capital. For
example, the greater availability in some scenarios of urban greenspace may improve urban
health and therefore increase human capital. Allsuch considerations emphasize the desirability
in any whole-economy assessment of such scenarios, even if only considering the scenarios’
GDP outcomes, of carrying out an economywide assessment with a well specified national
environment-economy model.
The work of TEEB, MA, and UKNEA, among
others, seem now to have established indicatorsof the natural environment, or natural capital,
as an important component of well-being measures. For example, the new framework being
adopted by the U.K. Government (Beaumont
2011) to assess trends in human well-being,and social progress more widely, includes thenatural environment as one of three “contextual domains” (along with governance and theeconomy) contributing to human well-being.

Inclusive Wealth ReportTable 5

Summary impacts for the change from the 2000 baseline to 2060 under each of the NEA scenarios:
Great Britain. All values given in £Million per annum.
Source: UKNEA, 2011, Chapter 26, Table 26.23

GF
High

GF
Low

GPL
High

GPL
Low

LS
High

LS
Low

NS
High

NS
Low

NW
High

NW
Low

WM
High

WM
Low

£ millions pa (real values, £ 2010)
Market agricultural output values1

590

220

-30

-290

430

350

1,200

680

-110

-510

880

420

Non-market GHG emissions2

-810

-800

2410

2410

570

-100

3400

3590

4570

4590

-1680

-2130

Non-market recreation3

4120

5710

5160

6100

1100

1540

3340

4490 23910 24170

-820

5040

Non-market urban greenspace4-1960 -1960

2350

2350

2160

2160 -9940 -9940

Total monetized values5

1940

9890 10570

4260

3950 -2000

3170

4730

4730 -24000 -24000-1180 33100 32980 -25620 -20670

Non-monetized impacts6
Change in farmland bird species7

0

0

0

0

0

0

-1

-1

-1

-1

0

0

Bird diversity (all species)8

++

++

++

++

-

-

++

+++

++

++

--

+

Rank: Market values only

4

8

9

11

5

7

1

3

10

12

2

6

Rank: All monetary values

8

7

4

3

5

6

10

9

1

2

12

11

Rank: +ve monetary values andno farmland bird losses

6

5

2

1

3

4

Rank: +ve monetary values andbiodiversity gains

4

3

2

1

Notes: Scenarios are as follows: BAU = Business as Usual; GPL = Green and Pleasant Land; LS = Local Stewardship; NS = National Security; NW =Nature at Work; WM = World Markets.
1.

Change in total GB farm gross margin.

2.

Change from baseline year (2000) in annual costs of greenhouse gas (GHG) emissions from GB terrestrial ecosystems in 2060 under the NEA
Scenarios (millions £/yr); negative values represent increases in annual costs of GHG emissions

3.

Annual value change for all of Great Britain.

4.

Annuity value; negative values indicate losses of urban greenspace amenity value.

5.

There is some double counting between urban recreation and urban greenspace amenity values. Further data is needed to correct for this.

6.

Note that some commentators prefer to use monetized values for biodiversity. See discussion in NEA Economics chapter.

7.

Expected impact on the mean number of species in the seeds and invertebrates guild (including many farmland bird species) present in each 10km
square in England and Wales from 1988 to 2060 (rounded to the nearest whole number). Note that the 2000 Baseline has 19 species in this guild.

8.

Based on relative diversity scores for all species.

CHAPTER 11 Safeguarding the future of the wealth of nature

261

6.

Conclusion

This chapter has reviewed a number of issues
relating to wealth accounting with a viewto extending and complementing the main
approaches to the subject that have been discussed in this report, always in the context ofa multi-capital framework for understanding
wealth creation.
The most important of these issues are thedistinction between weak and strong sustainability; and the identification of influences onhuman well-being beyond conventional measures of wealth as the discounted future flow of
consumption.
The fact that some natural capital may be
non-substitutable by other forms of capital shifts
attention to ways of measuring such capital thattake account of thresholds and minimum standards for its conservation to ensure the sustainability of the environmental functions which it
generates. The main section of this chapter has
identified principles of environmental sustainability that are particularly relevant to criticalnatural capital and shown how sustainability
standards in relation to these standards may beformulated. This then permits an indicator to
be derived that shows the “gap” between current use of the environment and its resources
and the sustainability standard, showing ineasily communicable form the extent to whichcurrent activities are sustainable, and the timethat will be taken on current trends before thesustainability standards will be achieved. New
methods of measuring the flows of resources
through the economy have been developed,
both to facilitate analysis of the sustainabilityof these flows, and to permit the construction of economic-environmental indicatorsof resource efficiency and dematerialization,
which can provide further guidance to policymakers on the joint achievement of economicand environmental objectives.
The maintenance and increase of humanwell-being is the purpose of economic activity.
There is little doubt of the importance of consumption to such well-being, but equally there262

is little doubt of the importance of a numberof other factors and influences. The substantial literature on this subject has surprisingly
underplayed the importance of natural capital as one of these factors and influences, but
the balance here has started to be corrected
through the various ecosystem assessmentsthat have been produced in recent years, with
their focus on the importance to human wellbeing of a whole range of ecosystem goods andservices. Even the limited valuation of thosethat have been shown to be possible in theseassessments suggests that it is beyond time that
inclusive accounting for natural capital, both assuggested in other chapters of this report, andin the broader approaches outlined here, is long
overdue.

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Conclusion

Lessons, findings, andrecommendations
Anantha Duraiappah and Pablo Fuentenebro

For decades, economists and governments have used conventional production indicators such as per capita gross domestic
product (GDP) or, more recently, the Human Development Index(HDI) to measure societies’ overall “well-being.”
The reliance on GDP per capita is understandable. It is easy tocompute, and it is based on a rigorous and well-tested economic
theory. Moreover, the data needed to compute GDP were relatively easy to compile and countries were quick to adopt this system of national accounts. However, as illustrated in this report,neither GDP per capita nor the HDI reflect the state of the naturalenvironment and both focus on the short term, with no indication of whether current well-being can be sustained. Therefore,
it is not surprising that we continue to see a degradation of thenatural environment. It should also not come as a surprise if we
continuously hear of the growth-versus-environment debate. We
are basically using the wrong measurement approach to guidepolicy-making.
The Inclusive Wealth Report (IWR) provides a metric of measurement for sustainable development. While GDP and the HDI
are based on a flow concept, inclusive wealth relies on the stocks
of different assets: natural capital (natural resources, land, andecosystem services, etc.); produced capital (machinery, buildings,etc.); and human capital (education, health, skills, etc.), which267

make up the productive base of a country. The Inclusive WealthIndex (IWI) is not intended to answer all of a decision-maker’squestions, but it can lend insights about the use of assets overtime.
In this report, the focus is on natural capital. Although it istrue that many developing countries have been depleting theirnatural resources over the past several decades, we are not suggesting that countries should stop using their natural capital
assets to achieve improvements in well-being; rather, we offer
more sustainable solutions for achieving these improvements(e.g., making larger investments in other parts of the economy,such as human capital). In this sense, what the 2012 IWR puts on
the table is the foundation for a more holistic approach to economic development than is currently practised.
To be clear, the IWI is an important step forward in understanding human well-being, the economy, wealth, and sustainability. Indeed, it’s an enormously valuable input into decisionmaking. That said, as a nascent index, it should not be seen as the
exclusive source of information and insight. For now, it is advisedthat the IWI be used in conjunction with GDP, the HDI and someof the specific environmental indicators such as the ecologicalfootprint and the ecological sustainability index among others togain the most comprehensive perspective possible.

Lessons learned
A number of key lessons emerge from this first report, including:
1. substitutions among the different capital assets; 2. the importance of not just one capital but the emphasis on a basket of interdependent capital assets; 3. population changes and their impact
on the returns to a nation’s productive base; 4. interconnected
externalities that accrue, particularly from the degradation anddecline of the natural capital base; and 5. estimation of shadow
prices, which are so critical in computing the inclusive wealth ofa country. These are elaborated in the following sections.
1. Substitution
The inclusive wealth framework allows substitution across thedifferent forms of capital and refrains from asserting any specificinterest of any particular constituency. Therefore, natural capital is not preserved for its own sake, but for its contribution tothe overall productive base of a country. For example, a country
with extensive commercially available forest stocks will, according to the inclusive wealth measure, be able to convert some ofthese forest stocks to other forms of capital assets that it might
268

Inclusive Wealth Reportneed to increase the well-being of its citizens and to maintaina sustainable path. The degree of substitutability is determinedby the ratio of the shadow prices of the capitals in question. The
shadow prices hold the key to the degree of substitution and/ortransformation in the country.
2. Health and other forms of capital
One of the crucial features of the inclusive wealth framework is
the emphasis on the importance of not just one form of capital,
but all capitals, for ensuring sustainability and improvement of
human well-being. Among the results is the importance of healthand education in wealth accounts. However, the use of healththrough the value of a statistical life (VSL) does bring with it anumber of issues related to morality and ethics. The fact that thereport finds this dimension to be significantly larger than the restof the other capitals is not surprising. Yet, if the authors were
to extend the equation on health to include it as a function of
the other capitals, specifically natural capital, this would likely
have changed the results. This feedback loop between the different forms of capital can be captured to a certain extent by the
shadow prices of the respective capital assets. We do understandthat the report states that the shadow prices of an asset are afunction of the stocks of all assets. That being the case, we would
have expected higher shadow prices in natural capital, whichmight not be reflected in the proxy prices used in computing thevalues in this report. Examples of how the mental health of populations has changed with the state of natural capital can be usedin computing the shadow price of nature. This shows again theimportance of the shadow prices in making the inclusive wealthframework functional.
3. Population change
The other useful and important inclusion in the inclusive wealthframework is the explicit treatment of population. By including
population, the framework acknowledges growing population
as an important variable in determining a country’s sustainable
track. This is demonstrated strongly by comparing the results ofchanges in the IWI and the Natural Capital Index as illustrated
clearly in Chapters 2 and 3. For instance, Saudi Arabia, which
had a positive average growth rate in IWI of 1.57 percent over theperiod under study, showed a negative growth rate of 1.12 percent
when population growth was factored in. Another example is
the rapid decline in IWI per capita seen in Nigeria which was notcompensated adequately by increases in the other capital assets
and had a negative growth rate of 1.87 percent in its inclusive
Lessons, findings, and recommendations

269

wealth per capita. This highlights the need for policy-makers to
introduce strategies for increasing the marginal rate of transformation of natural capital to human and produced capital, toensure the country is on a sustainable track. These are importantinvestment guidelines that the inclusive wealth framework provides not only for national policy-makers, but also the international organizations responsible for development.
4. Interconnected externalities
The growing frequency of global environmental problems suchas climate change, nitrogen deposition, and biodiversity loss,
among others, has impacts on a country’s wealth prospects andits ability to adopt a sustainable path. Therefore, even if a country adopts all the right measures to follow a sustainable path inorder to maintain or increase its productive base, there are someexternal variables beyond its control that can either increase or
reduce its inclusive wealth. This report takes climate change as
one key externality and makes an important point about the
impact of negative externalities on the inclusive wealth of anation. Information on these transboundary externalities mightalso be useful in determining international compensations either
in the form of financial or technology transfers, which has beena controversial issue in the international negotiations on climatechange. The analysis on climate change can be extended to otherexternalities such as biodiversity loss, acidification of oceans, andthe loss of fisheries. The report clearly highlights a need for a systematic research program on addressing these externalities.
5. Shadow prices
Shadow prices are both the strength and the Achilles heel of the
inclusive wealth framework. On one hand, The shadow pricecaptures the degree of substitution across the different formsof capital. It also reflects the contribution to inter-generational
well-being at each time period by each capital asset. The shadow
price also reflects expected future scarcities and captures theexternalities produced in the use of the capital. For example, theshadow price of manufactured capital also reflects, in principle,
the environmental externalities it caused in the transformation
process.
On the other hand, just as the shadow price is the strength of
the framework, it is also its Achilles heel. This is when we have to
move from theory to practice. In many cases, the market prices
we observe for many of the capitals are adequate for the exercise.
However, in many other cases, as the report rightly highlights,
it becomes a bit more problematic, especially for natural capital
270

Inclusive Wealth Reportand, to a lesser extent, human and social capital. The fact thatmany of the prices are not observable suggests using different
approaches to finding the shadow prices of these capitals.

Findings
A number of key findings are presented in this section. These arebased on the material presented in the earlier chapters of thereport.
Key finding 1

70 percent of countries assessed in the 2012 Inclusive WealthReport present a positive Inclusive Wealth Index (IWI) per
capita growth, indicating sustainability.
14 countries of the 20 accessed in this report were found to havepositive IWI growth rates. The 6 that experienced negative IWI
growth rates were Colombia, Nigeria, Russia, Saudi Arabia, South
Africa, and Venezuela. Of the 14 countries having positive growth
rates, only China returned a growth rate above 2 percent overthe past 19 years, while Chile, France, and Germany were in thesecond tier of countries having growth rates above 1 percent. The
remaining 10 showed growth rates of between 0.1 and 1 percent.
Therefore, although many of the countries in this first report had
positive growth rates, many were at the margin and have a highprobability of moving to an unsustainable trajectory. This was
especially true for Kenya, with a growth rate of 0.06 percent.
Key finding 2

High population growth with respect to IWI growth rates
caused 25 percent of countries assessed to become unsustainable.
One of the primary reasons five of the six countries experienced
negative growth rates were relatively high population growth
rates with respect to their IWI growth rates. The five countries were Colombia, Nigeria, Saudi Arabia, South Africa, andVenezuela. Russia was the exception to the sample of 20 countries that were used in this report. It had a negative population
growth rate, but was also the only country to have a negative IWI
growth rate before population dynamics were included in the
Lessons, findings, and recommendations

271

computations. This example illustrates how a negative population growth rate can counter a declining growth rate of IWI toreturn better growth rates of IWI on a per capita basis.
Key finding 3

While 19 out of the 20 countries experienced a decline in natural capital, six of them also saw a decline in their inclusive
wealth, thus following an unsustainable track.
Japan was the only country that experienced an increase in its
natural capital. This was from an increase in forest cover. But
for 12 countries, a decline in natural capital did not automatically translate to a decrease in the IWI growth rate. However, forsix countries – Colombia, Nigeria, South Africa, Russia, Saudi
Arabia, and Venezuela – decreases in their natural capital base
did contribute to the negative IWI growth rate. Yet, for most ofthese countries, in particular South Africa, a major cause in thedecrease of their natural capital came from the rapid drawdownof their fossil fuel asset base.
Key finding 4

Human capital has increased in every country, being theprime capital form that offsets the decline in natural capitalin most economies.
Brazil, in particular, has had success in increasing its humancapital by over 1.2 percent as compared to its IWI growth rate of
0.4 percent. Much of that increase, however, has come from thedrawdown of its natural capital base which has decreased at an
average of 0.7 percent, with very little increase in its manufactured capital. The key inference to be derived from this findingis that the rate of changes of the three capital asset bases and thecorresponding increase or decrease in the IWI growth rate, bothat an absolute and a per capita basis, have to be analyzed in an
integrated manner.
Key finding 5

There are clear signs of trade-off effects among different
forms of capital (manufactured, human, and natural capital)
as witnessed by increases and declines of capital stocks for 20
countries over 19 years.
A clear picture of trade-offs across the different forms of capital emerges from the results presented in the report. In many
countries, as highlighted in Key Finding 4, human capital has
increased from the reduction in natural capital. The more
important question to answer is if the transformation from one
272

Inclusive Wealth Reportcapital to another has been done in a manner as efficient as in theexample of Brazil. However, there are examples such as Nigeria,
where the massive drawdown of natural capital (primarily fossil fuels) has hardly been compensated by increases in human or
manufactured capital.
Key finding 6

Technological innovation and/or oil capital gains outweighdeclines in natural capital and damages from climate change,
moving a number of countries from an unsustainable to asustainable trajectory.
Total factor productivity (TFP) and, for some countries, the capitalgains from oil price fluctuations were found to play a key role inmoving them from an unsustainable trajectory to a sustainable
one. These countries included Russia, Nigeria, Saudi Arabia, andVenezuela. At the same time, Kenya, which had returned a positive IWI – albeit at a very low rate of 0.06 percent – returned negative IWI rates after adjustment for oil capital losses. This finding
demonstrates the sensitivity of some countries to market pricefluctuations of key commodities (such as oil) towards achieving
sustainability in the long run.
Key finding 7

25 percent of assessed countries, which showed a positive
trend when measured by GDP per capita and the HDI, were
found to have a negative IWI.
Colombia, Nigeria, Russia, Saudi Arabia, and Venezuela showed
positive growth rates for the HDI and GDP per capita, but returned
negative IWI growth rates. South Africa was the only country that
had positive GDP per capita growth rates but returned negative
growth rates for both the HDI and the IWI per capita. The biggest
discrepancies were found in the cases of Nigeria, South Africa,
and Venezuela. These results demonstrate how GDP per capita
focuses purely on the present income and production flow while
the IWI concentrates on the stocks of assets and their changes
over time.
Key finding 8

The primary driver of the difference in performance was thedecline in natural capital.
The main factor for the differences between the GDP per capita
and the HDI with the IWI per capita was the decline in natural capital. Prime examples of countries falling in this category include
Australia, Brazil, China, India, and Canada where the differences
Lessons, findings, and recommendations273

between GDP per capita and the IWI per capita ranged between
75 percent in the case of Canada to 95 percent for Australia.
Countries that performed better based on the IWI per capita wereFrance and Germany. Main reasons for this were an increase in
human capital and, in the case of France, some contribution ofincrease in natural capital.
Key finding 9

Estimates of inclusive wealth can be improved significantlywith better data on the stocks of natural, human, and social
capital and their values for human well-being.
The results presented in this report are based on a partial set ofdata on the various categories of capital. For example, social capital was not included in the analysis and there is some the possibility that the results might change when this capital category
is added. This, of course, has to be evaluated in more detail bothon the theoretical foundations and the empirical estimates. The
biggest gaps in data were found to be in the stocks of the different categories of natural capital and their corresponding values.
Many of the challenges in addressing and filling these gaps werediscussed in detail in Part II of this report. The task is not trivial,
but it is not impossible either.

Recommendations
Inclusive wealth offers policy-makers a comprehensive accounting tool for measuring the assets available in the economy. The
understanding of such asset portfolios and their changes overtime has important implications for sustaining the consumption
needs of present and future generations.
Recommendation 1

Countries witnessing diminishing returns in their natural
capital should build up their investments in renewable natural capital to increase their inclusive wealth and the wellbeing of their citizens.
The majority of countries have been drawing down their natural capital base to increase their IWI per capita growth. However,the declining natural capital asset base cannot be continued
274

Inclusive Wealth Reportindefinitely, and evidence from the IWI suggests that IWI can beincreased substantially if more investment is directed at building
up renewable natural capital assets in countries where IWI growth
rates are low. Examples of investment in renewable natural capital include reforestation (REDD+ programs), agro-biodiversity
landscapes, and seascapes.
Recommendation 2Countries should mainstream the Inclusive Wealth Index
within their planning and development ministries so thatprojects and activities are evaluated based on a balanced
portfolio approach that includes natural, human, and manufactured capital.
Economic planning, poverty reduction, and conservation strategies are typically designed to meet their specific objectives andare evaluated on their project level targets. This is a necessary
condition but not sufficient to ensure sustainability of the outcomes due to the high inter-dependency among the various
social, economic, and environmental components. Trade-offs
are inevitable, but not recognizing them can cause unintended
consequences that might result in unwarranted overall decreases
in well-being. In order to avert this outcome, governments
might require all projects to be evaluated at the sectoral level ofthe impacts they have on the three capital asset bases and thechanges that might occur as well as the overall change in the IWI.
This might require some tweaking of the IWI if it is to be used at
a sectoral level, but the benefits from getting a more inclusive
view of the final consequences on some common denominator,
such as the capital assets, might provide guidance in the transition toward sustainability.
Recommendation 3Countries should support/speed up the process of movingfrom an income-based accounting framework to a wealth accounting framework.
GDP, as highlighted many times in this report, is a flow and isbased on production and income. The present accounting systems used at the national level are based on economic production
and geared towards computing GDP. There is limited informationon the capital stocks and most of these are focused on manufactured capital. There is very little or no information on the humanand natural capital assets within an integrated framework that
can track the changes simultaneously to capture the inter-dependencies. There is work underway to revise the accounts toinclude environmental dimensions, but they are still conducted
Lessons, findings, and recommendations

275

within an income-driven framework and the IWI suggests a movetowards a wealth-based framework to give a fuller account of thechanging productive base of a country and its change over time.
Recommendation 4

Governments should move away from GDP per capita andinstead evaluate their macroeconomic policies – such as fiscal
and monetary policies – based on their contribution to the IWIof the country.
Governments use a combination of fiscal and monetary policies
to guide and steer an economy. The objective of these policies
has traditionally been to increase economic growth as measured
by GDP, keep inflation low, and, to some extent, generate employment. This would by conventional terms suggest a drawdown of
the natural and human capital asset base, and sometimes evenmanufactured capital, if the outlook is myopic and seeking quick
gains. The solution to the problem is to target increasing the IWI
and therefore focus on the investment in the different capital
asset bases to facilitate human development on a sustainablebasis.
Recommendation 5

Governments and international organizations should establish research programs for valuing key components of natural
capital, particularly ecosystem services.
The usefulness of the IWI will be fully realized once we have a setof functioning wealth accounts. The accounts developed in thisreport are only in their infancy with big data gaps in the naturaland human capital categories. Although much progress has been
made in developing a typology for the natural capital accounts,
there is still much work to be done, both theoretically andempirically, to make them fully operational so that they become
mainstream instruments in government policy-making. This canbe achieved to a large extent if governments and internationalorganizations form partnerships to design and fund research
programs in order to get better estimates of natural capital stocks
and their values.

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Inclusive Wealth Report

The way forward
The IWR should not be a one-off report, but instead should be institutionalized as a periodic publication providing timely updates
on the changes in the capital assets and the overall changes in the
productive base of nations. The IWR 2012 should be seen as the
beginning of a series of reports that will be produced every two
years in order to monitor the well-being of countries. In the longterm, we expect inclusive wealth to become an important criterion in assessments of societal progress. Each of the capital asset
categories will be updated as described below. In addition, newtheoretical insights and empirical data on total factor productivity, trade, and inequality with respect to the IWI will be further
developed and presented in future reports.
Natural capital
Efforts will be made to link existing research networks investigating the valuation of ecosystem services to explore ways andmeans to get better estimates of the flows and stocks of ecosystem services. In parallel, valuation of these stocks will be undertaken using both monetary and non-monetary techniques. Thismeta-network will oversee the filling of the gaps identified inthis report and also increase the number of countries in the data
set from the existing 20 to a more representative sample of the
global condition.
Human capital
Human capital presented in this report is limited to literacy rates
and the wage rates prevalent in the various countries. Although
there were estimates for health to be included in the humancapital category, they were not included in the final computations because of their relative dominance in influencing the rateof change in the final levels of inclusive wealth. The use of thevalue of a statistical life (VSL) as an additional indicator within thehuman capital component caused the human capital contribution to dominate the overall Inclusive Wealth Index, making theother categories relatively small and insignificant. A number ofrevisions can be made to address this dominance. A significant
modification that might address this issue will be making healthdependent in part on the relative changes in natural capital. A
well-documented example is the decline in water purification
ecosystem services and the impacts on human health. Actual
numerical estimates of this relationship are scarce, however, andLessons, findings, and recommendations277

need to be improved and presented in the next Inclusive WealthReport.
Produced capital
The produced capital category is well documented due to theavailability of data for many of the individual categories. These
will be updated automatically.
Social capital
One of the most promising concepts that has emerged in recent
times is without doubt that of social capital. Inspired by the workof Robert Putnam and other authors, the wealth accounting literature has picked up on this idea as one of the capital assets that
could contribute to the well-being of any given nation.
Although first developed as a sociological term to address thevalue of human relationships for civil society and communitybuilding, more recently the concept of social capital has takena new dimension as it has become increasingly clear that social
relationships and networks – and trust in individuals and institutions – play a decisive role for sustainable development and thewell-being of nations.

The IWR 2014
The next publication of the Inclusive Wealth Report is expected
in 2014. It is envisaged that the IWR 2014 will present updates on
the various capital assets but with a specific emphasis on social
capital. Participating organizations that focused on aspects of thenatural capital for this IWR will continue collecting and improving the natural capital asset categories and expanding the list of
ecosystem services covered by the wealth accounts. However, atthe same time, efforts to improve the theoretical and empiricalbasis for including social capital will be pursued.

278

Inclusive Wealth ReportAnnexes

279

Methodologicalannex

This annex aims to elaborate upon the methodological and data issues regarding the wealthaccounts presented in Chapters 2 and 3. We
focus here on the three capital forms (human,
manufactured, natural capital); also health capital; and the three adjustments to them: carbon
damages, total factor productivity, and oil capital gains.

1. Human capital
For human capital calculations, we followed
Arrow et al. (2012) and Klenow and RodríguezClare (1997). According to the method employedin these works, human capital per individual(“h”) can be defined as a function of educational
attainment (“A”) and the additional compensation over time of this training, which is assumed
to be equivalent to the interest rate, (“ρ”), which
was fixed at 8.5 percent in this case. It is additionally assumed that the amount of human capitalper person increases exponentially with theinterest rate and the average educational attainment per person – consistent with an economy
in steady state. Thus it is obtained that:￼
Equation 1

h=e(ρ·A)“A” is represented here by the average years
of total schooling per person and it is obtained
from such sources as Barro and Lee (2011), wheredata are presented every five years for our time
period of study (i.e., 1990, 1995, 2000, 2005 and2010). This implied that we were forced to use
linear interpolations for estimating the years of
total schooling on an annual basis. There were,
however, no estimates for Nigeria in the Barroand Lee (2010) dataset. In this case we modeled this country by combining educational

attainment parameters from Nigeria, whichwere available in the Human Development
Index database, and the progress made in thisregard by other African countries, particularly
Ghana, South Africa and Kenya using Barroand Lee (2010). Readers should particularly be
cautious when interpreting the human capitaltrends for this country. Human capital per capita is further extended considering the population of the country who reach the year of total
education, “P”. For simplicity we have assumed
that to be the age of 15. Therefore, the total
amount of human capital is:
Equation 2

H=hP
As the interest rate (“ρ”) is constant overtime, changes in human capital are basicallycaused by either the change in the number ofpeople educated, or an increase (decrease) in theyears of education.
Regarding the shadow price per unit ofhuman capital, Pkhuman, it is obtained by computing the present value of the average labor
compensation per unit of human capital, “r”,
received by workers over an entire life’s working
period, “T”, i.e.:
Equation 3
T

Pkhuman=∫ r·e -δtdt
t=0With regard to “T”, this parameter isobtained by using various demographic inputs
such as population and mortality rates by age
and gender, as well as other parameters related
to the labor market, particularly the participation of the population in the labor force by
age and gender. In our case, for each nation wecomputed these shadow prices for every year
within the time period 1990–2008. Concerning
the discount rate, “δ”, it was fixed in 8.5 percent.
Subsequently we used the average of this rental
price of one unit of human capital over time as
the representative weight for entering humancapital into the wealth accounting framework.
For further details, see Arrow et al. (2012).

281

Table 1

Table 2

Key variables and data sources used in themeasurement of human capital

Key variables and data sources used in themeasurement of manufactured capital

Variables

Data sources

Variables

Data sources

Population by age
and gender

United Nations Population
Division (2011)

Investment

United Nations Statistics
Division (2011b)

Mortality probability
by age and genderWorld Health Organization(2012)

Depreciation rate

It is assumed a rate of 7%

Assets lifetime

Discount rate

Klenow and Rodríguez-Clare(1997)

It is assumed indefinite
depreciation periods

Employment

Conference Board (2012)

Output growth

Educational
attainment

Conference Board (2012);
United Nations Statistics
Division (2011b)

Barro and Lee (2010)
Population

Employment
compensation

Conference Board (2012);
United Nations Statistics
Division (2011a)

United Nations Population
Division (2011)

Labour force by age
and genderInternational Labour
Organization (2011)

Productivity

United Nations Statistics
Division (2011b); Conference
Board (2012); and United
Nations Population Division(2011)

2. Manufactured capitalWith regard to manufactured capital, we followed the method developed in King andLevine (1994), who based their calculations on
the perpetual inventory method (PIM) by setting
an initial capital estimate. Regarding the initial
estimate, “K 0”, it is assumed that the economy isin a steady-state, implying this that the capitaloutput ratio is constant in the long term, andcan be derived as follows:
Equation 4k=I/y(б+γ+n)where “k” is the capital-output ratio; “I” isinvestment; “y” is the output of the economy;“γ” is the steady-state growth rate of the economy, estimated as a weighted average growthrate of the economy under study, and that of the
global economy (see King and Levine [1994]); “δ”
is the depreciation rate of the capital (here is set
at 7 percent, and it is additionally assumed to beconstant across countries and time); and “n” isthe population growth rate.
282

Once this ratio is measured, it is subsequently
multiplied by the output of the economy understudy, in order to obtain a first estimate of the
manufactured capital stock in the initial period,
K 0. Subsequently, the PIM allows capturing of
the dynamics in the manufactured capital accumulation by looking at the annual changes ininvestment. The corresponding formula of the
PIM combined with the initial estimate is:
Equation 5t

Kt = ∑ Ij (1–γ)t-j+(1–γ)tK0
j=1

Finally, regarding the lifetimes of the assets,
we have assumed indefinite depreciation periods. As mentioned in Chapter 2, we carriedout our initial estimate in 1970 in order tominimize errors in the time period under study(1990–2008). As capital depreciates over time,the initial capital estimate retained in 1990
would be about 22 percent and only 5 percent in2008. This means that any potential error in thedeparture point (year 1970) would be attenuatedin the relevant period under analysis. For further details on this method, see King and Levine(1994).

Inclusive Wealth Report3. Natural capital
3.1 Agricultural land
3.1.1 Cropland
Regarding the inclusion of this natural capital
asset, we primarily obtained this by analyzing
the physical amount of cropland area available
every year, and its corresponding shadow price.
We used cropland data from FAO for calculating the physical changes over the time span instudy, 1990–2008. Concerning the valuing of
this asset, we appealed conceptually to the netpresent value (NPV) of future rental flows. We
applied this evaluation on an annual basis so
as to obtain, subsequently, the average wealthvalue per hectare for the entire period of analysis. Once this later wealth value per hectare wasobtained, we multiplied this by the total number of hectares available in the country for cropland. This method is also used in other studies,such as the World Bank (2011A). In our method,
however, we introduce minor modifications byanalyzing a vast number of crops (159) in order
to arrive at a representative rental price perhectare for a specific year.
Concretely, we estimated the average rental
price per hectare (RPA) for country “i” in theyear “j” as follows:

1
A

Equation 7
∞

RPAij

t=0

(1+r)tWhaij=∑

where “r” is the discount rate, assumed to beequal to 5 percent and “t” is the planning horizon, here assumed up to infinity. Subsequently,
we used the average wealth values per hectare(Wha i) over the study period as a proxy of the
shadow price:
Equation 8

Wha i =

1
19

19

∑ Whaij
t=1

Finally, the total wealth in cropland land
(WCL) for country “i” in year “j” is derived asfollows:
Equation 9

WCLij=Wha i · CLAj
where “CLA” is the physical amount of total
crop land area of country “i” and in the year “j”,
while “WCL” is the total wealth in cropland in
the corresponding year.
3.1.2 Pastureland

Equation 6

RPAij=

To calculate the value of total wealth perhectare (Wha) we estimated the present valueof future rental flows, as follows:

159∑ Rik · Pijk · Qijk
k=1

where “Q”, “P” and “R” are the quantity of
production of crop “k”, (with k=1,2,..,159), priceper amount of crop k and the rental rate of cropk respectively; “j” is the year of analysis, with “j”
running from 1990 to 2008; and “A” is the total
area harvested. To estimate the rent by crop
we map FAO crop classification (HS) with those
sectoral rental rates provided by Narayanan andWalmsley (2008) in order to get the rental rateby crop group.

ANNEX Methodological annex

For pastureland, we applied a similar methodology as with cropland in that we aimed
at obtaining the total wealth per hectare of
pastureland and the corresponding physicalquantity available during the period of analysis.
However, while it is possible to find data of production, prices, and rental rates of the products
stemming from this kind of land, it is hard tolink such rents to a particular amount of land
involved in the production process (unlike cropland). Given this limitation, we assumed thatthe rents per hectare in pastureland are equal
to that of the cropland. This also means that the
total wealth per hectare in pastureland is identical to the estimates in the previous section for283

Table 3.1

Key variables and data sources used in themeasurement of agricultural land
Variables

Data sources

Quantity of crops
produced

FAO (2011)

Price of crops
produced

FAO (2011)

Rental Rate

Narayanan and Walmsley(2008)

Harvested area incrops

FAO (2011)

Discount rate

It is assumed a rate of 5%

Permant crops landarea

FAO (2011)

Permanent pastureland area

FAO (2011)

Table 3.2

Key variables and data sources used in themeasurement of forest wealth284

Variables

Data sources

Forest stocks

FAO (2010); FAO (2006); FAO(2001); FAO (1995)

Forest stock commercially available

FAO (2006)

Wood production

FAO (2011)

Value of wood
production

FAO (2011)

Rental rate

Bolt et al. (2002)

Forest area

FAO (2011)

Value of non-timber
forest benefits(NTFB)

Lampietti and Dixon (1995)

Percentage of forest
area used for the
extraction of NTFBWorld Bank (2006)

Discount rate

It is assumed a rate of 5%

cropland. Therefore the total wealth in pastureland (WPL) was estimated as follows:
Equation 10

WPLij=Wha i · PLA j
where “PLA” is the physical amount of pasture land area available in the period “j” andcountry “i”.

3.2 Forest resources
3.2.1 Timber
In order to value forest timber stocks, we followed the methodology developed by Arrow etal. (2012), which differs to some extent from thatof the World Bank (2006, 2011A). As a starting
point, we estimated the volume of timber commercially available. This first measure basicallystems from the multiplication of the forest area,
timber density per area, and the percentage ofsuch total volume that is commercially available – all these parameters are country-specificand were obtained from the Forest Resources
Assessment (FAO, 2010; FAO, 2006; FAO, 2001;
FAO, 1995). Unfortunately, parameters regarding
the volume, area, and density of forest are only
available for the following years: 1990, 2000,
2005, and 2010. We therefore carried out linear interpolations to derive estimates for those
years where data is not available.
With regard to the stumpage price, we followed the World Bank’s (2006) method byadopting a weighted average price of two different commodities: industrial roundwood
and fuelwood, which are also country-specificparameters. The weight attached to the different prices is based on the quantity of the commodity manufactured, while industrial roundwood and fuelwood prices are obtained fromthe value and quantity exported and produced
respectively. Three further steps were applied
regarding the rental price estimates: (1) we converted the annual estimated values from current to constant prices by using each countryspecific GDP deflator; (2) subsequently, we used
Inclusive Wealth Reportinformation on the regional rental rates for timber estimated by Bolt et al. (2002). Such rates are
assumed to be constant over time; and (3) lastly,
we estimated the average price over the entire
study period (1990–2008), thereby obtaining
our proxy value for the shadow price of timber.
Concerning the estimates of total timber
wealth, we multiplied the constant rental priceover time obtained in the last step by the total
volume of timber commercially available everyyear.
3.2.2 Non-timber forest resources
Consistent with the studies of Arrow et al.
(2012) and the World Bank (2006, 2011b), we valued non-timber forest benefits (NTFB) following
the work of Lampietti and Dixon (1995). Theseauthors estimated the economic benefits of
NTFR as US$190 per hectare for developed countries and as US$145 per hectare for developing
countries. We then multiplied these coefficientsby the forest area that is accessed by the population, which is assumed to be 10 percent of thetotal forest area. For the data on forest area, weused FAO (2012). Finally, the total wealth of NTFR
was calculated as the present value of future
benefits assuming an infinite time horizon anda discount rate of 5 percent.

species for Canada; 10 in South Africa; and 80
in the U.S. However, data on fisheries and prices
were not found for the years 2007 and 2008.
Therefore, we carried out our own estimates
based on linear trends for these two years to beconsistent with the rest of the wealth accounts.
Regarding the valuation of fisheries, ourstarting point was to derive prices per tonne
from the total landing value and quantity of the
Sea Around Us Project (SAUP 2011), which areavailable for the time period 1990–2006. It washowever only possible to obtain such prices for
20 species in the case United states; 7 species forSouth Africa; 6 for Canada; and 20 for Australia.
Given that the mapping between the stock
assessed and the corresponding prices of suchspecies was rather low, we opted for estimatinga representative price per tonne of fisheries foreach of the four countries. This was done by estimating a weighted (by extracted quantity) priceof those species reported by the Sea Around Us
Project, and using this as a proxy price for all thephysical stocks. We subsequently averaged theseweighted prices over time, and multiplied themby the fisheries rental rate from Narayanan andWalmsley (2008), thereby arriving at the averagerental price for fisheries and country.
The last step for obtaining the wealth of fisheries consisted in multiplying the average rental
price by the total stock of biomass available ineach of the years under analysis.

3.3 Fisheries
We valued the wealth of fisheries for four countries: Australia, Canada, South Africa, and theUnited States. We restricted our analysis to only
these countries due to lack of data in the otherregions of interest. In this regard, we obtained
the available stock of fisheries within thesecountries’ fishing areas from the RAM Legacy
Stock Assessment Database (Richard et al.,in press). From this database, we were able toobtain the total biomass expressed in tonnes
for several species which number vary according to the country. In the case of the above four
countries, the RAM Legacy Stock Assessment
Database reports 12 species for Australia; nine
ANNEX Methodological annex

Table 3.3

Key variables and data sources used in themeasurement of fisheries
Variables

Data sources

Fishery stocks

Richard et al. (in press)

Value of capture
fishery

SAUP (2011)

Quantity of capture
fishery

SAUP (2011) and Sumaila etal. (2005)

Rental rate

Narayanan and Walmsley(2008)

285

Table 3.4

Key variables and data sources used in themeasurement of fossil fuels
Variables

Data sources

Reserves

U.S. Energy Information
Administration (2011)

Production

U.S. Energy Information
Administration (2011)

PricesU.S. Energy Information
Administration (2011)

Rental rate

Narayanan and Walmsley(2008)

by using the U.S. GDP deflator. We obtained therental prices by multiplying the above estimatedprices and the corresponding sectoral rental
rates from Narayanan and Walmsley (2008).
We set the end of year reserves of coal,natural gas and oil to 2008 and obtained thisdataset from the U.S. Energy Information
Administration (2011).
The stocks of natural gas, oil, and coal fora previous year to 2008, were estimated asfollows:
Equation 11

Stock t-1 = Stockt + Productiont
Table 3.5

Key variables and data sources used in themeasurement of minerals
Variables

Data sources

Reserves

U.S. Geological Survey (2011)

Production

U.S. Geological Survey (2011)

PricesU.S. Geological Survey (2011))
and World Bank (2011b)

Rental rate

Narayanan and Walmsley(2008)

3.4 Fossil fuels
In our analysis, we followed the approach used
by Arrow et al. (2012). As noted in Chapter 2,
fossil fuels consist of three main components:
coal, natural gas, and oil. The methodology ofvaluing the wealth of these stated components
largely follows the same procedure.
We referred to BP Statistical Review of World
Energy (BP 2011) for prices of coal, natural gas,and oil. For coal, we averaged prices from four
sources: the U.S., Northwest Europe, Japan
Coking; and Japan Steam. For natural gas, we also
averaged prices from five sources: the European
Union (EU), United Kingdom, the U.S., Japan,
and Canada. Lastly, we averaged the prices offour types of oil grades: Dubai, Brent, Nigerian
Forcados, and West Texas Intermediate. We
adjusted for inflation before averaging over time286

where the corresponding stock under study
in the year t-1 is derived from the production
and stock in year “t”. Finally, we computed thewealth coal, natural gas, and oil by multiplying
the stocks and the unit rental price for each ofour 20 countries for the period under study.

3.5 Metals and minerals
In order to value metals and minerals, we followed the method used by Arrow et al. (2012).
We set the reserves base to 2008 and obtained
reserves data from the United States Geological
Survey published in their Mineral Commodity
Summaries and/or Minerals Yearbooks (U.S.
Geological Survey 2011). We focused on 10
mineral types: bauxite, copper, gold, iron,
lead, nickel, phosphate, silver, tin, and zinc.
As explained in Chapter 2 we only obtained
reserves data for 12 countries: Australia, Brazil,
Canada, Chile, China, Colombia, India, Japan,
Russia, South Africa, the U.S., and Venezuela.
Production data are based on United States
Geological Survey numbers published intheir Mineral Commodity Summaries and/or
Minerals Yearbook (U.S. Geological Survey 2011).
We filled in the missing years by extrapolating
linearly.
We calculated previous years’ stocks by using
the following equation:

Inclusive Wealth ReportEquation 12

Stockt-1 = Stockt + Productiont
where the production and stock in year“t”are used to compute the amount of the mineral available in the year “t-1”.
As far as prices are concerned, we obtained
world annual market prices for the 10 mineralcommodities from the World Bank (2011B) and
U.S. Geological Survey (2011) for the period
1990–2008. We converted to year 2000 constant prices and computed average prices foreach mineral. As with fossil fuels, we retrieved
sectoral rental rates of different mineral industries from Narayanan and Walmsley (2008) andmultiplied by the corresponding prices.
We finally valued minerals by multiplying
mineral stocks by rental prices to obtain the
total mineral wealth for each of the 12 countries
for the period under study.

4. Health Capital
As discussed in chapter 2, our health capital
estimates rely on the methodology developed inArrow et al. (2012). In this work, the total valueof health capital (VHeC) stems from multiplying the value of the total expected discounted
years of life remaining of a country’s population (HeC) and the value of a statistical life year
(VSLY), which is the constant shadow price of aunit of health capital. In other words:
As far as HeC is concerned, it is estimatedas follows:
Equation 13

from computing the density of age of death,“f(t)” – “t” being the year of death – and thecumulative distribution of age of death, “F(a)”,in the following way:
Equation 15

f(t|t≥a)=[1-F(a)]-1f(t)“δ” is the rate at which future years are discounted, assuming that the value of an additional year is independent of age.
“u” is time expressed in years.
Regarding the estimates of VSLY, these wereobtained by dividing the value of the statisticallife (VSL) and the average expected discounted
years of life remaining per person.
Probability of dying, by age group, wasobtained by the life tables of the World HealthOrganization (2012). The WHO life tables report
the probability of death for five-year age groups.
For our estimates, we additionally smoothed
the data between age groups in order to get theparameter for every age. Moreover, as the WHO
life tables are only available for the years 1990,
2000, and 2009, we used linear interpolations
for obtaining all the years of interest, 1990–2008.
Concerning the VSL, we used the value reported
by EPA of US$6.3 million in 2000 in the case of
the U.S. For the remaining countries, we utilized
an implied value of VSL estimated by multiplying
the US$6.3 million value for the U.S. and the GDP(per capita) ratio of the country under analysis
to the U.S. at the power of 0.6, as suggested by
Viscusi and Aldy (2003) and applied in Arrow etal. (2012). Finally, we applied a discount rate of
5 percent.

VHeC =HeC x VSLY
where:
Equation 14100

5. Adjustments
100

t-a

t=a

u=0

HeC= ∑ P(a ) [ ∑ f(t|t≥a)( ∑ (1-δ)u)]a=0“P(a)” is the population of age “a” available
in the country. Years of life reaming are truncated at the age of 100.
“f(t)=f(t|t≥a)” is the conditional density ofage of death given survival to age “a” that results
ANNEX Methodological annex

5.1 Carbon damages
Carbon damage estimates are based on themethod developed in Arrow et al. (2012). The
key methodological steps can be described asfollows: (1) obtain the total global carbon emissions for the period under analysis, 1990–2008;(2) derive the total global damages as a function
287

Table 4

Key variables and data sources used in themeasurement of health capital
Variables

Data sources

Population by age

United Nations Population
Division (2011)

Probability of dying
by ageWorld Health Organization(2012)

Value of statisticallife

U.S. Environmental
Protection Agency (2000)

Discount rate

It is assumed a rate of 5%

Table 5.1

Key variables and data sources used in themeasurement of carbon damages
Variables

Data sources

Carbon emission

Boden et al. (2011)

Forest area

FAO (2011)

carbon release perhectare of forest

Lampietti and Dixon 1995

Carbon costTol (2009)

Climate change
impacts

Nordhaus and Boyer (2000)

GDP

United Nations Statistics
Division (2011b)

Table 5.2

Key variables and data sources used in themeasurement of oil capital gains

288

of the emissions; and (3) allocate the global damages to the countries according to the potential
effect of global warming in their economies.
Global carbon emissions: Two sources ofcarbon emissions were taken into account: (i)carbon emissions stemming from fuel consumption and cement, which were obtained from theCarbon Dioxide Information Analysis Center(Boden et al. 2011); and (ii) emissions resulting
from global deforestation. In this case, we used
FAO (2011) data on the changes in annual global
forest land. It is further estimated that the average carbon release per hectare is equal to 100
tonnes of carbon (Lampietti and Dixon 1995).
Global carbon damages: The damages per
tonne of carbon released to the atmosphere
are estimated at US$50 (see Tol et al., 2009).
Multiplying the total global tonnes of carbon
released to the atmosphere by the price per
tonne, we obtain the total global carbon damages. Notice that this parameter is constant overtime.
Assigning carbon damages to countries: tocalculate the distribution of the damages thateach region will suffer, we referred to the studyof Nordhaus and Boyer (2000). This study presents the distribution of damages that different
regions and the global economy as a whole will
suffer as a percentage of the corresponding
regional and global GDP. By using country andglobal GDP information, we were able to reestimate regional percentage damages in termsof the total global GDP – and not related to thecountry GDP – as initially presented in Nordhaus
and Boyer (2000). Finally, we apportioned theglobal damages estimated in step 2 according tothis later percentage.

Variables

Data sources

Carbon emission

Boden et al. (2011)

Reserves

U.S. Energy Information
Administration (2011)

Oil production

U.S. Energy Information
Administration (2011)

Oil consumption

U.S. Energy Information
Administration (2011)

5.2 Oil capital gains

PricesBP (2011)

Rental rate

Narayanan and Walmsley(2008)

As noted in Chapter 2, gains in oil prices are separately accounted for in the wealth accounts. In
order to include this adjustment, we assumed anannual increase of 5 percent in the rental priceof oil, which corresponds to the annual averageoil price increase during the years 1990–2008
Inclusive Wealth ReportTable 5.3

Total factor productivity estimates
1990

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Australia

0.15 -1.02

1.78

0.36

BrazilCanadaChile
China
Colombia
EcuadorFranceGermany
India
Japan
Kenya
Nigeria
NorwayRussia*Saudi Arabia
South Africa
United Kingdom
United States
Venezuela

-6.50
-1.68
-0.39
-0.73
-2.51
-0.02
0.34
2.96
1.15
2.32
0.60
3.51
2.57

-1.56
0.01
7.24
4.33
2.24
-1.56
-0.05
1.05
1.57
-1.45
-4.13
-0.95
3.10

3.59 4.10
0.27 1.61
2.25 0.94
3.07 2.97-0.62 -2.14-2.58 1.27
-0.86 0.92
-0.34 1.97
1.83 2.60-0.16 -8.83-3.02 -0.07
0.83 -0.45
1.97 3.26-7.48 -10.59-4.64 -3.32-1.66 0.17
2.16 1.37
0.08 0.86-2.34 -4.49

-0.27
-1.97
3.52
2.14
-3.11
2.42
-0.27
2.12
-2.37
0.30
-2.05
-2.22
3.85

9.42 4.82 0.30
-3.72 -4.03 -5.08-1.41 0.60 0.91
-0.06 -0.77 1.83
2.97 7.86 3.32

0.53 -0.12
2.17
0.18
5.50
7.52
3.57
-2.01
0.90
1.76
2.81
1.14
1.56
-1.80
2.37
-1.08
-2.80
-0.44
0.39
-0.11
2.32

2.14

1.19

1.78

0.64 -0.34

1.56 -0.28 -0.88 -0.23 -1.70 -1.82

1.09 0.97 -2.58 -2.21 0.43 -0.71 -0.44-1.21 1.23 0.33 1.05 1.33 -0.52 0.35
1.42 0.87 -2.20 -12.18 -0.07 -1.67 -1.96-4.83 -1.36 -5.87 0.53 3.31 4.73 6.14
-3.21 1.52 -2.49 -7.30 0.28 -1.58 1.41
1.93 0.29 0.12 -5.30 2.33 0.46 -0.79-0.87 0.63 1.28 0.36 1.74 -0.46 0.74
1.36 1.66 -0.09 0.71 2.28 1.07 0.06
3.58 0.45 2.61 2.20 -0.16 1.31 -0.60
0.76 0.42 -2.15 0.01 1.00 0.14 0.73
1.09 -2.61 0.41 -0.50 -2.24 1.93 -2.47
3.08 0.37 -0.39 -1.89 3.58 5.69 16.09
2.54 1.87 -1.17 -0.71 1.64 0.94 0.33
-1.66 3.92 -3.06 8.21 11.43 6.29 5.32
0.99 0.54 0.59 -3.85 1.11 -3.92 -4.81
0.27 -1.58 -4.02 -2.02 0.19 -0.92 0.35
0.72 0.02 0.68 0.35 1.13 -0.01 0.49
1.29 0.66 0.44 1.47 1.26 -0.16 0.46
-1.97 4.40 -2.25 -8.34 1.49 0.90 -9.67-0.89 1.63
-0.67 -0.38-0.26 2.40
7.85 2.61-0.76 1.99
0.38 1.77-0.10 -0.54-0.25 0.35
3.69 2.33
0.98 1.47
0.02 1.60
6.57 6.18
0.76 1.07
7.45 6.59
2.70 0.86-0.83 0.48
1.15 1.08
0.95 1.67-8.14 16.57

-0.65
0.55
0.82
2.62
-0.24
2.49
-0.14
1.45
3.65
0.74
2.36
0.09
-0.34
4.69
1.18
0.58
-0.16
0.82
8.30

-0.40
-0.41
-3.76
4.65
4.33
-0.15
1.19
2.90
3.38
0.58
1.96
-0.43
-2.09
4.84
-1.38
0.35
1.34
0.03
2.62

0.11 -1.48
1.13
-1.05
0.61
6.07
1.43
-0.90
-0.51
1.31
2.79
1.57
2.22
0.32
-2.56
3.52
-2.93
-0.17
0.94
-0.09
2.12

-1.57
-1.82
-0.96
2.35
-2.95
3.54
-2.60
-0.64
0.72
-0.78
-3.35
-0.75
-3.92
-0.37
-1.39
-3.39
-0.85
-1.05
0.62

*Note: The average TFP presented in Section 5 of Chapter 2 for the case of Russia is computed considering only the years 1993–2008.
Source: Conference Board (2012).

(BP 2011). These increments in the rental priceof oil are multiplied by the stock of oil available
in each period. Data on oil stock rely on themethod presented above in Section 3.4.
Conversely, other countries that dependon oil imports may be negatively affected as
their capacity to build other capital forms isfrustrated by these higher prices. We therefore
allocate those gains in oil prices to those nations
that consume the commodity. To do so, we useddata on oil consumption from our country sample as well as total world oil consumption. We
were thus able to estimate the way in which theoil capital gains have to be distributed among
each of the 20 countries in this study, as well as
the rest of the world. Finally, we subtracted theoil capital gains from the losses due to oil consumption, thereby obtaining the net oil capitalgains/losses.

ANNEX Methodological annex

5.3 Total factor productivity (TFP)
Country estimates on total factor productivity were obtained from the Total Economy
Database (Conference Board, 2012). The corresponding values for all countries are listed inTable 5.3.

289

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Bolt, K., Matete, M. & Clemens, M. (2002).
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Lampietti, J. & Dixon, J. (1995). To see theforest for the trees: A guide to non-timber forest
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Inclusive Wealth ReportData annex: wealth by country

292 Australia
294 Brazil
296 Canada
298 Chile
300 China
302 Colombia
304 Ecuador
306 France
308 Germany
310

India

312

Japan

314

Kenya

316

Nigeria

318

Norway320 Russia
322 Saudi Arabia
324 South Africa
326 United Kingdom
328 United States
330 Venezuela

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291

Data annex: wealth by country

Australia

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

4,747,891

4,782,508

4,817,827

4,846,260

4,904,314

4,953,813

5,002,667

2

Produced capital

661,628

675,640

692,791

712,469

738,622765,188795,4593

Human capital

2,100,350

2,127,023

2,146,937

2,166,146

2,194,588

2,228,303

2,250,604

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

1,985,913

1,979,844

1,978,100

1,967,645

1,971,105

1,960,323

1,956,604

5

Agricultural land, rows 6 + 7

442,297

440,862443,913438,302446,695

441,218443,002

6

Cropland

45,78543,683

45,11544,26645,23138,37534,757

7

Pastureland

396,512397,179

398,798

394,037

401,464

402,843

408,245

8

Forest resources, rows 9 + 10

219,757

219,817219,877

219,937

219,996

220,056

220,116

9

Timber171,244

171,291

171,337

171,384

171,431

171,477

171,52410

Non-timber forest resources

48,51348,526

48,53948,55348,566

48,57948,592

11

Fisheries

308

278

261

245

238

236

233

12

Fossil fuels, rows 13 + 14 + 15

1,222,824

1,218,953

1,214,907

1,210,834

1,206,702

1,202,237

1,197,664

13

Oil

11,639

11,634

11,629

11,625

11,62011,615

11,61014

Natural gas

50,84850,09649,29348,43147,501

46,47045,40815

Coal

1,160,337

1,157,222

1,153,984

1,150,778

1,147,581

1,144,152

1,140,647

16

Minerals, rows 17 + 18 +…+ 26

100,728

99,93599,14398,327

97,47396,576

95,58917

Bauxite

10,882

10,816

10,752

10,685

10,617

10,548

10,47818

Appendix

7,131

7,069

6,997

6,927

6,851

6,769

6,667

19

Gold

8,951

8,744

8,530

8,312

8,086

7,863

7,607

20

Iron

44,15943,892

43,63743,36143,06942,74342,408

21

Lead

1,917

1,886

1,855

1,827

1,798

1,773

1,745

20,55520,505

20,464

20,417

20,36020,28920,20822

Nickel23

Phosphate

385

385

385

385

385

385

385

24

Silver

812

796

780

765

751

738

724

25

Tin

123

121

118

114

110

106

102

26

Zinc

5,812

5,720

5,627

5,535

5,445

5,361

5,264

27

Health capital

81,730,343

82,921,298

84,053,099

85,144,107

86,221,223

87,309,208

88,432,849

28

IWI adjustments excluding TFP, rows 29 + 30

-3,780-3,819-4,138-4,650-5,028-5,401-5,722

29

Carbon damages (annual change)

1,151

1,168

1,155

1,154

1,173

1,193

1,216

30

Oil capital gains (annual change)-4,930-4,987-5,293-5,804-6,201-6,594-6,939Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

277,717

276,116

274,842

273,377

273,651

273,413

273,07732

Per capita produced capital

38,70039,00839,52140,19041,21442,23343,42133

Per capita human capital

122,855

122,803

122,476

122,192

122,453

122,986

122,85234

Per capita natural capital

116,161

114,306

112,844

110,994

109,984

108,195

106,80435

Per capita health capital

4,780,628

4,787,429

4,794,960

4,802,963

4,810,964

4,818,810

4,827,216

36

TFP (in percentage)

0.15

-1.02

1.78

0.36

0.53

-0.12

2.14

37

Population

17,096,153

17,320,633

17,529,469

17,727,413

17,921,818

18,118,416

18,319,637

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

292

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

5,054,439

5,116,193

5,169,947

5,246,458

5,303,968

5,383,658

5,467,852

5,564,708

5,698,718

5,825,973

5,969,781

6,105,8312

831,255

868,670

910,913950,558

978,463

1,027,813

1,083,185

1,142,991

1,210,489

1,281,239

1,363,182

1,440,787

3

2,275,721

2,304,747

2,332,119

2,373,981

2,410,817

2,457,044

2,500,680

2,545,069

2,615,175

2,690,889

2,771,667

2,847,924

4

1,947,463

1,942,776

1,926,914

1,921,919

1,914,688

1,898,801

1,883,987

1,876,649

1,873,054

1,853,845

1,834,931

1,817,120

5

440,125

441,635

432,059433,745433,935

425,651

418,509

419,090423,888414,153

405,129

397,358

6

38,18542,184

43,61345,32747,73345,826

45,11245,78447,36645,76942,40342,255

7

401,940

399,451

388,446

388,418

386,203379,825

373,397373,306

376,522368,383

362,726

355,1038

220,176

220,235

220,295

220,355

220,070219,786

219,501

219,217

218,932

217,618

216,304

214,9909

171,570

171,617

171,663

171,710

171,488

171,267

171,045

170,823

170,602

169,577

168,553

167,52910

48,605

48,61948,632

48,64548,58248,51948,456

48,394

48,331

48,04147,75147,460

11

231

227

223

220

218

217

214

211

208

206

204

201

12

1,192,854

1,187,680

1,182,434

1,176,921

1,171,064

1,165,006

1,158,884

1,152,578

1,145,928

1,139,206

1,132,126

1,124,994

13

11,605

11,60011,595

11,588

11,582

11,577

11,572

11,567

11,563

11,55911,554

11,55014

44,354

43,25942,14540,98939,806

38,57437,30235,99634,55933,05331,511

29,93515

1,136,896

1,132,821

1,128,694

1,124,344

1,119,676

1,114,855

1,110,010

1,105,015

1,099,805

1,094,594

1,089,060

1,083,509

16

94,07792,99991,90390,67889,40088,14186,87985,552

84,09882,662

81,16879,57817

10,406

10,333

10,254

10,167

10,079

9,992

9,901

9,830

9,732

9,632

9,530

9,426

18

6,465

6,344

6,200

6,038

5,868

5,696

5,535

5,364

5,183

5,012

4,843

4,671

19

7,036

6,762

6,497

6,235

5,984

5,743

5,494

5,267

5,035

4,818

4,600

4,410

20

42,04841,693

41,34740,95640,54340,126

39,69939,166

38,56837,941

37,26036,480

21

1,695

1,662

1,625

1,585

1,547

1,510

1,473

1,437

1,396

1,359

1,324

1,290

22

20,066

19,963

19,871

19,752

19,61019,476

19,34819,222

19,084

18,95818,84318,707

23

385

385

385

382

375

367

358

349

339

328

318

307

24

709

689

666

638

611

583

558

528

495

472

446

420

25

97

93

88

84

79

76

74

74

73

72

71

70

26

5,170

5,075

4,970

4,841

4,704

4,571

4,437

4,317

4,193

4,070

3,933

3,796

27

89,574,97890,739,006

91,926,438

93,141,001

94,339,347

95,566,314

96,870,704

98,318,871

28-6,018-6,349-6,765-6,999-7,336-7,798-8,049-8,308-8,836-9,112-9,672-10,551

29

1,235

1,231

1,222

1,249

1,219

1,230

1,299

1,362

1,412

1,468

1,500

1,534

30

-7,253-7,580-7,987-8,248-8,555-9,028-9,348-9,670-10,248-10,580-11,172-12,085

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

272,842

273,084

272,851

273,761

273,652

274,620

275,596276,799

279,301

280,847

282,660

283,81032

44,872

46,36648,07549,60050,48352,42954,59656,85459,327

61,76364,54566,97033

122,845

123,019

123,081

123,875

124,383

125,333

126,042

126,596

128,173

129,717

131,234

132,376

34

105,125

103,698

101,695

100,286

98,78696,85894,95893,34891,80189,36786,881

84,46335

4,835,316

4,843,320

4,851,539

4,860,118

4,867,322

4,874,825

4,882,566

4,890,556

4,898,914

4,909,316

4,919,915

4,930,699

36

1.19

1.78

0.64

-0.34

1.56

-0.28

-0.88

-0.23

-1.70

-1.82

0.11

-1.48

37

18,525,153

18,734,878

18,947,894

19,164,351

19,382,188

19,604,051

19,840,120

20,103,822

20,403,520

20,744,295

21,119,988

21,513,817

ANNEX Data

99,955,087 101,840,301 103,908,549 106,078,149

293

Data Annex: Wealth by Country

Brazil

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

4,922,507

5,034,400

5,141,044

5,252,759

5,380,368

5,523,537

5,668,095

2

Produced capital

1,059,810

1,069,536

1,073,024

1,081,225

1,100,729

1,125,808

1,150,665

3

Human capital

2,406,780

2,510,655

2,617,003

2,722,790

2,833,959

2,950,267

3,074,410

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

1,455,917

1,454,210

1,451,016

1,448,744

1,445,680

1,447,463

1,443,019

5Agricultural land, rows 6 + 7

231,816

235,014

236,710239,353

241,228

247,997248,521

6

Cropland

55,081

56,59656,60957,56857,76062,84562,749

7

Pastureland

176,735

178,418

180,101

181,784

183,468

185,151

185,772

8

Forest resources, rows 9 + 10

1,019,148

1,014,845

1,010,542

1,006,238

1,001,935

997,631

993,328

9

Timber878,888875,289871,691

868,093

864,494

860,896857,29710

Non-timber forest resources

140,261

139,556

138,851

138,146

137,440

136,735

136,030

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

151,293

151,128

150,959

150,779

150,587

150,389

150,178

13

Oil

81,482

81,476

81,471

81,46581,45981,45281,44514

Natural gas

13,564

13,46813,362

13,243

13,12012,99012,84615

Coal

56,24656,184

56,12656,07156,00955,94655,888

16

Minerals, rows 17 + 18 +…+ 26

53,65953,22352,80552,37451,93051,44750,992

17

Bauxite

3,117

3,102

3,089

3,075

3,064

3,049

3,033

18

Appendix

2,688

2,681

2,675

2,667

2,660

2,652

2,644

19

Gold

2,345

2,276

2,209

2,154

2,099

2,050

2,003

20

Iron

40,22039,914

39,62039,30038,96738,597

38,246

21

Lead

44

43

43

43

43

42

42

3,311

3,300

3,290

3,280

3,261

3,245

22

Nickel3,328

23

Phosphate

859

859

859

859

859

859

859

24

Silver

-

-

-

-

-

-

-

25

Tin

349

337

325

314

303

296

288

26

Zinc

710

700

686

671

656

641

632

27

Health capital

28

IWI adjustments excluding TFP, rows 29 + 30

-15,470-15,963-16,494-17,346-18,476-19,884-21,308

29

Carbon damages (annual change)-8,590-8,717-8,624-8,616-8,754-8,906-9,08130

Oil capital gains (annual change)-6,880-7,246-7,870-8,730-9,722-10,978-12,226

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

32,89333,08933,25833,46033,754

34,12834,49032

Per capita produced capital

7,082

7,030

6,941

6,887

6,906

6,956

7,002

33

Per capita human capital

16,083

16,502

16,93017,344

17,77918,22918,70734

Per capita natural capital

9,729

9,558

9,387

9,229

9,070

8,943

8,781

35

Per capita health capital

1,705,962

1,709,706

1,713,565

1,717,459

1,721,322

1,725,165

1,728,796

36

TFP (in percentage)

-6.50

-0.27

-1.56

3.59

4.10

2.17

1.09

37

Population

255,297,511 260,126,396 264,886,415 269,616,728 274,376,251 279,214,853 284,114,750

149,650,206 152,146,887 154,582,103 156,985,824 159,398,558 161,848,162 164,342,524

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

294

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

5,829,884

5,992,024

6,146,495

6,299,015

6,490,400

6,632,379

6,758,525

6,896,408

7,044,434

7,153,950

7,264,466

7,413,777

2

1,182,836

1,212,368

1,230,625

1,253,267

1,273,852

1,287,776

1,295,990

1,312,601

1,331,940

1,360,796

1,404,541

1,464,091

3

3,208,527

3,345,651

3,486,299

3,620,695

3,793,288

3,925,014

4,046,622

4,171,206

4,303,947

4,390,723

4,463,687

4,559,539

4

1,438,521

1,434,005

1,429,571

1,425,053

1,423,261

1,419,590

1,415,914

1,412,601

1,408,547

1,402,432

1,396,238

1,390,147

5

249,046249,570

250,191

250,812

252,787

252,917

253,109

253,780

253,780

253,780

253,780

253,972

6

62,65462,55862,55862,55863,771

63,90164,572

65,24465,72465,72465,72465,916

7

186,393

187,013

187,633

188,254

189,016

189,016

188,536

188,536

188,056

188,056

188,056

188,0568

989,024

984,721980,417976,114

973,146

970,179

967,211964,244961,277

956,334

951,392

946,4509853,699

850,101

846,502842,904

840,690

838,477

836,263

834,050

831,836

827,429

823,023

818,61610

135,325

134,620

133,915

133,210

132,456

131,702130,948

130,194

129,441

128,905

128,370

127,834

12

149,944

149,702

149,448

149,147

148,879

148,572

148,250

147,895

147,526

147,157

146,788

146,330

13

81,43781,42881,41981,40881,39881,386

81,37481,362

81,34881,33481,31881,302

14

12,687

12,521

12,344

12,135

11,945

11,712

11,45911,182

10,901

10,618

10,3369,974

1555,82055,75355,68555,60455,53655,47455,41755,352

55,27755,20655,13455,05416

50,50750,01249,51548,98048,44847,922

47,343

46,68145,96445,16044,27743,395

17

3,016

2,999

2,979

2,960

2,940

2,921

2,896

2,866

2,834

2,801

2,764

2,724

18

2,637

2,631

2,626

2,620

2,615

2,610

2,605

2,588

2,565

2,539

2,504

2,466

19

1,958

1,919

1,878

1,839

1,798

1,769

1,738

1,701

1,671

1,637

1,598

1,556

20

37,87137,47437,08336,65636,23335,80735,33534,80934,24333,60432,89032,183

11

21

41

41

40

40

40

39

39

38

37

36

34

33

22

3,225

3,201

3,175

3,146

3,118

3,089

3,060

3,027

2,980

2,928

2,891

2,856

23

859

859

859

859

859

859

859

859

859

859

859

859

24

-

-

-

-

-

-

-

-

-

-

-

-

25

280

275

269

263

258

252

247

242

237

233

228

223

26

620

613

605

597

588

577

565

552

538

524

508

494

27

289,110,033 294,156,897 299,191,599 304,164,825 309,009,448 313,756,570 318,372,370 322,807,862 327,020,940 330,966,728 334,654,704 338,164,850

28-22,814-23,930-24,443-25,521-26,317-26,196-26,170-27,392-29,168-31,194-33,106-35,036

29-9,220-9,189-9,123-9,327-9,103-9,183-9,695-10,168-10,542-10,958-11,196-11,44930-13,594-14,740-15,320-16,194-17,214-17,013-16,475-17,223-18,625-20,236-21,910-23,587

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

34,93735,37035,74936,11336,69436,99337,21037,50637,87638,061

38,27538,706

32

7,088

7,156

7,157

7,185

7,202

7,183

7,135

7,139

7,161

7,240

7,400

7,644

33

19,22819,74920,277

20,75821,446

21,892

22,27922,68523,141

23,36023,51823,804

34

8,621

8,465

8,315

8,170

8,047

7,918

7,795

7,682

7,573

7,461

7,356

7,258

35

1,732,555

1,736,364

1,740,131

1,743,811

1,747,029

1,750,002

1,752,833

1,755,599

1,758,300

1,760,853

1,763,214

1,765,475

36

0.97

-2.58

-2.21

0.43

-0.71

-0.44

-0.89

1.63

-0.65

-0.40

1.13

-1.57

37

166,869,168 169,409,713 171,936,271 174,425,387 176,877,135 179,289,227 181,633,074 183,873,377 185,986,964 187,958,211 189,798,070 191,543,237

ANNEX Data

295

Data Annex: Wealth by Country

Canada

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

8,602,456

8,684,872

8,754,117

8,821,980

8,901,305

8,966,504

9,032,373

2

Produced capital

1,037,863

1,065,359

1,088,187

1,107,455

1,132,513

1,153,643

1,177,693

3

Human capital

3,984,467

4,045,095

4,097,546

4,152,545

4,213,547

4,264,748

4,313,830

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

3,580,126

3,574,418

3,568,384

3,561,979

3,555,246

3,548,113

3,540,849

5Agricultural land, rows 6 + 7

30,81730,81030,83830,86530,89230,92030,947

6

Cropland

23,58523,551

23,611

23,67023,72923,78823,848

7

Pastureland

7,232

7,259

7,227

7,195

7,164

7,131

7,099

8

Forest resources, rows 9 + 10

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

9

Timber

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

10

Non-timber forest resources

97,382

97,382

97,382

97,382

97,382

97,382

97,382

11

Fisheries

313

253

198

145

123

136

152

12

Fossil fuels, rows 13 + 14 + 15

1,661,199

1,656,219

1,650,857

1,645,063

1,638,865

1,632,305

1,625,626

13

Oil

1,393,134

1,393,118

1,393,102

1,393,084

1,393,066

1,393,047

1,393,027

14

Natural gas

162,323

158,319

153,858

149,012

143,815

138,285

132,649

15

Coal

105,742

104,782

103,898

102,967

101,984

100,973

99,95016

Minerals, rows 17 + 18 +…+ 26

21,994

21,332

20,68920,104

19,563

18,94918,321

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

4,149

3,994

3,847

3,707

3,587

3,448

3,317

19

Gold

3,996

3,843

3,703

3,571

3,444

3,312

3,168

20

Iron

5,159

5,078

5,004

4,936

4,854

4,767

4,690

21

Lead

172

157

139

130

121

109

96

5,819

5,687

5,554

5,448

5,320

5,183

22

Nickel5,955

23

Phosphate

119

119

119

119

119

119

119

24

Silver

487

469

453

441

431

414

397

25

Tin

-

-

-

-

-

-

-

26

Zinc

1,956

1,853

1,736

1,647

1,559

1,460

1,351

27

Health capital

28

IWI adjustments excluding TFP, rows 29 + 30

58,78062,25064,89567,86671,30474,68378,232

29

Carbon damages (annual change)

1,986

2,015

1,993

1,992

2,023

2,058

2,099

30

Oil capital gains (annual change)

56,79460,23562,90265,874

69,281

72,624

76,133

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

310,548309,602308,394

307,338

306,846

306,002305,33132

Per capita produced capital

37,46737,97838,33538,581

39,04039,371

39,81133

Per capita human capital

143,839

144,201

144,350

144,665

145,249

145,544

145,82534

Per capita natural capital

129,242

127,422

125,709

124,091

122,557

121,087

119,69535

Per capita health capital

4,968,627

4,974,061

4,979,964

4,986,015

4,991,778

4,997,043

5,002,678

36

TFP (in percentage)

-1.68

-1.97

0.01

0.27

1.61

0.18

-1.21

37

Population

27,700,854

28,051,725

28,386,162

28,704,519

29,009,032

29,302,092

29,582,222

137,635,198 139,530,996 141,362,059 143,121,176 144,806,653 146,423,819 147,990,342

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

296

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

9,140,269

9,241,793

9,355,364

9,475,508

9,663,691

9,900,493

10,149,382

10,374,359

10,605,677

10,744,377

10,909,131

11,062,192

2

1,216,007

1,254,582

1,299,425

1,352,879

1,397,071

1,445,944

1,500,496

1,563,323

1,637,394

1,719,229

1,802,291

1,883,697

3

4,390,833

4,461,389

4,537,908

4,612,564

4,764,641

4,960,580

5,162,654

5,332,617

5,497,739

5,562,490

5,651,995

5,731,080

4

3,533,428

3,525,822

3,518,031

3,510,065

3,501,979

3,493,970

3,486,232

3,478,420

3,470,544

3,462,658

3,454,846

3,447,416

530,89730,84730,79630,74630,69630,70330,71130,71930,72630,73530,74030,740

6

23,81723,78723,757

23,727

23,697

23,70023,70323,70623,71023,71323,71523,715

7

7,079

7,059

7,039

7,019

6,999

7,003

7,008

7,012

7,017

7,022

7,026

7,026

8

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

1,865,803

9

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

1,768,421

10

97,382

97,382

97,382

97,382

97,382

97,382

97,382

97,382

97,382

97,382

97,382

97,382

11

165

172

171

179

193

187

187

194

200

207

213

219

12

1,618,858

1,611,926

1,604,744

1,597,405

1,589,924

1,582,459

1,575,228

1,567,915

1,560,535

1,553,156

1,545,862

1,538,956

13

1,393,007

1,392,986

1,392,965

1,392,944

1,392,922

1,392,899

1,392,874

1,392,850

1,392,826

1,392,800

1,392,773

1,392,747

14

126,962

121,064

114,881

108,496

101,986

95,441

89,072

82,67476,19969,737

63,40557,43815

98,88997,87696,89895,96595,016

94,11993,281

92,391

91,51090,62089,684

88,77016

17,706

17,075

16,516

15,931

15,363

14,81814,303

13,79013,28012,758

12,227

11,697

17

-

-

-

-

-

-

-

-

-

-

-

-

18

3,191

3,056

2,945

2,824

2,702

2,588

2,481

2,373

2,259

2,144

2,030

1,914

19

3,019

2,876

2,739

2,603

2,466

2,336

2,214

2,101

1,996

1,906

1,817

1,735

20

4,607

4,522

4,446

4,367

4,306

4,237

4,162

4,098

4,030

3,955

3,881

3,811

21

86

76

67

59

51

46

42

38

34

29

25

21

22

5,049

4,901

4,776

4,641

4,511

4,385

4,269

4,137

3,996

3,831

3,650

3,467

23

119

119

119

117

115

111

107

103

100

98

96

92

24

380

364

349

333

316

298

280

263

248

234

223

213

25

-

-

-

-

-

-

-

-

-

-

-

-

26

1,255

1,161

1,075

986

896

817

747

677

617

561

505

444

27

149,470,088 150,915,058 152,396,756 153,962,880 155,530,462 157,198,315 158,945,088 160,738,032 162,558,738 164,417,500 166,306,372 168,210,367

28

81,67685,906

89,682

94,38598,833

103,634

107,831

113,065

118,800

125,873

131,604

139,034

29

2,131

2,124

2,109

2,156

2,104

2,123

2,241

2,350

2,437

2,533

2,588

2,646

30

79,544

83,782

87,57392,22996,729101,511

105,590

110,714116,363

123,340

129,016

136,388

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

306,204

306,894

307,906

308,977

312,062

316,494

321,096324,771328,518

329,300

330,807

331,91932

40,737

41,661

42,767

44,115

45,114

46,22347,471

48,94050,71952,69254,65256,52033

147,095

148,150

149,353

150,406

153,861

158,578

163,331

166,938

170,296

170,482

171,390

171,960

34

118,372

117,083

115,786

114,456

113,087

111,694

110,294

108,893

107,502106,125

104,764

103,439

35

5,007,333

5,011,463

5,015,720

5,020,414

5,022,420

5,025,244

5,028,545

5,031,932

5,035,364

5,039,157

5,043,051

5,047,126

36

1.23

0.33

1.05

1.33

-0.52

0.35

-0.67

-0.38

0.55

-0.41

-1.05

-1.82

37

29,850,242

30,113,972

30,383,823

30,667,365

30,967,236

31,281,727

31,608,562

31,943,605

32,283,413

32,627,978

32,977,334

33,327,954

ANNEX Data

297

Data Annex: Wealth by Country

Chile

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

646,491

657,770

673,869

691,511705,494

720,106

735,8812

Produced capital

60,58863,78968,554

74,64280,97889,587

98,866

3

Human capital

360,831369,882

382,991

395,363

403,536

410,714418,377

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

225,071

224,100

222,324

221,506

220,981219,806

218,637

5

Agricultural land, rows 6 + 7

100,947

100,249

98,76998,26898,096

97,33596,712

6

Cropland

19,35918,661

17,181

16,362

16,191

15,23814,603

7

Pastureland

81,58881,58881,58881,906

81,90682,096

82,1098

Forest resources, rows 9 + 10

68,20568,392

68,57968,766

68,953

69,14069,327

9

Timber64,48164,65464,82765,00065,17365,34665,52010

Non-timber forest resources

3,724

3,738

3,752

3,766

3,780

3,794

3,808

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

4,546

4,503

4,468

4,435

4,403

4,373

4,344

13

Oil

1,124

1,124

1,124

1,124

1,123

1,123

1,123

14

Natural gas

975

964

952

938

924

909

895

15

Coal

2,447

2,415

2,392

2,372

2,355

2,341

2,326

16

Minerals, rows 17 + 18 +…+ 26

51,37350,95650,50950,03849,52948,95848,253

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

46,03645,67545,29044,87944,43743,94043,319

19

Gold

2,488

2,461

2,431

2,401

2,366

2,325

2,277

20

Iron

1,565

1,545

1,527

1,511

1,493

1,473

1,452

21

Lead

-

-

-

-

-

-

-

-

-

-

-

-

-

22

Nickel-23

Phosphate

-

-

-

-

-

-

-

24

Silver

1,284

1,275

1,261

1,247

1,233

1,219

1,204

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

27,245,613

27,833,091

28,440,705

29,056,234

29,661,663

30,243,946

30,796,048

28

IWI adjustments excluding TFP, rows 29 + 30

-2,235-2,372-2,458-2,656-2,815-3,048-3,30829

Carbon damages (annual change)-1,291-1,310-1,296-1,295-1,316-1,338-1,36530

Oil capital gains (annual change)-944-1,062-1,162-1,361-1,500-1,710-1,943

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

49,022

48,98049,26549,644

49,771

49,97550,29732

Per capita produced capital

4,594

4,750

5,012

5,359

5,713

6,217

6,757

33

Per capita human capital

27,361

27,54328,00028,38328,46828,50328,59634

Per capita natural capital

17,067

16,687

16,254

15,902

15,59015,254

14,94435

Per capita health capital

2,065,968

2,072,562

2,079,246

2,085,966

2,092,550

2,098,902

2,104,882

36

TFP (in percentage)

-0.39

3.52

7.24

2.25

0.94

5.50

1.42

37

Population

13,187,821

13,429,315

13,678,373

13,929,390

14,174,890

14,409,416

14,630,769

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

298

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

757,556

779,700

794,206

807,011827,664

847,814869,697

901,137

924,828

953,410

983,475

1,018,637

2

109,137

119,010

124,999

132,510

138,822

145,617

152,876

161,374

173,859

186,027

200,076

218,3893

430,446443,394453,707459,514474,533

486,143502,619

523,379

535,952

553,969

571,489

589,3844

217,973

217,296

215,500

214,986

214,309

216,054214,202

216,384

215,017

213,414

211,910

210,864

596,64996,63095,62095,93896,192

98,827

97,938101,176

100,858

100,319

99,912

99,9196

14,584

14,565

13,524

13,397

13,651

13,111

12,222

12,286

11,968

11,42910,94010,933

7

82,06482,06482,09682,54182,541

85,71585,71588,89088,89088,89088,97388,985

8

69,51469,701

69,88970,07670,18570,29370,40270,511

70,62070,732

70,84370,9549

65,69365,866

66,03966,212

66,311

66,41066,50866,607

66,70666,80866,91067,012

10

3,822

3,836

3,850

3,863

3,874

3,884

3,894

3,904

3,914

3,924

3,933

3,942

12

4,313

4,284

4,268

4,254

4,236

4,222

4,199

4,187

4,164

4,139

4,122

4,098

13

1,123

1,123

1,123

1,123

1,122

1,122

1,122

1,122

1,122

1,122

1,122

1,122

14

879

864

855

846

837

828

814

806

790

775

762

748

15

2,311

2,298

2,291

2,285

2,277

2,271

2,263

2,259

2,251

2,242

2,238

2,229

16

47,496

46,68145,72344,71943,69642,712

41,66340,51039,374

38,22537,03235,893

17

-

-

-

-

-

-

-

-

-

-

-

-

18

42,643

41,90841,032

40,11539,17038,25737,27936,20035,13934,07032,962

31,900

19

2,232

2,192

2,148

2,099

2,061

2,026

1,991

1,955

1,918

1,880

1,843

1,807

20

1,432

1,410

1,391

1,370

1,350

1,333

1,314

1,295

1,277

1,257

1,236

1,215

21

-

-

-

-

-

-

-

-

-

-

-

-

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

1,189

1,171

1,152

1,134

1,116

1,097

1,079

1,060

1,040

1,018

991

972

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

27

31,322,020

31,826,576

32,319,014

32,806,209

33,191,814

33,570,962

33,943,159

34,307,277

34,663,583

35,020,770

35,371,110

35,715,824

28-3,478-3,667-3,765-3,796-3,820-3,949-4,121-4,330-4,657-5,015-5,293-5,75229-1,386-1,381-1,371-1,402-1,368-1,380-1,457-1,528-1,584-1,647-1,683-1,72130-2,092-2,286-2,394-2,394-2,452-2,569-2,664-2,802-3,073-3,368-3,611-4,032

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

51,04851,84552,142

52,33653,04153,71454,49355,85956,732

57,892

59,12760,649

32

7,354

7,913

8,207

8,594

8,896

9,226

9,579

10,003

10,665

11,296

12,02913,00333

29,00629,48329,78729,80030,41130,80031,49332,44332,877

33,63834,35835,092

34

14,68814,44914,148

13,942

13,734

13,68813,421

13,413

13,19012,95912,74012,55535

2,110,643

2,116,247

2,121,846

2,127,535

2,127,108

2,126,899

2,126,792

2,126,632

2,126,375

2,126,508

2,126,530

2,126,500

36

0.87

-2.20

-12.18

-0.07

-1.67

-1.96

-0.26

2.40

0.82

-3.76

0.61

-0.96

37

14,840,038

15,039,162

15,231,557

15,419,820

15,604,200

15,783,991

15,959,793

16,132,209

16,301,726

16,468,677

16,633,254

16,795,593

11

ANNEX Data

299

Data Annex: Wealth by Country

China

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

11,903,258

12,117,426

12,358,580

12,633,483

12,938,297

13,263,921

13,614,788

1

Inclusive Wealth Index, rows 2 + 3 + 4

2

Produced capital

962,551

1,019,570

1,103,917

1,233,621

1,385,242

1,552,091

1,734,193

3

Human capital

5,647,423

5,807,404

5,967,512

6,126,514

6,285,442

6,446,801

6,627,185

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

5,293,284

5,290,452

5,287,152

5,273,349

5,267,612

5,265,029

5,253,409

5Agricultural land, rows 6 + 7

2,463,917

2,466,208

2,468,489

2,461,321

2,463,347

2,470,029

2,467,822

6

Cropland609,245

611,535

613,816

606,648

608,674

615,356

613,149

7

Pastureland

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

8

Forest resources, rows 9 + 10

778,586

787,996

797,406

806,816

816,225825,635

835,045

9

Timber740,244

749,169

758,094

767,019775,945784,870

793,795

10

Non-timber forest resources

38,34238,82739,31139,79640,281

40,76541,25011

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

1,953,591

1,939,754

1,925,533

1,910,368

1,894,090

1,876,385

1,858,563

13

Oil

119,345

119,324

119,302

119,281

119,259

119,236

119,21214

Natural gas

28,12627,97927,831

27,67527,511

27,34327,14415

Coal

1,806,120

1,792,451

1,778,400

1,763,412

1,747,320

1,729,806

1,712,207

16

Minerals, rows 17 + 18 +…+ 26

97,19096,494

95,723

94,844

93,95092,98091,98017

Bauxite

1,487

1,483

1,479

1,473

1,467

1,459

1,449

18

Appendix

7,015

6,957

6,892

6,826

6,758

6,672

6,587

19

Gold

4,025

3,920

3,797

3,657

3,517

3,395

3,268

20

Iron

60,88360,48460,03659,50558,96258,397

57,833

21

Lead

1,319

1,300

1,282

1,264

1,246

1,218

1,184

22

Nickel

1,459

1,437

1,414

1,392

1,369

1,339

1,307

23

Phosphate

15,237

15,237

15,237

15,237

15,237

15,237

15,23724

Silver

735

733

731

728

725

713

697

25

Tin

1,493

1,474

1,453

1,430

1,407

1,379

1,346

26

Zinc

3,537

3,469

3,401

3,332

3,262

3,171

3,071

27

Health capital

28

IWI adjustments excluding TFP, rows 29 + 30

-13,116-15,094-16,998-20,222-22,423-24,811-27,575

29

Carbon damages (annual change)-1,930-1,959-1,938-1,936-1,967-2,001-2,04130

Oil capital gains (annual change)-11,186-13,136-15,060-18,286-20,456-22,810-25,535

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

10,394

10,43910,516

10,628

10,768

10,926

11,10432

Per capita produced capital

841

878

939

1,038

1,153

1,279

1,414

33

Per capita human capital

4,931

5,003

5,078

5,154

5,231

5,310

5,405

34

Per capita natural capital

4,622

4,558

4,499

4,436

4,384

4,337

4,285

35

Per capita health capital

1,066,327

1,068,383

1,069,996

1,071,390

1,072,819

1,074,401

1,075,223

36

TFP (in percentage)

-0.73

2.14

4.33

3.07

2.97

7.52

-4.83

37

Population

1,221,152,645 1,240,178,816 1,257,491,628 1,273,548,469 1,289,016,309 1,304,308,252 1,318,367,691

1,145,195,229 1,160,799,514 1,175,230,312 1,188,687,527 1,201,522,570 1,213,986,610 1,226,134,423

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

300

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

13,970,089

14,358,243

14,758,174

15,233,596

15,615,719

16,094,833

16,632,529

17,244,067

17,845,470

18,525,829

19,206,254

19,960,009

2

1,926,842

2,140,688

2,363,037

2,642,738

2,866,569

3,168,772

3,532,122

3,940,841

4,399,104

4,919,505

5,514,849

6,159,399

3

6,797,566

6,967,572

7,149,236

7,346,155

7,510,958

7,693,865

7,882,376

8,068,536

8,241,502

8,416,403

8,577,371

8,727,850

45,245,681

5,249,984

5,245,902

5,244,704

5,238,192

5,232,196

5,218,031

5,234,690

5,204,864

5,189,921

5,114,035

5,072,761

52,463,713

2,470,515

2,467,947

2,467,650

2,463,305

2,459,123

2,450,485

2,477,916

2,461,512

2,461,493

2,422,971

2,422,864

6

609,041

615,843

613,274

612,977

608,633

604,450

595,812623,244606,839

606,821568,298

568,1927

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

1,854,673

8

849,909864,773879,637

894,501

909,663926,898

944,133

961,368

978,602995,729992,779

989,830

9808,175

822,554

836,933

851,313865,692

882,144898,596915,048931,500

947,952

944,328

940,70510

41,73442,21942,704

43,18843,97144,75445,537

46,32047,10347,77748,451

49,12512

1,841,176

1,824,750

1,809,295

1,794,460

1,778,062

1,759,973

1,738,295

1,711,565

1,682,444

1,652,403

1,620,284

1,584,641

13

119,188

119,163

119,139

119,114

119,088

119,062

119,035

119,008

118,980

118,951

118,922

118,893

14

26,921

26,692

26,444

26,17525,87725,55525,217

24,81624,32423,74723,06522,31615

1,695,067

1,678,895

1,663,713

1,649,171

1,633,097

1,615,356

1,594,042

1,567,741

1,539,140

1,509,704

1,478,297

1,443,433

16

90,88389,94589,02388,09387,161

86,202

85,11983,84182,30680,29678,00175,426

17

1,436

1,423

1,409

1,395

1,379

1,361

1,340

1,313

1,277

1,234

1,185

1,129

18

6,492

6,397

6,297

6,183

6,069

5,959

5,842

5,698

5,551

5,383

5,203

5,022

19

3,114

2,959

2,807

2,650

2,488

2,320

2,140

1,952

1,755

1,541

1,300

1,050

20

57,226

56,66756,131

55,62755,12954,60654,01553,291

52,341

50,981

49,38147,517

21

1,146

1,115

1,086

1,051

1,015

980

930

876

816

745

669

587

22

1,274

1,239

1,204

1,168

1,131

1,093

1,049

995

943

885

837

785

23

15,237

15,237

15,237

15,237

15,237

15,237

15,237

15,237

15,237

15,237

15,237

15,237

24

680

663

644

623

597

557

525

492

459

424

387

350

25

1,315

1,282

1,245

1,199

1,155

1,126

1,079

1,024

966

907

840

789

26

2,962

2,962

2,962

2,962

2,962

2,961

2,961

2,961

2,961

2,961

2,960

2,960

11

27 1,332,617,688 1,346,598,128 1,359,666,865 1,371,523,323 1,382,958,035 1,393,156,143 1,402,473,188 1,411,505,672 1,420,612,032 1,429,087,741 1,437,692,473 1,446,348,252
28-30,953-33,921-37,125-42,923-45,754-50,254-56,480-67,159-72,187-81,938-88,792-99,404

29-2,072-2,065-2,050-2,096-2,046-2,064-2,179-2,285-2,369-2,462-2,516-2,57330-28,881-31,856-35,075-40,827-43,708-48,190-54,302-64,874-69,818-79,476-86,276-96,831

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

11,286

11,496

11,71812,003

12,22012,516

12,86013,25913,64814,093

14,53415,027

32

1,557

1,714

1,876

2,082

2,243

2,464

2,731

3,030

3,364

3,742

4,173

4,637

33

5,491

5,578

5,676

5,788

5,878

5,983

6,094

6,204

6,303

6,402

6,491

6,571

34

4,238

4,203

4,165

4,133

4,099

4,069

4,034

4,025

3,980

3,948

3,870

3,819

35

1,076,558

1,078,124

1,079,549

1,080,691

1,082,208

1,083,381

1,084,333

1,085,313

1,086,432

1,087,105

1,087,940

1,088,892

36

-1.36

-5.87

0.53

3.31

4.73

6.14

7.85

2.61

2.62

4.65

6.07

2.35

37

1,237,849,861 1,249,020,152 1,259,476,966 1,269,116,737 1,277,903,627 1,285,933,789 1,293,396,654 1,300,552,134 1,307,593,489 1,314,581,402 1,321,481,935 1,328,275,524

ANNEX Data

301

Data Annex: Wealth by Country

Colombia

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

903,171914,042928,157

946,140

967,300

986,640

1,008,714

2

Produced capital

168,089

171,135

175,807

184,987

196,129

206,709216,208

3

Human capital

283,546

293,004

302,567

312,409323,278

334,553

345,796

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

451,536449,903449,783

448,743447,893445,378446,7105Agricultural land, rows 6 + 7

232,755

231,727

232,238

231,825

231,629

229,812

231,913

6

Cropland

25,81424,78725,29824,885

24,68922,871

21,147

7

Pastureland

206,941

206,941

206,941

206,941

206,941

206,941

210,766

8

Forest resources, rows 9 + 10

89,45489,31089,16589,021

88,876

88,731

88,587

9

Timber

74,20074,08073,96073,84073,72073,60073,48010

Non-timber forest resources

15,255

15,23015,205

15,181

15,15615,131

15,107

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

127,176

126,732

126,264

125,800

125,310

124,776

124,173

13

Oil

11,666

11,663

11,66011,656

11,653

11,648

11,64314

Natural gas

7,984

7,830

7,681

7,525

7,364

7,205

7,039

15

Coal

107,526

107,239

106,924

106,619

106,293

105,923

105,491

16

Minerals, rows 17 + 18 +…+ 26

2,150

2,134

2,116

2,097

2,079

2,059

2,037

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

-

-

-

-

-

-

-

19

Gold

-

-

-

-

-

-

-

20

Iron

-

-

-

-

-

-

-

21

Lead

-

-

-

-

-

-

-

2,150

2,134

2,116

2,097

2,079

2,059

2,037

22

Nickel23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

46,460,586

47,397,148

48,336,059

49,277,776

50,223,541

51,173,868

52,125,802

28

IWI adjustments excluding TFP, rows 29 + 30

-2,266-2,377-2,607-2,753-2,839-2,953-3,26029

Carbon damages (annual change)-1,379-1,399-1,384-1,383-1,405-1,429-1,45730

Oil capital gains (annual change)

-887

-978

-1,223-1,370-1,434-1,524-1,803

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

27,20127,003

26,90526,92027,021

27,06627,18032

Per capita produced capital

5,062

5,056

5,096

5,263

5,479

5,670

5,826

33

Per capita human capital

8,540

8,656

8,771

8,889

9,031

9,178

9,317

34

Per capita natural capital

13,59913,291

13,03812,76812,512

12,21812,03735

Per capita health capital

1,399,275

1,400,212

1,401,154

1,402,079

1,402,972

1,403,818

1,404,530

36

TFP (in percentage)

-2.51

-3.11

2.24

-0.62

-2.14

3.57

-3.21

37

Population

33,203,321

33,849,971

34,497,319

35,146,220

35,797,965

36,453,337

37,112,621

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

302

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

1,028,526

1,048,333

1,058,760

1,065,335

1,057,391

1,068,058

1,083,506

1,100,426

1,118,9781,142,433

1,172,824

1,205,2002

224,561

230,849

229,093

228,540

226,654

227,993

231,215

236,346

243,934

255,351

270,082

286,9953

357,270369,287

381,683

393,953

405,032

416,085

427,195

438,464

449,914465,389481,217497,3664

446,695

448,197447,985

442,842425,706

423,979

425,096425,616

425,130

421,693421,525

420,8395

232,750

235,130

235,775

231,598

215,521214,809

217,101

218,856

219,713217,736

219,089

220,008

6

21,97822,59822,53023,465

21,34819,28819,355

19,144

18,653

17,395

18,431

17,868

7

210,771

212,532

213,244

208,133

194,173

195,521

197,746

199,713201,060

200,341

200,658

202,1398

88,442

88,29888,15388,00987,86487,72087,57587,43087,28687,141

86,99786,852

973,36073,24073,12073,00072,881

72,761

72,641

72,521

72,401

72,281

72,161

72,041

10

15,082

15,057

15,03315,00814,984

14,95914,934

14,91014,885

14,86014,836

14,811

12

123,490122,780

122,121

121,368

120,526

119,737

118,801

117,808

116,722

115,522

114,245

112,869

13

11,638

11,632

11,626

11,62011,615

11,611

11,607

11,603

11,598

11,594

11,590

11,585

14

6,830

6,611

6,429

6,230

6,017

5,801

5,588

5,372

5,138

4,886

4,618

4,303

15

105,022

104,537

104,066

103,518

102,893

102,325

101,606

100,834

99,98599,042

98,037

96,980

16

2,013

1,989

1,936

1,867

1,794

1,713

1,619

1,521

1,409

1,294

1,194

1,110

17

-

-

-

-

-

-

-

-

-

-

-

-

18

-

-

-

-

-

-

-

-

-

-

-

-

19

-

-

-

-

-

-

-

-

-

-

-

-

20

-

-

-

-

-

-

-

-

-

-

-

-

11

21

-

-

-

-

-

-

-

-

-

-

-

-

22

2,013

1,989

1,936

1,867

1,794

1,713

1,619

1,521

1,409

1,294

1,194

1,110

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

27

53,078,951

54,032,565

54,985,580

55,936,715

57,032,036

58,131,789

59,236,536

60,347,508

61,466,017

62,591,840

63,723,927

64,859,114

28-3,387-3,478-3,379-3,474-3,439-3,411-3,579-3,669-3,809-3,983-4,180-4,26029-1,480-1,475-1,464-1,497-1,461-1,474-1,556-1,632-1,692-1,759-1,797-1,83730-1,908-2,003-1,915-1,977-1,978-1,938-2,023-2,037-2,117-2,225-2,383-2,423

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

27,22827,27327,076

26,791

26,15826,001

25,96325,96225,99826,14526,443

26,779

32

5,945

6,006

5,859

5,747

5,607

5,550

5,540

5,576

5,668

5,844

6,089

6,377

33

9,458

9,607

9,761

9,907

10,02010,12910,237

10,345

10,453

10,65010,85011,051

34

11,825

11,66011,457

11,137

10,531

10,321

10,186

10,042

9,877

9,650

9,504

9,351

35

1,405,132

1,405,667

1,406,185

1,406,712

1,410,895

1,415,152

1,419,454

1,423,770

1,428,095

1,432,421

1,436,766

1,441,128

36

1.52

-2.49

-7.30

0.28

-1.58

1.41

-0.76

1.99

-0.24

4.33

1.43

-2.95

37

37,775,054

38,439,099

39,102,653

39,764,166

40,422,597

41,078,136

41,731,914

42,385,712

43,040,558

43,696,540

44,352,327

45,005,782

ANNEX Data

303

Data Annex: Wealth by Country

Ecuador

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

245,770

251,957

258,419

264,907

271,747

278,107283,3722

Produced capital

40,29340,96541,831

42,67743,71344,59545,247

3

Human capital

133,539

139,272

145,128

151,052

156,958

162,778

167,871

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

71,93871,72071,46071,17871,07670,73470,254

5Agricultural land, rows 6 + 7

10,75010,843

10,896

10,926

11,137

11,108

10,943

6

Cropland

4,007

4,103

4,138

4,075

4,160

4,112

4,098

7

Pastureland

6,742

6,739

6,759

6,852

6,978

6,997

6,845

8

Forest resources, rows 9 + 10

21,39621,09020,784

20,47820,172

19,866

19,5609Timber

18,025

17,767

17,50917,252

16,994

16,736

16,47810

Non-timber forest resources

3,371

3,323

3,275

3,227

3,178

3,130

3,082

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

39,79239,78639,78039,77339,76639,75939,75113

Oil

38,991

38,98938,98638,98338,98038,97638,97314

Natural gas

438

434

431

427

423

419

414

15

Coal

364

364

364

364

364

364

364

16

Minerals, rows 17 + 18 +…+ 26

-

-

-

-

-

-

-

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

-

-

-

-

-

-

-

19

Gold

-

-

-

-

-

-

-

20

Iron

-

-

-

-

-

-

-

21

Lead

-

-

-

-

-

-

-

22

Nickel

-

-

-

-

-

-

-

23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

9,817,970

10,065,068

10,311,540

10,554,806

10,791,625

11,020,030

11,236,968

28

IWI adjustments excluding TFP, rows 29 + 30

993

1,006

950

1,074

1,085

1,133

1,169

29

Carbon damages (annual change)

-230

-233

-231

-231

-234

-238

-243

30

Oil capital gains (annual change)

1,223

1,239

1,181

1,304

1,319

1,371

1,412

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

23,95324,011

24,09424,18524,32024,42924,46232

Per capita produced capital

3,927

3,904

3,900

3,896

3,912

3,917

3,906

33

Per capita human capital

13,015

13,272

13,531

13,791

14,047

14,29814,49234

Per capita natural capital

7,011

6,835

6,663

6,498

6,361

6,213

6,065

35

Per capita health capital

956,862

959,172

961,424

963,629

965,810

967,985

970,036

36

TFP (in percentage)

-0.02

2.42

-1.56

-2.58

1.27

-2.01

1.93

37

Population

10,260,587

10,493,498

10,725,281

10,953,182

11,173,647

11,384,506

11,584,074

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

304

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

287,461

292,988296,813

301,890

307,366

311,820

319,020

327,184

335,370

344,192

351,206

360,0322

45,95546,766

46,40647,18947,15048,64450,02551,54653,50655,54057,57460,4203

171,531

176,539

180,972

185,592

191,807

195,484

201,947

208,528

215,111222,296

227,640

233,896

4

69,97569,68369,436

69,10968,40867,691

67,047

67,11066,753

66,35565,99165,716

5

10,977

10,997

11,063

11,051

10,666

10,262

9,933

10,312

10,275

10,19910,155

10,200

6

4,116

4,116

4,083

4,081

3,836

3,562

3,407

3,457

3,439

3,351

3,309

3,425

7

6,861

6,882

6,980

6,970

6,830

6,700

6,526

6,856

6,837

6,848

6,846

6,775

8

19,254

18,94818,642

18,33618,03017,724

17,418

17,112

16,806

16,50016,194

15,888916,221

15,96315,705

15,447

15,18914,932

14,674

14,41614,15813,901

13,643

13,385

10

3,034

2,986

2,937

2,889

2,841

2,793

2,745

2,696

2,648

2,600

2,552

2,503

12

39,74439,73739,73039,721

39,71239,70539,696

39,68539,671

39,656

39,642

39,628

13

38,96938,96638,963

38,95938,956

38,95338,94938,94438,94038,93538,931

38,926

14

411

407

403

398

392

389

383

377

367

357

347

338

15

364

364

364

364

364

364

364

364

364

364

364

364

16

-

-

-

-

-

-

-

-

-

-

-

-

17

-

-

-

-

-

-

-

-

-

-

-

-

18

-

-

-

-

-

-

-

-

-

-

-

-

19

-

-

-

-

-

-

-

-

-

-

-

-

20

-

-

-

-

-

-

-

-

-

-

-

-

21

-

-

-

-

-

-

-

-

-

-

-

-

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

27

11,445,958

11,651,848

11,861,388

12,079,502

12,301,842

12,532,058

12,767,501

13,003,969

13,238,154

13,468,576

13,696,772

13,922,913

28

1,211

1,273

1,474

1,548

1,554

1,635

1,697

1,774

1,809

1,747

1,759

1,282

29

-247

-246

-244

-250

-244

-246

-260

-272

-282

-293

-300

-307

30

1,458

1,520

1,718

1,798

1,798

1,881

1,957

2,047

2,091

2,040

2,059

1,588

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

24,41524,49824,43324,45424,487

24,42324,563

24,77024,97825,23525,35825,613

32

3,903

3,910

3,820

3,822

3,756

3,810

3,852

3,902

3,985

4,072

4,157

4,298

33

14,56914,761

14,897

15,034

15,281

15,311

15,54915,787

16,022

16,29816,436

16,639

34

5,943

5,827

5,716

5,598

5,450

5,302

5,162

5,081

4,972

4,865

4,765

4,675

35

972,138

974,269

976,392

978,492

980,067

981,566

983,023

984,488985,979

987,453

988,957

990,480

36

0.29

0.12

-5.30

2.33

0.46

-0.79

0.38

1.77

2.49

-0.15

-0.90

3.54

37

11,774,005

11,959,586

12,148,188

12,345,023

12,552,036

12,767,415

12,987,992

13,208,869

13,426,402

13,639,708

13,849,721

14,056,740

11

ANNEX Data

305

Data Annex: Wealth by Country

France

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

9,153,530

9,380,150

9,593,125

9,786,530

9,982,546

10,183,155

10,405,136

2

Produced capital

2,120,057

2,180,924

2,233,377

2,269,909

2,307,108

2,345,287

2,382,088

3

Human capital

6,882,044

7,047,584

7,207,779

7,364,404

7,522,874

7,684,895

7,869,655

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

151,429

151,641

151,969

152,217

152,564

152,973

153,394

5

Agricultural land, rows 6 + 7

68,416

68,09367,881

67,594

67,406

67,272

67,135

6

Cropland

42,94743,00543,04843,504

43,614

43,62543,554

7

Pastureland

25,46825,08824,83324,09023,792

23,647

23,5828

Forest resources, rows 9 + 10

80,806

81,481

82,156

82,832

83,507

84,182

84,858

9

Timber

76,241

76,89177,541

78,19078,84079,49080,13910

Non-timber forest resources

4,565

4,590

4,616

4,641

4,667

4,693

4,718

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

2,207

2,067

1,932

1,791

1,651

1,519

1,401

13

Oil

473

473

472

472

471

471

471

14

Natural gas

1,445

1,345

1,248

1,142

1,033

930

840

15

Coal

289

249

211

177

146

118

90

16

Minerals, rows 17 + 18 +…+ 26

-

-

-

-

-

-

-

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

-

-

-

-

-

-

-

19

Gold

-

-

-

-

-

-

-

20

Iron

-

-

-

-

-

-

-

21

Lead

-

-

-

-

-

-

-

-

-

-

-

-

-

22

Nickel-23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

28

IWI adjustments excluding TFP, rows 29 + 30

-40,671-42,507-42,856-43,095-43,890-45,384-46,668

29

Carbon damages (annual change)-27,056-27,454-27,160-27,137-27,571-28,048-28,60230

Oil capital gains (annual change)-13,616-15,052-15,696-15,957-16,319-17,336-18,067

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

161,414

164,691

167,742

170,461

173,221

176,044

179,22132

Per capita produced capital

37,38538,29139,05239,53740,03440,54541,03033

Per capita human capital

121,359

123,737

126,033

128,272

130,540

132,854

135,549

34

Per capita natural capital

2,670

2,662

2,657

2,651

2,647

2,645

2,642

35

Per capita health capital

4,750,249

4,754,071

4,758,507

4,763,473

4,768,749

4,774,321

4,778,834

36

TFP (in percentage)

0.34

-0.27

-0.05

-0.86

0.92

0.90

-0.87

37

Population

56,708,260

56,956,057

57,189,616

57,412,239

57,628,904

57,844,501

58,057,570

269,378,375 270,773,126 272,137,184 273,481,644 274,817,762 276,168,209 277,447,481

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

306

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

10,572,275

10,769,237

10,995,980

11,243,897

11,380,112

11,575,374

11,836,216

12,023,558

12,198,377

12,425,226

12,690,734

12,955,131

2

2,417,481

2,465,405

2,528,515

2,608,251

2,677,189

2,741,261

2,806,191

2,875,263

2,951,230

3,032,756

3,126,767

3,215,068

3

8,000,912

8,149,438

8,312,538

8,480,548

8,546,143

8,675,649

8,869,402

8,985,972

9,083,079

9,228,001

9,399,180

9,574,982

4

153,881

154,394

154,927

155,099

156,781

158,464

160,623

162,323

164,068

164,468

164,788

165,0815

67,05066,977

66,916

66,482

66,314

66,144

66,442

66,26966,13366,02865,83765,616

6

43,60343,641

43,67543,824

43,831

43,827

43,82943,82943,961

43,85843,68343,435

7

23,44823,33623,242

22,65822,48322,317

22,61322,44022,172

22,17022,154

22,181

8

85,53386,20986,88487,55989,47691,39393,31095,226

97,143

97,687

98,23098,774

980,78981,43982,08982,73884,632

86,52788,42190,315

92,20992,737

93,266

93,795

10

4,744

4,770

4,795

4,821

4,844

4,866

4,889

4,912

4,934

4,949

4,964

4,979

12

1,298

1,209

1,127

1,057

990

927

872

827

792

753

720

691

13

470

470

470

469

469

468

468

468

467

467

467

466

14

760

690

627

569

510

453

403

360

324

286

253

225

15

67

49

31

20

12

6

1

-

-

-

-

-

16

-

-

-

-

-

-

-

-

-

-

-

-

17

-

-

-

-

-

-

-

-

-

-

-

-

18

-

-

-

-

-

-

-

-

-

-

-

-

19

-

-

-

-

-

-

-

-

-

-

-

-

20

-

-

-

-

-

-

-

-

-

-

-

-

21

-

-

-

-

-

-

-

-

-

-

-

-

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

11

27

278,757,355 280,152,845 281,710,499 283,485,355 285,664,955 288,042,974 290,548,401 293,092,341 295,612,510 298,007,774 300,324,825 302,615,437

28-47,743-49,139-49,323-50,406-51,140-51,524-53,999-55,906-57,593-59,809-61,452-63,205

29-29,039-28,943-28,733-29,376-28,670-28,922-30,534-32,026-33,203-34,513-35,261-36,05930-18,704-20,197-20,590-21,030-22,469-22,601-23,465-23,880-24,389-25,295-26,192-27,146

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

181,435

184,102

187,161

190,420

191,614

193,651

196,668

198,419

199,985

202,438

205,536

208,623

32

41,48742,14643,03744,17245,07845,86046,62747,44948,38449,41150,64051,774

33

137,307

139,316

141,486

143,622

143,897

145,140

147,372

148,291

148,911150,347

152,227

154,190

34

2,641

2,639

2,637

2,627

2,640

2,651

2,669

2,679

2,690

2,680

2,669

2,658

35

4,783,857

4,789,254

4,794,944

4,800,947

4,809,926

4,818,824

4,827,678

4,836,771

4,846,384

4,855,281

4,863,986

4,873,159

36

0.63

1.28

0.36

1.74

-0.46

0.74

-0.10

-0.54

-0.14

1.19

-0.51

-2.60

37

58,270,419

58,496,138

58,751,572

59,047,795

59,390,720

59,774,531

60,183,884

60,596,691

60,996,506

61,378,065

61,744,596

62,098,413

ANNEX Data

307

Data Annex: Wealth by Country

Germany

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

13,494,774

14,083,223

14,372,673

14,673,642

14,977,692

15,315,106

15,615,130

2

Produced capital

3,429,436

3,537,002

3,653,438

3,746,853

3,848,136

3,941,350

4,026,148

3

Human capital

8,745,701

9,236,828

9,417,687

9,631,571

9,840,253

10,090,276

10,311,159

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

1,319,637

1,309,393

1,301,548

1,295,218

1,289,303

1,283,481

1,277,823

5Agricultural land, rows 6 + 7

35,26633,51433,15233,56533,85033,91933,907

6

Cropland

24,27923,092

22,89823,29523,542

23,58923,594

7

Pastureland

10,988

10,422

10,254

10,27010,30910,330

10,3138

Forest resources, rows 9 + 10

74,02475,45576,88678,31779,74881,17982,6109Timber

70,651

72,07173,492

74,91376,33377,754

79,17410

Non-timber forest resources

3,373

3,383

3,394

3,404

3,415

3,425

3,436

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

1,210,347

1,200,424

1,191,510

1,183,336

1,175,704

1,168,383

1,161,306

13

Oil

1,373

1,373

1,372

1,372

1,371

1,371

1,370

14

Natural gas

19,496

18,90818,311

17,71517,096

16,441

15,73315

Coal

1,189,478

1,180,144

1,171,826

1,164,250

1,157,237

1,150,571

1,144,203

16

Minerals, rows 17 + 18 +…+ 26

-

-

-

-

-

-

-

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

-

-

-

-

-

-

-

19

Gold

-

-

-

-

-

-

-

20

Iron

-

-

-

-

-

-

-

21

Lead

-

-

-

-

-

-

-

-

-

-

-

-

-

22

Nickel-23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

28

IWI adjustments excluding TFP, rows 29 + 30

-247,407-61,240-61,947-63,567-64,703-66,180-68,035

29

Carbon damages (annual change)-38,778-39,349-38,928-38,894-39,516-40,200-40,99330

Oil capital gains (annual change)-208,630-21,892-23,019-24,672-25,187-25,980-27,041

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

170,608

176,810179,025

181,321

183,786

186,930

189,96432

Per capita produced capital

43,35744,40645,50746,30047,21948,10748,98033

Per capita human capital

110,568

115,965

117,306

119,017

120,746

123,158

125,439

34

Per capita natural capital

16,684

16,43916,212

16,005

15,821

15,666

15,54535

Per capita health capital

4,816,778

4,831,696

4,846,510

4,861,690

4,877,841

4,895,001

4,903,615

36

TFP (in percentage)

2.96

2.12

1.05

-0.34

1.97

1.76

1.36

37

Population

79,098,094

79,651,903

80,282,985

80,926,118

81,495,194

81,929,441

82,200,333

380,997,967 384,853,746 389,092,265 393,437,706 397,520,567 401,044,675 403,078,784

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

308

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

15,887,971

16,164,650

16,394,381

16,643,601

17,134,904

17,597,384

18,059,692

18,618,523

19,187,437

19,300,630

19,415,161

19,473,621

2

4,108,484

4,199,334

4,300,666

4,391,920

4,490,123

4,544,070

4,589,704

4,631,312

4,672,874

4,741,768

4,824,522

4,908,363

3

10,507,000

10,697,589

10,831,148

10,993,968

11,392,897

11,807,459

12,229,877

12,752,922

13,285,925

13,336,130

13,373,728

13,353,882

4

1,272,486

1,267,727

1,262,566

1,257,714

1,251,884

1,245,856

1,240,112

1,234,290

1,228,639

1,222,732

1,216,911

1,211,377

5

33,88833,97833,54533,38133,31533,18433,25033,27333,30933,14233,15033,096

6

23,587

23,67823,54423,50823,51023,46323,534

23,66523,66923,594

23,61623,7297

10,301

10,29910,002

9,873

9,804

9,720

9,716

9,609

9,640

9,548

9,534

9,366

8

84,04185,472

86,90388,33488,721

89,10789,49489,88090,26790,43790,60890,779980,59582,01583,43684,85685,24385,62986,016

86,402

86,78986,96087,13087,301

10

3,446

3,457

3,467

3,478

3,478

3,478

3,478

3,478

3,478

3,478

3,478

3,478

12

1,154,558

1,148,277

1,142,118

1,135,999

1,129,849

1,123,565

1,117,368

1,111,136

1,105,063

1,099,152

1,093,153

1,087,502

13

1,370

1,369

1,369

1,368

1,368

1,367

1,367

1,366

1,366

1,366

1,365

1,365

14

15,035

14,355

13,63012,945

12,253

11,56010,86910,230

9,613

9,003

8,424

7,924

15

1,138,153

1,132,553

1,127,118

1,121,686

1,116,227

1,110,638

1,105,132

1,099,540

1,094,084

1,088,784

1,083,364

1,078,214

16

-

-

-

-

-

-

-

-

-

-

-

-

17

-

-

-

-

-

-

-

-

-

-

-

-

18

-

-

-

-

-

-

-

-

-

-

-

-

19

-

-

-

-

-

-

-

-

-

-

-

-

20

-

-

-

-

-

-

-

-

-

-

-

-

21

-

-

-

-

-

-

-

-

-

-

-

-

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

11

27

404,625,745 405,791,197 406,783,838 407,810,922 408,497,310 409,124,395 409,709,013 410,285,656 410,858,766 411,078,165 411,293,753 411,500,848

28-69,282-70,327-69,878-71,143-71,740-72,254-74,908-77,314-79,615-83,583-82,496-87,106

29-41,621-41,482-41,182-42,104-41,092-41,453-43,763-45,901-47,589-49,466-50,538-51,68130-27,661-28,845-28,696-29,039-30,648-30,801-31,145-31,413-32,026-34,116-31,959-35,425

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

192,988

196,291

199,102202,110

207,988

213,478

218,948

225,612232,460

233,845

235,289

236,11532

49,90550,99352,23053,33354,50255,12555,64356,121

56,61357,451

58,46759,513

33

127,627

129,903

131,539

133,505

138,290

143,239

148,269

154,535

160,962

161,579

162,074

161,91434

15,457

15,394

15,333

15,273

15,19615,11415,035

14,957

14,885

14,815

14,748

14,68835

4,914,919

4,927,613

4,940,202

4,952,225

4,958,439

4,963,173

4,967,126

4,971,692

4,977,648

4,980,584

4,984,394

4,989,385

36

1.66

-0.09

0.71

2.28

1.07

0.06

-0.25

0.35

1.45

2.90

1.31

-0.64

37

82,326,019

82,350,467

82,341,545

82,349,027

82,384,256

82,432,026

82,484,111

82,524,343

82,540,739

82,536,138

82,516,297

82,475,271

ANNEX Data

309

Data Annex: Wealth by Country

India

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

3,841,876

3,915,155

3,985,438

4,055,314

4,154,840

4,245,038

4,344,540

2

Produced capital

474,905

499,132

525,665

553,714

587,458

632,813676,302

3

Human capital

1,682,622

1,735,084

1,783,266

1,828,822

1,898,877

1,949,002

2,009,276

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

1,684,349

1,680,939

1,676,508

1,672,777

1,668,505

1,663,223

1,658,962

5

Agricultural land, rows 6 + 7

529,078

529,370

528,786

529,072

529,049

528,318

528,6146

Cropland

495,172

494,886

494,681

496,046496,201

496,084

496,817

7

Pastureland

33,90634,485

34,10533,02632,84832,234

31,796

8

Forest resources, rows 9 + 10

63,28063,64264,00464,36664,72865,09065,453

9

Timber

47,67948,00548,332

48,65948,98649,312

49,63910

Non-timber forest resources

15,601

15,637

15,672

15,707

15,743

15,77815,814

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

1,039,306

1,035,400

1,031,344

1,027,122

1,022,672

1,017,936

1,013,200

13

Oil

47,14347,13847,132

47,12847,122

47,116

47,10914

Natural gas

54,576

54,10953,61353,06052,44351,79051,06615

Coal937,587

934,154

930,598

926,934

923,107919,030

915,024

16

Minerals, rows 17 + 18 +…+ 26

52,68552,52752,37452,21752,05551,87851,696

17

Bauxite

1,582

1,574

1,566

1,557

1,548

1,539

1,529

18

Appendix

27,51527,50427,49327,481

27,471

27,461

27,452

19

Gold

109

108

106

104

102

100

98

20

Iron

19,90919,774

19,643

19,511

19,371

19,216

19,058

21

Lead

3,569

3,568

3,566

3,564

3,563

3,561

3,559

22

Nickel

-

-

-

-

-

-

-

23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

28

IWI adjustments excluding TFP, rows 29 + 30

-23,275-23,921-24,737-25,388-26,752-28,762-30,324

29

Carbon damages (annual change)-16,906-17,155-16,971-16,957-17,228-17,526-17,872

30

Oil capital gains (annual change)-6,370-6,767-7,766-8,432-9,524-11,236-12,452

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

4,397

4,390

4,379

4,369

4,390

4,401

4,422

32

Per capita produced capital

544

560

578

597

621

656

688

33

Per capita human capital

1,926

1,945

1,959

1,970

2,006

2,021

2,045

34

Per capita natural capital

1,928

1,885

1,842

1,802

1,763

1,724

1,688

35

Per capita health capital

548,699

550,985

553,204

555,367

557,488559,571561,563

36

TFP (in percentage)

1.15

-2.37

1.57

1.83

2.60

2.81

3.58

37

Population

479,444,845 491,428,918 503,451,427 515,506,557 527,592,037 539,698,924 551,765,844

873,785,449 891,910,180 910,064,576 928,226,051 946,373,316 964,486,155 982,553,253

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

310

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

4,444,223

4,547,857

4,660,523

4,783,274

4,887,274

5,015,770

5,153,632

5,317,030

5,504,897

5,709,605

5,938,610

6,163,964

2

718,617765,762822,034

881,774

929,645989,505

1,063,654

1,161,489

1,279,094

1,415,941

1,578,775

1,736,341

3

2,071,594

2,132,517

2,194,344

2,257,997

2,325,478

2,400,173

2,468,580

2,540,713

2,618,017

2,692,677

2,767,258

2,843,220

4

1,654,012

1,649,578

1,644,144

1,643,503

1,632,150

1,626,092

1,621,398

1,614,829

1,607,786

1,600,988

1,592,577

1,584,404

5

528,540

529,102528,815

533,558

527,120

526,147

526,942526,281525,624

525,960

525,188525,1856

496,867

497,265

497,259

502,417496,195

495,453

496,420495,821495,187

495,412494,722494,8277

31,67331,83731,55631,14130,92530,69430,522

30,46130,43730,54830,46630,358

865,81566,17766,53966,901

68,035

69,16970,30371,437

72,57073,39374,21575,037

949,96650,29350,61950,946

51,96752,98754,00855,02956,04956,836

57,62358,41010

15,84915,884

15,92015,955

16,06816,181

16,295

16,408

16,521

16,556

16,592

16,627

12

1,008,148

1,002,987

997,666

992,127

986,291

980,289

973,931

967,206

960,081952,580

944,659

936,238

13

47,10347,09747,09047,08447,07747,07047,06447,05747,05047,04247,03547,02814

50,32149,53048,74847,92147,036

46,07445,072

44,03642,93841,80740,65539,472

15

910,724

906,360

901,828

897,121892,177

887,145881,795

876,113870,093863,730

856,969

849,738

16

51,50851,31351,12450,91750,70450,48750,22349,90549,51149,056

48,51547,943

17

1,519

1,509

1,497

1,484

1,471

1,455

1,438

1,419

1,398

1,374

1,340

1,304

18

27,44427,43627,42927,422

27,416

27,40927,40327,39727,392

27,38627,37927,373

19

95

93

91

85

82

78

75

72

69

67

64

62

20

18,89318,721

18,554

18,37418,185

17,995

17,76017,473

17,112

16,692

16,20015,678

21

3,557

3,555

3,553

3,552

3,550

3,549

3,547

3,544

3,541

3,537

3,532

3,527

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

11

27

563,822,972 575,855,439 587,844,529 599,778,823 612,478,869 625,147,836 637,802,472 650,470,761 663,176,750 675,852,825 688,566,885 701,324,474

28-31,631-32,870-34,930-36,936-37,819-39,670-42,204-44,284-46,696-50,685-53,782-57,52929-18,145-18,085-17,954-18,356-17,915-18,072-19,079-20,011-20,747-21,566-22,033-22,53130-13,486-14,785-16,976-18,580-19,904-21,598-23,124-24,273-25,949-29,119-31,749-34,998

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

4,442

4,465

4,497

4,539

4,562

4,607

4,660

4,735

4,829

4,935

5,059

5,176

32

718

752

793

837

868

909

962

1,034

1,122

1,224

1,345

1,458

33

2,070

2,094

2,118

2,143

2,171

2,205

2,232

2,262

2,296

2,327

2,357

2,388

34

1,653

1,620

1,587

1,559

1,523

1,494

1,466

1,438

1,410

1,384

1,357

1,330

35

563,508

565,412567,276

569,105

571,676574,218

576,735

579,231581,712584,123586,528

588,921

36

0.45

2.61

2.20

-0.16

1.31

-0.60

3.69

2.33

3.65

3.38

2.79

0.72

37

1,000,558,144 1,018,471,141 1,036,258,683 1,053,898,107 1,071,374,264 1,088,694,080 1,105,885,689 1,122,991,192 1,140,042,863 1,157,038,539 1,173,971,629 1,190,863,679

ANNEX Data

311

Data Annex: Wealth by Country

Japan

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 445,239,588

46,482,041

47,572,051

48,484,836

49,282,111

50,076,142

50,769,414

2

Produced capital

10,477,873

11,023,621

11,502,652

11,914,529

12,279,380

12,629,497

13,010,380

3

Human capital

34,210,115

34,902,509

35,509,166

36,005,829

36,433,990

36,875,690

37,183,925

4Natural capital, rows 5 + 8 + 11 + 12 + 16

551,600

555,911560,233

564,478

568,741

570,955

575,108

5

Agricultural land, rows 6 + 7

238,273

236,641

235,008

233,292

231,576

227,810

225,968

6

Cropland

219,439

217,807

216,174

214,458

212,742

210,859

209,017

7

Pastureland

18,834

18,834

18,834

18,834

18,834

16,951

16,9518

Forest resources, rows 9 + 10

272,350

278,657

284,964

291,270

297,577

303,883

310,1909Timber

264,516

270,825

277,134

283,443

289,752

296,061

302,37010

Non-timber forest resources

7,834

7,832

7,830

7,827

7,825

7,823

7,820

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

10,695

10,356

10,029

9,706

9,398

9,090

8,794

13

Oil

344

343

342

342

341

341

340

14

Natural gas

4,124

3,917

3,709

3,496

3,291

3,080

2,878

15

Coal

6,228

6,096

5,977

5,868

5,765

5,670

5,576

16

Minerals, rows 17 + 18 +…+ 26

30,281

30,25730,23330,21030,19030,17230,156

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

15

12

10

8

7

6

6

19

Gold

243

236

229

221

213

205

198

20

Iron

-

-

-

-

-

-

-

21

Lead

22

21

20

19

19

18

18

22

Nickel

-

-

-

-

-

-

-

23

Phosphate

-

-

-

-

-

-

-

24

Silver

29,797

29,79429,792

29,79029,78929,78729,786

25

Tin

-

-

-

-

-

-

-

26

Zinc

205

193

182

171

163

154

148

27

Health capital

28

IWI adjustments excluding TFP, rows 29 + 30

-57,150-59,545-62,047-63,420-67,346-69,578-71,733

29

Carbon damages (annual change)-17,467-17,724-17,534-17,519-17,800-18,108-18,465

30

Oil capital gains (annual change)-39,683-41,821-44,512-45,900-49,547-51,470-53,269

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

370,054378,817386,207392,103397,124402,261

406,757

32

Per capita produced capital

85,70889,84093,38396,354

98,949101,453

104,237

33

Per capita human capital

279,835

284,447

288,276

291,183

293,591

296,222

297,91234

Per capita natural capital

4,512

4,531

4,548

4,565

4,583

4,586

4,608

35

Per capita health capital

6,580,499

6,575,081

6,570,512

6,566,779

6,563,560

6,560,725

6,557,058

36

TFP (in percentage)

2.32

0.30

-1.45

-0.16

-8.83

1.14

0.76

37

Population

804,473,747 806,782,226 809,339,559 812,004,560 814,522,375 816,723,323 818,419,057

122,251,184 122,703,017 123,177,552 123,653,405 124,097,649 124,486,744 124,814,986

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

312

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

51,455,643

51,890,580

52,249,233

52,625,167

53,089,312

53,541,390

53,716,452

53,898,780

54,181,705

54,496,153

54,902,443

55,105,917

2

13,361,418

13,596,956

13,806,766

14,004,745

14,199,502

14,312,635

14,411,869

14,520,082

14,655,788

14,787,389

14,896,443

14,956,648

3

37,514,964

37,710,158

37,854,589

38,027,036

38,292,340

38,625,921

38,696,227

38,764,627

38,906,104

39,089,726

39,387,731

39,531,806

4

579,261

583,467

587,878

593,386

597,470

602,834

608,355

614,071

619,814619,037

618,268

617,4635

224,085

222,243

220,611220,067

217,555

216,300

215,170

214,249

213,328

212,449

211,570

210,6506

207,134

205,292

203,660

202,153

200,605

199,349

198,219

197,298

196,378

195,499

194,620

193,699

7

16,951

16,951

16,951

17,913

16,951

16,951

16,951

16,951

16,951

16,951

16,951

16,951

8

316,497

322,803329,110

335,416

342,256

349,096355,936

362,776

369,615369,897

370,179

370,4619308,679

314,987

321,296327,605

334,441

341,277

348,114354,950

361,786

362,065

362,344362,623

10

7,818

7,816

7,813

7,811

7,815

7,818

7,822

7,826

7,830

7,832

7,835

7,838

12

8,539

8,294

8,047

7,807

7,574

7,366

7,190

6,999

6,834

6,663

6,499

6,339

13

339

338

337

337

336

335

334

333

332

331

330

329

14

2,684

2,496

2,306

2,111

1,928

1,721

1,546

1,355

1,192

1,022

858

699

15

5,516

5,460

5,404

5,359

5,310

5,310

5,310

5,310

5,310

5,310

5,310

5,310

16

30,14130,12630,11130,09630,08430,07230,06030,04830,03630,02830,02030,014

17

-

-

-

-

-

-

-

-

-

-

-

-

18

6

6

6

5

5

5

5

5

5

5

5

5

19

191

184

176

169

162

155

148

141

134

126

119

113

20

-

-

-

-

-

-

-

-

-

-

-

-

21

17

17

17

16

16

16

16

15

15

15

15

15

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

29,78529,78429,78329,781

29,78029,77929,77829,777

29,776

29,776

29,776

29,776

25

-

-

-

-

-

-

-

-

-

-

-

-

26

141

136

130

125

121

117

113

109

105

105

105

105

11

27

819,853,210 821,081,383 822,196,152 823,267,869 824,263,392 825,174,647 826,012,559 826,799,277 827,555,249 828,344,866 829,085,774 829,794,623

28-72,983-73,194-75,822-77,049-77,787-79,326-83,447-83,977-86,801-88,408-89,519-90,194

29-18,747-18,685-18,550-18,965-18,509-18,672-19,712-20,675-21,436-22,281-22,764-23,27930-54,235-54,509-57,273-58,084-59,278-60,654-63,735-63,301-65,365-66,127-66,755-66,915

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

411,344414,046

416,224

418,589

421,700

424,769

425,699

426,754428,677

430,920433,958

435,466

32

106,813

108,493

109,986

111,396

112,790

113,549

114,213

114,966

115,954

116,929

117,744

118,19333

299,900

300,897

301,554

302,473304,164

306,437

306,665

306,926

307,819

309,096311,327

312,394

34

4,631

4,656

4,683

4,720

4,746

4,783

4,821

4,862

4,904

4,895

4,887

4,879

35

6,554,024

6,551,585

6,549,714

6,548,408

6,547,301

6,546,492

6,546,088

6,546,343

6,547,480

6,550,004

6,553,236

6,557,327

36

0.42

-2.15

0.01

1.00

0.14

0.73

0.98

1.47

0.74

0.58

1.57

-0.78

37

125,091,571 125,325,617 125,531,619 125,720,310 125,893,623 126,048,366 126,184,149 126,299,414 126,392,944 126,464,789 126,515,486 126,544,640

ANNEX Data

313

Data Annex: Wealth by Country

Kenya

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

74,06175,97678,006

79,677

82,141

84,47585,973

2

Produced capital

16,194

16,505

16,732

16,893

17,228

17,772

18,3003

Human capital

31,42232,937

34,57236,30038,08239,893

41,567

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

26,44526,53426,703

26,484

26,831

26,81026,1055Agricultural land, rows 6 + 7

24,30024,39824,57524,36424,72024,70724,011

6

Cropland

4,965

5,063

5,240

5,029

5,385

5,372

4,676

7

Pastureland

19,335

19,335

19,335

19,335

19,335

19,335

19,335

8

Forest resources, rows 9 + 10

2,145

2,136

2,128

2,120

2,111

2,103

2,094

9

Timber

1,240

1,235

1,229

1,224

1,219

1,213

1,208

10

Non-timber forest resources

905

902

899

896

892

889

886

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

-

-

-

-

-

-

-

13

Oil

14

Natural gas

-

-

-

-

-

-

-

15

Coal

-

-

-

-

-

-

-

16

Minerals, rows 17 + 18 +…+ 26

-

-

-

-

-

-

-

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

-

-

-

-

-

-

-

19

Gold

-

-

-

-

-

-

-

20

Iron

-

-

-

-

-

-

-

21

Lead

-

-

-

-

-

-

-

-

-

-

-

-

-

22

Nickel-23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

11,515,272

11,795,499

12,068,500

12,331,103

12,579,972

12,813,141

13,030,845

28

IWI adjustments excluding TFP, rows 29 + 30

-689

-666

-706

-732

-766

-807

-844

29

Carbon damages (annual change)

-375

-380

-376

-376

-382

-389

-396

30

Oil capital gains (annual change)

-314

-285

-330

-356

-384

-418

-448

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

3,159

3,134

3,115

3,083

3,083

3,080

3,050

32

Per capita produced capital

691

681

668

654

647

648

649

33

Per capita human capital

1,340

1,359

1,381

1,404

1,429

1,455

1,474

34

Per capita natural capital

1,128

1,095

1,066

1,025

1,007

978

926

35

Per capita health capital

491,116

486,611

481,924

477,091

472,170

467,194462,224

36

TFP (in percentage)

0.60

-2.05

-4.13

-3.02

-0.07

1.56

1.09

37

Population

23,447,177

24,240,108

25,042,330

25,846,436

26,642,887

27,425,720

28,191,597

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

314

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

88,29390,48893,194

95,80698,657

101,533

104,343

107,371

110,893

114,503

118,496

122,8122

18,847

19,50420,09921,07821,72622,44622,93623,54424,724

26,34528,30930,4983

43,22044,89046,62948,45750,51752,701

54,97957,30259,646

61,59563,591

65,636

4

26,22726,095

26,46626,271

26,414

26,386

26,427

26,525

26,52426,563

26,596

26,678

5

24,141

24,017

24,397

24,211

24,36324,344

24,39524,502

24,511

24,55824,60024,691

6

4,806

4,682

5,062

4,876

5,028

5,009

5,060

5,167

5,176

5,223

5,265

5,356

7

19,335

19,335

19,335

19,335

19,335

19,335

19,335

19,335

19,335

19,335

19,335

19,335

8

2,086

2,078

2,069

2,061

2,051

2,042

2,032

2,023

2,013

2,004

1,996

1,987

9

1,203

1,197

1,192

1,187

1,180

1,173

1,167

1,160

1,154

1,148

1,142

1,136

10

883

880

877

874

871

868

865

862

859

857

854

851

-

-

-

-

-

-

-

-

-

-

-

-

14

-

-

-

-

-

-

-

-

-

-

-

-

15

-

-

-

-

-

-

-

-

-

-

-

-

16

-

-

-

-

-

-

-

-

-

-

-

-

17

-

-

-

-

-

-

-

-

-

-

-

-

18

-

-

-

-

-

-

-

-

-

-

-

-

19

-

-

-

-

-

-

-

-

-

-

-

-

20

-

-

-

-

-

-

-

-

-

-

-

-

21

-

-

-

-

-

-

-

-

-

-

-

-

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

27

13,237,214

13,436,135

13,632,749

13,831,408

14,325,900

14,839,376

15,371,173

15,919,376

16,482,552

17,061,690

17,654,765

18,267,227

28

-821

-909

-929

-1,006-966-985-1,060-1,148-1,268-1,410-1,457-1,448

29

-402

-401

-398

-407

-397

-401

-423

-444

-460

-478

-489

-500

30

-419

-508

-531

-598

-569

-584

-637

-705

-808

-931

-969

-948

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

3,050

3,047

3,059

3,065

3,076

3,083

3,087

3,094

3,114

3,134

3,161

3,194

32

651

657

660

674

677

682

678

678

694

721

755

793

33

1,493

1,512

1,531

1,550

1,575

1,600

1,626

1,651

1,675

1,686

1,696

1,707

34

906

879

869

841

823

801

782

764

745

727

710

694

35

457,326

452,450

447,531442,553446,621450,663454,697458,743462,804

466,920

470,979

475,024

36

-2.61

0.41

-0.50

-2.24

1.93

-2.47

0.02

1.60

2.36

1.96

2.22

-3.35

37

28,944,780

29,696,410

30,462,154

31,253,701

32,076,186

32,927,864

33,805,301

34,702,176

35,614,576

36,540,948

37,485,246

38,455,418

11
12
13

ANNEX Data

315

Data Annex: Wealth by Country

Nigeria

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

811,870814,540

817,352

821,034

824,682

827,780

827,9032

Produced capital

64,80563,41662,03061,22960,12458,26356,9583

Human capital

127,568

131,746

136,237

141,017

146,048

151,300

155,188

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

619,497619,378

619,086

618,788618,510618,216

615,757

5

Agricultural land, rows 6 + 7

86,28586,59786,74386,88987,03487,19085,1896

Cropland

38,39838,71038,85739,00339,14739,39837,397

7

Pastureland

47,88747,88747,88747,88747,887

47,792

47,7928

Forest resources, rows 9 + 10

10,261

10,029

9,796

9,564

9,332

9,100

8,868

9

Timber

6,056

5,923

5,791

5,659

5,527

5,395

5,262

10

Non-timber forest resources

4,205

4,105

4,005

3,905

3,805

3,705

3,605

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

522,952

522,752

522,546

522,335

522,143

521,927

521,700

13

Oil

311,466

311,449

311,432

311,416

311,399

311,382

311,365

14

Natural gas

209,543

209,360

209,172

208,978

208,804

208,604

208,395

15

Coal

1,943

1,942

1,941

1,941

1,941

1,940

1,940

16

Minerals, rows 17 + 18 +…+ 26

-

-

-

-

-

-

-

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

-

-

-

-

-

-

-

19

Gold

-

-

-

-

-

-

-

20

Iron

-

-

-

-

-

-

-

21

Lead

-

-

-

-

-

-

-

22

Nickel

-

-

-

-

-

-

-

23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

50,334,009

51,609,921

52,888,276

54,172,647

55,468,850

56,782,764

58,139,943

28

IWI adjustments excluding TFP, rows 29 + 30

12,187

12,80913,49914,204

15,177

15,735

16,60929

Carbon damages (annual change)-1,511-1,534-1,517-1,516-1,540-1,567-1,59830

Oil capital gains (annual change)

13,69814,34315,016

15,72016,717

17,302

18,207Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

8,322

8,147

7,978

7,824

7,675

7,524

7,351

32

Per capita produced capital

664

634

605

584

560

530

506

33

Per capita human capital

1,308

1,318

1,330

1,344

1,359

1,375

1,378

34

Per capita natural capital

6,350

6,195

6,043

5,897

5,756

5,619

5,468

35

Per capita health capital

515,971

516,171516,261

516,266

516,217516,138

516,257

36

TFP (in percentage)

3.51

-2.22

-0.95

0.83

-0.45

-1.80

3.08

37

Population

97,552,057

99,986,136 102,444,773 104,931,559 107,452,627 110,014,688 112,618,306

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

316

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

829,093834,028

837,054

839,902844,121847,825

856,984

862,814870,189

878,882

886,129

892,5122

55,98954,93553,87152,64952,21951,63052,621

52,43751,90054,17756,60458,437

3

159,284

163,596

168,129

172,868

178,281

181,094

190,175

196,559

203,192

209,160

215,480

222,1394

613,820

615,497

615,054614,385

613,621615,100

614,188613,817615,097

615,545614,045

611,936

5

83,72885,88385,95786,017

86,07788,351

88,471

89,18991,584

93,37993,37992,781

6

36,79938,95439,02839,08839,147

41,662

41,78143,09845,49247,88748,48547,887

7

46,92946,92946,92946,92946,92946,69046,69046,09146,09145,49244,89444,894

8

8,635

8,403

8,171

7,939

7,707

7,475

7,242

7,010

6,778

6,546

6,314

6,082

9

5,130

4,998

4,866

4,734

4,601

4,469

4,337

4,205

4,072

3,940

3,808

3,676

10

3,505

3,405

3,305

3,205

3,105

3,006

2,906

2,806

2,706

2,606

2,506

2,406

12

521,457

521,212

520,926

520,429

519,838

519,274

518,475

517,618

516,735

515,620514,352

513,07313

311,346

311,328

311,309311,291

311,271311,253

311,233

311,213311,191

311,170

311,150

311,13114

208,170

207,944

207,677

207,199

206,627

206,082

205,302

204,465

203,605

202,511201,264

200,004

15

1,940

1,940

1,940

1,940

1,940

1,940

1,939

1,939

1,939

1,939

1,939

1,939

16

-

-

-

-

-

-

-

-

-

-

-

-

17

-

-

-

-

-

-

-

-

-

-

-

-

18

-

-

-

-

-

-

-

-

-

-

-

-

19

-

-

-

-

-

-

-

-

-

-

-

-

20

-

-

-

-

-

-

-

-

-

-

-

-

21

-

-

-

-

-

-

-

-

-

-

-

-

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

27

59,515,600

60,919,166

62,362,819

63,857,618

66,234,181

68,697,758

71,251,916

73,896,825

76,632,906

79,480,595

82,415,435

85,446,251

28

17,64418,806

19,983

21,125

21,66822,86524,25025,721

26,66728,41330,122

31,66129-1,622-1,617-1,605-1,641-1,602-1,616-1,706-1,789-1,855-1,928-1,970-2,01430

19,266

20,423

21,58822,76623,26924,48025,95527,51028,52230,34132,092

33,676

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

7,193

7,069

6,930

6,790

6,662

6,530

6,440

6,326

6,223

6,131

6,030

5,924

32

486

466

446

426

412

398

395

384

371

378

385

388

33

1,382

1,387

1,392

1,398

1,407

1,395

1,429

1,441

1,453

1,459

1,466

1,474

34

5,325

5,217

5,092

4,967

4,843

4,738

4,616

4,500

4,399

4,294

4,179

4,062

35

516,320

516,337

516,315516,278

522,744

529,126

535,459

541,768

548,069

554,494

560,834

567,125

36

0.37

-0.39

-1.89

3.58

5.69

16.09

6.57

6.18

0.09

-0.43

0.32

-0.75

11

37

115,268,715 117,983,368 120,784,408 123,688,536 126,704,722 129,832,447 133,067,097 136,399,438 139,823,340 143,338,939 146,951,477 150,665,730

ANNEX Data

317

Data Annex: Wealth by Country

NorwayUNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

1,234,748

1,237,315

1,241,297

1,247,372

1,256,971

1,269,777

1,282,556

2

Produced capital

285,082285,719

285,846

287,239

289,670

292,817

298,124

3

Human capital

745,122

747,655

752,401

757,810765,750

775,809784,547

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

204,545

203,941

203,050

202,323

201,551

201,152

199,886

5Agricultural land, rows 6 + 7

5,031

5,206

5,170

5,222

5,310

5,810

5,835

6

Cropland

4,454

4,598

4,552

4,588

4,645

5,114

5,155

7

Pastureland

577

608

619

634

665

696

680

8

Forest resources, rows 9 + 10

19,885

20,152

20,42020,688

20,955

21,223

21,4909Timber17,01817,28017,542

17,80518,06718,32918,59110

Non-timber forest resources

2,867

2,872

2,878

2,883

2,888

2,894

2,899

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

179,629

178,583

177,460

176,413

175,286

174,119

172,560

13

Oil

57,10857,092

57,07457,05457,03257,00856,98114

Natural gas

122,128

121,103

120,003

118,980

117,879

116,740

115,211

15

Coal

392

387

383

379

375

371

368

16

Minerals, rows 17 + 18 +…+ 26

-

-

-

-

-

-

-

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

-

-

-

-

-

-

-

19

Gold

-

-

-

-

-

-

-

20

Iron

-

-

-

-

-

-

-

21

Lead

-

-

-

-

-

-

-

22

Nickel

-

-

-

-

-

-

-

23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

27,441,713

27,647,776

27,865,291

28,094,258

28,333,341

28,580,953

28,821,708

28

IWI adjustments excluding TFP, rows 29 + 30

-1,981-1,869-1,753-1,717-1,700-1,716-1,766

29

Carbon damages (annual change)-3,350-3,399-3,363-3,360-3,414-3,473-3,54130

Oil capital gains (annual change)

1,369

1,530

1,610

1,643

1,713

1,757

1,775

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

291,112290,250

289,642

289,456

290,030

291,294

292,47832

Per capita produced capital

67,21367,024

66,69966,65566,83867,174

67,98533

Per capita human capital

175,675

175,385

175,564

175,852

176,687

177,975

178,91034

Per capita natural capital

48,22547,84147,37946,95046,505

46,14545,58335

Per capita health capital

6,469,836

6,485,625

6,502,044

6,519,344

6,537,562

6,556,624

6,572,587

36

TFP (in percentage)

2.57

3.85

3.10

1.97

3.26

2.37

2.54

37

Population

4,241,485

4,262,932

4,285,620

4,309,369

4,333,931

4,359,096

4,385,139

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

318

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

1,298,103

1,316,951

1,330,194

1,343,194

1,368,686

1,391,764

1,414,575

1,441,934

1,475,161

1,496,853

1,530,436

1,565,688

2

307,134

319,590329,345336,940

344,354

350,550

356,364

364,862

377,202393,111

411,441

431,416

3

793,050

800,885

806,048

813,177

832,884

851,923

871,422

893,013916,759

925,420

943,660

962,294

4

197,919

196,476

194,802

193,078

191,448

189,290

186,789

184,060

181,199

178,322

175,335

171,978

5

5,351

5,397

5,351

5,371

5,397

5,392

5,361

5,361

5,340

5,335

5,320

5,280

6

4,650

4,655

4,572

4,557

4,567

4,552

4,516

4,505

4,469

4,449

4,420

4,378

7

701

742

778

814

830

840

845

856

871

887

900

902

8

21,75822,02522,29322,56023,01723,47323,92924,38524,841

25,29725,753

26,209918,853

19,116

19,37819,64020,072

20,50420,936

21,36821,801

22,233

22,66523,097

10

2,904

2,910

2,915

2,921

2,945

2,968

2,992

3,016

3,040

3,064

3,088

3,112

12

170,811

169,054

167,158

165,146

163,035

160,426

157,499

154,314151,018

147,689

144,262

140,488

13

56,95456,92856,90256,87456,84656,81956,791

56,76556,741

56,71856,69656,676

14

113,494

111,767

109,903107,926

105,867

103,314

100,453

97,332

94,08190,80787,454

83,746

15

363

359

354

345

322

293

255

216

197

165

111

66

16

-

-

-

-

-

-

-

-

-

-

-

-

17

-

-

-

-

-

-

-

-

-

-

-

-

18

-

-

-

-

-

-

-

-

-

-

-

-

19

-

-

-

-

-

-

-

-

-

-

-

-

20

-

-

-

-

-

-

-

-

-

-

-

-

21

-

-

-

-

-

-

-

-

-

-

-

-

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

27

29,070,870

29,324,031

29,575,192

29,821,168

30,054,703

30,280,821

30,518,786

30,795,961

31,130,935

31,529,132

31,983,651

32,467,125

28-1,682-1,566-1,398-1,232-1,095-973-1,119-912-873-1,096

-941

-852

29

-3,595-3,583-3,557-3,637-3,550-3,581-3,780-3,965-4,111-4,273-4,366-4,464

30

1,914

2,017

2,159

2,405

2,455

2,608

2,661

3,053

3,238

3,177

3,425

3,612

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

294,215

296,661

297,872

299,095

303,212306,853

310,305

314,349

319,071

320,607324,106

327,62132

69,612

71,99273,75075,02876,28777,28978,17379,54281,587

84,20087,13390,274

33

179,745

180,410

180,499

181,074

184,513

187,830

191,158

194,682

198,291

198,214

199,843

201,36134

44,85844,25943,622

42,99342,413

41,73440,974

40,12639,19338,194

37,131

35,98635

6,588,908

6,605,630

6,622,798

6,640,415

6,658,178

6,676,256

6,694,683

6,713,680

6,733,491

6,753,152

6,773,304

6,793,765

36

1.87

-1.17

-0.71

1.64

0.94

0.33

0.76

1.07

-0.34

-2.09

-2.56

-3.92

37

4,412,092

4,439,248

4,465,664

4,490,859

4,513,953

4,535,599

4,558,660

4,587,046

4,623,298

4,668,802

4,722,016

4,778,959

11

ANNEX Data

319

Data Annex: Wealth by Country

Russia

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

11,309,075

11,351,800

11,306,998

11,201,869

11,073,422

10,978,441

10,885,180

2

Produced capital

2,202,470

2,234,585

2,187,143

2,114,905

2,026,699

1,939,838

1,847,614

3

Human capital

1,811,819

1,822,524

1,853,463

1,849,791

1,836,557

1,855,028

1,879,906

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

7,294,786

7,294,690

7,266,393

7,237,173

7,210,166

7,183,574

7,157,660

5Agricultural land, rows 6 + 7

175,215

175,215

175,215

172,973

172,116

171,079

170,851

6

Cropland105,705

105,705

105,705

103,798

103,093

102,300

101,171

7

Pastureland

69,50969,50969,50969,17569,022

68,77969,6792,242,485

2,243,068

2,243,651

2,244,234

2,244,818

2,245,401

8

Forest resources, rows 9 + 10

2,241,902

9

Timber

1,987,892

1,988,465

1,989,038

1,989,611

1,990,184

1,990,757

1,991,330

10

Non-timber forest resources

254,010254,020

254,030

254,040

254,050

254,060

254,070

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

4,794,458

4,794,458

4,766,279

4,739,354

4,713,237

4,687,710

4,662,013

13

Oil

496,396496,396496,332

496,275

496,223

496,172

496,122

14

Natural gas

2,166,073

2,166,073

2,142,138

2,119,051

2,096,350

2,074,119

2,051,645

15

Coal

2,131,988

2,131,988

2,127,809

2,124,028

2,120,665

2,117,420

2,114,245

16

Minerals, rows 17 + 18 +…+ 26

83,212

82,533

81,831

81,19680,57979,96879,396

17

Bauxite

459

450

443

436

431

426

421

18

Appendix

6,045

5,911

5,776

5,663

5,552

5,451

5,350

19

Gold

6,705

6,580

6,452

6,321

6,192

6,076

5,968

20

Iron

60,10059,91959,73359,561

59,39559,22359,065

21

Lead

-

-

-

-

-

-

-

22

Nickel

8,283

8,096

7,896

7,722

7,550

7,371

7,206

23

Phosphate

1,440

1,399

1,356

1,321

1,291

1,258

1,226

24

Silver

-

-

-

-

-

-

-

25

Tin

180

177

175

172

167

163

160

26

Zinc

-

-

-

-

-

-

-

27

Health capital

28

IWI adjustments excluding TFP, rows 29 + 30

-6,024-6,375-7,136-1,738

3,776

6,253

10,457

29

Carbon damages (annual change)

1,455

1,476

1,461

1,459

1,483

1,508

1,538

30

Oil capital gains (annual change)-7,479-7,851-8,596-3,197

2,293

4,744

8,919

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

76,28776,35475,93875,20874,38573,83073,32232

Per capita produced capital

14,857

15,03014,68914,19913,614

13,045

12,44533

Per capita human capital

12,222

12,25912,44812,41912,337

12,475

12,66334

Per capita natural capital

49,20849,06548,801

48,58948,434

48,31048,21435

Per capita health capital

1,512,705

1,500,267

1,487,022

1,473,268

1,459,506

1,446,001

1,430,705

36

TFP (in percentage)-7.48-10.59

-1.08

-1.66

37

Population

224,248,712 223,050,376 221,414,260 219,436,772 217,271,210 215,018,298 212,398,067

148,243,501 148,673,813 148,897,737 148,945,559 148,866,314 148,698,582 148,456,965

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

320

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

10,790,061

10,698,680

10,694,557

10,653,287

10,561,905

10,504,167

10,439,861

10,402,659

10,367,033

10,341,726

10,337,446

10,327,366

2

1,758,121

1,669,937

1,590,359

1,527,453

1,464,410

1,411,687

1,369,602

1,337,632

1,314,714

1,306,155

1,315,707

1,335,387

3

1,897,227

1,919,639

2,020,765

2,067,294

2,063,814

2,084,155

2,088,485

2,110,408

2,125,437

2,132,756

2,142,820

2,135,477

4

7,134,713

7,109,104

7,083,434

7,058,540

7,033,681

7,008,324

6,981,773

6,954,619

6,926,882

6,902,815

6,878,918

6,856,502

5

172,335

171,780

171,387

171,682

171,444

171,278

170,982

170,747

170,510

170,358

170,338

170,3636

102,287

101,160

100,260

99,80099,38999,05898,32597,996

97,69997,533

97,531

97,5897

70,04870,62071,12771,882

72,05572,21972,65672,751

72,811

72,82572,807

72,7738

2,245,984

2,246,567

2,247,150

2,247,733

2,248,739

2,249,746

2,250,752

2,251,759

2,252,765

2,257,969

2,263,172

2,268,376

9

1,991,903

1,992,477

1,993,050

1,993,623

1,994,659

1,995,696

1,996,732

1,997,769

1,998,805

2,003,990

2,009,175

2,014,360

10

254,080

254,090

254,100

254,110254,080

254,050

254,020

253,990

253,960

253,979

253,998

254,017

12

4,637,588

4,612,565

4,587,367

4,562,303

4,537,392

4,511,938

4,485,436

4,458,247

4,430,490

4,402,134

4,373,825

4,346,947

13

496,072

496,021495,969

495,914495,855495,791

495,721495,644495,566

495,486

495,404

495,32414

2,030,300

2,008,215

1,986,175

1,964,340

1,942,633

1,920,380

1,897,342

1,873,649

1,849,707

1,825,189

1,800,779

1,778,009

15

2,111,216

2,108,328

2,105,222

2,102,048

2,098,905

2,095,767

2,092,373

2,088,953

2,085,217

2,081,459

2,077,642

2,073,614

16

78,80678,192

77,53076,822

76,10675,36374,60373,866

73,11772,35571,58270,816

17

415

410

404

397

390

383

374

365

354

344

333

323

18

5,252

5,156

5,053

4,943

4,827

4,693

4,562

4,432

4,296

4,156

4,013

3,868

19

5,868

5,767

5,657

5,531

5,398

5,250

5,101

4,958

4,814

4,674

4,537

4,382

20

58,90558,741

58,55758,36058,17357,983

57,77557,55557,336

57,10556,86756,640

11

21

-

-

-

-

-

-

-

-

-

-

-

-

22

7,021

6,813

6,599

6,373

6,141

5,919

5,698

5,506

5,308

5,110

4,910

4,719

23

1,189

1,152

1,109

1,068

1,029

989

948

907

866

825

783

744

24

-

-

-

-

-

-

-

-

-

-

-

-

25

156

154

152

150

147

146

145

144

143

141

140

139

26

-

-

-

-

-

-

-

-

-

-

-

-

27

209,844,768 207,288,365 204,622,041 201,820,230 201,686,715 201,456,825 201,232,379 201,168,744 201,353,170 201,492,543 201,828,067 202,342,203

28

12,07913,555

14,244

14,802

15,561

15,994

16,877

18,033

19,111

20,24822,902

21,608

29

1,562

1,556

1,545

1,580

1,542

1,555

1,642

1,722

1,786

1,856

1,896

1,939

30

10,517

11,998

12,69913,222

14,01914,43815,235

16,311

17,325

18,39221,006

19,668

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

72,83772,411

72,61072,591

72,262

72,18472,05872,08772,072

72,06372,141

72,13732

11,86811,303

10,798

10,40810,019

9,701

9,453

9,269

9,140

9,101

9,182

9,328

33

12,807

12,993

13,72014,086

14,12014,322

14,415

14,624

14,776

14,861

14,954

14,91634

48,162

48,11648,09348,097

48,12348,161

48,19048,19348,156

48,10048,00547,89335

1,416,537

1,402,974

1,389,277

1,375,195

1,379,887

1,384,396

1,388,954

1,394,033

1,399,811

1,404,031

1,408,484

1,413,368

36

3.92

-3.06

8.21

11.43

6.29

5.32

7.45

6.59

4.69

4.84

3.52

-0.37

37

148,139,274 147,749,214 147,286,725 146,757,517 146,161,742 145,519,641 144,880,469 144,306,982 143,843,159 143,510,059 143,294,533 143,163,100

ANNEX Data

321

Data Annex: Wealth by Country

Saudi Arabia

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

3,737,877

3,774,763

3,812,699

3,854,090

3,892,059

3,931,841

3,978,736

2

Produced capital

251,105259,288

267,701

277,482281,622

286,148

290,429

3

Human capital

749,332

779,068

809,853

842,842878,168

914,935

959,551

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

2,737,441

2,736,406

2,735,144

2,733,767

2,732,270

2,730,758

2,728,756

5Agricultural land, rows 6 + 7

222,981223,227

223,322

223,372

223,372

223,372

223,006

6

Cropland

4,474

4,720

4,815

4,865

4,865

4,865

4,499

7

Pastureland

218,507

218,507

218,507

218,507

218,507

218,507

218,507

8

Forest resources, rows 9 + 10

307

307

307

307

307

307

307

9

Timber

-

-

-

-

-

-

-

10

Non-timber forest resources

307

307

307

307

307

307

307

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

2,514,153

2,512,873

2,511,516

2,510,088

2,508,591

2,507,080

2,505,444

13

Oil

2,208,253

2,208,180

2,208,105

2,208,032

2,207,956

2,207,880

2,207,804

14

Natural gas

305,900

304,693

303,410302,056

300,634

299,200

297,640

15

Coal

-

-

-

-

-

-

-

16

Minerals, rows 17 + 18 +…+ 26

-

-

-

-

-

-

-

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

-

-

-

-

-

-

-

19

Gold

-

-

-

-

-

-

-

20

Iron

-

-

-

-

-

-

-

21

Lead

-

-

-

-

-

-

-

-

-

-

-

-

-

22

Nickel-23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

43,005,876

44,546,954

46,065,521

47,506,994

48,802,269

49,923,521

50,867,503

28

IWI adjustments excluding TFP, rows 29 + 30

99,401

104,148

109,058

114,326

120,119

126,703

132,668

29

Carbon damages (annual change)-2,743-2,783-2,754-2,751-2,795-2,844-2,90030

Oil capital gains (annual change)

102,144

106,932

111,811

117,077

122,915

129,547

135,568

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

231,604

226,444

221,809

217,995

214,818

212,626

211,78732

Per capita produced capital

15,55915,554

15,574

15,695

15,544

15,474

15,45933

Per capita human capital

46,43046,735

47,11447,67348,46949,47851,07734

Per capita natural capital

169,616

164,154

159,121

154,627

150,804

147,674

145,25135

Per capita health capital

2,664,709

2,672,321

2,679,930

2,687,090

2,693,584

2,699,759

2,707,667

36

TFP (in percentage)

9.42

4.82

0.30

-4.64

-3.32

-2.80

0.99

37

Population

16,139,053

16,669,764

17,189,075

17,679,720

18,117,969

18,491,845

18,786,467

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

322

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

4,027,123

4,074,370

4,123,822

4,178,275

4,246,410

4,324,887

4,414,396

4,505,246

4,599,901

4,712,636

4,829,904

4,946,619

2

297,222305,305

315,320

326,649

336,670

347,554362,693377,769

399,295

427,445465,583

509,4243

1,002,567

1,043,575

1,084,828

1,129,909

1,190,117

1,259,918

1,336,631

1,415,084

1,490,981

1,578,481

1,660,501

1,736,685

4

2,727,335

2,725,490

2,723,674

2,721,717

2,719,624

2,717,415

2,715,072

2,712,394

2,709,625

2,706,711

2,703,820

2,700,510

5

223,372

223,372

223,372

223,372

223,380

223,382

223,389

223,274

223,285

223,229

223,231223,044

6

4,865

4,865

4,865

4,865

4,873

4,875

4,882

4,767

4,778

4,722

4,724

4,537

7

218,507

218,507

218,507

218,507

218,507

218,507

218,507

218,507

218,507

218,507

218,507

218,507

8

307

307

307

307

307

307

307

307

307

307

307

307

9

-

-

-

-

-

-

-

-

-

-

-

-

10

307

307

307

307

307

307

307

307

307

307

307

307

12

2,503,656

2,501,811

2,499,995

2,498,038

2,495,937

2,493,726

2,491,377

2,488,813

2,486,034

2,483,175

2,480,283

2,477,159

13

2,207,726

2,207,647

2,207,574

2,207,495

2,207,420

2,207,347

2,207,263

2,207,177

2,207,085

2,206,996

2,206,912

2,206,822

14

295,930

294,164

292,421290,543

288,518

286,379

284,113281,636

278,949

276,178

273,371

270,337

15

-

-

-

-

-

-

-

-

-

-

-

-

16

-

-

-

-

-

-

-

-

-

-

-

-

17

-

-

-

-

-

-

-

-

-

-

-

-

18

-

-

-

-

-

-

-

-

-

-

-

-

19

-

-

-

-

-

-

-

-

-

-

-

-

20

-

-

-

-

-

-

-

-

-

-

-

-

21

-

-

-

-

-

-

-

-

-

-

-

-

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

27

51,653,325

52,451,038

53,491,637

54,931,509

56,599,668

58,633,721

60,885,016

63,138,334

65,242,255

67,192,578

69,013,598

70,732,235

28

139,214145,897

153,298

160,616

168,263

176,146

184,165

192,817

201,949

211,667

220,903

230,153

29-2,944-2,934-2,913-2,978-2,907-2,932-3,096-3,247-3,366-3,499-3,575-3,65630

142,159

148,831

156,211

163,594

171,169

179,079

187,261

196,064

205,315215,166

224,478

233,809

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

211,724

211,583

210,626

208,442205,323

201,504

197,650

194,076

191,335

190,030

189,377

189,043

32

15,62615,855

16,105

16,296

16,27916,193

16,23916,273

16,60917,236

18,255

19,46833

52,70954,19355,40856,36857,54558,702

59,846

60,95962,01863,65065,107

66,37034

143,388

141,535

139,113

135,778

131,500

126,609

121,565

116,844112,708

109,144

106,015103,20435

2,715,646

2,723,788

2,732,103

2,740,372

2,736,719

2,731,842

2,726,068

2,719,866

2,713,778

2,709,440

2,705,972

2,703,146

36

0.54

0.59

-3.85

1.11

-3.92

-4.81

2.70

0.86

1.18

-1.38

-2.93

-1.39

37

19,020,639

19,256,649

19,578,923

20,045,276

20,681,576

21,463,072

22,334,371

23,213,767

24,041,116

24,799,436

25,504,176

26,166,639

11

ANNEX Data

323

Data Annex: Wealth by Country

South Africa

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

1,395,238

1,428,824

1,464,157

1,501,291

1,540,528

1,580,925

1,589,2022

Produced capital

210,303

210,742

210,353

209,911

210,679

213,045

216,788

3

Human capital

647,995

682,885

720,559

760,164

800,745

841,487

849,058

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

536,941

535,197533,246

531,215

529,105

526,393523,356

5

Agricultural land, rows 6 + 7

77,50977,98978,39078,79079,271

79,691

79,831

6

Cropland

11,45011,69011,931

12,171

12,411

12,671

12,651

7

Pastureland

66,05966,29966,45966,61966,86067,02067,1808Forest resources, rows 9 + 10

9,156

9,156

9,156

9,156

9,156

9,156

9,156

9

Timber

6,901

6,901

6,901

6,901

6,901

6,901

6,901

10

Non-timber forest resources

2,255

2,255

2,255

2,255

2,255

2,255

2,255

11

Fisheries

344

425

432

432

429

510

521

12

Fossil fuels, rows 13 + 14 + 15

422,948

420,745

418,487

416,159

413,683

411,077

408,473

13

Oil

131

131

131

131

129

128

126

14

Natural gas

907

907

906

856

802

748

696

15

Coal

421,910

419,707417,450

415,173

412,752

410,202407,650

16

Minerals, rows 17 + 18 +…+ 26

26,984

26,881

26,781

26,677

26,56725,95825,375

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

2,879

2,879

2,879

2,879

2,878

2,846

2,817

19

Gold

10,012

10,012

10,011

10,011

10,010

9,550

9,114

20

Iron

3,705

3,639

3,575

3,508

3,435

3,363

3,293

21

Lead

86

82

78

72

67

62

58

3,087

3,067

3,045

3,023

3,001

2,977

22

Nickel3,107

23

Phosphate

5,778

5,766

5,754

5,745

5,736

5,725

5,714

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

1,417

1,417

1,417

1,417

1,417

1,411

1,404

27

Health capital

65,694,193

66,518,470

67,381,812

68,216,264

68,931,906

69,468,059

69,855,871

28

IWI adjustments excluding TFP, rows 29 + 30

-6,693-7,074-7,252-7,325-7,555-7,842-8,08429

Carbon damages (annual change)-3,898-3,956-3,913-3,910-3,972-4,041-4,12130

Oil capital gains (annual change)-2,794-3,118-3,339-3,415-3,582-3,800-3,963

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

37,92037,90937,89037,90237,99838,18437,68032

Per capita produced capital

5,716

5,591

5,444

5,300

5,197

5,146

5,140

33

Per capita human capital

17,611

18,11818,647

19,191

19,751

20,325

20,13134

Per capita natural capital

14,593

14,20013,80013,411

13,051

12,714

12,40935

Per capita health capital

1,785,464

1,764,841

1,743,753

1,722,220

1,700,258

1,677,875

1,656,305

36

TFP (in percentage)

-3.72

-4.03

-5.08

-1.66

0.17

-0.44

0.27

37

Population

36,793,907

37,690,924

38,641,823

39,609,488

40,542,036

41,402,400

42,175,740

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

324

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

1,596,272

1,602,714

1,606,490

1,611,499

1,632,188

1,655,592

1,677,745

1,708,515

1,741,738

1,770,990

1,804,168

1,846,068

2

221,340

226,513229,755

234,073

237,523

242,010248,344257,232

268,383

282,294

299,798

321,335

3

854,820

859,425

863,252

867,165

887,510909,670928,775

954,703

980,525

999,666

1,019,044

1,042,9784

520,112516,776

513,484

510,261

507,155

503,912500,626

496,580

492,831

489,030

485,326

481,755

5

79,791

79,81379,78379,78379,78379,78379,78379,73379,733

79,573

79,573

79,573

6

12,611

12,611

12,581

12,581

12,581

12,581

12,581

12,531

12,531

12,371

12,371

12,371

7

67,18067,202

67,202

67,202

67,202

67,202

67,202

67,202

67,202

67,202

67,202

67,202

8

9,156

9,156

9,156

9,156

9,156

9,156

9,156

9,156

9,156

9,156

9,156

9,156

9

6,901

6,901

6,901

6,901

6,901

6,901

6,901

6,901

6,901

6,901

6,901

6,901

10

2,255

2,255

2,255

2,255

2,255

2,255

2,255

2,255

2,255

2,255

2,255

2,255

11

690

706

749

893

1,157

1,241

1,461

979

736

603

428

382

12

405,683

402,871

400,106

397,266

394,393

391,571388,548

385,482

382,390379,282

376,135

372,965

13

125

123

122

120

119

117

116

114

113

111

110

108

14

648

608

569

523

465

401

338

276

215

134

51

1

15

404,910402,140

399,415396,623

393,810391,053

388,094

385,092

382,063

379,036

375,974

372,856

16

24,792

24,22923,69023,163

22,66622,161

21,67821,22920,815

20,416

20,034

19,678

17

-

-

-

-

-

-

-

-

-

-

-

-

18

2,787

2,755

2,727

2,701

2,673

2,648

2,625

2,605

2,585

2,564

2,541

2,520

19

8,682

8,273

7,877

7,498

7,151

6,801

6,474

6,177

5,918

5,679

5,458

5,271

20

3,217

3,142

3,075

2,999

2,920

2,837

2,750

2,661

2,571

2,478

2,382

2,271

21

53

49

45

40

38

35

33

31

29

26

24

21

22

2,952

2,925

2,899

2,873

2,847

2,819

2,790

2,762

2,731

2,701

2,674

2,651

23

5,703

5,693

5,682

5,672

5,662

5,652

5,642

5,632

5,622

5,612

5,603

5,594

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

1,398

1,391

1,385

1,380

1,374

1,368

1,364

1,362

1,359

1,356

1,353

1,350

27

70,083,468

70,186,497

70,218,336

70,217,206

70,721,432

71,206,093

71,659,780

72,062,790

72,399,448

72,701,292

72,935,830

73,098,253

28-8,350-8,625-8,860-9,048-9,142-9,581-10,147-10,603-11,359-11,970-12,505-12,550

29-4,184-4,170-4,140-4,233-4,131-4,167-4,399-4,614-4,784-4,973-5,080-5,19530-4,166-4,455-4,720-4,815-5,011-5,414-5,747-5,989-6,575-6,997-7,424-7,355

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

37,232

36,83036,39836,00335,96035,97935,97936,17736,44436,64336,93937,431

32

5,163

5,205

5,205

5,229

5,233

5,259

5,326

5,447

5,616

5,841

6,138

6,515

33

19,93819,75019,55819,373

19,553

19,76919,917

20,215

20,516

20,684

20,864

21,14734

12,131

11,875

11,634

11,40011,173

10,951

10,736

10,515

10,312

10,118

9,937

9,768

35

1,634,663

1,612,881

1,590,905

1,568,736

1,558,099

1,547,440

1,536,729

1,525,892

1,514,861

1,504,240

1,493,287

1,482,141

36

-1.58

-4.02

-2.02

0.19

-0.92

0.35

-0.83

0.48

0.58

0.35

-0.17

-3.39

37

42,873,355

43,516,225

44,137,342

44,760,380

45,389,577

46,015,405

46,631,364

47,226,670

47,792,787

48,330,914

48,842,462

49,319,363

ANNEX Data

325

Data Annex: Wealth by Country

United Kingdom

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

10,718,589

10,759,091

10,791,161

10,814,707

10,876,817

10,925,053

11,014,382

1

Inclusive Wealth Index, rows 2 + 3 + 4

2

Produced capital

858,527

858,756

863,088

870,846

885,913902,168

922,850

3

Human capital

9,690,694

9,734,250

9,765,131

9,785,201

9,835,566

9,870,866

9,943,081

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

169,368

166,085

162,941

158,661

155,338

152,019

148,451

5

Agricultural land, rows 6 + 7

38,26038,13437,98136,85436,591

36,52836,7706

Cropland

14,053

13,942

13,91012,931

12,552

12,596

12,935

7

Pastureland

24,207

24,192

24,071

23,92324,03923,932

23,835

8

Forest resources, rows 9 + 10

17,155

17,317

17,47917,641

17,803

17,965

18,128

9

Timber16,335

16,491

16,64816,804

16,961

17,117

17,27310

Non-timber forest resources

820

826

831

837

843

848

854

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

113,953

110,634

107,481

104,165

100,943

97,52593,55413

Oil

29,95329,93629,91929,901

29,90029,89929,89714

Natural gas

72,09569,96967,88665,43362,81959,992

56,62415

Coal

11,905

10,728

9,676

8,831

8,224

7,634

7,033

16

Minerals, rows 17 + 18 +…+ 26

-

-

-

-

-

-

-

17

Bauxite

-

-

-

-

-

-

-

18

Appendix

-

-

-

-

-

-

-

19

Gold

-

-

-

-

-

-

-

20

Iron

-

-

-

-

-

-

-

21

Lead

-

-

-

-

-

-

-

-

-

-

-

-

-

22

Nickel-23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

28

IWI adjustments excluding TFP, rows 29 + 30

-41,741-42,841-43,194-43,901-44,794-45,590-46,88029

Carbon damages (annual change)-29,973-30,415-30,089-30,064-30,544-31,073-31,68630

Oil capital gains (annual change)-11,768-12,426-13,105-13,837-14,250-14,517-15,194

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

187,341

187,540

187,589

187,490

188,055

188,372

189,39132

Per capita produced capital

15,005

14,96915,00415,097

15,317

15,555

15,86833

Per capita human capital

169,375

169,676

169,753

169,642

170,052

170,196

170,97034

Per capita natural capital

2,960

2,895

2,833

2,751

2,686

2,621

2,553

35

Per capita health capital

5,240,952

5,252,398

5,264,819

5,278,043

5,291,731

5,305,741

5,317,476

36

TFP (in percentage)

-1.41

0.60

0.91

2.16

1.37

0.39

0.72

37

Population

57,214,474

57,369,629

57,525,459

57,681,639

57,838,596

57,997,210

58,156,871

299,858,301 301,328,111 302,861,135 304,446,186 306,066,282 307,718,160 309,247,775

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

326

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

11,135,097

11,234,807

11,411,886

11,559,921

11,712,256

11,936,976

12,189,626

12,405,182

12,639,749

12,926,705

13,151,028

13,423,672

2

949,730

978,851

1,013,382

1,045,854

1,067,088

1,110,234

1,159,837

1,214,277

1,276,785

1,342,894

1,420,522

1,494,113

3

10,040,361

10,114,759

10,261,920

10,382,294

10,517,359

10,702,768

10,909,691

11,074,183

11,249,633

11,471,386

11,620,942

11,822,300

4145,006

141,196

136,584

131,774

127,809

123,974

120,098

116,723

113,331

112,425

109,564

107,260

5

36,961

36,82036,19235,65635,63335,681

35,63935,83935,63937,49337,092

37,1696

13,504

13,254

12,544

12,46011,985

12,266

11,997

12,334

12,14012,903

12,887

12,718

7

23,45723,566

23,64823,196

23,64823,41523,642

23,50523,49924,59024,20524,451

8

18,29018,452

18,614

18,776

19,13819,501

19,863

20,226

20,58821,042

21,496

21,950917,43017,586

17,743

17,89918,25818,617

18,976

19,336

19,695

20,147

20,59821,050

10

860

866

871

877

880

884

887

890

893

896

898

900

12

89,75685,924

81,77977,34273,03868,79264,59660,658

57,10353,89050,977

48,14013

29,89629,89529,89329,89229,891

29,89029,89029,88929,88829,88729,88729,886

14

53,40950,076

46,38042,32338,411

34,53230,68027,04823,742

20,75318,046

15,428

15

6,450

5,954

5,506

5,126

4,736

4,370

4,025

3,721

3,473

3,249

3,044

2,826

16

-

-

-

-

-

-

-

-

-

-

-

-

17

-

-

-

-

-

-

-

-

-

-

-

-

18

-

-

-

-

-

-

-

-

-

-

-

-

19

-

-

-

-

-

-

-

-

-

-

-

-

20

-

-

-

-

-

-

-

-

-

-

-

-

21

-

-

-

-

-

-

-

-

-

-

-

-

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

11

27

310,802,832 312,411,630 314,120,704 315,967,570 317,959,110 320,082,456 322,350,792 324,786,151 327,406,927 330,007,489 332,781,801 335,698,193

28-47,291-47,601-47,905-48,711-48,350-49,194-51,668-53,780-56,049-57,931-58,687-60,474

29-32,171-32,064-31,832-32,544-31,762-32,041-33,827-35,479-36,784-38,235-39,063-39,94730-15,120-15,537-16,073-16,166-16,588-17,153-17,842-18,301-19,265-19,696-19,624-20,527

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

190,935

192,087

194,505

196,350

198,187

201,162204,509

207,127

209,953

213,530

215,958

219,089

32

16,285

16,736

17,272

17,76418,057

18,71019,45920,275

21,20822,18323,327

24,38633

172,163

172,937

174,905

176,347

177,967

180,364

183,035

184,903

186,863

189,490

190,832

192,953

34

2,486

2,414

2,328

2,238

2,163

2,089

2,015

1,949

1,882

1,857

1,799

1,751

35

5,329,379

5,341,463

5,353,897

5,366,833

5,380,280

5,394,045

5,408,176

5,422,883

5,438,407

5,451,232

5,464,747

5,478,969

36

0.02

0.68

0.35

1.13

-0.01

0.49

1.15

1.08

-0.16

1.34

0.94

-0.85

37

58,318,771

58,488,026

58,671,413

58,874,117

59,097,129

59,339,971

59,604,347

59,891,788

60,202,727

60,538,143

60,896,101

61,270,318

ANNEX Data

327

Data Annex: Wealth by Country

United States

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

1

Inclusive Wealth Index, rows 2 + 3 + 4

86,441,991

87,502,754

88,869,537

90,148,995

91,772,804

93,471,285

95,000,514

2

Produced capital

11,049,849

11,288,591

11,565,418

11,897,811

12,298,176

12,747,787

13,276,863

3

Human capital

68,515,458

69,356,545

70,467,276

71,436,979

72,685,177

73,955,459

74,986,345

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

6,876,684

6,857,618

6,836,843

6,814,205

6,789,452

6,768,039

6,737,306

5Agricultural land, rows 6 + 7

1,058,225

1,058,225

1,054,460

1,048,311

1,043,827

1,041,349

1,031,848

6

Cropland

465,418

465,418

461,462

458,409456,404

456,404

449,382

7

Pastureland

592,807592,807592,998

589,902587,424584,945582,467

8

Forest resources, rows 9 + 10

2,065,797

2,076,896

2,087,996

2,099,095

2,110,195

2,121,294

2,132,394

9

Timber

1,972,748

1,983,726

1,994,704

2,005,683

2,016,661

2,027,639

2,038,618

10

Non-timber forest resources

93,04993,17093,292

93,41393,53493,655

93,776

11

Fisheries

19,566

18,287

19,265

20,417

19,63919,82018,306

12

Fossil fuels, rows 13 + 14 + 15

3,685,096

3,657,176

3,629,102

3,601,334

3,571,923

3,542,734

3,512,969

13

Oil

148,197

148,122

148,047

147,975

147,902

147,830

147,757

14

Natural gas

569,377

552,088534,660

516,983

498,597

480,428

462,00915

Coal

2,967,522

2,956,967

2,946,395

2,936,376

2,925,424

2,914,477

2,903,203

16

Minerals, rows 17 + 18 +…+ 26

48,00147,03346,01945,04843,86742,842

41,78817

Bauxite

32

32

32

32

32

32

32

18

Appendix

11,876

11,565

11,228

10,884

10,537

10,184

9,817

19

Gold

7,349

7,094

6,809

6,522

6,240

5,966

5,684

20

Iron

17,697

17,57017,445

17,321

17,19017,05016,911

21

Lead

824

799

777

758

739

718

695

22

Nickel

-

-

-

-

-

-

-

23

Phosphate

6,961

6,784

6,611

6,481

6,330

6,170

6,003

24

Silver

890

866

842

820

623

602

581

25

Tin

-

-

-

-

-

-

-

26

Zinc

2,373

2,324

2,275

2,230

2,177

2,119

2,064

27

Health capital

28

IWI adjustments excluding TFP, rows 29 + 30

-150,531-153,489-161,467-169,287-177,953-183,066-192,933

29

Carbon damages (annual change)-31,046-31,504-31,166-31,140-31,638-32,185-32,82030

Oil capital gains (annual change)-119,484-121,986-130,301-138,147-146,316-150,881-160,113

Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

341,211

342,065

344,088345,659

348,325

350,969

352,64632

Per capita produced capital

43,617

44,12944,77945,62046,67847,86649,28433

Per capita human capital

270,450

271,128

272,837

273,911275,878

277,690

278,35234

Per capita natural capital

27,14426,80826,471

26,12825,76925,41325,00935

Per capita health capital

6,219,740

6,228,201

6,236,985

6,245,836

6,254,455

6,262,842

6,271,192

36

TFP (in percentage)

-0.06

-0.77

1.83

0.08

0.86

-0.11

1.29

37

Population

1,575,703,370 1,593,219,496 1,610,863,123 1,628,934,347 1,647,854,829 1,667,943,485 1,689,419,253

253,339,097 255,807,342 258,275,919 260,803,255 263,468,980 266,323,717 269,393,632

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

328

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

96,860,029

98,635,343 100,559,984 102,540,187 104,697,019 106,716,286 108,575,657 110,319,477 112,347,445 114,286,433 116,089,191 117,832,867

2

13,894,079

14,621,021

15,452,515

16,331,550

17,170,541

17,870,398

18,581,882

19,365,782

20,206,106

21,039,001

21,778,585

22,338,447

3

76,252,680

77,322,887

78,436,760

79,557,553

80,875,168

82,198,111

83,348,548

84,319,434

85,513,573

86,631,596

87,691,545

88,872,818

4

6,713,270

6,691,435

6,670,709

6,651,084

6,651,309

6,647,777

6,645,227

6,634,260

6,627,767

6,615,835

6,619,061

6,621,602

5

1,028,326

1,027,590

1,025,853

1,027,122

1,028,473

1,023,813

1,020,838

1,009,987

1,005,176

993,517997,579

1,002,242

6446,373444,365

441,356

441,356

441,435

435,504

432,175

420,828

416,018

404,110

407,677

412,3397

581,954583,225

584,497585,766

587,037

588,309588,663

589,159

589,159

589,407589,902589,9028

2,143,493

2,154,593

2,165,693

2,176,792

2,207,871

2,238,950

2,270,029

2,301,108

2,332,187

2,363,276

2,394,365

2,425,454

92,049,596

2,060,574

2,071,553

2,082,531

2,113,490

2,144,448

2,175,407

2,206,366

2,237,325

2,268,294

2,299,263

2,330,232

10

93,89894,01994,14094,261

94,381

94,502

94,622

94,742

94,862

94,982

95,102

95,223

11

17,885

17,28018,327

17,51017,376

18,416

18,644

18,26815,994

15,87315,753

15,63212

3,482,881

3,452,382

3,422,254

3,392,068

3,360,886

3,330,729

3,300,646

3,270,632

3,240,943

3,210,480

3,179,443

3,147,142

13

147,685

147,613

147,544

147,475

147,406

147,337

147,269

147,202

147,138

147,074

147,009

146,94414

443,544424,960

406,563

387,824

368,661

350,170

331,513313,351

295,717277,641

258,820

239,00315

2,891,652

2,879,809

2,868,147

2,856,769

2,844,819

2,833,222

2,821,864

2,810,079

2,798,087

2,785,765

2,773,614

2,761,195

16

40,68539,59038,58237,59336,70435,86935,06934,26533,46632,68831,921

31,131

17

32

32

32

32

32

32

32

32

32

32

32

32

18

9,447

9,092

8,786

8,511

8,255

8,038

7,824

7,602

7,385

7,156

6,932

6,682

19

5,371

5,054

4,759

4,454

4,164

3,906

3,666

3,443

3,221

3,003

2,797

2,596

20

16,770

16,63016,501

16,35916,25616,141

16,032

15,91015,78815,67015,553

15,433

21

671

645

617

593

568

544

520

497

474

451

428

406

22

-

-

-

-

-

-

-

-

-

-

-

-

23

5,835

5,672

5,523

5,381

5,264

5,132

5,003

4,872

4,739

4,628

4,519

4,408

24

552

525

499

473

450

431

414

398

381

366

349

332

25

-

-

-

-

-

-

-

-

-

-

-

-

26

2,008

1,941

1,865

1,790

1,715

1,646

1,578

1,512

1,446

1,382

1,310

1,241

27

1,711,797,760 1,734,673,570 1,757,474,908 1,779,726,753 1,800,392,264 1,820,588,825 1,840,361,793 1,859,838,765 1,879,204,928 1,898,185,434 1,916,894,686 1,935,521,474

28-200,119-209,639-219,761-229,270-235,612-245,425-256,481-269,037-278,151-286,892-297,843-296,327

29-33,323-33,211-32,971-33,709-32,899-33,188-35,038-36,749-38,101-39,604-40,462-41,37730-166,797-176,427-186,789-195,561-202,713-212,236-221,444-232,288-240,050-247,288-257,382-254,950

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

355,263357,392

360,043

362,979

366,657

369,942

372,740

375,156

378,503

381,509384,039

386,35132

50,961

52,97755,32657,81260,133

61,94963,79265,856

68,07570,232

72,04773,243

33

279,679

280,170

280,833

281,623

283,231284,948

286,135

286,739

288,099

289,192

290,096

291,39734

24,62324,24623,88423,54423,29323,045

22,81322,561

22,32922,08521,897

21,71135

6,278,524

6,285,366

6,292,426

6,300,000

6,305,114

6,311,248

6,317,953

6,324,624

6,331,120

6,336,484

6,341,358

6,346,200

36

0.66

0.44

1.47

1.26

-0.16

0.46

0.95

1.67

0.82

0.03

-0.09

-1.05

37

272,643,340 275,986,072 279,300,030 282,496,310 285,544,778 288,467,308 291,290,823 294,063,120 296,820,296 299,564,470 302,284,564 304,989,064

ANNEX Data

329

Data Annex: Wealth by Country

Venezuela

UNIT: millions of constant US$ of year 2000
1990

1991

1992

1993

1994

1995

1996

2,285,995

2,314,030

2,346,965

2,381,450

2,411,767

2,444,462

2,473,349

1

Inclusive Wealth Index, rows 2 + 3 + 4

2

Produced capital

314,531315,583

323,326

328,782

328,775

328,951

327,6593

Human capital

811,085

839,333

867,927

898,270929,890963,691

995,198

4

Natural capital, rows 5 + 8 + 11 + 12 + 16

1,160,380

1,159,113

1,155,712

1,154,397

1,153,103

1,151,820

1,150,492

5

Agricultural land, rows 6 + 7

191,961

191,934

189,739

189,704

189,765

189,853

189,958

6

Cropland

31,701

31,71829,52329,52329,59329,681

29,786

7

Pastureland

160,260

160,216

160,216

160,181

160,172

160,172

160,172

8

Forest resources, rows 9 + 10

61,686

61,34561,00460,66460,32359,98259,641

9

Timber

48,992

48,721

48,45048,18047,90947,63847,367

10

Non-timber forest resources

12,694

12,624

12,554

12,484

12,414

12,344

12,273

11

Fisheries

12

Fossil fuels, rows 13 + 14 + 15

895,522894,678

893,859

892,966

892,003

891,029889,98913

Oil

704,519704,499

704,478

704,457

704,435

704,411704,38514

Natural gas

181,824

181,033

180,273

179,461

178,588

177,701

176,745

15

Coal

9,180

9,146

9,107

9,047

8,980

8,917

8,860

16

Minerals, rows 17 + 18 +…+ 26

11,210

11,156

11,11011,064

11,011

10,957

10,904

17

Bauxite

696

692

690

685

677

668

660

18

Appendix

-

-

-

-

-

-

-

19

Gold

-

-

-

-

-

-

-

20

Iron

10,515

10,463

10,41910,37910,334

10,288

10,244

21

Lead

-

-

-

-

-

-

-

22

Nickel

-

-

-

-

-

-

-

23

Phosphate

-

-

-

-

-

-

-

24

Silver

-

-

-

-

-

-

-

25

Tin

-

-

-

-

-

-

-

26

Zinc

-

-

-

-

-

-

-

27

Health capital

40,519,332

41,511,144

42,485,864

43,447,231

44,402,602

45,356,546

46,303,369

28

IWI adjustments excluding TFP, rows 29 + 30

30,086

31,62533,27734,94936,727

38,63040,766

29

Carbon damages (annual change)-2,185-2,217-2,193-2,191-2,226-2,265-2,31030

Oil capital gains (annual change)

32,271

33,84235,47037,141

38,95340,89543,076Per Capita Values

1990

1991

1992

1993

1994

1995

1996

31

Per capita Inclusive Wealth Index

116,128

114,768

113,736

112,846

111,813110,936

109,93032

Per capita produced capital

15,97815,652

15,66915,57915,242

14,92914,56333

Per capita human capital

41,203

41,62842,06042,565

43,11143,73544,23334

Per capita natural capital

58,94757,48856,00754,70153,45952,273

51,13535

Per capita health capital

2,058,368

2,058,804

2,058,899

2,058,760

2,058,566

2,058,395

2,057,996

36

TFP (in percentage)

2.97

7.86

3.32

-2.34

-4.49

2.32

-1.97

37

Population

19,685,177

20,162,745

20,635,233

21,103,592

21,569,680

22,034,909

22,499,248

Data for TFP and population was obtained from Conference Board (2012), and United Nations Population Division (2011) respectively.

330

Inclusive Wealth ReportUNIT: millions of constant US$ of year 2000
1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

1

2,507,152

2,542,069

2,572,990

2,606,770

2,641,291

2,699,686

2,751,639

2,812,216

2,881,059

2,960,935

3,026,548

3,093,738

2

331,648

336,840

337,252

341,656

342,361

341,265

331,778

330,120

336,861

351,871375,717396,2013

1,026,470

1,057,782

1,089,829

1,122,793

1,158,235

1,220,119

1,282,936

1,346,215

1,409,677

1,476,011

1,519,055

1,567,039

4

1,149,034

1,147,447

1,145,909

1,142,320

1,140,695

1,138,302

1,136,926

1,135,881

1,134,521

1,133,053

1,131,776

1,130,499

5

189,994

190,046

189,967

187,877

187,904

187,043

187,043

187,482

187,482

187,482

187,482

187,482

629,822

29,87429,79529,81329,83928,97828,97829,41829,41829,41829,41829,4187

160,172

160,172

160,172

158,065

158,065

158,065

158,065

158,065

158,065

158,065

158,065

158,065859,30058,95958,61858,27757,93657,59557,25456,91356,572

56,23155,89055,549947,097

46,82646,55546,28546,01445,74345,47245,201

44,93044,66044,38944,11810

12,203

12,133

12,063

11,993

11,923

11,852

11,782

11,712

11,642

11,572

11,502

11,431

12

888,890887,639

886,563885,454884,193883,054882,071

880,986

880,025878,964

878,093877,22213

704,356

704,329704,304

704,276

704,249704,225704,204

704,181704,158

704,135

704,114704,09214

175,755

174,649

173,706

172,750

171,634

170,635

169,776

168,819

167,995

167,080

166,351

165,621

15

8,779

8,662

8,553

8,429

8,310

8,195

8,091

7,985

7,872

7,749

7,629

7,509

16

10,85010,802

10,761

10,711

10,662

10,61010,557

10,50010,442

10,376

10,310

10,245

17

652

643

636

629

621

612

602

592

582

572

562

553

18

-

-

-

-

-

-

-

-

-

-

-

-

19

-

-

-

-

-

-

-

-

-

-

-

-

20

10,19910,15910,125

10,083

10,042

9,998

9,955

9,908

9,860

9,804

9,748

9,692

21

-

-

-

-

-

-

-

-

-

-

-

-

22

-

-

-

-

-

-

-

-

-

-

-

-

23

-

-

-

-

-

-

-

-

-

-

-

-

24

-

-

-

-

-

-

-

-

-

-

-

-

25

-

-

-

-

-

-

-

-

-

-

-

-

26

-

-

-

-

-

-

-

-

-

-

-

-

27

47,249,928

48,195,525

49,138,680

50,079,442

51,001,632

51,920,979

52,838,203

53,754,606

54,670,550

55,587,690

56,502,565

57,414,082

28

42,88545,17047,62649,722

51,94454,38857,57860,542

63,35566,033

68,68071,64629-2,345-2,337-2,320-2,372-2,315-2,335-2,466-2,586-2,681-2,787-2,847-2,91230

45,22947,50849,94652,09554,25956,72360,043

63,12866,037

68,82071,52874,557

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

31

109,186

108,523

107,719

107,062

106,458

106,820

106,916

107,337

108,050

109,144

109,684

110,264

32

14,443

14,380

14,11914,032

13,79913,503

12,891

12,60012,633

12,97013,616

14,12133

44,70345,15745,626

46,114

46,68348,277

49,84951,382

52,86854,40855,05155,851

34

50,04048,98547,974

46,91645,97645,04044,17643,35442,54941,76641,01640,29235

2,057,725

2,057,498

2,057,198

2,056,794

2,055,631

2,054,378

2,053,054

2,051,703

2,050,341

2,049,035

2,047,682

2,046,302

36

4.40

-2.25

-8.34

1.49

0.90

-9.67

-8.14

16.57

8.30

2.62

2.12

0.62

37

22,962,221

23,424,338

23,886,213

24,348,304

24,810,691

25,273,336

25,736,393

26,199,994

26,664,122

27,128,721

27,593,427

28,057,485

11

ANNEX Data

331

Glossary of terms

Absolute decoupling: refers to a situation in

involved in the resource use or environmental
impact.

which there is an overall reduction in requiredmaterial inputs or pollution outputs, even while
the economy grows, whether through productivity improvements or through a decrease inpollution, or a combination of the two.

quantity of resources, measured by mass, being
used by an economy.

Adjusted net savings: a measure of net change

Ecosystem: a mesh of human and naturalin the value of a country’s capital stocks, including produced, human, and at least some stocksof natural capital.

resources interacting with one another at a
multitude of speeds and across often overlapping spatial scales.

Adjusted Inclusive Wealth Index (IWIadj): an

Ecosystem services: provisioning services suchindex that reflects when a country’s capital
assets are corrected for specific factors that
affect the size of its productive base. In thisreport we take into account the following threecomponents: carbon damages; oil capital gains
and; total factor productivity.

as food, water, timber, and genetic resources;
regulating services that affect climate, floods,
disease, wastes, and water quality; cultural services that provide recreational, aesthetic, andspiritual benefits; and supporting services suchas soil formation, pollination, and nutrient
cycling.

Dematerialization: an absolute decrease in the

Biodiversity: the variability among living organ-

isms from all sources and the ecological complexes of which they are part, including diversity within species, between species, and of
ecosystems.
Biosphere: a limited space made up of air, earth,and water and in which life is possible.

Environmental sustainability: the maintenanceof the minimum thresholds of natural capitalthat are required to sustain important environmental functions.
Externalities: the effects of activities on thewell-being of people who have not been parties
to the negotiations that led to those activities.

Carbon emissions: the release of carbon dioxide

gas into the atmosphere.
Comprehensive wealth: the shadow value ofFossil fuels: fuels such as natural gas, coal, andpetroleum that are formed in the earth fromplant or animal remains.

all the capital assets in a country. See inclusive
wealth.

Global genuine saving rate: the world’s grossDecoupling: a decline in the ratio of the amountused of a certain resource, or of the environmental impact, to the value generated or otherwise332

savings plus educational expenditures minus
produced capital depreciation and the values of natural resource depletion and carbon
emissions.

Gross domestic product: the market value ofNon-renewable resources: Natural resources

all final goods and services produced within an
economy.

that cannot be regenerated or grown at a sustainable rate to meet demand, including fossil
fuels, metals, and minerals.

Health capital: measured here essentially by theextensions (reductions) in the individual’s life
expectancy. Such changes are basically analyzed
by calculating the expected discounted years oflife remaining of a given population.

Oil capital gains: measure of a change in wealthdue to changes in price given a fixed quantityof oil.
Produced capital: see manufactured capital.

Human capital: the knowledge, skills, competencies, and attributes embodied in individuals
that facilitate the creation of personal, social,and economic well-being.
Human Development Index: a measure of devel-

opment designed by the United Nations thatcombines indicators of life expectancy, educational attainment, and income.

Relative decoupling: refers to a situation where

productivity/efficiency improvements havebeen realized but total inputs, or pollution outputs, continue to increase as economic output
increases.
Renewable resources: natural resources whose

supply can essentially never be exhausted, usually because they are continuously produced.

Inclusive investment: the measurement of thephysical changes in the assets of the economy,
while holding shadow prices constant.

Rental prices: market prices minus production
costs of resources.

Inclusive wealth: the shadow value of all the

Shadow price: the shadow price of a capital

capital assets in a country. In this report comprehensive wealth and inclusive wealth are usedinterchangeably.

asset is the contribution a marginal unit of theasset is forecast to make to human well-being.
Social capital: aspects of social structure that

Manufactured capital: includes roads, build-ings, ports, machinery, and equipment. In common parlance, including national accounts, thiscategory pretty much exhausts the list of capital
assets. When national income accountants andinternational organizations speak of investment, they usually mean the accumulation of
manufactured capital, also known as produced
capital.

facilitate action, in terms of the importanceof obligations and expectations, information
channels, and social norms to education.
Strong sustainability: perception that substi-

Millennium Ecosystem Assessment: a pioneer-tutability of manufactured for natural capital isseriously limited by such environmental characteristics as irreversibility, uncertainty, and theexistence of “critical” components of natural
capital, which make a unique contribution to
welfare.

ing study from 2005 of the services humanity
enjoys from ecosystems.

Sustainable development: development that

Natural capital: everything in nature (biotic
and abiotic) capable of providing human beings
with well-being, either directly or through the
production process.
Glossary of Terms

meets the needs of the present without compromising the ability of future generations tomeet their own needs.

333Sustainability gap: indicates the degree of con-sumption of natural capital, either in the past or
present, that is in excess of what is required forenvironmental sustainability.
Total factor productivity: the proportion of

output not explained by the amount of inputs
used in production, and captures the effect oftechnical progress, the efficiency with which
inputs are used, institutional conditions, andthe impact of environmental factors such as
climate.
Value of statistical life: an approach measuring

a society’s willingness to pay to avoid additional
occurrences of death.
Weak sustainability: the perception that welfare

is not normally dependent on a specific form ofcapital and can be maintained by substituting
manufactured for natural capital, though withexceptions.

334

Inclusive Wealth ReportContributing organizations

The IWR is a joint initiative of the United Nations University
International Human Dimensions Programme on Global
Environmental Change (UNU-IHDP) and the United Nations
Environment Programme (UNEP), in collaboration with the
UN-Water Decade Programme on Capacity Development (UNWDPC) and the Natural Capital Project.
UNU-IHDPThe International Human Dimensions Programme on Global
Environmental Change (IHDP) is an interdisciplinary science
program, working towards a better understanding of the interactions of humans with and within their natural environment. IHDP
advances interdisciplinary research and collaborates with thenatural and social sciences. It enhances the capacities of scienceand policy communities through a large network and furthersa shared understanding of the social causes and implications ofglobal change. The program facilitates dialogue between scienceand policy to ensure that research results feed into policy-planning and law-making processes, and offers education and training to future leaders in the field.
IHDP was founded by the International Council for Science(ICSU) and the International Social Science Council (ISSC) of
UNESCO in 1996. The IHDP Secretariat is hosted by the United
Nations University (UNU) in Bonn who joined as third sponsor
in 2007. IHDP’s research is guided by an international ScientificCommittee comprised of renowned scientists from various disciplinary and regional backgrounds. Visit www.ihdp.unu.edu formore information.
UNEP
The United Nations Environment Programme (UNEP) is the voice
for the environment in the UN system. Established in 1972, UNEP’s
mission is to provide leadership and encourage partnership incaring for the environment by inspiring, informing, and enabling
nations and peoples to improve their quality of life withoutcompromising that of future generations. UNEP is an advocate,educator, catalyst and facilitator promoting the wise use of theplanet’s natural assets for sustainable development. It works withmany partners, UN entities, international organizations, national335

governments, non-governmental organizations, business, industry, the media and civil society. UNEP’s work involves providing
support for: environmental assessment and reporting; legal andinstitutional strengthening and environmental policy development; sustainable use and management of natural resources;
integration of economic development and environmental protection; and promoting public participation in environmental
management. For more information, please visit: www.unep.org
UNW-DPCThe UN-Water Decade Programme on Capacity Development(UNW-DPC), established in 2007, is a joint program of UN-Water,
the interagency mechanism formed by the United Nations HighLevel Committee on Programmes in 2003. UNW-DPC’s mission isto enhance the coherence and effectiveness of the capacity development activities of UN-Water and seeks to strengthen the ability of the UN-Water members and partners to support Member
States to achieve the Millennium Development Goals (MDGs)
related to freshwater and sanitation. UNW-DPC is funded by theGerman Federal Government, located in Bonn, Germany, andhosted by the United Nations University.
Natural Capital Project
People all over the world rely on functioning ecosystems to live
healthy and productive lives. One effective strategy to protect ourenvironment and human well-being is to focus conservation on theprotection of ecosystem services. The Natural Capital Project works
to develop and provide practical ecosystem services concepts andtools, apply these tools in select areas around the world in order todemonstrate the impact of ecosystem service approaches in policy
and decision outcomes, and engage and educate influential leaders and practitioners to advance change in policy and practice. The
Natural Capital Project is an innovative partnership among Stanford
University, The Nature Conservancy, University of Minnesota, andWorld Wildlife Fund aimed at aligning economic forces with conservation. Its vision is a world in which people and institutions recognize natural systems as capital assets, appreciate the vital roles theyplay in supporting human well-being and incorporate the intrinsic
and economic values of natural capital into decision making.

336

Inclusive Wealth Report