Predictors of Successin a Greening World
December 2021

In partnership with

Predictors of Success in a Greening World

2This document has been prepared by:
Pia Andres, Grantham Research Institute andDepartment of Geography and Environment,
London School of Economics
Joris Bucker, Institute for New Economic Thinking,
School of Geography and the Environment, University of Oxford
Dr Matthew Ives, Institute for New Economic Thinking,Smith School of Enterprise and the Environment, University of Oxford
Dr Penny Mealy, Smith School of Enterprise and the Environment,
University of Oxford and and SoDa Labs, Monash Business School
Dr Kevin Tang, Oxford Sustainable Finance Group, Smith School of Enterpriseand the Environment, University of Oxford
Dr Michael Urban, Lombard Odier
Dr Matthew McCarten, Oxford Sustainable Finance Group,
Smith School of Enterprise and the Environment, University of Oxford
Sugandha Srivastav, Smith School of Enterprise and the Environment,
University of Oxford
Prof Cameron Hepburn, Smith School of Enterprise and the Environment,
University of Oxford

Important
information.
Please readinformation
the important information
enddocument.
of the document. Note all data used in thisPlease readthe importantat the endatofthethe
report are based on the most recent data computed based on the baci database (Gaulier, G. and Zignago, S., 2010. Baci:
Lombard
Odier·
December
2021
international trade database at the product-level (the 1994-2007 version). - we are using the most recent data ie 1995-2019,
HS92 nomenclature).

Predictors of Success in a Greening World

3

Abstract

The transition to a green economy is shifting the global competitiveness landscape. As
more countries, regions, and corporates commit to net zero targets, capabilities need toadapt to meet the changes in demand for products and skills. At the time of publication,
total government COVID-19 recovery spending exceeded USD$3.4 trillion, of which over
USD$0.5 trillion were allocated to green recovery spending, creating new stimulus and newopportunities for the green transition.
Who are the likely winners and losers from this transition? This report makes use of cuttingedge research to identify the emerging global trends in green competitiveness, examinesome countries in detail, and identify how governments might take advantage of these green
prosperity opportunities. Overall, we find that a number of countries are actively capitalisingon the growing green products market, particularly Germany, China, the US, Italy and Austria,
and that early leaders on key renewable generation technologies, such as Germany and China,
are most likely to gain from the global transition to net zero. We examine seven case studies
in more detail: China, the US, Brazil, Australia, the UAE, Switzerland, and Singapore. These
countries provide a broad range of green growth archetypes, from leading exporters to thosebeing left behind in the race to a greening world. The detailed findings contained in the report
are likely to be of value to governments, corporates, civil society, and investors.
We offer further insights into investment implications at the corporate level, specifically in
relation to the wind and solar industries. Overall, we find that Asian wind and solar firms
tend to be more domestically oriented, whereas Western firms are more dependent on global
trade. Thanks to a buoyant domestic market and strong export prospects, Chinese windand solar firms are likely to consolidate their leading position, while supply chains risks andtrade tensions could be key destabilisers for the United States and its wind and solar firms. In
Europe, we find interesting and promising results for Spain and Italy.

Predictors of Success in a Greening World

4

Contents
3

8

3

27

52

Abstract

Executive Summary
Background and key findings

9

Key Terms

21

Introduction

2. Emerging winners in a greening world
The green imperative

28

What is a green product?

29

Measuring green competitiveness

32

Which countries are currently well placed to succeedin the green economy?

38

Which countries have the greatest green productgrowth potential?

40

Which countries have the greatest green energy potential?

42

3. Greening the COVID-19 recovery
Why is a green covid recovery important?

54

A global comparison between countries' green indicesand green recovery spending

54

Clean vs traditional stimulus spending post-COVID19

56

Green recovery and green complexity

58

Spending on renewables

60

Big spending in the pipeline? The US infrastructure deal
and the EU green deal

62

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Predictors of Success in a Greening World

5

64

68

4. Country Case Studies

China case study
At a glance: policy ambition and green complexity

90

69

Trends in green competitiveness74

Trends in green energy

78

Policy and economic environment

82

Made in China 2025

84

Environmental credentials and policy ambition

85

Green strengths and opportunities

86

Summary89

United States of America case study
At a glance: policy ambition and green complexity

91

Trends in green competitiveness

94

Trends in green energy

99

Green strengths and opportunities

102

Policy and economic environment

104

Environmental credentials and policy ambition

106

The Build Back Better Plan and US green recovery spending

107

Summary109

Predictors of Success in a Greening World

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112

126

140

Brazil case study
At a glance: policy ambition and green complexity

113

Trends in green competitiveness

114

Trends in green energy

117

Policy and economic environment

119

Environmental credentials and policy ambition

122

Green strengths and opportunities

123

Summary

125

Australia case study
At a glance: policy ambition and green complexity

127

Trends in green competitiveness

130

Trends in green energy

133

Policy and economic environment

135

Environmental credentials and policy ambition

136

Green strengths and opportunities

137

Summary

139

United Arab Emirates case study
At a glance: policy ambition and green complexity

141

Trends in green competitiveness

144

Trends in green energy

148

Policy and economic environment

150

Operation 300bn

151

Environmental credentials and policy ambition

152

Summary155

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Predictors of Success in a Greening World

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156

172

186

212

216

226

Singapore case study
At a glance: policy ambition and green complexity

157

Trends in green competitiveness

160

Trends in green energy

164

Policy and economic environment

167

Environmental credentials and policy ambition

168

Green strengths and opportunities

169

Summary

171

Switzerland case study
At a glance: policy ambition and green complexity

173

Trends in green competitiveness

176

Trends in green energy

180

Policy and economic environment

182

Environmental credentials and policy ambition

183

Green strengths and opportunities

184

Summary

185

5. What could this mean for companies
and their investors?

6. Conclusion

7. Appendix

8. ReferencesPredictors of Success in a Greening World

8

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Predictors of Success in a Greening World

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Executive Summary
BackgroundAs environmental challenges such as climate change, biodiversity loss, air pollution, andplastic contamination become increasingly pressing, countries around the world are pledging
to transition to more sustainable energy and production systems. Capital allocation in the eraof climate change will play a key role in shaping such pathways, determining which industries
survive, thrive, and come to define the new industrial landscape. Equally, the risk and return
profiles of financial investments are increasingly shaped by this transition. This environmentof evolving comparative advantage poses a key question: which countries, regions andeconomic assets are poised to appreciate in value, and which are set to decline? The world is in
the midst of a new green industrial revolution, and industries, investors and governments that
actively invest in and foster high-growth, climate compatible industries have much to gain.
This report makes use of cutting-edge research to identify which countries are specialising in
high-growth green industries; which countries are laggards, and the extent to which countries
have used the COVID-19 pandemic to gain from a “green recovery”. Regions that manage
to capture market share and high value components of relevant supply chains will likely be
best placed to benefit economically, while those that continue to focus on and specialise in
declining dirty sectors risk being left with stranded assets.
To define a set of globally traded “green” products, we use a list of 295 products, based on
environmental goods lists compiled by the WTO, the OECD, and APEC. This report uses
the Green Complexity Index (GCI) to measure the number and complexity (a proxy fortechnological sophistication) of the green products that a country has exported competitively.
Research further suggests that industrial development is often path-dependent: countries andregions are significantly more likely to develop competitiveness in products and services that
require similar capabilities to those they already produce. Therefore, identifying productsthat are closely related to a country’s existing capabilities can provide insights into what those
future paths might look like.
The Green Complexity Potential (GCP) measures each country’s average relatedness tocomplex green products it does not yet export competitively and is a strong predictor of future
GCI. We build on these ranking analyses through a case study approach, diving deeper into thegreen competitiveness profiles of Australia, Brazil, the US, the UAE, China, Switzerland, andSingapore.

Predictors of Success in a Greening World10

Key findings
As the world wakes up to the possibilities of a greening global economy, we see greencompetitiveness spread unevenly around the world (Figure 1). Europe, North America,
China, Japan, and India are among the most highly ranked regions for green complexity;
Africa, Australia and parts of South America rank lowest. Germany currently holds top rank in
GCI (and has done so throughout the last two decades), followed by Italy, Austria, and the US.
The opportunities to benefit from the transition to the green economy are numerous
and varied across countries. While countries that have built up strong manufacturing
and technological capabilities, such as Germany, the US and China, are currently wellplaced to benefit from the green transition, many countries have competitive strengths
and endowments that could allow them to capitalize on the burgeoning demand for green
products, technologies, and energy over the coming years. The largest sub-categories of green
products by trade value are renewable energy, efficient consumption of energy technologies,
carbon capture and storage, and wastewater management and potable water treatment. Given
the considerable future growth likely in clean energy technologies, and the global abundanceof renewable energy potential, the countries most likely to gain from the clean energy
transition are those who manufacture and export equipment for renewable energy generationand integration - such as solar panels, wind turbines, electrolysers, and batteries.
Among the countries analysed in the case study section of this report, the US ranks
highest, but is running a very close race with China, which has seen a dramatic increase
in its GCI over the course of the period (Figure 2). Singapore and the UAE have increased
their GCI slightly. Brazil, Australia, and Switzerland have all lost green competitiveness overthe past 25 years.

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Lombard Odier · December 2021

Predictors of Success in a Greening World11` Fig. 1: World map with countries coloured according to their Green Complexity Index(GCI). Note the logarithmic colour scale.

5.0
80

2.5

60

1.0

40
0.0

20

-0.5

0
-20

-0.85

-40

-1

-60
-150

-100

-50

0

50

100

150

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

` Fig. 2: GCI through time for the countries assessed in this report as well as the top 3
ranked countries - Germany, Italy, and Austria.
6

Green complexity index

5
4
3
2
1
0
-1
1995-1999

China

1999-2003
China

2003-2007
USA

USA
BrazilSingapore
Germany
Singapore
GermanyItaly

2007-2011
Year
BrazilAustralia
Italy
Austria

2011-2015

2015-2019

Australia
UAE
UAE
Austria
Switzerland

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

Predictors of Success in a Greening World

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China

China's rise to prominence inmanufacturing is exceeded by its green
manufacturing export expansion. Thesedevelopments are thought to be driven by its
cheap labour force, but also by well targetedindustrial strategies to grow domesticenergy security and strengths in key clean

technology such as renewables and energy
storage. China is blessed with some of thehighest renewable energy potential of all
countries, but with a large population andincreasing GDP per capita it is unlikely to be amajor green energy exporter.

United States of America (US)The US has the world’s largest economy,
with vast natural wealth and a track record
as one of the world’s great innovators.
While the US currently supplies much of its
own substantial green product market, it has
seen a gradual decline in its green complexity
and green complexity potential in exports
over the study period, mirroring the decline
in its overall economic complexity. However,the country remains highly competitive inglobal comparison and has immense green
energy potential, more than enough tobecome a green energy exporter. President
Biden’s efforts to prioritise climate action andto pass legislation expanding electric public
transport and a clean electricity grid may
contribute to providing the country with thegreen post-COVID stimulus it needs.

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BrazilBrazil has strong renewable energy
endowments, but has experienced ageneral decline in green competitivenessand potential since the turn of the century.
This decline in Brazil’s green potential
means its probability of moving into new
more complex green products has fallen,suggesting that reversing this negative trend

in green competitiveness may become
increasingly difficult. On a more positivenote, Brazil has leveraged its local hydro,
wind, and solar resources to grow a local
wind turbine manufacturing industry andcompetitive strengths in the export ofhydraulic turbines.

Australia

Australia has seen a long-term decline
in its green competitiveness, but
has immense potential in its natural
renewable energy endowments andaccess to minerals critical to the morematerials-based green energy transition.
Although it is currently lagging in its capacity

to export green complex products, it could
leverage these natural advantages to carveout an advantage in the green economy going
forward.

Predictors of Success in a Greening World

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The United Arab Emirates (UAE)

While a major exporter of hydrocarbons,the UAE has actively pursued a diversified
industrial strategy that appears to haveresulted in an increase in its greencompetitiveness over the last decade. It
now has competitiveness in a selection ofgreen products, such as limestone materials
and manganese oxides, which are bothused in wastewater management; and parts

and accessories for surveying instruments,
which have important applications forenvironmental monitoring. The UAE does
not have an overabundance of renewablepotential given its sparsely populated landmass, but its proximity to the greening EU
economy, high solar irradiance, and low solar
costs make it a good candidate for capturingsome of the green energy export market.

Singapore

Singapore recently overtook Germany
to become ranked second to Japan in
the economic complexity of its exports,
but this has not translated into greencompetitiveness. Singapore is also lacking
in renewable resources, with only a small
land mass and relatively low wind speeds. It

does, however, have competitive strengths
in some complex green products, such as
chromatographs and microtomes, which aretechnologies commonly used for monitoring
air pollution or assessing environmental
influences.

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Predictors of Success in a Greening World

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Switzerland

Switzerland already utilises a large
amount of renewable energy and has asignificant role in green finance, but its
green export competitiveness has beenfalling in recent years, suggesting it is not
capturing the opportunities available ina growing green EU market. Switzerland
has enough renewable potential to transition
relatively easily to supplying all its own

energy needs from green resources, and toeven export locally. Switzerland also has
strengths in some complex green products,
such as railway parts and biogas equipment,
and the potential of making gains in thegrowing wind turbine industry.

Predictors of Success in a Greening World16

The global diversity shown by these examples is explained to some extent by the factthat green competitiveness appears to have a clear positive correlation with income level(Figure 3). Most countries with below-average GDP per capita also rank below average in GCI,
such as Brazil. Countries with high GCI tend to be higher income, such as the US or Singapore.
Nevertheless, there are low- and middle-income countries with above-average GCI, such as
China, and high-income countries with relatively low GCI, such as Australia and the UAE.
The green competitiveness landscape is thus incredibly diverse, but by no means static.
The investment and policy choices countries make in the short term will play a significant rolein shaping their capacities to be leaders or laggards in the green economy over the longer term.
The COVID-19 pandemic and associated recovery spending present a unique opportunity forcountries to invest in green R&D and low-carbon infrastructure, upgrade their technologicalcapabilities and support their workforce to take advantage of new green jobs and transitionout of dwindling, emissions-intensive industries. Our analysis shows that not all countries
are seizing this opportunity. While countries such as China, the US, Germany, Denmark,France, Spain, South Korea, and the UK currently rank highly in GCI and are also spending asignificant proportion of their recovery spending on green initiatives, other countries ranking
highly in GCI such as Italy, Czechia and Romania are spending relatively little on their green
recovery. While it remains to be seen whether green recovery spending translates into greater
green competitiveness in global markets, such differences in policy stances towards green
spending and investment could drive significant changes in countries' capacities to benefit
from the green transition going forward.
Political ambition and trade relationships will also shape future green competitiveness.
Brazil’s green competitiveness is declining, whilst a pivot away from fossil fuel and mineralexports for the UAE and Australia will require strong political leadership to unlock their green
potential. China, whilst a leader in green product manufacturing, must deal with the threatof international climate regulation if it does not make its energy mix cleaner with appropriate
carbon prices and other regulations. Partisan politics in the US have hindered progress andtensions with China are likely to continue to affect trade, although the Biden administration’scommitment to tackling climate change is suggestive of a friendlier climate for green
investments. Switzerland has a global role to play in green finance and may take advantage
of its proximity to the rapidly greening EU. Singapore has also yet to realise its potential
as a “green services hub”, leveraging its reputation as a well-functioning bureaucracy andinternational financial centre.
Although the pathways towards green competitiveness vary geographically andtechnologically, with early leaders showing clear advantages, there is ample potential
for interesting new dynamics to emerge in a post-pandemic world. Investment in green
technologies is not without its challenges: renewable energy projects in particular have highcapital costs and carry significant risk in many developing countries. Yet, these technologies
have also exhibited remarkable learning rates which has led to cost declines and rapid growth.

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Predictors of Success in a Greening World17` Fig. 3: GCI against income {LN(GDP per capita)} for all countries. LN=Natural
Logarithm.

All countries: LN(GDP per capita) vs Green Complexity Index

Green Complexity Index

2.0
1.5

USA

China

1.0
Switzerland

0.5
0.0

UAE

Brazil

-0.5
6

7

8

9

10

Singapore

Australia

11

LN(GDP per capita)
Country of interest :

True

False

Source: World bank GDP data 2019 in current US dollars sourced on 25 June 2021 from https://data.
worldbank.org/indicator/NY.GDP.MKTP.KD

It is likely that products which are complementary to renewable energy, such as batteries andelectrolysers for green hydrogen, will also grow substantially in the years to come. The fate of
the hydrocarbon sector is also clear. Most hydrocarbon generators, if not already uneconomic,
are set to become more expensive than low-carbon alternatives in the next 5-10 years.
To curate portfolios that will maximise value, investors may need to disentangle shortterm noise from long term trends. As this report shows, a global green race is underway, inwhich early movers will be rewarded and laggards risk losing global competitiveness. Suchfindings are likely to be of value to governments, corporates, civil society, and private sector
investors.
The urgency of increasing investment into renewable energy sources has been highlighted
by the recent European gas crisis. Although some commentators blame climate policies for
extreme price rises, they could also be seen as a result of too little investment in renewableenergy capacity, rather than too much. GCI and GCP rankings can help investors to identify
which countries are developing, and are likely to develop, their green industries. But what
information can we offer to those making investment decisions at the corporate level?

Predictors of Success in a Greening World

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Building on the our earlier findings, we use a case study approach to answer this question bycarrying out an in-depth analysis of the wind and solar industry—two sources of clean energythat are critical to the climate transition and are projected to continue their cost declines
by recent University of Oxford research, thereby offsetting inflationary pressures. We firstrecalculate CI and CP scores for each country based on a subset of green products related to
the wind and solar industry. Denmark, Finland, Estonia, and India show higher rankings in CI(Complexity Index) for wind and solar relative to their GCI rank overall. China and Italy rank
highly in both wind and solar CI and CP (Complexity Potential), without significant movementin the rankings. Spain, France, Turkey, and Poland also all rank highly in wind and solar relatedCP.
We build on these country-level findings by developing a sample of corporates across the windand solar value chain (Figure 4), consisting of pureplay wind and solar companies.
Most companies are concentrated in midstream activities, involving the manufacturing ofwind and solar products, and Chinese and US companies dominate the sample. Interestingly,
Asian wind and solar companies (Chinese, Japanese, Indian and Thai) generate most of theirrevenues domestically, whilst North American and European companies generate a higher
proportion abroad. This highlights the importance of considering multiple sources of datawhen analysing the green competitiveness landscape, as results based on trade data may notreflect opportunities in domestically oriented economies.

` Fig 4: Wind and solar value chain
Downstream

Generationand distribution

Wind turbine components
Blades, towers, nacelle,bearings, castings
Metals and minerals
CopperAluminium
Rare Earth

Upstream
InputsMidstream

Construction and installation

Midstream

Wind farm

Product manufacturing

Cabling,
engineering
design,construction,lease andinsurance,
commissioning,development,
finance,
O&M

Wind energy
generation

Solar Power
Plant
Solar energy
generation

Mixed windand solar
developers
Chemicals
Plastics
PolysiliconAncillary services
All non-module hardware(inverters, trackers, steel structures, cabling)
Monitoring and controls
PV manufacturing equipment

Mixed windandsolar generation
Solar Panel
Components
Wafer, cell, modulePredictors of Success in a Greening World

20

Analysing the wind and solar industries through both the country-level and corporate-level
lens offers several interesting implications for investors. In general, China is clearly playing an
increasingly central role in the wind and solar landscape. It is also worth noting that China’s
dominance in supplying raw materials, such as aluminium and rare earth metals, presents
significant supply chain risks for companies in the US and Europe, who rely on Chinese
imports to drive production. Interestingly, currently peripheral European countries in highvalue wind and solar products may play a key role in the energy transition. Italy, Spain, andTurkey, for example, have high CP ranks and are developing trailblazing domestic wind andsolar companies.

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Predictors of Success in a Greening World21

Key terms` Revealed Comparative Advantage (RCA)

A measure of the relative advantage of a certain country in exporting a certain product.
An RCA of a country-product pair of 0.5 means that the country exports half of what is
expected, given the global average exports of that product and the country’s total export
value. A country exports a product competitively if it has RCA > 1 for that product.

` Product Complexity Index (PCI)

A proxy for technological sophistication. Products which are more complex tend to open up
better diversification paths for countries which export them.

` Economic Complexity Index (ECI)

An index that ranks countries according to the similarity of their export baskets. Countries
with high ECI tend to specialize in products with high Product Complexity Index (PCI) - seeabove for definition.

` Green Complexity Index (GCI)

An index that captures the number and the complexity of green products a country iscurrently exporting competitively.

` Green Complexity Potential (GCP)The Green Complexity Potential (GCP) measures each country’s average proximity tocomplex green products it does not yet export competitively. It is a strong predictor of future
GCI.

` Green Energy Potential (GEP)The total renewable energy potential of a country in terms of access to hydro, biomass,solar and wind resources. The focus of this study is on country's technical potential, which
is a subset of a country’s geographical potential. The geographical potential is the energy
flux theoretically extractable in areas that are considered suitable and available for thisproduction; that is to say, in areas which are not excluded by other incompatible land cover/use and/or by constraints set on local characteristics such as elevation and minimum
average wind speed. The technical potential is the geographical potential after the losses
incurred during the conversion from the extractable primary energy flux to secondary
energy carriers or forms (electricity, fuel) are taken into account.

` Proximity between a country and a product

The average proximity between the product and all products the country has competitive
export capabilities in. This is a highly correlated with the probability with which a country
will develop new export capabilities in this product.

` Proximity between products

The probability that two products are both exported with comparative advantage by thesame country. This is a proxy for the relatedness or similarity of two products within the
product space.

Predictors of Success in a Greening World23

1. Introduction

Predictors of Success in a Greening World24

1. Introduction

How capital is allocated in the era of climate change will determine not only humanity’s
progress towards addressing the climate crisis, but also which industries and companies willsurvive, thrive, and come to define the new industrial landscape. The changing risks associatedwith continuing climate change are expected to affect the valuation of many assets: someassets will not be able to withstand physical climate risks; other assets may be subject to new
regulation as well as liabilities that change their economic calculus. Asset managers, banks,financiers, and advisors are faced with a new challenge of preserving portfolio value in an era
where the old rules of what constitutes a good investment need updating. In this environmentof evolving comparative advantage, the key question is: which countries, regions and economic
assets are poised to appreciate in value, and which are set to decline?
The transition to a net-zero emissions economy will undoubtedly shift the global
competitiveness landscape. Demand for zero-emissions technologies will increase further as
regulation, political will, and the impacts of climate change compel societies to demand andadopt cleaner modes of production and operation. Perhaps more importantly, the demand forcarbon-intensive products will fall as the costs of clean technologies continue their decline andthe social and economic license to operate in a polluting manner erodes.
The world is in the midst of a new green industrial revolution, driven by mega-trends that
include a groundswell of climate activism, which has compelled major economies all over
the world to adopt net-zero targets; learning curves which are placing renewable energy
amongst the cheapest sources of electricity in the world; automation, which is enhancing ourcapacity to dynamically optimise and integrate intermittent technologies; electrification,
which is transforming transport; and a geopolitical push to reduce dependence on imported
fossil fuels. These trends point in the direction of a smarter, greener, more efficient, andpotentially cheaper economy. Recent modelling efforts show that if solar photovoltaics, wind,batteries, and hydrogen electrolysers continue to follow their current exponentially increasing
deployment trends for another decade, we will achieve a near net-zero emissions energy system
within 25 years1. This extraordinary transformation assumes that the growth in deploymentof these technologies witnessed over the past two decades is maintained for only one more
decade. As such, there is much to gain by fostering high-growth, climate compatible industries2.

12

Way et al. 2021
Mealy and Teytelboym 2020

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Lombard Odier · December 2021

Predictors of Success in a Greening World

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China’s early and aggressive entry into the market for solar panels is just one example ofhow decisive policy coupled with pre-existing industrial capabilities can allow a country, in ashort space of time, to capture the lion’s share of a growing global market early in the productlifecycle. There are clear lessons to be learned from China’s strategic dominance in solar,
and in Europe, from the Danish firm Ørsted’s dramatic growth from deploying offshore windtechnologies. Can these experiences be re-created elsewhere, and how can investors get aclearer sense of the global green competitiveness landscape? Answering these questions is theobjective of this work.
This report makes use of cutting-edge research to identify which countries are specialising in
high-growth green industries; which countries are laggards; and the extent to which countries
have used the COVID-19 pandemic to gain from a “green recovery”. Our measures of greencompetitiveness are based on research by Mealy and Teytelboym (2020)3,4 to develop measuresof competitiveness in producing “green” products. They capture the number and complexityof green products that countries are currently exporting competitively, as well as the relative
ease with which they are likely to increase their green complexity in the future. “Complexity”
is a proxy for technological sophistication, and products which are more complex tend to be
associated with higher income and open up better diversification paths for countries that
produce and export them.
The report complements this global green competitiveness analysis with seven country casestudies for a range of major economies: China, the US, Brazil, Australia, Switzerland, theUnited Arab Emirates, and Singapore. These case studies combine a data-driven approachwith a qualitative analysis of the local policy environment, barriers to finance, natural resource
endowments, and economic structure. The results of this analysis carry important implications
for investment strategy, industrial policy, and government spending. While all countries havesome form of green comparative advantage or potential, some are much further ahead in thegreen race than others.
Following on from the case studies, we also offer insights into investment implications at thecorporate level, specifically in relation to the wind and solar industries. This discussion seeks tooverlay a company-level perspective onto the country-level green competitiveness results, byanalysing a sample of the largest wind and solar companies, the majority of whom are active incomplex midstream manufacturing activities.

3
4

Mealy and Teytelboym 2020.
Who in turn built on work by Cesar Hidalgo, B. Klinger, A.-L. Barabasi, and R. Hausmann. 2007. “The Product Space
Conditions the Development of Nations.” Science 317(5837) <https://doi.org/10.1126/science.1144581>.

Predictors of Sucess in a Greening World27

2. Emerging winners
in a greening world› The green imperative› What is a green product?
› Measuring greencompetitiveness› Analysis of recent and pasttrends in green volumes› Which countries are
currently well placed
to succeed in the green
economy?
› Which countries havethe greatest green energy
potential?

Predictors of Success in a Greening World28

2. Emerging winners in a greening world
The green imperative
As environmental challenges such as climate change, biodiversity losses, air pollution, andplastic contamination become increasingly pressing, countries around the world are pledging
to transition to more sustainable energy and production systems. Given the myriad ofenvironmental challenges, this requires changes along multiple dimensions, such as reducing
greenhouse gas emissions, adapting to a changing climate, improving extraction practices,
promoting a circular economy, and many more.
Achieving these goals requires, in many cases, the use of new technologies. One of the mostintuitive examples is the production of energy, which traditionally involves the burning offossil fuels. To produce energy in a “cleaner” way, we must turn to new technologies such as
solar panels and wind turbines for electricity; hydrogen and batteries for energy storage andmobility; geothermal energy and heat pumps for heating, new biodegradable and recyclable
materials, and so on. This implies that global demand for products associated with this majortransition will increase as more and more countries take steps towards net zero and “greening”
their economies. The transition to a more sustainable economy thus presents an enormous
opportunity for producers of “green” products. Companies and regions that manage to capture
market share and high value components of such supply chains will be best placed to benefit
economically1, while those that continue to focus and specialise in declining sectors risk being
left behind holding stranded assets2.
In this section of the report, we explore trends in global trade of “green” technologies within
the harmonised commodity description and coding system (an international nomenclature forthe classification of products). We also analyse a range of countries for their competitiveness in
producing and exporting green technologies: the United States, Switzerland, Australia, Brazil,
Singapore, China, and the United Arab Emirates. We do not identify declining sectors, nor are
we able to measure the sustainability of the upstream production processes of these products.
Rather, we focus on which countries have been successful in producing the technologies
required to transition to a greener economy, and which countries have the potential to capture
the most economic benefits from doing so in the future.

1
2

Cesar Hidalgo, B. Klinger, A.-L. Barabasi, and R. Hausmann. 2007. “The Product Space Conditions the Development of
Nations.” Science 317(5837) <https://doi.org/10.1126/science.1144581>.
J. F. Mercure et al., ‘Macroeconomic Impact of Stranded Fossil Fuel Assets’, Nature Climate Change, 2018 <https://doi.
org/10.1038/s41558-018-0182-1>.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

29

What is a green product?
A product might be considered green if the use of non-renewable energy and materials
and the creation of waste are minimised in its production. Alternatively, a product could be
regarded as green if it provides environmental benefits in its use. That is, the manufacture of
the product could involve non-renewables and waste, but the product itself is a required input
into an environmental use case, such as reducing pollution, or supplying renewable energy.
We deliberately employ the latter definition of “green products” for this study as it provides
a better understanding of those products that are likely to create the greatest export earnings
potential in a greening world. It should be noted that this does not exclude the possibility
that such products can also be used for an unrelated or even a polluting purpose. However,this “dual-use” problem is not considered a major concern for our purposes, which are tounderstand which countries are well-placed to meet increasing demand for such technologies
in the transition to a cleaner global economy.
To this end, we use a list of 295 products from the Harmonised System's 6-digit level toidentify “green” trade. This list is based on environmental goods lists compiled by the WTO,
the OECD, and APEC (see Mealy & Teytelboym3 for more detail). The products are further
assigned to 19 (not mutually exhaustive) “green categories”. Table 1 provides this list of 19
categories with an example product for each category4,5. Using this list of products, we compilea panel dataset of countries’ green exports and competitiveness between 1995 and 2019, as
detailed in the next section.

3
4
5

Penny Mealy and Alexander Teytelboym, ‘Economic Complexity and the Green Economy’, Research Policy, 2020, 103948<https://doi.org/10.1016/j.respol.2020.103948>.
Pia Andres and Penny Mealy, ‘Green Transition Navigator’, Retrieved from Www.Green-Transition-Navigator.Org, 2021.
To demonstrate how our green goods classification compares to other definitions of sustainability, we provide a mapping of our
19 categories to the six environmental goals set out in the “EU taxonomy for sustainable activities” in the Appendix.

Predictors of Success in a Greening World30` Table 1: 19 green product categories used in this analysis
Category

Example productEnvironmental benefit

Air Pollution Control

Condensers for steam or vapour power
units.

Used to cool gas streams to temperatures whichallow the removal of contaminants, e.g. volatileorganic compounds (VOC) like benzene.

Clean Up or
Remediation of Soiland Water

Centrifuges not elsewhere specified(Oil Skimmer).

Equipment used to remove oil floating on waterand is commonly used for oil spill remediations.

Cleaner or MoreResource EfficientTechnologies andProducts

Parts for domestic non-electric thermic
appliances (parts of solar stoves).

Parts are used in the maintenance and repairof solar stoves.

Efficient Consumptionof Energy Technologies
and Carbon Captureand Storage

Auxiliary plant for steam/vapour
generating boilers (multiple ex-outs
including (i) soot removers, (ii) superheaters and economisers with a stream
or other vapour production, (iii) auxiliary
plant for use with steam generating boilers
and super-heated water boilers).

Components of industrial air pollution control
plant (e.g., soot removers) help minimise therelease of pollutants into the atmosphere. Thisequipment is also used to support waste heatrecovery processes in waste treatment,or renewable energy resource recovery
applications.

Energy Efficiency

Air conditioners not elsewhere specified
with reverse cycle refrigeration (Energy
efficient air conditioning machines
which conform to the energy efficiency
standard and are so certified by theauthority in destination country. Also
have applications in geothermal heatpump systems).

Energy efficient air conditioners use lesselectricity and produce less emissions.
Geothermal pump systems transfer heatavailable in land and water masses to heat orcool buildings.

Environmental
Monitoring Analysis
and Assessment
Equipment

Monoculars, telescopes, etc.

Applications in environmental monitoring,
analysis, and assessment equipment.

Renewable bamboo-based products are
Environmentally
substitutions of wooden necessities. Since
Preferable Products
Parquet panels and tiles, of wood (bamboo
bamboo is characterized by a short growing
based on End-Use orbuilding products).
cycle, these environment-friendly products canDisposal Characteristics
save a great deal of water, soil and air resources.
Gas Flaring Emission
Reduction

Industrial furnace, oven, incinerator
non-electric not elsewhere specified(waste incinerators; heat or catalytic
incinerators).

Used to destroy solid and hazardous wastes.
Catalytic incinerators are designed for thedestruction of pollutants by heating polluted air
and oxidation of organic components.

Heat and Energy
Management

Supported catalysts, nickel based.

Heat/energy savings and management.

PleasePlease read
read thethe important
important information
information at
at thethe endend ofof thethe document.
document.
LombardLombard Odier
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2021

Predictors of Success in a Greening World

31

Category

Example productEnvironmental benefit

Management of Solidand Hazardous Waste
and Recycling Systems

Sheet/film not cellular/reinforced
polymers of ethylene (HDPE or flexible
membrane landfill liners and/or covers
for methane collection; plastic andpolyethylene geomembranes for soil
protection, water tightness, anti-erosionof soil…).

Membrane systems have multiple uses including(i) to line landfills to prevent leachate (water runoff) from contaminating groundwater resources,(ii) to cover landfills and prevent methanefrom escaping into atmosphere and (iii) for thereinforcement and protection of soil, including
under oil refineries, gas stations etc.

Binder or baler twine, of sisal or agave.

More biodegradable than synthetic fibre
alternatives and made from a renewable
resource. When used in fishing nets that include
use of turtle excluder devices, reduces turtle
mortality by 90-100 per cent.

Natural Risk
Management

Photogrammetrical surveying
instruments, appliances.

Photogrammetry is an aerial remote sensing
technique which forms the baseline of many
Geographic Information Systems (GIS) and Land
Information Systems (LIS), which are importantfor monitoring and managing natural risks suchas floods or earthquakes.

Noise and Vibration
Abatement

Air or gas compressors, hoods (industrial
hoods; aerators; blowers; and diffusers).

Air handling equipment. Transport or extractionof polluted air, corrosive gases, or dust.

Renewable Energy

Towers and lattice masts, iron, or steel(prefabricated modular type joined byshear connectors of towers for windturbine).

Used to elevate and support a wind turbine forthe generation of renewable energy.

Resources and Pollution
management

Air compressors mounted on wheeled
chassis for towing (air compressors usedin the transportation or extraction ofpolluted air, corrosive gases, or dust).

Air handling equipment. Transport or extractionof polluted air, corrosive gases, or dust.

Waste Management,
Recycling andRemediations

Mats, matting and screens, vegetableplaiting material (from coconut fibre/
coco-coir).

Used for soil erosion as a soil cover,biodegradable from waste.

Wastewater
Management andPotable Water
Treatment

Limestone materials for manufacture oflime or cement.

Used in chemical recovery systems for
wastewater management.

Water supply

Mineral and aerated waters not sweetened
Potable water supply and distribution.
or flavoured.

Natural Resource
Protection

OthersDistilling or rectifying plant (distilling
apparatus for desalination systems,
biogas refinement equipment and solvent
recycling plants).

Desalination plants remove salt from water andare important in conditions of water scarcity.
Biogas refinement equipment "upgrades" biogas
resulting from organic matter to give it the same
properties as natural gas. Allows the recovery
and reuse of solvents, (e.g., solvents used in theprinting, painting or dry-cleaning industries).

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.greentransition-navigator.org.

Predictors of Success in a Greening World

32

Measuring green competitivenessIndustrial development is often path-dependent6; this is supported by empirical evidence
showing that countries and regions are significantly more likely to develop competitivenessin products and services which require similar capabilities to those they already possess7.
There is further evidence to suggest that countries which specialise in more technologicallysophisticated products tend to enjoy greater income and growth8.
To capture these phenomena, we employ an approach first introduced by Hidalgo et al.9
and extended by Mealy and Teytelboym10 to measure competitiveness in exporting green
products. The proximity of a product to a country's current capabilities is strongly associatedwith the probability that this country will develop competitiveness in this product in the future(if it does not already export it competitively)11. We use the algorithm developed by Hidalgo
et al.12 to calculate the Product Complexity Index (PCI), which is a proxy for technologicalsophistication13. This report will also occasionally refer to the Economic Complexity Index(ECI), which measures the overall complexity of a country’s export basket.
The product space can be visualised as a network of products (Figure 1), some of which arecloser to each other and some of which are further apart. It shows that more technologicallysophisticated activities, such as producing machinery or chemicals, are in the denser “core”,
while agriculture or resource extraction are in the periphery. This difference in density implies
that specialising in sectors which are located in the core opens up new proximate industrial
diversification paths which are both more numerous and higher in complexity14.

6
7

8
9
10
11
12
13

14

M Grubb, Jean Charles Hourcade, and K Neuhoff, Planetary Economics: Energy, Climate Change and the Three Domains of
Sustainable Development, Planetary Economics (London, UK, 2014) <https://doi.org/10.4324/9781315857688>.
Cesar Hidalgo et al. ‘The Product Space Conditions the Development of Nations’, Science, 317.5837 (2007) <https://doi.
org/10.1126/science.1144581>; Frank Neffke, Martin Henning, and Ron Boschma, ‘How Do Regions Diversify over Time?
Industry Relatedness and the Development of New Growth Paths in Regions’, Economic Geography, 87.3 (2011) <https://doi.
org/10.1111/j.1944-8287.2011.01121.x>.
Cesar Hidalgo, B. Klinger, A.-L. Barabasi, and R. Hausmann. 2007. “The Product Space Conditions the Development of
Nations.” Science 317(5837) <https://doi.org/10.1126/science.1144581>; Ricardo Hausmann, Jason Hwang, and Dani Rodrik,‘What You Export Matters’, Journal of Economic Growth, 12.1 (2007) <https://doi.org/10.1007/s10887-006-9009-4>.
Cesar Hidalgo, B. Klinger, A.-L. Barabasi, and R. Hausmann. 2007. “The Product Space Conditions the Development of
Nations.” Science 317(5837) <https://doi.org/10.1126/science.1144581>.
Penny Mealy and Alexander Teytelboym, ‘Economic Complexity and the Green Economy’, Research Policy, 2020, 103948<https://doi.org/10.1016/j.respol.2020.103948>
Cesar Hidalgo, B. Klinger, A.-L. Barabasi, and R. Hausmann. 2007. “The Product Space Conditions the Development of
Nations.” Science 317(5837) <https://doi.org/10.1126/science.1144581>.
Ibid.
The Product Complexity Index (PCI) and the Economic Complexity Index (ECI) are dimensionality reduction algorithms
which are calculated conjointly. PCI ranks products according to the similarity of the countries which export them, while ECI
ranks countries according to the similarity of their export baskets. Countries which are higher in ECI tend to be higher-income,grow faster, and export products which are high in PCI. PCI is used as a proxy for technological sophistication. Intuitively,
products which are high in PCI are those located in the denser core of the product space (Figure 3: the product space ).
C. A. Hidalgo and R. Hausmann, ‘The Building Blocks of Economic Complexity’, Proceedings of the National Academy of
Sciences, 106.26 (2009) <https://doi.org/10.1073/pnas.0900943106>; Penny Mealy, J. Doyne Farmer, and Alexander
Teytelboym, ‘Interpreting Economic Complexity’, Science Advances, 5.1 (2019) <https://doi.org/10.1126/sciadv.aau1705>.
Cesar Hidalgo, B. Klinger, A.-L. Barabasi, and R. Hausmann. 2007. “The Product Space Conditions the Development of
Nations.” Science 317(5837) <https://doi.org/10.1126/science.1144581>.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World33` Fig 1: The product space

Source: Hidalgo, C.A., Klinger, B., Barabási, A.L. and Hausmann, R., 2007. The product space conditions
the development of nations. Science, 317(5837), pp.482-487. Reprint with permission.

Predictors of Success in a Greening World34

We apply the approach of Mealy and Teytelboym15 here and combine these measures ofcomplexity with the WTO, OECD, and APEC lists of traded green products to develop indicesof green complexity (at times referred to as “green competitiveness”). We use two key metrics
to assess countries' progress in capitalising on the growing green product market. The Green
Complexity Index (GCI) measures the number and complexity of green products that a country
has exported competitively. It constitutes a composite measure of green competitiveness. Dueto the aforementioned path dependency often observed in industrial development, identifying
products that are closely related to a country’s capabilities can provide some insight into what
those future paths might look like. The Green Complexity Potential (GCP) measures eachcountry’s average proximity to complex green products that it does not yet export competitively.
It has been shown to be a significant predictor of a country’s future GCI16. To prevent ouranalysis from being skewed by short-term fluctuations in trade, we use annual average values
over rolling 5-year periods (1995-1999, 1996-2000, etc). For more detail on the mathematicalrepresentation and interpretation of PCI and ECI, please refer to the Appendix and Mealy et al.
201917.

` Fig. 2: Change in share of green products in global trade

Share of category in total trade (%)

10
9.5
9
8.5
8
7.5
7
1995-1999

1999-2003

2003-2007

2007-2011Year

2011-2015

2015-2019

All green products

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

15
16
17

Mealy and Teytelboym, 2020.
Mealy and Teytelboym, 2020.
Penny Mealy, J. Doyne Farmer, and Alexander Teytelboym. 2019. “Interpreting Economic Complexity.” Science Advances 5(1).

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

35

Analysis of recent and past trends in green trade volumes
The share of green products in global trade has increased from roughly 8.2% in 1995-1999 to 9.4%
in 2015-2019 (Figure 2). This upwards trend recovered around 2010, following a slight dip after the
global financial crisis. Note that the decline following the global financial crisis in 2009 is relative
to total export volume and thus in addition to the absolute decline in export volume. Most striking
is the positive trend in the share of green trade over the last 4 years, showing a rate of increaseslightly above 2% since 2013-2017. If global green share continues to grow at this rate it could
make up roughly 17-18% of total trade by mid-century.
While this is a modest increase, we might expect green products to increase in significance evenmore rapidly as renewable technologies become even more competitive18, and as countries
around the world start to implement net-zero-CO2 emissions targets, COP26-revised ambitions,and the UN Sustainable Development Goals.
Among the countries analysed in this report, the importance of “green” in country-level
exports is uneven (Figure 4).

Annual change in share of total trade (%)` Fig. 3: Change in share of green products in global trade
2.0
1.5

1.0
0.5
0.0

-0.5
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year
All green products

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

18

Rupert Way and others, Empirically Grounded Technology Forecasts and the Energy Transition, 2021 <https://www.inet.
ox.ac.uk/publications/no-2021-01-estimating-the-costs-of-energy-transition-scenarios-using-probabilistic-forecastingmethods/>.

Predictors of Success in a Greening World36

The share of green products in US exports has remained around 11% throughout the period,
while China’s green share increased from 7% to about 12% between 1995 and 2019. Singapore
also shows an increasing trend, from 5% to 8%, as do the United Arab Emirates (albeit from amuch lower starting point). Conversely, Switzerland, Brazil, and Australia have seen a decline
in the share of their exports that are classified as “green”.
Within the set of products which are defined as “green”, the most significant sub-categories
are renewable energy (currently 3.53% of total trade and 37.28% of green trade); efficient` Fig 4: Green export share (%) over time for key countries assessed in this report

Green export share (%) over time

12
10
8

6
4
2
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019

Year
China
UAE

USA
Singapore

BrazilAustralia

Switzerland

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World37

consumption of energy technologies and carbon capture and storage (3.44% of total trade and36.28% of green trade); and wastewater management and potable water treatment (2.65% of
total trade and 27.92% of green trade) (Figure 5).
Renewable energy technologies (which include products such as wind turbines and solar
panels) have increased their share of global trade volumes by close to 1 percentage point andmay grow more rapidly in the future as the world transitions to clean energy and net zero19.

` Fig. 5: The share of green product categories in global trade from 1995-1999 to 20152019

4

Share of category in total trade (%)

3.5
3
2.5
2
1.5
1
0.5
0
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year
Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).
19 M.C. Ives et al, A New Perspective on Decarbonising the Global Energy System, Oxford University Smith School of Enterpriseand the Environment, 2021 <www.energychallenge.info>.

Predictors of Success in a Greening World

38

Which countries are currently well placed to succeed in the green economy?
Green competitiveness is currently spread unevenly around the world (Figure 6). Europe,
North America, China, Japan, and India rank highly among regions for green complexity;
Africa, Australia and parts of South America rank lowest. Germany currently holds top rank in
GCI20 (and has done so throughout the last two decades), followed by Italy, Austria, and the
US. Among the countries analysed in this report, the US ranks highest, but is currently in a tightrace with China, which has manufactured a dramatic increase in its GCI over the course of theperiod (Figure 7). Singapore and the UAE have increased their GCI slightly. Brazil, Australia,
and Switzerland have all unfortunately lost green competitiveness over the past 15 years.
The disparity between countries that is shown in Figure 6 is explained to some extent by thefact that green competitiveness appears to have a clear positive correlation with income level,
as shown in Figure 8.
Most countries with below-average GDP per capita also rank below average in GCI, such as
Brazil. Countries with high GCI tend to be higher-income, such as the US, Switzerland, orSingapore. Nevertheless, there are low- and middle-income countries with above-average
GCI, such as China, and high-income countries with relatively low GCI, such as Australia andthe UAE.

` Fig. 6: World map with countries coloured according to their Green Complexity Index(GCI). Note the logarithmic colour scale.

5.0
80

2.5

60

1.0

40
0.0

20

-0.5

0
-20

-0.85

-40

-1

-60
-150

-100

-50

0

50

100

150

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

20 The top 10 countries by GCI in most recent period are Germany, Italy, Austria, US, China, Japan, Denmark, Czech Republic,
United Kingdom, France, and Sweden.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

39` Fig. 7: GCI through time for the countries assessed in this report as well as the top 3
ranked countries - Germany, Italy, and Austria
6

Green complexity index

5
4
3
2
1
0
-1
1995-1999

China

1999-2003
ChinaUSA

2003-2007
USA Brazil

SingaporeSingapore
Germany Germany
Italy

2007-20112011-2015

2015-2019Year
BrazilAustralia

Australia
UAE

Italy
Austria

Austria
Switzerland

UAE

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

` Fig. 8: GCI against income {log(GDP per capita)} for all countries
All countries: LN(GDP per capita) vs Green Complexity Index

Green Complexity Index

2.0
1.5

USA

China

1.0
Switzerland

0.5
0.0

UAE

Brazil

-0.5
6

7

8

9

10

Singapore

Australia

11

LN(GDP per capita)
County of interest :

True

False

Source: World bank GDP data 2019 in current US dollars sourced on 25 June 2021 from https://data.
worldbank.org/indicator/NY.GDP.MKTP.KD

Predictors of Success in a Greening World

40

Which countries have the greatest green product growth potential?
The Green Complexity Potential (GCP) provides a measure of a country’s proximity to green
products that it is not yet competitive in (and those products’ PCI). It is a strong predictor of
future GCI for that country. Figure 9 shows a world map of GCP by country21. The difference
between high and low scoring countries is even larger than for the GCI (Figure 7, on previouspage) and shows very different patterns. Asia’s exports are getting greener, as are southern
Europe’s, while large parts of Europe and North America are ranked somewhat lower by GCP
than they are by GCI. Africa and South America have diverging regions. China currently ranks
first in the world on GCP, followed by Italy and Spain.
Among the countries considered in this report, GCP has been increasing steadily for China,
while staying stagnant for the US and Singapore (Figure 10). The UAE have seen a slight uptick
in GCP, predicting a potential further increase in green competitiveness. As with their GCI
rankings, GCP has declined for Brazil, Australia, and Switzerland22.
In the absence of policy action to counter-act these trends, all three countries may experience
further declines in GCI in the future.

21 The top 10 countries by GCP are China, Italy, Spain, France, Germany, Turkey, Poland, India, Austria, and the Netherlands.
22 Switzerland is combined with Liechtenstein in the Green Transition Navigator used for GCI, GCP and its RCA as both countries
report trade data conjointly to UN Comtrade..

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World41

� Fig. 9: World map with countries coloured according to their Green Complexity
Potential (GCP). Note the logarithmic colour scale.

5.0
80

2.5

60

1.0

40
0.0

20

-0.5

0
-20

-0.85

-40

-1

-60
-150

-100

-50

0

50

100

150

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

` Fig. 10: Green Complexity Potential through time for the countries examined in thisreport, as well as Italy and Spain who along with China make up the top three ranked
countries; and Germany, which holds top rank in GCI.
4.5
4

Green complexity potential

3.5
3
2.5
2
1.5
1
0.5
0
-0.5
-1
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019

Year
China

USA

BrazilChina Italy
Singapore

USA Spain

Brazil SwitzerlandAustralia

Australia

UAE

UAE

Singapore

Italy

Spain

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

Predictors of Success in a Greening World

42

Which countries have the greatest green
energy potential?
With the recent pledges from China, India, Australia, and the new US
administration, about 135 countries have declared a Net Zero or Carbon Neutrality
goal, covering 88% of global greenhouse gas emissions, 90% of the world’s GDP and
85% of the world’s population23. As the energy sector is considered one of the easiest
to decarbonise, and the largest source of emissions (nearly three quarters of global
greenhouse gas emissions)24, it is the sector where the greatest progress towards
these goals has already taken place. Europe, the UK, and the US have all seen a
gradual decline in emissions since 2010 despite continuing growth in GDP25. Much ofthis progress has come from fuel switching from coal to gas, but renewables such as
solar and wind have seen impressive growth in recent years26.
With growing confidence in continued demand for green energy products has comean impressive increase in new investment in projects to meet this demand. The Asian
Renewable Energy Hub (AREH) along the north coast of Western Australia (WA) iscurrently in its planning stage. With a capacity of 26GW it will, if completed, rank as
the world's largest energy development project, topping even China's 22 GW Three
Gorges Dam development. The AREH project plans to export most of its energy
production to Indonesia and Singapore through high voltage submarine power cables
and as green ammonia (hydrogen-based fuel).
Similar large scale green energy projects are also in planning in the northernhemisphere, with a $5 billion-dollar green hydrogen production facility planned for
NEOM, Saudi Arabia28. When operational, it will be powered by 4 GW of solar, windand storage and plans to produce roughly 650 tons per day of green hydrogen forexport to Europe and globally, most likely to meet the growing demands for cleantransport fuels in busses and heavy goods vehicles.
Given recent persistent declines in the cost of renewables29, countries are looking togreen energy production not only for export opportunities but as a means of reducing
their own dependence on imports of fossil fuels. Most recently, India’s Prime
Minister Narendra Modi announced a National Hydrogen Mission for the country.

23 Net Zero Tracker, Accessed 14/11/2021 https://www.zerotracker.net/ .
24 Hannah Ritchie and Max Roser (2020) - "CO2 and Greenhouse Gas Emissions". Published online at
OurWorldInData.org. Retrieved from: 'https://ourworldindata.org/co2-and-other-greenhouse-gasemissions'.
25 William F. Lamb and others, ‘A Review of Trends and Drivers of Greenhouse Gas Emissions by Sector from 1990
to 2018’, Environmental Research Letters, 2021 <https://doi.org/10.1088/1748-9326/abee4e>.
26 Lamb and others.
27 https://asianrehub.com/.
28 https://www.ammoniaenergy.org/articles/saudi-arabia-to-export-renewable-energy-using-green-ammonia/
29 J.D. Farmer and François Lafond, ‘How Predictable Is Technological Progress?’, Research Policy, 45.3 (2016),
647–65 <https://doi.org/10.1016/j.respol.2015.11.001>.

PleasePlease read
read thethe important
important information
information at
at thethe endend ofof thethe document.
document.
LombardLombard Odier
Odier ·· December
December 2021
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Predictors of Success in a Greening World

43

India now has some of the lowest solar costs “in history”30 which will be leveraged,
along with the country’s large land mass, to produce low-cost green hydrogen andammonia, and hopefully to build an Indian electrolyser manufacturing capability31.
The proposal involves making it mandatory for Indian fertiliser plants and oil
refineries to purchase green hydrogen, thereby creating domestic demand andreducing the nation’s dependence on fossil fuels.
Renewable energy increasingly appears to be playing a central role in decarbonising
the energy sector. However, mitigating emissions through renewables will requirea) the electrification of a greater part of the energy sector, and b) the use of energy
storage in the form of batteries and green fuels, such as green ammonia ande-methanol. Producing clean energy will require both sufficient clean energy sources(e.g., solar radiation or wind), and the equipment to harness it for human use.
Within our list of 295 “green” products, 62 relate to renewable energy – these include
products such as “towers and lattice masts, iron or steel” which are used to “elevateand support a wind turbine for the generation of renewable energy”; “hydraulicturbines, water wheels” with different power levels and parts thereof, used forhydropower generation; photosensitive/photovoltaic/LED semiconductor devices –i.e., solar photovoltaic cells; and others32. Our dataset therefore allows us to identify
which countries are well-placed to competitively export this equipment to meet thesegrowing markets.
As more and more countries transition to net zero, they will need increasing amountsof such equipment from domestic production or imports. Countries which produce
clean energy or relevant equipment will therefore likely enjoy increase global
demand for their exports. Our analysis shows that renewable energy has gained themost in terms of share of global trade values in recent decades (Figure 5).
Renewable energy is a key consideration in any strategy to carve out a competitive
advantage in a net zero economy. Countries must consider which parts of the value
chain are feasible for them to capture given existing comparative advantage; butalso, which are high in value added. Given input-output linkages as one driver ofagglomeration economics, a comparative advantage in producing energy from arenewable source may be a “way in” to higher value-added parts of the supply chain(such as manufacturing technologically sophisticated equipment). This is particularly
relevant in cases where transport costs matter.

30 IEA, World Energy Outlook 2020, 2020, MML.
32 Electrolysers are the main technology used to generate hydrogen from water.
32 Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transition-navigator.org.

Predictors of Success in a Greening World

44

With renewable energy exports growing from $133bn in 1995-1999 to $604bn in 2015-2019(Figure 11) and demand for green fuels also growing, the question arises as to which countries
are most likely to benefit from the decarbonisation of global energy.

` Fig. 11: Global trade volume for green products (USD billions)

700000000

Global trade volume (USD bn)
Global trade volume (USD bn)

600
600
600000000
500
500
500000000
400000000
400
400
300
300000000
300
200
200000000
200
100
100000000
100
00.2
0 1995-1999

1999-2003

2003-2007

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

2007-20112011-2015

2015-2019

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World45

To answer this question, we must first look at the renewable energy potential available aroundthe world. The potential availability of renewable energy sources varies over time and location.
This variation is not only caused by climatic or resource characteristics, but also by topography,
land cover/land use, labour costs, access to finance, and political support. The geographicaland technical potential33 for energy from solar and wind from renewables does not appear to bea limiting factor globally, with estimates of global solar resources ranging from between 1,500
and 50,000 EJ/yr (onshore and offshore wind resources ranging from between 1,000 and 3,000
thousand EJ/year; bioenergy between 34 and 1,270 EJ/yr; and hydropower between 30 and 52
EJ/yr )34. Utilising some of these energy sources will exclude others in certain locations35, but the
combined total global technical potential is at least between 3 to 50 times greater than current
global primary energy demand, which lies at around 600 EJ36.
With such enormous global potential, the question then moves on to which countries might
have a competitive advantage in terms of their access to these renewable resources. China,
Brazil, and the US have the world’s largest hydro and biomass resources, both of which
provide valuable dispatchable energy generation. However, these resources are dwarfed by
the combined solar and wind potential of the planet, and they do not appear to have the samepotential for declining costs shown by solar and wind37.

33 The geographical potential is the energy flux theoretically extractable in areas that are considered suitable and available forthis production i.e. in areas which are not excluded by other incompatible land cover/use and/or by constraints set on local
characteristics such as elevation and minimum average wind speed; the technical potential is the geographical potential after
the losses of the conversion from the extractable primary energy flux to secondary energy carriers or forms (electricity, fuel) aretaken into account Bert J M de Vries, Detlef P van Vuuren, and Monique M Hoogwijk, ‘Renewable Energy Sources: Their Global
Potential for the First-Half of the 21st Century at a Global Level: An Integrated Approach’, Energy Policy, 35.4 (2007), 2590–2610<https://doi.org/10.1016/J.ENPOL.2006.09.002>.
34 Bert J M de Vries, Detlef P van Vuuren, and Monique M Hoogwijk, ‘Renewable Energy Sources: Their Global Potential for theFirst-Half of the 21st Century at a Global Level: An Integrated Approach’, Energy Policy, 35.4 (2007), 2590–2610 <https://doi.
org/https://doi.org/10.1016/j.enpol.2006.09.002>; Patrick Moriarty and Damon Honnery, ‘What Is the Global Potential for
Renewable Energy?’, Renewable and Sustainable Energy Reviews, 16.1 (2012), 244–52 <https://doi.org/https://doi.
org/10.1016/j.rser.2011.07.151>; Elise Dupont, Rembrandt Koppelaar, and Hervé Jeanmart, ‘Global Available Wind Energy
with Physical and Energy Return on Investment Constraints’, Applied Energy, 209.July 2017 (2018), 322–38 <https://doi.
org/10.1016/j.apenergy.2017.09.085>; Elise Dupont, Rembrandt Koppelaar, and Hervé Jeanmart, ‘Global Available Solar
Energy under Physical and Energy Return on Investment Constraints’, Applied Energy, 257.October 2019 (2020), 113968<https://doi.org/10.1016/j.apenergy.2019.113968>; Hans-Holger Rogner and others, ‘Energy Resources and Potentials’,
Global Energy Assessment (GEA), 2012, 425–512 <https://doi.org/10.1017/cbo9780511793677.013>; Kelly Eurek and others, ‘An
Improved Global Wind Resource Estimate for Integrated Assessment Models’, Energy Economics, 64 (2017), 552–67 <https://doi.org/10.1016/j.eneco.2016.11.015>; Stephanie Searle and Chris Malins, ‘A Reassessment of Global Bioenergy Potential in
2050’, GCB Bioenergy, 2015, 328–36 <https://doi.org/10.1111/gcbb.12141>.
35 de Vries, van Vuuren, and Hoogwijk, ‘Renewable Energy Sources: Their Global Potential for the First-Half of the 21st Century ata Global Level: An Integrated Approach’.
36 IEA, MML.
37 Way and others.

Predictors of Success in a Greening World46

The distribution of solar and wind resources also appears to be quite variable on a global scale,with solar irradiance highest in the tropical regions (Figure 12), and wind potential, particularly
offshore which has the greater energy potential, highest in the temperate regions (Figure 13).
Given this apparent abundance of solar and wind resources, how much each will contribute to
the energy mix in any given country at any point in time will depend on the economic viabilityof these resources in comparison to alternative sources of energy – their economic potential38.
Global estimates of the economic potential of renewables have concluded that most countries
will have access to sufficient cost-effective solar and wind resources to meet their domestic
electricity demands when the local levelized costs for these technologies go below 10c/kWh41.

` Fig 12: A map of estimated solar photovoltaic (PV) power generation potential
expressed as kWh/kWp (kWp=kilowatt potential)39.

60°N

60°N

45°N

45°N

30°N

30°N

15°N

15°N

0°

0°

15°S

15°S

30°S

30°S

45°S

45°S

45°s

Long-term average of photovolaic power potential (PVOUT)
Daily totals: 2.0 2.4 2.8 3.2 3.6 4.0 4.4 4.8 5.2 5.6 6.0

6.4

Yearly totals: 730 876 1022 1168 1314 1461 1607 1753 1899 2045 2191 2337

kWh/kWp

Source: https://globalsolaratlas.info40

38 The economic potential is the technical potential up to an estimated production cost of the secondary energy form, which iscompetitive with a specified, locally relevant alternative. A flexible way to represent the economic potential is in the form of theenergy production potential as function of the production cost, the so-called long-run supply cost curve - de Vries, van Vuuren,and Hoogwijk, ‘Renewable Energy Sources: Their Global Potential for the First-Half of the 21st Century at a Global Level: An
Integrated Approach’.
39 Fig 12 represents the long-term average of yearly/daily potential electricity production from a 1 kW-peak grid-connected solar
photovoltaic (PV) power plant.
40 Global Solar Atlas 2.0, a free, web-based application is developed and operated by the company Solargis s.r.o. on behalf of theWorld Bank Group, utilizing Solargis data, with funding provided by the Energy Sector Management Assistance Program(ESMAP). For additional information: https://globalsolaratlas.info

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Lombard Odier · December 2021

Predictors of Success in a Greening World

47

With about 75% of the world’s population living in regions where the levelised cost of solar PV
is now already at or below 12c/kWh42, and given solar costs have declined consistently at around
10% per year since 198043, it appears that most countries will have access to this domestic
economic potential well before 2030.
This consistent and rapid decline in solar costs potentially explains the exponential increase insolar deployment, (Figure 14)44 which is likely to overtake hydropower as the primary source ofgreen energy before the end of this decade.

` Fig. 13: A map of global wind power density potential expressed as W/m2 at 100m
height.

Source: https://globalwindatlas.info/45

41 de Vries, van Vuuren, and Hoogwijk, ‘Renewable Energy Sources: Their Global Potential for the First-Half of the 21st Century ata Global Level: An Integrated Approach’.
42 World Bank, Solar Photovoltaic Power Potential by Country, 2020 <https://documents.worldbank.org/en/publication/
documents-reports/documentdetail/466331592817725242/global-photovoltaic-power-potential-by-country> [accessed 30
November 2020].
43 Farmer and Lafond 2016.
44 See Way et al. (2021) Figure 1 for a clearer graphical representation of the exponential increase in deployment of solar and windover the last two decades.
45 Global Wind Atlas 3.0, a free, web-based application developed, owned and operated by the Technical University of Denmark(DTU). The Global Wind Atlas 3.0 is released in partnership with the World Bank Group, utilizing data provided by Vortex,
using funding provided by the Energy Sector Management Assistance Program (ESMAP). For additional information: https://globalwindatlas.info

Predictors of Success in a Greening World48

The most compelling implication of this global potential for renewables and the steady decline
in their costs is that the countries most likely to gain from the clean energy transition are thosewhich manufacture and export equipment for renewable energy generation and integration- such as solar panels, wind turbines, electrolysers, and batteries46. Based on current export
data, (Figure 15) this would include China, Germany, the United States, Japan, South Korea,
and Italy.

` Fig. 14: Global renewable energy generation by source
3 500

Renewable energy capacity (GW)

3 000
2 500
2 000
1 500
1 000
500
0

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

Year
Total renewable energy
Hydropower
TotalWind
renewable energy
Hydropower
MarineSolar
Solar
Liquid biofuels
Bioenergy
Liquid biofuels
BiogasMarineWind
Bioenergy
Biogas

Source: IRENA (2021), Renewable Capacity Statistics 2021; & IRENA (2020), Renewable Energy
Statistics 2020, The International Renewable Energy Agency, Abu Dhabi.

46 Note that these are not the only technologies that make up the renewable energy product category, but they are the most
predominant.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

49

Each of these countries (along with Denmark) were early adopters of renewable technologies– suggesting that early efforts to decarbonise can translate into green export competitivenessand growth.
In the short term, there will also be opportunities for countries that possess a naturaladvantage, such as those countries which already have access to sufficient solar and wind at
costs below 10c/kWh (e.g., India, Australia, China, Chile, and Brazil), to not only meet theirown clean energy goals but to potentially export low-cost green energy at a premium to regions
facing either long-term or short-term limits (e.g., Europe, Japan, and Singapore).

` Fig. 15: Largest exporters of Renewable Energy products from 2015-2019

France, Monaco
3.0%

Republic of Korea
7.0%

China
22.0%

Germany
12.0%

USA
10.0%

Japan
9.0%

Italy
3.0%

Other Asia
3.0%

Canada
2.0%

Spain
2.0%

Thailand
2.0%

Belgium
2.0%

Singapore
2.0%

Uk
2.0%

Mexico3.0%

Netherlands
2.0%

Malaysia
2.0%

Denmark
1.0%

Hungary
1.0%

Sweden1.0%

Viet Nam
1.0%

Czechia
1.0%

Austria
1.0%

Romania Philipines
1.0%
1.0%

Turkey
1.0%

India
1.0%

Slovakia
1.0%

Romania
1.0%

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

Predictors of Success in a Greening World

50

Table 2 provides estimates of the current economic potential for each of the major renewableenergy sources for a range of countries, including the seven countries included as case studies
in this report. The potentials for each renewable resource are combined47 in an estimate of
total economic generation potential per capita, which is then compared with each country’s
current average energy usage per capita, to provide an indication of the green energy export
potential for each country. The countries in Table 2 are separated by a black line above which
are those countries who possess much higher per capita green energy generation potential
than the current highest average annual energy usage per capita (89 MWh/yr/cap). This
demarcation separates our seven case study countries between Australia, Brazil, Switzerland,
and the United States, which have an overabundance, and the UAE, China, and Singapore,
which are either close to or below this global maximum average annual energy usage. Such
differences in green energy potential will be discussed in more detail for each of these casestudy countries in Section 4, with a focus on solar potential, given its enormous energy
potential and expected continuing declines in costs48.
Having access to sufficient economic potential for renewable energy does not necessarilymean a country will capitalise on this potential. There will be social and political, as well as
technical, barriers to the widespread adoption of renewable technologies in many countries,that might slow or limit the uptake of renewables. However, the list of new major green energy
export investments on the horizon suggests that examining differences between countries’
green energy potential might provide insights as to which countries are most likely to seize theopportunity presented by renewables.

47

48

Utilising some energy sources will exclude others in certain locations (de Vries et al., 2007a). See Appendix for details on how
these generation sources are combined.
Farmer and Lafond; Way and others.

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Lombard Odier · December 2021

Predictors of Success in a Greening World51` Table 2 - Estimates of current technical potential of renewable resources per personcompared with current average annual per capita usage for a range of countries,
including the seven countries used as case studies in this report.
Generation potential (EJ/yr)
Onshorewind)

Offshore
wind

Solar
PV

Hydro

Bioenergy

Est.
Total

Population(millions)Averageannual energy
usage percapita(MWh/yr/cap)

Total
generation
potential
per capita(MWh/yr/cap)

Australia

230

89

8

<1

8

319.0

25

64

3,408

Norway

5

41

7

1

1

48.0

5

68

2,508

Canada

38

121

104

2

3

225.0

37

89

1,687

Russia

107

123

47

5

10

170.1

144

57

327

US

130

25

174

1

11

200.6

329

79

169

Brazil

80

25

16

3

14

108.0

209

17

141

Japan

4

23

40

<1

<1

62.5

127

40

137

Switzerland

<1

-

4

<1

<1

4

9

34

130

U.A.E.

<1

<1

3

–

<1

3.2

10

89

94

South
Africa

28

12

7

<1

1

18.8

58

31

91

China

117

35

218

6

16

376

1,402

26

74

Singapore

<1

<1

1

0

<1

1

6

60

53

2,005

1,134

1,008

30

100

3,169

7,566

58

116

Global                          Source: See Appendix for Data

The horizontal line above the UAE is close to the current maximum average annual energy
usage per capita. All countries above this line have more green energy potential than would
be required for them to consume energy at this current maximum average.

Predictors of Sucess in a Greening World

53

3. Greening
the COVID-19
recovery› Why is a green COVID-19
recovery important?
› A comparison between
countries' green indices andgreen recovery spending› Clean vs traditional stimulus
spending post-COVID-19› Green recovery and green
complexity› Spending on renewables› Big spending in the pipeline?
The US infrastructure deal
and the EU green dealPredictors of Success in a Greening World

54

3. Greening the COVID-19 recovery
Why is a green COVID-19 recovery important?
The research by Mealy and Teytelboym used extensively in this study has provided evidence
that countries which rank highly in GCI also tend to have lower emissions, higher green
patenting rates, and higher environmental policy stringency – even after controlling for per
capita GDP1. Moreover, they observe a “green get greener effect”, meaning that it seems to beeasier for countries with advanced green production capabilities to diversify into new green
export opportunities2.
Their evidence further suggests that countries that provided more targeted green stimulus
packages after the Global Financial Crisis of 2008 tended to experience greater GCI gains in thefollowing years3. Building on this pioneering work, we examine in this section the proportion of
COVID-19 recovery spending different countries dedicate to the green economy, with the ideathat given the enormous sums in current recovery spending plans, these programmes may wellinfluence the green competitiveness of countries over the next decade.

A global comparison between green indices and green recovery spending
COVID-19 represents a global health crisis that has directly impacted the lives of millions
around the world. Its health impacts and the subsequent attempts by governments to limit
the deleterious public health consequences has led to an economic emergency, affecting the
livelihoods of many. Indeed, many governments have had to cope with the trade-off between
lockdowns to protect their population and health services, and opening up economic activities
to allow people to earn a living4,5. In the short term, predominantly higher-income countries
countries have been able to provide liquidity for both businesses and individuals to minimise theeconomic harm of lockdowns and other measures to curtail the pandemic. Recovery spending,on the other hand, is aimed at stimulating longer term and structural re-growth6.
The Oxford University Economic Recovery Project7, housed within the Smith School ofEnterprise and the Environment at the University of Oxford, investigates the extent to whichthese fiscal spending plans have prioritised greener alternatives over maintaining current
practices.

1
2
3
4
5
6
7

Mealy and Teytelboym (2020)
Mealy and Teytelboym (2020)
Mealy and Teytelboym (2020)
Anton Pichler and others, ‘In and out of the UK Lockdown: Propagation of Supply and Demand Shocks in a Dynamic InputOutput Model’, 2020.
e.g., The Economist, ‘How to Assess the Costs and Benefits of Lockdowns’, The Economist, July 2021 <https://www.economist.
com/finance-and-economics/2021/07/01/how-to-assess-the-costs-and-benefits-of-lockdowns>.
Cameron Hepburn and others, ‘Will COVID-19 Fiscal Recovery Packages Accelerate or Retard Progress on Climate Change?’,
Oxford Review of Economic Policy, 36.Supplement_1 (2020), S359–81 <https://doi.org/10.1093/oxrep/graa015>.
Brian O’Callaghan and others, Global Recovery Observatory, Oxford University Economic Recovery Project, 2020 <https://recovery.smithschool.ox.ac.uk/tracking/> [accessed 25 June 2021].

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

55

Austria, for example, provided liquidity support to its airlines in return for targets on greenhousegas reductions8. Other countries have prioritised renewable energy projects over more
traditional infrastructure spending, such as South Korea’s recovery investment in smart grid andrenewables technologies9. The Recovery Project has gathered data on the 50 largest economies
as well as an additional 39 emerging market and developing economies10, put together in the
Global Recovery Observatory11. For the following analysis, we use data that was available in
September 2021 which includes spending plans up to June 2021. Green recovery spending plansannounced afterwards or those still being formed are not taken into consideration. The data
set is periodically updated and refined, and assessments of what policies are deemed green
and count towards recovery spending is done transparently but can be open to interpretation insome cases.

8

Philipp Grüll and Sarah Lawton, ‘The Green Compromise in the Austrian Airlines Bailout’, Euractiv.Com, 10 June 2020
<https://www.euractiv.com/section/aviation/news/the-green-compromise-in-the-austrian-airines-bailout/>.
9 Sarwat Chowdhury, ‘South Korea’s Green New Deal in the Year of Transition’, UNDP Blog, 2021 <https://www.undp.org/
blogs/south-koreas-green-new-deal-year-transition> [accessed 10 August 2021].
10 Oxford University Economic Recovery Project and others, Global Recovery Observatory: Draft Methodology Document, 2021
<https://recovery.smithschool.ox.ac.uk/wp-content/uploads/2021/03/20210201-Global-Recovery-Observatory-DraftMethodology-Document-.pdf> [accessed 10 August 2021].
11 Available online via https://recovery.smithschool.ox.ac.uk/tracking/Predictors of Success in a Greening World56

The large discrepancy between countries in terms of the amounts reserved to spend on recovery
and the proportion that is green is shown in Figure 16. While some countries have plans to spend
up to 10% of GDP on COVID-19 recovery, such as Spain, South Korea, and Australia, others
barely reach 0.1%, such as Russia, Singapore, or the UAE. Brazil, despite reserving less than
0.1% of GDP for recovery spending, has pledged over 50% of that amount for green causes.
Jamaica, Turkey, and Mauritius are the only three countries that aim to spend their entire
recovery budget on green projects, with Bangladesh close behind at 87% green of total recovery
spending. The Nordic countries of Norway, Denmark, and Finland spend above 50% on green
projects, with total recovery spending at around 2-3% of GDP, while Germany reaches 45%
green projects. Switzerland reaches over 50% as well, although on a much smaller total spending
plan. China has pledged 12% of its recovery spending to green projects. Until the passing of
the recent Infrastructure Bill, the US had pledged less than 10% to green projects. Besides
Brazil, all countries we discuss in-depth in this report have used less than 15% of their recovery
spending for building a green economy. Both the UAE and Singapore have no green spendingplans in their limited recovery spending portfolio. This means that these countries have not (yet)revealed plans to leverage any COVID-19 recovery spending for green investment, but it does
not necessarily mean they did not invest in a greener future. For example, Singapore released
its Green Plan 2030, which marks a much needed step to green their economy independently of
COVID-1912,13,14.

Clean vs traditional stimulus spending post-COVID-19
It has been suggested that a sustainable recovery could be sufficient to address climatechange15, given the large sums of money involved16. However, of the money that is earmarked
for long term recovery, only 21% is deemed green17. The IEA released a report based on thesame dataset, amended with data of their own. Their model estimates that current spendingplans only meet 35% of the emission reductions necessary to put countries on a 2050 net-zeroemissions pathway. Advanced economies meet about 60%, whereas emerging and developing
countries meet only 20%18.

12 Robert Carnell and Prakash Sakpal, Singapore Green Plan 2030 – Important Steps towards a Sustainable Future, 2021 <https://think.ing.com/articles/singapore-green-plan-2030-important-steps-towards-a-sustainable-future/#a3>.
13 For more on Singapore, see the case study in Section 4. Carnell and Sakpal, 2021.
14 For more on Singapore, see the case study in Section 4.
15 Hepburn et al. 2020.
16 The IEA IEA, Sustainable Recovery Tracker report used the same dataset and estimated that current spending plans only meet
35% of emission reductions necessary to put countries on a 2050 net-zero emissions pathway. Advanced economies meet about
60%, whereas emerging and developing countries meet only 20%. Source IEA, Sustainable Recovery Tracker (Paris, France,2021) <//www.iea.org/reports/sustainable-recovery-tracker>.
17 https://recovery.smithschool.ox.ac.uk/tracking/ , as of May 25th, 2021
18 IEA, Sustainable Recovery Tracker, 2021.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World57` Fig 16: Covid recovery spending by various countries around the world.

Size of countries denotes absolute recovery spending in US dollars, x axis denotes therecovery spending as percentage of GDP (note the log scale) and the y-axis the percentageof recovery spending that is green. Countries that have no green recovery spending plans
have their labels rotated vertically to aid readability.
100

JAM

MUS

TUR

429bn
100bn
5bn

BGD

Absolute covid
recovery spending
in US$

DNK
CHE

BRA
COL

NOR

PAN

DEU

SWE

40

FRA
POL

ISR
AUT

KEN

SEN

20

10-2

10-1

BEL

INDPAKHTI TTO SUR

IRL
IRQ

HND
EGY KAZ
SAU
BLZ
BHS
ZAF
PRT
KGZ
KNA
NGA
LCA
ARG
MEX
BOL VCTITADOMSLV GHA
CZE
ARE
ECU
THA
MYS

RUS

SGP

0

BRA
IDN

USA

CHL

100

KDR

CHN

JPN

ESP

GBR
AUS

PER
DMA

60

FIN CANPHL
MAR

Recovery green percentage

80

101

Recovery percentage of GDP

Source: Note - figure uses slightly different definitions and therefore deviates slightly from figure on
Global Recovery Observer https://recovery.smithschool.ox.ac.uk/tracking/Predictors of Success in a Greening World

58

However, some countries do show sustainable leadership, including northern European
countries, Spain, and South Korea19. Directing COVID-19 recovery funding toward green
spending as opposed to neutral or fossil-fuel projects has multiple economic implications
on top of decreasing greenhouse gases (GHGs). It provides more future-proof stable jobs20,
minimising fossil fuel stranded asset risk, and directing the economy toward a green growth
path21. However, emerging market economies appear to suffer from relatively high interest
rates and debt constraints22, limiting their green recovery potential. In this report, we havestressed the path-dependency of development and diversification. Investment in longlasting fossil-fuel based infrastructure can mean locking an economy into fossil fuels for theforeseeable future, increasing existing inertia of fossil-fuel based energy systems and the riskof asset stranding23.
Green recovery spending, on the other hand, if significant enough, can accelerate a country’s
progress and allow its economy to thrive in a world that makes progresses towards net zerotargets.

Green recovery and green complexity
The GCI and GCP of all countries are plotted against their green share of recovery
in Figure 17. While their spending is small in absolute terms, Brazil and Switzerland are theonly two case study countries that plan to spend a significant share of recovery investment on
green projects. Other relatively low GCI/GCP countries (Australia, Singapore, and the UAE)
barely spend anything on green recovery, while the US and China have green recovery plans ofabout 9-12% of total recovery spending.

19 Brian J. O’Callaghan and Em Murdock, Are We Building Back Better? Evidence from 2020 and Pathways to Inclusive Green
Recovery Spending - Summary for Policymakers, 1386 <https://wedocs.unep.org/bitstream/handle/20.500.11822/35282/
AWBBB_ES.pdf> [accessed 10 August 2021].
20 Robert Pollin and others, Green Growth A U.S. Program for Controlling Climate Change and Expanding Job Opportunities,
2014; Heidi Garrett-Peltier, ‘Green versus Brown: Comparing the Employment Impacts of Energy Efficiency, Renewable
Energy, and Fossil Fuels Using an Input-Output Model’, Economic Modelling, 61 (2017), 439–47 <https://doi.org/10.1016/j.
econmod.2016.11.012>.
21 Hepburn et al. 2020.
22 O’Callaghan and Murdock; Ulrich Volz and others, Debt Relief for a Green and Inclusive Recovery Debt Relief for a Green andInclusive Recovery A Proposal (Berlin, 2020).
23 Galina Alova, ‘A Global Analysis of the Progress and Failure of Electric Utilities to Adapt Their Portfolios of Power-Generation
Assets to the Energy Transition’, Nature Energy, 5.11 (2020), 920–27 <https://doi.org/10.1038/s41560-020-00686-5>;
Alexander Pfeiffer and others, ‘Committed Emissions from Existing and Planned Power Plants and Asset Stranding Required
to Meet the Paris Agreement’, Environmental Research Letters, 13.5 (2018) <https://doi.org/10.1088/1748-9326/aabc5f>;
Conor Hickey and others, ‘Can European Electric Utilities Manage Asset Impairments Arising From Net Zero Carbon
Targets?’, SSRN Electronic Journal, 2020 <https://doi.org/10.2139/SSRN.3531724>.
24 In Figure 17 the dark green countries are the case study countries. The crosses (x) indicate Singapore and the UAE, who both
spend zero on renewables, as well as the countries with these 3-digit codes: 'CRI', 'CUB', 'CZE', 'DMA', 'DOM', 'ECU', 'SLV','ATG', 'GHA', 'GRD', 'ARG', 'GTM', 'GUY', 'HTI', 'HND', 'IDN', 'IRN', 'IRQ', 'KAZ', 'KGZ', 'BHS', 'MYS', 'MEX', 'MNG','MAR', 'BRB', 'NIC', 'BEL', 'NGA', 'PRY', 'PER', 'PHL', 'PRT', 'ROU', 'RUS', 'RWA', 'KNA', 'LCA', 'VCT', 'BOL', 'SAU', 'SGP','VNM', 'ZAF', 'SUR', 'THA', 'TTO', 'ARE', 'EGY', 'BLZ', 'BFA', 'URY', 'VEN'.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World59` Fig. 1724: GCI and GCP vs Percentage green spending of recovery. Size of countries
indicates percentage of green spending of GDP
100

Jamaica

Mauritius

Turkey

3.7%
1.2%
0.05%

Bangladesh

Percentage
green
recovery of GDP

Recovery green percentage

80

60

BrazilFinland

CanadaNorwaySwitzerland, Liechtenstein

PanamaColombia40

0

SwedenRepublicof Korea

Israel20

Denmark

PolandAustria

Kenya
Senegal
Chile
Pakistan
IrelandUnited Kingdom

Spain

UAE Netherlands
xx x
x x
x
Singapore
1
0

China
USA

Japan

India

xxxxxxxxxxxx xxxx xx xx xx x

Australia-1Germany

France, Monaco

Italy
2

5

4

3

GCI
100

TurkeyMauritius

Jamaica
Bangladesh

Recovery green percentage

80

Switzerland,
Liechtenstein60
NorwayDenmark

Finland
CanadaBrazilPanamaColombia
40

France, Monaco

PolandSenegal20

Republic of Korea

Kenya

Australia

IrelandSingaporexxxxxxxxxx xxxxx xxxxxxxxxx
xx xx xx x xxxxx x x xxxxxxxxxx
x

UAE

-1

0

Spain

Austria

United Kingdom

Chile

0

Germany

Swedenx

Pakistanxx x x

x

China
USA

Japan
x x

1

India

x

2

x

Italy

x Netherlands

3

GCP

Source: Global Recovery Observer https://recovery.smithschool.ox.ac.uk/tracking

4Predictors of Success in a Greening World

60

Turkey, although it scores relatively low on GCI, has high GCP and has intentions to spend
a large portion of its recovery spending on green recovery, potentially enabling it to reach its
green complexity potential faster than others. Many EU countries seem to be spending a good
portion on green recovery, but some barely spend any, such as Italy, the Netherlands, Portugal,
and Czechia. Many low-GCI/GCP countries across the world do not intend to spend any of
their COVID-19 recovery on green projects.
Green recovery spending as percentage of GDP is presented in Figure 1825. Brazil (green
recovery spending equals 0.015% of GDP) announced some green spending but its recovery
spending is relatively small as a percentage of GDP. Australia (0.16%), with its modest green
spending but large recovery spending is placed in the centre, well above the US (0.05%) and not
far from China (0.36%). All of these countries, however, stay far below the top spenders Spain(3.7%) and South Korea (3.2%).
We identify 4 categories of countries26 as shown in Figure 18. A number of EU countries plus
Canada, South Korea, China, and Turkey are shown as "leading green spenders", owing totheir high GCI score and above average green recovery spending. Other European countries,
including Switzerland, as well as the US, Israel, India, Malaysia, Thailand, Mexico, andSingapore, also have a high GCI score, but spend less than average on their green recovery.
We group these countries in a category called "falling behind". A third category, gaining
momentum, includes Jamaica, as well as Senegal and Panama, all featuring a low GCI score
but more than average spending on green recovery. While this approach does have obvious
methodological drawbacks, this might indicate that these countries are better placed to
improve on green metrics and may jump ahead compared to their peer countries. The final
category, "missed opportunities", is made up of countries that have a low GCI score, and spend
below average or even nothing on green recovery. This group of countries includes Australia,
Brazil, the UAE, and many developing and emerging economies in our sample. Note that thiscategorisation may change as countries announce new recovery green spending packages, andwe should be cautious to draw conclusions too early.

Spending on renewables
Renewable energy projects in our recovery spending dataset come in various forms, such as
subsidies for rooftop solar installations, or loan guarantees for large-scale wind farms. Figure
4 visualises how much countries intend to spend on renewable energy projects. Emergent
economies Bangladesh, Colombia, and Brazil are reserving a large proportion of their recovery
spending on renewables, as well as Norway and Canada.

25 Note that it uses a logarithmic scale to distinguish between the different countries.
26 Note that only spending agreed by national governments is classified by the Oxford Economic Recovery Project. Any spendingplans that are still being made or negotiated on May 25th (e.g. the Biden administration’s American Jobs Plan) have not been
considered here yet.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World61` Fig. 1827: GCI and GCP vs Percentage green be spending of GDP. Note the log scale on
the y-axis.

Spain

Gaining
momentum

United Kingdom
France, Monaco

Green recovery percentage of GDP

CanadaSenegal10-1Denmark

Republic of Korea

100

Jamaica
PanamaBangladesh
Australia
Chile
IrelandFinland

Norway,Svalbard
and Jan
Mayen

Germany

PolandJapan
China

TurkeySwitzerland

SwedenIsraelAustria

Mauritius
PakistanUSA

Colombia Kenya

India

Missedopportunities

-1

Italy

Netherlands

Brazil0

Leadinggreen spendersPHL
IDN AREZAE
SGP BEL

CUB

CRI

ECU

DOM EGY VNM

MYS THA

0

1

MEX
PRT

ROU

2

Falling behind

CZE

3

4

5

GCI

Source: Global Recovery Observer https://recovery.smithschool.ox.ac.uk/tracking.

27 In Figure 18, the UAE (ARE), Singapore (SGP) and selected other countries are added underneath as their recovery spendingplans include zero green projects. The full ist of country codes of countries with zero green recovery spending: 'CRI', 'CUB','CZE', 'DMA', 'DOM', 'ECU', 'SLV', 'ATG', 'GHA', 'GRD', 'ARG', 'GTM', 'GUY', 'HTI', 'HND', 'IDN', 'IRN', 'IRQ', 'KAZ', 'KGZ','BHS', 'MYS', 'MEX', 'MNG', 'MAR', 'BRB', 'NIC', 'BEL', 'NGA', 'PRY', 'PER', 'PHL', 'PRT', 'ROU', 'RUS', 'RWA', 'KNA', 'LCA','VCT', 'BOL', 'SAU', 'SGP', 'VNM', 'ZAF', 'SUR', 'THA', 'TTO', 'ARE', 'EGY', 'BLZ', 'BFA', 'URY', 'VEN'

Predictors of Success in a Greening World

62

Interestingly, countries that spend heavily on renewables tend to have lower GCI and GCP
scores. Looking at a different measure, among the countries in our database, Norway, South
Korea, and Canada spend the largest fraction - all above 0.75% of their GDP - on renewableenergy projects. Given the declines anticipated in renewable energy costs this may well help
them transition their economies faster towards net zero.

Big spending in the pipeline? The US infrastructure deal and the EU green deal
The US government on November 5th passed a large infrastructure and investment plan forthe coming 8 years, which would include green infrastructure investment into renewableenergy projects, as well as more conventional maintenance of highways and bridges28. While
the original $2 trillion American Jobs Plan has been scaled back, the US congress approved
the bipartisan infrastructure bill of about $550 billion (the headline of $1 trillion USD includes
renewal of ongoing infrastructure spending). About 38% of the new spending (roughly $214
billion or 1.0% of GDP) can be classified as green. If this were included in the COVID-19
recovery spending, it would bring the US into the middle realm of the Leading green spenders29.
Another bill that is currently being negotiated, the Build Back Better Act, currently has aheadline figure of $550 billion spending on clean energy investments30.
The recently announced plans for the EU green deal will enter the country-level negotiation
phase this year and was therefore not taken into consideration for this report31. The EU green
deal will be financed by one third of the combined EU’s 1 trillion-euro seven-year budget(2021-2028) and 750 billion NextGenerationEU Recovery Plan (2021-2023), highlighting theneed for a green COVID-19 recovery. This would raise the full EU’s green spending by about
4% as a percentage of GDP in Figure 18. Taking only the NextGenerationEU funding into
account would mean a rise of 1.7%.

28 White House, American Jobs Plan (Washington, DC, 2021) <www.whitehouse.gov/briefing-room/statementsreleases/2021/03/31/fact-sheet-the-american-jobs-plan/>.
29 See the US case study in Section 4, for more information
30 House Committe on the Budget, ‘The Build Back Better Act: Transformative Investments in America’s Families & Economy’,2021 <https://budget.house.gov/publications/report/build-back-better-act-transformative-investments-america-s-familieseconomy> [accessed 8 November 2021].
31 European Commission, European Green Deal (Brussels, 2021) <https://ec.europa.eu/info/strategy/priorities-2019-2024/
european-green-deal_en>.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World63

� Fig 1932: GCI vs Percentage renewables spending of total recovery spending, and GCP
vs Percentage renewables spending of GDP. Country size indicates absolute value of
renewables spending plans.
70

Bangladesh

Recovery renewables percentage

60

Brazil50

Norway, Svalbard and Jan Mayen

Colombia
40

Canada30
PolandSwitzerland, Liechtenstein

20

Finland10

Germany

Denmark

France, Monaco

Republic of
Korea

China

Spain
Australia
SwedenNetherlands
Chile
Ireland xx x Singaporexxxxx
xxxxxxxxxxxxxxx xxxxxx xxxxxxxxx xxxxx xxx x
x x
xx
x
0
United Arab Emirates
UK
-1
0
1
2

x

x

USA
x

3

5

4

GCI
Norway, Svalbard and Jan Mayen
Republic of
Korea

Renewables percentage of GDP

0.8

CanadaPolandNorway, Svalbard and Jan Mayen

0.6

Denmark
0.4
France, Monaco
Finland
0.2

Australia
Bangladesh

0.0

Spain

Germany

Colombia
Chile IrelandBrazil Singapore
xxx
xxxxxx x xxxxx xxx x xxxx
xxxxxxxx xx xx x
United Arab Emirates
0
1

xxxxxxxxxxxxxxx xxxxxx xxxxxx xxxxxxxxxxxxxxxxxxx-1

Sweden
x

x x

China

UK

Switzerland, Liechtenstein

Netherlands
x

2

x

xx xx

USA

x

x

3

4

GCP

Source: Global Recovery Observer https://recovery.smithschool.ox.ac.uk/tracking
32 In Figure 19 the size of the countries represents the absolute spending on renewables as part of covid recovery. In dark blue thecase study countries. The crosses (x) indicate Singapore and the UAE, who both spend zero on renewables, as well as thecountries with these 3-digit codes: 'CRI', 'CUB', 'CZE', 'DMA', 'DOM', 'ECU', 'SLV', 'ATG', 'GHA', 'GRD', 'ARG', 'GTM', 'GUY','HTI', 'HND', 'IDN', 'IRN', 'IRQ', 'KAZ', 'KGZ', 'BHS', 'MYS', 'MEX', 'MNG', 'MAR', 'BRB', 'NIC', 'BEL', 'NGA', 'PRY', 'PER','PHL', 'PRT', 'ROU', 'RUS', 'RWA', 'KNA', 'LCA', 'VCT', 'BOL', 'SAU', 'SGP', 'VNM', 'ZAF', 'SUR', 'THA', 'TTO', 'ARE', 'EGY','BLZ', 'BFA', 'URY', 'VEN'.

Predictors of Sucess in a Greening World

65

Country Case
Studies› China› United States of America› Brazil› Australia› United Arab Emirates› Singapore› Switzerland

Predictors of Success in a Greening World66

4. Country Case Studies

We are now presenting a range of countries in more detail. The seven countries are chosen for
their interest and importance to the finance community, their economic strength, their regional
importance, and as examples of contrast in terms of green complexity, green energy potential
and green recovery spending (Table 3).

Table 3: The contrasting elements of the seven case study countries
Country

GCI

GDP/Capita

Green Recovery
Archetypes

GEP

RegionChina

Higher

Lower

Leading spenderMed

East Asia

USA

HigherHigherFalling behindHighNorth America

Brazil

Lower

Lower

Missed opportunity

High

South America

Australia

Lower

HigherMissed opportunity

High

Oceania

UAE

HigherHigherFalling behindMedMiddle East

Singapore

HigherHigherFalling behind

Low

South-East Asia

Switzerland

HigherHigherFalling behindHigh

EuropeSource: GCI from Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved fromwww.green-transition-navigator.org.

With their diverse backgrounds, these countries represent a variety of archetypes, challenges,
and opportunities.
Two of our case study countries, Brazil and Australia, have lower than average GCI scores; therest are above average. The US, Brazil, Switzerland, and Australia all have enough potential ingreen energy resources to produce more than double their own energy needs. China, the UAE,
and Singapore do not have enough to meet their current needs. Brazil and China are part of the
BRICS countries of major emerging economies. They are economic and regional powerhouses,
but their GDP per capita is still significantly lower than that of developed economies.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World67

In contrast, Switzerland, Singapore, and the UAE are among of the highest-income countries on
the planet. However, only China is planning to spend more than average on a green recovery,
the others less, although that may be in part due to separately announced plans (Singapore), or
by policy that is still being developed (the US). Together, these countries represent about 43% of
global green export value, with the majority coming from China (19%) and the US (10%).
Each country faces unique challenges and opportunities. China is a leading green manufacturer
and wants to transform into a top green innovator as well. The US still has a higher GCI thanChina, but has dropped slightly in the rankings and is trying to find a strategy to remain at thetop, with ambitious plans being negotiated. Brazil has enormous green energy potential but
has been dropping in GCI rank and has recently neglected some of its most important natural
resources. Australia and the UAE are both facing a challenge to move away from their fossil fueldominated exports and carbon intensive industries. Singapore has limited natural resourceson its own and is already looking to import green energy from abroad. Switzerland has almost
100% carbon free electricity but missed out on expanding its green product manufacturingbase in its COVID-19 recovery plans. We begin with China.

Predictors of Success in a Greening World

68

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

69

China case study
Policy ambition and green complexity
Over the past decade, China has become theworld’s largest manufacturing economy. Not
surprisingly, China is also the world’s largest
emitter of greenhouse gases. However,its global dominance in manufacturing ismirrored, and even surpassed, by its clean
technology production capabilities.
China currently ranks 42nd in economic
complexity and 5th in green complexity,
reflecting this strategic focus on clean energy
products. Its first place in green complexity
potential also indicates China is well-placed
to rise or remain near the top of the green
complexity rankings in the years to come.
China’s not only dominates exports of clean
energy technology, but it also has the world’s
largest installed capacity of solar (255 GW)
and wind (288 GW). China’s president Xi

Jinping announced in September 2020 at theUnited Nations General Assembly that China
would aim for emissions to peak before 2030
and to become carbon neutral before 20601,
increasing its 2016 Nationally Determined
Contributions (NDC)2 commitment.
China’s national industrial strategy is aimed
at reaching the technological frontier. Madein China 2025, announced in 2015 as a major
piece of industrial policy, identifies ten
industries for which China aims to become
the world leader by 2025. The chosenindustries include both green vehicles andrail transport technology. Its focus on hightech industries may raise both its economic
and green complexity ranking3. Recently,
China’s 14th 5-year plan (for 2021-2025) wasapproved and emphasises a similar set ofindustries. It also outlines plans for more

1 Xi Jinping, ‘Statement by H.E. Xi Jinping President of the People’s Republic of China at the General Debate of the 75th Session of
The United Nations General Assembly’, Ministry of Foreign Affairsof the People’s Republic of China, 2020 <https://www.fmprc.gov.cn/mfa_eng/zxxx_662805/t1817098.shtml>.
2 Nationally determined contributions (NDCs) are at the heart of the Paris Agreement and the achievement of these long-termgoals. NDCs embody efforts by each country to reduce national emissions and adapt to the impacts of climate change. The Paris
Agreement (Article 4, paragraph 2) requires each Party to prepare, communicate and maintain successive nationally determined
contributions (NDCs) that it intends to achieve. Parties shall pursue domestic mitigation measures, with the aim of achieving theobjectives of such contributions.
3 State Council of The People’s Republic of China, ‘“Made in China 2025” Plan Issued’, 2015 <http://english.www.gov.cn/policies/
latest_releases/2015/05/19/content_281475110703534.htm>.

Predictors of Success in a Greening World70

scientific and technological self-reliance andstronger collaboration between industry andresearch institutions4.
Beyond its country borders, China exerts
economic influence though bilateral andmultilateral projects. A major example ofthis is the Belt and Road Initiative (BRI), a
large infrastructure development strategy,planned in 2015 to be worth a cumulative
6 trillion USD5 , with a major focus on 68
Asian, African, and European countries.
Energy is one of the priority areas of the
BRI. Although renewables are an increasing
part of the strategy, as much as 90% ofenergy loans by six major Chinese banks on
the BRI programme have gone to fossil fuelinfrastructure in the period 2014 – 20186. For
pure electricity generating projects this was
about two thirds of the total, with, with one

third going to renewables, predominantly
hydropower. In 2019, coal accounted for
40% of China’s overseas plant capacity, 27%
for hydro and 11% for other renewables7.
Since 2019 there have been signs that somecoal projects will be put on hold in favourof more renewable projects, as renewableenergy prices have continued to fall, andcountries try to align their policies with their
Paris commitments8. In September 2021
China also pledged to stop building newcoal energy plants abroad, although at thetime of writing the details of this pledge arestill to be determined9. In another show ofinternational green leadership ambition,
China is to host the UN Biodiversity
Conference COP15 in spring 202210.

4 Smriti Mallapaty, ‘China’s Five-Year Plan Focuses on Scientific Self-Reliance’, Nature (NLM (Medline), 2021), 353–54 <https://doi.org/10.1038/d41586-021-00638-3>.
5 Lihuan Zhou and others, Moving the Green Belt and Road Initiative: From Words to Actions, 11 August 2018 <https://www.wri.
org/research/moving-green-belt-and-road-initiative-words-actions> [accessed 19 August 2021].
6 Zhou et al. 2018.
7 Xinyue Ma, Understanding China’s Global Power (Boston, MA, 2020) <https://doi.org/10.1038/s41586-019-1368-z>.
8 Christian Shepherd, ‘China Turns Its Back on Bangladesh BRI Coal Projects’, Financial Times, 2021 <https://www.ft.com/
content/30840645-58d2-4da5-be05-f476623677d2> [accessed 19 August 2021].
9 Azi Paybarah, ‘China Says It Won’t Build New Coal Plants Abroad. What Does That Mean?’, The New York Times (New York, 22
September 2021) <https://www.nytimes.com/2021/09/22/world/asia/china-coal.html>.
10 The first part of the COP15 will take place online in October 2021. See https://www.un.org/en/food-systems-summit-2021-en/
un-biodiversity-conference

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

71

Predictors of Success in a Greening World

72

China at a glance

1,402,000

14,722,730

Population (thousands)

GDP (current US$, millions)

17,312GDP / capita (US$, PPP)5
GCI rank

1
GCP rank

42
ECI rank

18.74 %
Global share of green
exports

12.58 %
Share of green in
total exports

Electric floor
lamps
Highest RCA green productOptical devices
Most complex competitve

Predictors of Success in a Greening World

73

2060

1.4°C

Net zero target

Temp change since 1961

0.5 (rank: 11/230)

26

CO2 intensity (kg/PPP$ GDP)50

Avg energy use(MWh/yr/cap)

32

Global Energy Potential(MWh/yr/cap)

Climate risk index rank85
Extreme risk index rank

12 % (131/213)
Renewable energy consumption

12 %Share of green in covid recovery

Predictors of Success in a Greening World

74

Trends in green competitiveness

China’s share in global green exports
increased from 3.42% in 1995-99 to 18.74%.
Its share of green imports increased as well,
but to lesser extent: from 2.87% at the startof the period to 8% during the most recent
period. China is a net exporter of green
goods (reflecting its dominance in global
manufacturing exports more broadly).

Export values increased in many categories
over the course of the study period, but
especially in more complex ones. The top
three categories are renewable energy,
followed by efficient consumption of energy
technologies and carbon capture and storage
and wastewater management and potablewater treatment.

China’s GCI rank increased from 25th to 5th
over the course of the study period, while
its GCP rank increased from 7 to 1. This
indicates that China not only increased its
green export share, but also moved into
relatively complex green technologies.
Its high Green Complexity Potential inparticular indicates that China is wellpositioned to further increase its global greencompetitiveness in the future. Renewableenergy technologies are China’s mostimportant green export, as well as import.
Global market concentration in this category,as measured by the Hirschmann-Herfindahl
Index "HHI"11 is 0.08, which suggests fairly
low supply vulnerability. However, for someindividual products within the category,market concentration is much higher: forexample, the HHI for solar panels is 0.18.
However, this primarily reflects China’s own
dominance in producing solar panels (itcurrently captures 38% of global solar panel
exports).

As Figure 21 shows, China’s averageproximity to green products has increased forall environmental categories. This indicatesthat China’s productive capabilities are
increasingly aligning with those required tocompetitively produce green technologies.
This is also captured by its high rank in Green
Complexity Potential.

11

Figure 22 shows importers’ shares in China’s
green exports for those countries whose
share is at least 2%. The United States are by
far the most significant green export market
for China, with a share of 15.6%; followed byHong Kong (7.4%), Japan (6%) and Germany(4.2%). This is broadly in line with the patternobserved for China’s exports overall: the US
is the biggest importer (16.7%), followedby Hong Kong (10.4%) and Japan (5.9%)(Figure 23).

The Hirschmann-Herfindahl Index provides a measure of market concentration based on countries’ global market shares andis used to determine market competitiveness.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World75

� Fig 20: Export value over time by environmental category, China.
140000Trade value ($millions)

120000100000
80000
60000
40000
20000
0
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World76

� Fig. 21: Average proximity over time by environmental category, China.
0.6

Average proximity

0.55
0.5
0.45
0.4
0.35
0.3
0.25
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World77

� Fig. 22: Largest importers of China’s green exports. Only countries that import >2%of Chinese exports are shown separately.

Germany
4.2%

Japan
6.0%

USA
15.6%

South Korea
4.0%

Others37.2%

Hong Kong
7.4%

Viet Nam
3.8%

Mexico3.0%

Indonesia
2.4%

Australia
2.5%

Netherlands
2.5%

Indien
3.1%

Malaysia
2.2%

UK
2.2%

Thailand2.0%

� Fig. 23: Largest importers of China’s overall exports. Only countries that import >2%of Chinese exports are shown separately.

Japan
5.9%

South Korea
4.2%

Germany
3.8%

Viet Nam
3.8%

USA
16.7%

Others39.1%

Hong Kong
10.4%

Indonesia
2.8%

UK
2.5%

Mexico2.4%

Netherlands
2.5 %Australia
2.0%

Singapore
2.0%

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World

78

Trends in green energy

The growth in demand for solar PV since
2000, mostly from Europe (following
Germany’s Energiewende programme)
generated sufficient growth in demandby 2009 for China and other low-cost
manufacturing regions to enter the PV supply
market, supported by targeted manufacturingsubsidies. At this point, PV module prices fell
dramatically, halving in less than 2 years, withconcurrent rapid increases in deployment,
particularly in China (Figure 24).
Further supported by a large domestic
market incentivised by their own Feedin-Tariff scheme, China has successfullygrown its solar photovoltaics production
capacity such that it now dominates this
rapidly growing and potentially enormous
market. Currently, 22% of all exports ofrenewable energy technology originate in
China, followed by Germany, which produces
only 12% of world exports. Besides being avery successful export strategy, the moveinto solar technologies was part of a longstanding effort by the Chinese government
to increase domestic energy generation
capacity. Beginning in the 2001 to 2005
‘10th Five-Year’ plan and continuing withsubsequent five-year plans, China has tripledits hydro capacity (Figure 25) with over half(51%) of the hydro capacity installed in 2012
taking place in China. In September 2013,
China introduced the influential Air Pollution
Action Plan which subsequently led to analmost exponential growth in low carbon
energy generation - mostly in hydro, solar,
and wind. China currently has the highest
renewable energy generation capacity of all� Fig. 24: Solar capacity in China 2005-2020.
280

240

240

204

Megawatts

200

175

160

130

120
77

80
40

31

43

28
27
17
0.07 0.08 0.10 0.14 0.3 0.9
02005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Year
Centralised solar PV

Distributed solar PV

Total solar PV

Source: Trends and contradictions in China’s Renewable Energy Policy https://www.energypolicy.columbia.
edu/research/commentary/trends-and-contradictions-china-s-renewable-energy-policy#_edn13

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World79

countries at over 900GW (Figure 25) - threetimes that of the United States, which is insecond place(~300GW). China’s estimatedgreen energy potential is below its current
energy demands, but with the richesthydropower resources in the world (17% of
the global capacity) and the second largest
technical generation potential for solar(Figure 26), it is well placed to increase its
domestic renewable energy capacity. Despitea recent downturn in renewable investments
during the COVID-19 pandemic, China is
still predicted to have sufficient installedcapacity of solar for the foreseeable future12
in the coming years (SolarPower Europe,
2018). However, this will be shaped heavily
by an ongoing contradiction within the power
sector between long-term market-oriented
reforms on the one hand and short-term
administrative planning on the other13.
As it has one of the highest green energy
potentials of any country in Asia, China
may also develop an export strategy forgreen energy to capitalise on any short-term
green premia created in local countries withaggressive net zero targets.

12 SolarPower Europe, Global Market Outlook For Solar Power / 2018 - 2022, 2018, https://www.solarpowereurope.org/
wp-content/uploads/2018/09/Global-Market-Outlook-2018-2022.pdf
13 SIPA Center on Global Energy Policy; Columbia University, Trends and Contradictions in China’s Renewable Energy Policy,
Date accessed: 03/11/2021, https://www.energypolicy.columbia.edu/research/commentary/trends-and-contradictions-chinas-renewable-energy-policy#_edn13.

� Fig. 25: China’s renewable energy generation capacity (GW) by energy source
1 000

Renewable energy capacity (GW)

900
800
700
600
500
400
300
200
100
0

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

Year
Total
renewableenergy Hydropower
Hydropower Marine
Total
renewableenergyWind
Solar
Bioenergy
Solar
Liquid biofuels
Liquid biofuels
BiogasMarineWind
Bioenergy
Biogas

Source: IRENA (2021), Renewable Capacity Statistics 2021; & IRENA (2020), Renewable Energy
Statistics 2020, The International Renewable Energy Agency, Abu Dhabi.

Predictors of Success in a Greening World80

� Table 4: Estimates of China's current technical potential for annual renewable energy
generation which is used to calculate its per capita renewable energy potential incomparison with its current average annual per capita usage.

China
Onshore wind generation potential (EJ/yr)

117

Offshore wind generation potential (EJ/yr)

35

Solar PV generation potential (EJ/yr)

218

Hydro generation potential (EJ/yr)

6

Bioenergy generation potential (EJ/yr)

16

Est. Total generation potential (EJ/yr)
Population (millions)

376
1,402

Average annual energy usage per person (MWh/yr/cap)

26

Total generation potential per person (MWh/yr/cap)

74

Source: See Appendix for Data Sources

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Lombard Odier · December 2021

Predictors of Success in a Greening World81

� Fig. 26: Estimates of solar photovoltaic potential (kWh/kWp) and practical potential

zonation used to determine the China’s economic potential for solar. The practicalpotential zonation of the land is based on topography, usage, and proximity to humansettlement

Photovoltaic power output (Practical potential, Level 0)
2.0

3.0

4.0

5.0

6.0 kWh/kWp N/A

Source: https://globalsolaratlas.info/

Pratical potential zonation:
LCOE average (country range)

Level 2

Level 1

Level 0

Predictors of Success in a Greening World

82

Policy and economic environment

While there has been an increased focus
on green technologies in China’s exports,
the country’s rise to prominence inmanufacturing green technologies partly
reflects its expansion of manufacturingexports more broadly. It is now the largest
manufacturing economy in the world, having
surpassed the United States in 2010.

from state-owned enterprises14. China’s
manufacturing boom is thought to have been
the result of its ability to take advantage ofcheap labour resources, successfully support
target sectors, and use aggressive measures
to bring about technology transfer, such as
by making it a condition of market access forforeign companies15.

In 2016, China captured 23.6% of world
manufacturing output. The focus of Chinese
manufacturing shifted from upstream to
mid- and downstream products over the past
decade, and thus towards products which
are higher in complexity. Moreover, changes
in policy allowed private enterprises to gainin significance and capture market share

These industrial policy practices have led
to trade tensions with the rest of the world,
and in particular the US. Examples include
the US-China trade war over solar panels in
201216 and an escalating tit-for-tat tariff war
launched by former US President Donald
Trump in 201817. Despite ongoing tensions,
China and the US surprised the world with a� Fig. 27: The green bars show installed solar capacity in GW. The line shows export
values for solar panels in USD 1,000.

3.0

200

Solar capacity (GW)

150

2.0

125
1.5

100

1.0

75
50

Export value (USD 1,000)

2.5

175

0.5

25
0

0.0
1995

2000

2005

2010

2015

2019

Year
Installed solar capacity (GW)

Export values in USD 1,000

Source: NEMET, G. F. (2006): “Beyond the learning curve: factors influencing cost reductions inphotovoltaics,” Energy policy, 34, 3218–3232, Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version)..
Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World83

new pledge at the recent COP26 to collaborate
on Enhancing Climate Action in the 2020s.
Green energy technology has formed a key
part of China’s industrial strategy since its
tenth 5-year plan of 2001-2005, which aimed
to “[promote] new energy and renewableenergy like solar PV and wind” as a principal
target18. We can observe China’s exportsof renewables and other green energy
technologies start to increase exponentially inthe early 2000s.
For example, it is now the world’s largest
manufacturer of solar panels, batteries, andelectric vehicles. Support for clean energy
policies has at times been contingent on local

content requirements – for example, 70%
local content was required for projects to beeligible for wind tenders in 2003-2009.
There was also a local content eligibility
requirement for grants from the Special Fundfor Wind Power Manufacturing from 2008201119. China’s push to manufacture clean techhas tended to precede a push for deploymentof these technologies – for example, the valueof China’s exports of solar panels peaked in2011 (prior to the US and the EU imposing
anti-dumping duties on these exports), whilesolar photovoltaic generation capacity was
only just beginning to increase around thattime.

14 Kerry Liu, ‘Chinese Manufacturing in the Shadow of the China–US Trade War’, Economic Affairs, 38.3 (2018), 307–24 <https://doi.org/10.1111/ecaf.12308>.
15 Kerry Liu 2018.
16 Llewelyn Hughes and Jonas Meckling, ‘The Politics of Renewable Energy Trade: The US-China Solar Dispute’, Energy Policy, 105(2017), 256–62 <https://doi.org/10.1016/J.ENPOL.2017.02.044>.
17 Kerry Liu 2018.
18 IEA, ‘The 10th Five-Year Plan for Economic and Social Development of the People’s Republic of China (2001-2005)’, IEA/IRENA
Renewables Policies Database, 2021 <https://www.iea.org/policies/1736-the-10th-five-year-plan-for-economic-and-socialdevelopment-of-the-peoples-republic-of-china-2001-2005?page=4&q=China> [accessed 19 July 2021].
19 OECD, ‘Overcoming Barriers to International Investment in Clean Energy’, in Green Finance and Investment (Paris, France:
OECD Publishing, Paris, 2015) <https://doi.org/10.1787/9789264242661-18-en>.

Predictors of Success in a Greening World

84

Made in China 2025
“Made in China 2025” is an industrial strategy aimed at helping China movefurther towards the technological frontier. It includes some clean technologies,
such as electric vehicles, and aims to improve sustainability by reducing energy andwater use, as well as emissions, per unit of output. It also targets new information
technologies, biomedicine, and other high-tech sectors. Policies aimed at achieving
these goals include emissions targets, targeted subsidies, preferential credit,
insurance products and other measures to facilitate financing activities of firms
engaged in relevant activities, as well as financial support for foreign investment.
Made in China 2025 also includes an “internationalisation” pillar. This refers toefforts to set up bilateral capacity cooperation agreements, establish “overseas
R&D centres”, and encourage the acquisition of foreign technology companies by
Chinese firms20.
China is currently facing the risk of a middle-income trap. Its growth was slowing
before COVID-19, due in part to its ageing population and reduced supply of cheap
labour. It has been very successful in scaling up low-cost manufacturing of existing
technologies; however, its R&D expenditure as a percentage of GDP still lags
behind other manufacturing economies21, and while the share of patents originatingin China – a common proxy for innovative output – has been on the rise, high quality
patents such as triadic patent families are still lagging22. The “Made in China 2025”
strategy aims to upgrade technological and innovative capabilities in high-tech
sectors, which may cause existing trade tensions to further intensify23.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

85

Environmental credentials and policy ambition

Notwithstanding its strong capabilities
to manufacture cleaner technologies,
China performs poorly on metrics such as
manufacturing industry energy consumption
per unit of GDP, and coal continues to makeup the lion’s share of its energy mix (57.64%
in 2019, followed by oil which accounts
for nearly 20%24). However, it has recently
increased its policy ambition, setting acarbon neutrality target for 2060 andspecifying several sustainability goals in its
aforementioned “Made in China” strategy.
Its carbon emissions trading scheme is also
expected to become operational in 2021,
following ten years of preparation and pilot
projects25.

According to the University of Oxford’s Global
Recovery Observatory, with $429 USD in totalof planned projects as of May 2021 China haspresented one of the most ambitious postCOVID-19 recovery plans. About 12% of thiscan be deemed green, similar to the US andJapan, but this is much lower than leading
countries. Combined, their green plans makeup about 0.3% of China’s GDP. Owing more to
the absolute size of the recovery package thanits green credentials, that is enough for China
to be included in the leading green spenders
category of countries with high GCI and morethan average spending as percentage of GDP
on green recovery.

20 Kerry Liu, 2018.
21 Kerry Liu, 2018.
22 China Power Team, Is China Leading in Global Innovation? China Power. Updated January 28, 2021. Accessed July 19, 2021., 2019<https://chinapower.csis.org/china-innovation-global-leader/>.
23 Kerry Liu, 2018.
24 Hannah Ritchie and Max Roser, ‘China: Energy Country Profile’, Our World in Data, 2021 <https://ourworldindata.org/energy/
country/china> [accessed 19 July 2021].
25 Hongqiao Liu, ‘In-Depth Q&A: Will China’s Emissions Trading Scheme Help Tackle Climate Change?’, Carbon Brief, 2021
<https://www.carbonbrief.org/in-depth-qa-will-chinas-emissions-trading-scheme-help-tackle-climate-change>.

Predictors of Success in a Greening World

86

Green strengths and opportunities

China’s NDC has recently called for further
R&D spending in renewable energy andrelated technologies, including desalinationand climate change risk assessment
methodology26. Some environmental
monitoring technology is highly complex andclose to China’s current strengths, such as
exposure meters, or electrical measurement
instruments and their components (Figure28). Figure 28 divides all green products into
those which China exports competitively,
with RCA>1 (“Current Strengths”); andthose which it does not currently export
competitively, with RCA<1 (“Potential
Opportunities”). The horizontal axis
shows the products’ proximity to China’s
current productive capabilities, which iscorrelated with the probability that China willdevelop competitiveness in those productsin the future where it does not alreadyhave it. The vertical axis shows ProductComplexity Index (PCI). PCI is a proxy
for technological sophistication. For somecountries, including China, there is a tradeoff between transitioning into “proximate”
versus “complex” new products. If those
products which are high in complexity tend

to be relatively further away from existing
capabilities, it will be riskier for them totransition into products which are more
likely to open up greater diversification
opportunities.
One of China’s “Made in China 2025” target
industries is green vehicles. Policies havebeen in place for Chinese consumers to buy
hybrid and electric cars since 2009, and in2035 all new vehicles sold must be electric,
hybrid, or fuel-cell driven, according toa Ministry of Industry and Information
Technology guided report27. Electric andhybrid vehicles represent about 5% of new
car sales today and perhaps 20% in 2025,
making it already the world’s largest EV
market in absolute numbers28.
In our dataset, China’s share of global exportof new energy vehicles (which includes gas
powered vehicles besides electric, hybrid,and hydrogen-powered ones), is only 1%,
compared to 12-25% for Germany, Japan,
and the US - all three countries with large
automotive sectors. China has not yet
developed competitive export capabilities

26 NDRC, China’s Intended Nationally Determined Contribution: Enhanced Actions on Climate Change (Beijing, 2015) <https://
www4.unfccc.int/sites/ndcstaging/PublishedDocuments/China First/China’s First NDC Submission.pdf>.
27 Shunsuke Tabeta, ‘China Plans to Phase out Conventional Gas-Burning Cars by 2035’, Nikkei Asia, 27 October 2020 <https://asia.
nikkei.com/Business/Automobiles/China-plans-to-phase-out-conventional-gas-burning-cars-by-2035>.
28 The Economist, ‘What Is China’s Five-Year Plan? The Economist Explains’, The Economist, 4 March 2021 <https://www.
economist.com/the-economist-explains/2021/03/04/what-is-chinas-five-year-plan>; IEA, ‘Reports: Electric Vehicles’, IEA,
2020 <https://www.iea.org/reports/electric-vehicles>.

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Lombard Odier · December 2021

Predictors of Success in a Greening World87

� Fig. 28: China’s green export products divided into current strengths and potential
opportunities. Size of product indicates China’s current RCA, colours represent
product categories (see legend)

China: Current Strengths

China: Potential Opportunities

Optical devices

2.0

Exposure
meters(concentrated solar)

1.5
Photovoltaic
cells

1.0
0.5
0.0
-0.5
-1.0

Product Complexity Index

Product Complexity Index

1.5

-1.5

Electricalmeasurement
instruments
and components

0.5

-0.5

-1.5

-2.0
0.45

0.50

0.55

0.60

0.65

Proximity to Country

Management of Solid and Hazardous Waste and Recycling Systems
Natural Resource Protection
Energy Efficiency
Heat and Energy Management
Gas Flairing Emission Reduction
EfficientConsumptionof EnergyTechnologiesandCarbonCaptureandStorage
Environmental Monitoring, Analysis and Assessment Equipment
Renewable Energy
Noise and Vibration Abatement
Resources and Pollution Management

0.35

0.40

0.45

0.50

0.55

Proximity to Country

Waste Water Management and Potable Water Treatment
Air Pollution Control
Natural Risk Management
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
OthersEnvironmentalPreferableProductsbasedonEnd-UseorDisposalCharacteristics
Waste Management, Recycling and Remediation
Water supply
Bubbles are sized by RCA

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

Predictors of Success in a Greening World88

in this area, with RCA in alternative vehicles
currently at 0.06 and proximity to current
productive export capabilities comparatively
low at about 0.4. Since 2017, EVs have theirown export code (separated from other “newenergy” vehicles), but this is not reflected in
our longitudinal data covering the period of
1995-2019 and therefore using the original
1992 version of the HS nomenclature.
Tracking this new export code, we see that
China was the 8th largest net exporter of EVs
in 2020, with exports up 260% compared to
the year before, now capturing 4.6% of global
export markets for EVs29,30.

Separately, our longitudinal dataset showsthat China has export capabilities(RCA = 1.1 > 1) in environmentally friendly
and less-polluting busses (those that don’t
run on diesel) and is a major player on its
export market (Figure 29). But making
busses is significantly less complex (productcomplexity index (PCI: 0.43) than newenergy vehicles (PCI: 1.87). The question
remains whether this will help improve
China’s EV capability for the next decade, orwhether its EV demand will be mostly met byimports from other countries.

� Fig. 29: China’s share in global exports of new electric vehicles(also includes gas powered)
16
14
12
10
8
6
4
2
0
1995-1999

1999-2003

2003-2007

870290 – Buses except diesel powered

2007-20112011-2015

870390 – Other Vehicles incl. Gas Turbine Powered

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.
32 Daniel Workman, ‘Electric Cars Exports by Country’, World’s Top Exports, 2021 <https://www.worldstopexports.com/electriccars-exports-by-country/>.
33 Workman, Daniel, ‘Electric Cars Exports by Country’, World’s Top Exports, 2021 <https://www.worldstopexports.com/electriccars-exports-by-country/>

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Lombard Odier · December 2021

Predictors of Success in a Greening World89

Summary� China’s rise to prominence in manufacturing green technologies exceeds its broader
manufacturing and export expansion, but may partly reflect a shift towards more
technologically sophisticated exports in general.

� These developments are thought to be driven by its ability to take advantage of cheap

labour, as well as targeted industrial policy which includes industry-specific subsidies,preferential credit, and measures which aggressively target technology transfer, as well asprotectionist provisions such as local content requirements.

� China is the world’s largest emitter of green house gases, and its production processes for
manufactured goods are considered very polluting.

� However, China has recently increased its environmental ambitions in raising its Nationally
Determined Contribution under the Paris Agreement and setting a carbon neutrality target
for 2060.

� The “Made in China 2025” strategy targets sustainability and some key green technologies
such as electric vehicles, as well as digitalisation and high-tech industries more broadly.

� China has enormous green energy potential and access to very cheap solar resources, but
due to its large population it might only export green energy in the short-term.

� Trade tensions between China and the rest of the world, especially the US, have beenongoing for years and intensified in 2018 under President Trump. At COP26, China andthe US surprised the world with a new pledge to collaborate in the form of a US-China Joint
Declaration on Enhancing Climate Action in the 2020s.

� While China has been very adept at technology adoption and manufacturing, it has not, sofar, contributed much at the innovation frontier.

� Its ageing population and rising standards of living have led to a rapid increase in the costof labour. With growth starting to slow, the question arises whether China can escape themiddle-income trap and take the leap from technology adopter to frontier innovator.

Predictors of Success in a Greening World

90

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Predictors of Success in a Greening World

91

United States of America case study
Policy ambition and green complexity
The United States has a long history as a
global innovator and boasts some of the mostprogressive and innovative green states in theworld, such as California.
It is therefore not surprising that the US holds
the 4th highest rank in Green Complexity
Index (after Germany, Italy and mostrecently Austria) and rank 12th in Green
Complexity Potential.
What is perhaps surprising is that its GCI and
GCP have declined slightly since 1995, as has
its manufacturing competitiveness overall.
The US currently captures about 10% of
global green exports, a decline from 17% in
1995-99. Green products make up about 11%
of its total exports.
The US is the world’s second-largest emitterof greenhouse gases and has historically
been hamstrung by climate and otherenvironmental issues being highly politicised.

Former Republican President Donald Trump,
who questioned the existence and threat ofanthropogenic climate change and promised
to bring back coal mining and manufacturingjobs, rolled back many of the previous
administration’s environmental protections
and pulled the country out of the Paris
Climate Accord.
The current Democrat Biden
administration has worked hard to reverse
many of these decisions since coming
to power in January, re-joining the Paris
agreement and recently setting targets toreach net zero greenhouse gas emissions
by 2050 and to support clean energy
technologies through the Glasgow
Breakthrough Agenda at COP26.
The administration’s economic agenda
strongly ties the green transition to
infrastructure investments and job creation.
To what extent the current level of ambition
can be realised remains to be seen.

Predictors of Success in a Greening World

92

United States at a glance

329,000

20,936,600

Population (thousands)

GDP (current US$, millions)

65,280GDP / capita (US$, PPP)

4

8
ECI rank

GCI rank

12
GCP rank

10.18 %
Global share of green
exports

Rail locomotives(diesel-electric)
Highest RCA green productPlease read the important information at the end of the document.
Lombard Odier · December 2021

11.34 %
Share of green in
total exports

Profile projectors
Most complex competitivePredictors of Success in a Greening World

93

2050

1.3°C

Net zero target(proposed)

Temp change since 1961

79

0.24 (rank: 52/230)
CO2 intensity (kg/PPP$ GDP)

169

Avg energy use(MWh/yr/cap)-

Global Energy Potential(MWh/yr/cap)

Climate risk index rank

127
Extreme risk index rank

8.7 % (146/213)
Renewable energy consumption

8%
Share of green in covid recovery

Predictors of Success in a Greening World

94

Trends in green competitiveness

The United States’ green competitivenesshas been on a slowly declining trend. It held
second rank in Green Complexity Index until
2003-2007, when it was overtaken by Italy. It
was overtaken again by Austria in 2015-2019
and now holds rank 4. Its Green Complexity
Potential peaked in 2005-2009 and has been
declining ever since, to its current rank of
12. The US still has a large domestic green
market that it is mostly met by domestic
industry (Section 5), but in exports at least
further declines in green complexity may
lie ahead unless the new administration’s
policies manage to reverse this trend.
The United States’ share in global exports ofgreen products declined significantly overthe course of the period: from 17.04% in
1995-1999 down to 10.18% in 2015-2019. Its
share in green imports fluctuated somewhat,
declining in the years leading up to the global
financial crisis following its peak in 19982002, then reversing back to an upwards
trend. It now stands at close to 14%, as it did
at the start of the period. This makes the US a
net importer of green goods.

Overall trade volume increased in many
green categories, including products
related to efficient consumption of energy
technologies and carbon capture andstorage; renewable energy; and wastewater
management and potable water treatment(Figure 29). However, trade values haveplateaued or even slightly decreased sincearound 2011-2015, even though green
products continued to gain in importance asa share of global trade. This is reflected in the
country’s falling green competitiveness.
As is the case with overall GCP, averageproximity to production capabilities in mostgreen categories peaked during the early
2000s (Figure 30). It has been on a declining
trend since then, apart from a brief recovery
following the global financial crisis of 2008.
Since around 2011-2015, this decline has been
steeper than ever.

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Lombard Odier · December 2021

Predictors of Success in a Greening World95` Fig29: Export value over time by environmental category, United States

80000

Trade value ($millions)

70000
60000
50000
40000
30000
20000
10000
0
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World96` Fig. 30: Average proximity over time by environmental category, United States.
0.5

Average proximity

0.45

0.4

0.35

0.3

0.25
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).
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Lombard Odier · December 2021

Predictors of Success in a Greening World97

� Fig. 31: Largest importers of US green exports. Only countries that import >2% ofAmerican exports are shown separately.

China
7.9%

Germany
4.9%

Canada17.4%

South Korea
4.2%

Others26.3%

Mexico16.3%

Singapore
3.1%

Belgium
2.9%

UK
3.5%

Japan
4.1%

Netherlands
2.7%

Brazil2.1%

France2.2%

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

In summary, our analysis implies that US’
productive capacities are becoming lesssuited to producing clean technologies,
relative to other countries. This is partly
mirrored by a fall in overall economic
complexity – with the US’ rank in Economic
Complexity Index after some fluctuation
falling from 6 to 8 over the last two decades(1995-99 to 2015-19). The most important
importers of green technologies producedin the United States are its immediateneighbours Canada (17.4%) and Mexico(16.3%) (Figure 31). Strikingly, while the US
accounts for about 15.6% of China’s green
exports, China only accounts for 7.9% of
green exports from the US. Figure 32 shows
the distribution for overall exports, which
paints a broadly similar picture.

Predictors of Success in a Greening World98` Fig. 32: Largest importers of US overall exports. Only countries
that import >2% of American exports are shown separately.

Canada16.7%

Mexico15.6%

Others
35.4%

China
6.8%
Germany
4.0%

United Kingdom
3.4%South Korea
3.8%

Japan
4.6%

Netherlands
3.2%

India
2.2%
Belgium
2.2%

Brazil2.2%

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

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Predictors of Success in a Greening World

99

Trends in green energy

The US is one of a number of countries whoseenergy emissions intensity has declined
since 20101. Much of this progress has been
the outcome of the switch away from coalin favour of fracking gas. Renewable energy
capacity has also increased since the 1990’s
in the US and currently accounts for 8.71%
of per capita energy, compared to 4.47% in

1995, with the state of California leading theway. The country did, however, start with avery high level of per capita emissions, withmost of the country’s energy mix still being
made up by fossil fuels (83%) - close to theglobal average of 84%2.

� Fig. 33: USA’s renewable energy generation capacity by source.

Renewable energy capacity (GW)

350 000
300 000
250 000
200 000
150 000
100 000
50 000
0

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

Year
Total renewable energy
MarineTotal renewableenergyHydropower
Solar
Solar
Bioenergy

Hydropower
Wind
MarineBioenergy
Liquid biofuels

Wind
Biogas

Source: IRENA (2021), Renewable Capacity Statistics 2021; & IRENA (2020), Renewable Energy
Statistics 2020, The International Renewable Energy Agency, Abu Dhabi.

1 Lamb and others.
2 Hannah Ritchie and Max Roser, ‘Energy’, Our World in Data, 2020 <https://ourworldindata.org/energy> [accessed 19 August2021].

Predictors of Success in a Greening World

100

The US is, however, blessed with some of
the world’s greatest technical potential forhydropower, biomass, solar, and wind. The
relatively large population of 330 million
is widely distributed over the land surface,giving it a high practical solar potential
zonation3 (Figure 34) and consequently
high solar economic potential. Its current
estimated green energy potential (170MWh/yr/cap) is well above its very highaverage energy usage (79 MWh/yr/cap)
and an average solar PV LCOE of 10c/

kWh indicating considerable potential for
expansion of green energy for both thedomestic market and for export.
Most of the new renewable growth in the US
is from onshore wind (Figure 33), although
the US is predicted to have the third highest
solar installations in the coming years, behind
China and India, thanks to recent declines
in costs for solar PV4 and opportunities forfurther integration through improved gridinterconnectedness across the country’s

� Table 5: Estimates of the US's current economic potential for annual renewable energy
generation which is used to calculate its per capita renewable energy potential incomparison with its current average annual per capita usage
United States
Onshore wind generation potential (EJ/yr)

130

Offshore wind generation potential (EJ/yr)

25

Solar PV generation potential (EJ/yr)

174

Hydro generation potential (EJ/yr)

1

Bioenergy generation potential (EJ/yr)

11

Est. Total generation potential (EJ/yr)

331

Population (millions)

329

Average annual energy usage per person (MWh/yr/cap)

79

Total generation potential per person (MWh/yr/cap)

279

Source: Appendix for Data Sources

3 The solar practical zonation excludes land with physical or technical constraints, such as rugged terrain, extreme remoteness,built-up environment, and dense forests, and ‘soft’ constraints, such as regulations related to protection of cropland andconservation areas.
4 SolarPower Europe, ‘Solar Power 2019–2023’, Global Market Outlook, 2018, 94.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

101

vast land mass4. As will be discussed below,
should the Build Back Better Act currently
before US Senate get passed, the US will
become one of the largest investors in
renewable capacity in the coming years.
The United States have a mix of existing
strengths and new opportunities in the green
economy (Figure 34)6. High complexity
strengths highlighted on the plot include
profile projectors (which are used in themeasurement, recording, analysis andassessment of environmental samples orenvironmental impact), and cleaner vehicles
such as hybrids or EVs. The latter are a clear
strategic priority for the Biden Administrationand the Breakthrough Agenda from COP26.

� Fig. 34: Estimates of solar photovoltaic potential (kWh/kWp) and practical potential
zonation used to determine the US’s economic potential for solar.

Photovoltaic power output (Practical potential, Level 0)
2.0

3.0

4.0

5.0

6.0 kWh/kWp N/APratical potential zonation:

Level 2

Level 1

Level 0LCOE average (country range)

Source: https://globalsolaratlas.info/

5 Patrick R. Brown and Audun Botterud, ‘The Value of Inter-Regional Coordination and Transmission in Decarbonizing the US
Electricity System’, Joule, 2021, 115–34 <https://doi.org/10.1016/j.joule.2020.11.013>
6 For a more in-depth explanation of how to read this figure, please refer to the section Green strengths and opportunities within
the China case study.

Predictors of Success in a Greening World

102

Green strengths and opportunities

There is a positive correlation between
complexity and proximity, which implies
that products which would be easier for the
US to develop a new competitive advantage
in, are also higher in complexity - opening
up a greater number of new (complex)
diversification opportunities (Figure 35). Highcomplexity opportunities for the US include
machines and appliances designed for a wide
range of areas of environmental management
including waste, wastewater, drinking waterproduction and soil remediation; and electric
generating sets used in the production ofrenewable energy. Figure 35 also highlights
optical devices, appliances, and equipment

at the top left. This product category includes
solar heliostats, which orient mirrors inconcentrated solar power systems to reflectsunlight on to a CSP receiver. This productgroup is highlighted as an example of
one that is high in complexity but low inproximity, implying that the US could gainfrom producing this product but is unlikely
to easily develop a competitive advantage.
In contrast, this is China’s most complex
competitive product, demonstrating how thegreen indices might be used for industrial
policy.

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Lombard Odier · December 2021

Predictors of Success in a Greening World103

� Fig. 35: United States’ green export products divided into current strengths andpotential opportunities. Size of product indicates country’s current RCA, colours
represent product categories (see legend)7USA. Puerto Rico and US Virgin Islands:
Current Strengths

Product Complexity Index

2.0
1.5

Other vehicles
incl. Gas Turbine
Powered (Evsand hybrid
vehicles)Profile projectors, nes

1.5
Product Complexity Index

2.5

USA. Puerto Rico and US Virgin Islands:
Potential Opportunities

1.0
0.5
0.0
-0.5
-1.0

Machines andmechanicalappliances, nes
Optical devices,
applicances andequpement

0.5Electric
generating sets

-0.5

-1.5

-1.5
0.35

0.40
0.45
Proximity to Country

0.50Management of Solid and Hazardous Waste and Recycling Systems
Natural Resource Protection
Energy Efficiency
Heat and Energy Management
Gas Flairing Emission Reduction
EfficientConsumptionof EnergyTechnologiesandCarbonCaptureandStorage
Environmental Monitoring, Analysis and Assessment Equipment
Renewable Energy
Noise and Vibration Abatement
Resources and Pollution Management

0.25

0.30

0.35

0.40

Proximity to Country

Waste Water Management and Potable Water Treatment
Air Pollution Control
Natural Risk Management
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
OthersEnvironmentalPreferableProductsbasedonEnd-UseorDisposalCharacteristics
Waste Management, Recycling and Remediation
Water supply
Bubbles are sized by RCA

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

7 For an in-depth explanation of how to read this figure, please refer to the section Green strengths and opportunities within the
China case study.

Predictors of Success in a Greening World

104

Policy and economic environment

The past few decades have seen a decline
in US manufacturing employment which
is well-documented in the literatureand is usually attributed to offshoring(especially to China) and/or to automation8.
Manufacturing employment has been on
the decline since the 1970s, with 2 million
jobs lost between 1980 and 2000; however,this trend accelerated rapidly after 2000.
Five and a half million manufacturingjobs were lost between 2000 and 2017, a
substantial share of which occurred even
before the great recession9. Real value added
in manufacturing nevertheless continued
to increase until the early 2000s, reaching apeak just before the global financial crisis of
200810. This “decoupling” of employment
and value added was primarily driven bycomputers and electronic products, such as
semiconductors11.

recently, manufacturing output growth, is
not necessarily a negative trend. High-skilledservices, such as software engineering, arearguably highly sophisticated and high invalue added. Our methodology for measuring
complexity does not capture this, as it isbased on manufacturing exports. However,
manufacturing has historically provided
important employment opportunities to lowskilled workers. Charles et al.12 argue that thefall in manufacturing employment has driven
substantial declines in employment rates
among prime-age workers, accompanied
by higher opioid use in those affected.
Moreover, they find that manufacturing itself
has become increasingly capital-intensive
and high-skilled, implying that erecting tradebarriers to prevent offshoring and support
American manufacturers may not help lowskilled workers.

The US, like many – especially rich –countries, has experienced a sectoral
shift towards services. A decline in
manufacturing employment and, more

The structural shifts in the US economy thathave transpired over the past few decades
have resulted in political tensions whicharguably contributed to the election of

8 Teresa C. Fort, Justin R. Pierce, and Peter K. Schott, ‘New Perspectives on the Decline of US Manufacturing Employment’,
Journal of Economic Perspectives, 32.2 (2018), 47–72 <https://doi.org/10.1257/jep.32.2.47>.

9 Kerwin Kofi Charles, Erik Hurst, and Mariel Schwartz, ‘The Transformation of Manufacturing and the Decline in US
Employment’, NBER Macroeconomics Annual, 33 (2019), 307–72 <https://doi.org/10.1086/700896>.

10
11

12

Fort et al., 2018.

Fort, Pierce, and Schott; Susan N Houseman, Understanding the Decline of U.S. Manufacturing Employment, Upjohn InstituteWorking Paper, 2018 <https://doi.org/10.17848/wp18-287>.
Charles, Hurst, and Schwartz, 2019.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

105

former President Donald Trump in 2016
and continue to loom large in US political
discourse. Concerns over the competitivenessof US manufacturing, the effects of climate
policy thereon, offshoring to China, andloss of employment in polluting sectors
such as coal mining and fracking, continue
to be highly divisive and pose a potential
political barrier to the transition to a net zeroeconomy. The Biden administration has
adopted a “Green New Deal” style rhetoric aspart of their Build Back Better Plan, linking

the greening of the economy to infrastructure
investment and job creation and promises
to revive American manufacturing. Policies
such as the “Buy American” provisionin public procurement indicate that theadministration is not opposed to protectionist
measures, and ongoing trade tensions with
China are likely to continue.

Predictors of Success in a Greening World

106

Environmental credentials and policy ambition

The US are the world’s second-largest emitterof greenhouse gases, having been overtaken
by China in 200613. Climate policy in the
US has depended largely on the current
administration’s stance on the issue. The
Obama era saw multiple policies aimed at
reducing greenhouse gas emissions, suchas the Clean Power Plan; renewable energy
tax credits; the creation of ARPA-E; or thesigning of the Paris climate accord. President
Trump, who famously called climate changea “hoax”, spent much of his tenure rollingback environmental protections14 and pulled
the United States out of the Paris agreement,
which the current President Biden promptly
re-joined15 .
The American Clean Energy and Security
Act of 2009, which attempted to introduce
a cap-and-trade system, was blocked by the

Senate after passing through Congress. Asof today, the United States still do not have anational carbon price. However, some states
have responded by cooperatively introducing
their own: the Regional Greenhouse Gas
Initiative (RGGI) was established in 2019.
RGGI is a carbon trading system covering
the power sector in Connecticut, Delaware,
Maine, Maryland, Massachusetts, New
Hampshire, New Jersey, New York, Rhode
Island, Vermont, and Virginia.
The Biden administration has made climatechange a priority. President Biden has
pledged to half greenhouse gas emissions
by 203016 and reach net zero by 205017.
The Biden Climate Plan is strongly tied
to infrastructure investments, economic
inclusion, and job creation, as we will set out
in more detail in the following section.

13 Hannah Ritchie and Max Roser, ‘CO2 and Greenhouse Gas Emissions’, Our World in Data, 2020 <https://ourworldindata.org/
co2-and-other-greenhouse-gas-emissions#citation> [accessed 19 August 2021].
14 Nadja Popovich, Livia Albeck-Ripka, and Kendra Pierre-Louis, ‘The Trump Administration Rolled Back More Than 100
Environmental Rules. Here’s the Full List.’, The New York Times, 20 January 2021 <https://www.nytimes.com/interactive/2020/
climate/trump-environment-rollbacks-list.html> [accessed 19 August 2021].
15 Oliver Milman, ‘Biden Returns US to Paris Climate Accord Hours after Becoming President’, The Guardian, 20 January 2021
<https://www.theguardian.com/environment/2021/jan/20/paris-climate-accord-joe-biden-returns-us> [accessed 19 August2021].
16 The White House, ‘FACT SHEET: President Biden Sets 2030 Greenhouse Gas Pollution Reduction Target Aimed at Creating
Good-Paying Union Jobs and Securing U.S. Leadership on Clean Energy Technologies’, White House Statements and Releases,
2021 <https://www.whitehouse.gov/briefing-room/statements-releases/2021/04/22/fact-sheet-president-biden-sets-2030greenhouse-gas-pollution-reduction-target-aimed-at-creating-good-paying-union-jobs-and-securing-u-s-leadership-on-cleanenergy-technologies/> [accessed 19 August 2021].
17 Biden Harris Democrats, ‘The Biden Plan for a Clean Energy Revolution and Environmental Justice’, Battle for the Soul of the
Nation, 2021 <https://joebiden.com/climate-plan/> [accessed 19 August 2021].
18 The White House, ‘FACT SHEET: The American Jobs Plan’, White House Statements and Releases, 2021 <https://www.
whitehouse.gov/briefing-room/statements-releases/2021/03/31/fact-sheet-the-american-jobs-plan/> [accessed 19 August2021].

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Lombard Odier · December 2021

Predictors of Success in a Greening World

107

The Build Back Better Plan and US green recovery
spending
In Section 3, we discussed countries’ plans to spend on green recovery post
COVID-19. Any policy that was still being negotiated in the national parliaments
was excluded from the analysis.
The Biden administration began with significant ambition: the American Jobs
Plan announced in March 2021 could have added green spending worth 2% ofGDP. The American Jobs Plan was eventually incorporated into the $1 trillion
Infrastructure Investment and Jobs Act (of which $550 billion is new spending),
passed by the Senate in August 2021 and by the House in November. Based on arough breakdown, about 20% of this can be deemed green (mainly investment inEVs, railway transportation, and clean electricity)18.
A further $2.2 trillion Build Back Better Act was passed in the House ofRepresentatives along party lines, but has yet to pass through the Senate. Thissecond bill is aimed at securing better social welfare provisions, including muchof Biden’s American Families Plan, and to support his recent commitments on
climate change. This latter component, which will include significant spending on
renewables and reducing methane emissions, will likely have the greatest impact
on the US’s green competitiveness.
A breakdown of some of the key green components of only the recently passed
Infrastructure Investment and Jobs Act are as follows:
EVs: The Infrastructure bill contains $7.5 billion for EV infrastructure
and a further $7.5 billion for electric and clean busses and ferries. This isabout 10% of the figure originally envisioned by the Biden administrationfor electric vehicle investment as a whole. Some of the remainder is to be
included in the Build Back Better Act.
Clean electricity: The recently passed Infrastructure bill aims to spend$73 (original plan: $100) billion on the electricity grid, energy efficiency,
and renewable energy, to put the US electricity system on a pathway
toward carbon-free electricity by 2035. An additional $21 billion is plannedfor plugging former oil and gas wells and cleaning up abandoned mines.
Public transport: $39 billion will go to modernising and upgrading thelarge repair backlog of the Department of Transportation, as well as
expanding the public transit network. A further $66 billion will be spent on
modernising and expanding passenger railway and electrifying freight railtransport. This is scaled back from the original $85 + $80 billion package
respectively.

Predictors of Success in a Greening World

108

While the American Jobs Plan proposal contained $465 billion of dedicatedgreen spending, the Infrastructure bill that was accepted by congress has about$214 billion. None of the money originally intended to be invested in housing
including energy efficiency retrofitting ($200 billion) or (clean energy) R&D andmanufacturing ($566 billion) is in the bipartisan infrastructure deal. Much of thegreen spending detailed above has thus been moved to the second “Build Back
Better Act”, which has yet to pass through the Senate.
The original spending associated with the full American Jobs Plan would havecatapulted the US to near the top of the Leading green spenders as the fifth biggest
green recovery spender as share of GDP, close to Denmark and the UK. However,with only the bipartisan infrastructure deal passed, the gains are significantly lower.

` Figure 36 shows the impact of the bipartisan infrastructure deal, which still puts theUS squarely in the Leading green spenders corner.
Reproduction of figure 18, including the potential impact of the recently passed bipartisan
infrastructure deal. Note that the y-axis is logarithmic.
Spain

Republic of Korea

United Kingdom

Green recovery percentage of GDP

Canada100
Senegal10-1

Jamaica
PanamaBangladesh
Australia
Chile
IrelandGermany
USA with bipartisan
infrastructure plan

France, Monaco

Norway,Svalbard
and Jan
Mayen

Finland

Leadinggreen spenders

Denmark

PolandJapan
China

TurkeyIsraelSwitzerland,
Liechtenstein

SwedenUS infrastructure
spending potential

Gaining
momentum

Austria

Mauritius
PakistanUSA

Colombia Kenya

India

Missedopportunities Brazil

0
-1

Italy

Netherlands

PHL
IDN AREZAE
SGP BEL

CUB

CRI

ECU

DOM EGY VNM

MYS THA

0

1

MEX
PRT

ROU

2

Falling behind

CZE

3

GCI

Source: Global Recovery Observer https://green-transition-navigator.org

45

Predictors of Success in a Greening World

109

Summary` US green complexity and green complexity potential have declined slightly over the study
period, as has its overall economic complexity.

` However, the country remains highly competitive in global comparison, with a GCI rank of
4 and a GCP rank of 8.

` The United States has substantial green energy potential, more than enough to meet future
domestic demands and even become a green energy exporter.

` President Biden has made climate change one of his top priorities and pledged to halfgreenhouse gas emissions by 2030 and reach net zero by 2050.

` The bipartisan infrastructure deal aims to expand and electrify public transport and build aclean electricity grid. It includes ambitious public infrastructure investments and promises
to generate employment for American workers, although it misses many other investments
originally planned by the Biden administration.

` The administration is presenting a firm stance on China, emphasising the importance of

supply chain resilience, and aiming to boost American manufacturing using policies such as
the “Buy American” provision for public procurement.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

111

BrazilPolicy ambition and green complexity
Despite a proud history of technologicalprogress, particularly in aviation, Brazil
stands out in modern times for its relatively
low investment in R&D, combined witheconomic and political volatility, high levelsof corruption, and low capacity of industries
to generate innovation1. Such problems haveno doubt contributed to its declining ECI,GCI and GCP rankings.
The current Bolsonaro government has been
widely criticised for its poor environmental
record. However, Brazil updated its NDC2
in 2020 with a new intermediate target.
Compared to 2005 levels, Brazil wants tolower its emissions by 37% in 2025 and by
43% in 20303. This was written with a longterm goal of carbon neutrality by 2060.
As Brazil is able to produce much of its
electricity from hydropower, a large part ofthe country’s emissions are from agriculture(33%), land-use change (e.g. deforestation)(23%) and transport (15%)4 . Accordingly,
Gurgel, Paltsev, and Breviglieri5 argue
that the 2030 goal could be achieved quite
cheaply at 0.7% of GDP in 2030, mostly
through reducing deforestation and changes
to agricultural practices. After 2030, though,more ambitious policy changes, such asa carbon pricing mechanism, might benecessary to remain on track. Gramkow andAnger-Kravi6 also believe that with the rightmix of green stimulus, paid for by a carbon
tax, Brazil could increase economic growth
while lowering emissions from a business-asusual baseline. However, as noted in Section
3, Brazil has allocated only a fraction of its
GDP to spend on stimulus following the
COVID-19 pandemic. Nonetheless, the small
amount it has allocated for recovery has beenover 50% green, with a focus on renewableenergy projects. This was still quite little
spending, and consequently Brazil has ended
up in the falling behind category.

1 Marisa Moser, Mauri Aparecido de Oliveira, and Ricardo Luiz Pereira Bueno, ‘Comparison between Brazil and the 30 Most
Innovative Countries in the World’, EMAJ: Emerging Markets Journal, 7.2 (2018), 19–28 <https://doi.org/10.5195/emaj.2017.141>.
2 Nationally Determined Contribution
3 UNFCCC, ‘Federative Republic of Brazil First Nationally Determined Contribution towards Achieving the Objective of theUnited Nations Framework Convention on Climate Change (Updated Submission)’, 2020 <https://www4.unfccc.int/sites/
ndcstaging/PublishedDocuments/Brazil First/Brazil First NDC (Updated submission).pdf>.
4 USAID, Greenhouse Gas Emissions in Brazil, USAID, 2018.
5 ‘The Impacts of the Brazilian NDC and Their Contribution to the Paris Agreement on Climate Change’, Environment andDevelopment Economics, 24.4 (2019), 395–412 <https://doi.org/10.1017/S1355770X1900007X>.
6 Camila Gramkow and Annela Anger-Kraavi, ‘Developing Green: A Case for the Brazilian Manufacturing Industry’,
Sustainability 2019, Vol. 11, Page 6783, 11.23 (2019), 6783 <https://doi.org/10.3390/SU11236783>.

Predictors of Success in a Greening World

112

Brazil at a glance

212,560

1,444,733

Population (thousands)

GDP (current US$, millions)

15,076
GDP / capita (US$, PPP)

9376
ECI rank

GCI rank

72
GCP rank

3.83 %
0.50 %

Share of green in
total exports

Global share of green
exports

Binder twine, sisal
Highest RCA green productRefrig compressors
Most complex competitive

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Lombard Odier · December 2021

Predictors of Success in a Greening World

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2050

1.2°C

Net zero target(proposed)

Temp change since 1961

17

0.14 (rank: 120/230)
CO2 intensity (kg/PPP$ GDP)Avg energy use(MWh/yr/cap)

141

27

Global Energy Potential(MWh/yr/cap)

Climate risk index rank

123
Extreme risk index rank

44 % (57/213)
Renewable energy consumption

Share of green in covid recovery

Predictors of Success in a Greening World

114

Trends in green competitiveness

Both Brazil’s green competitiveness and its
green competitiveness potential have seen adeclining trend over the course of the study
period. Its GCI declined from rank 48 torank 93 and GCP fell from rank 43 to rank 72,
suggesting that GCI is likely to fall further inthe future. As can be seen in Figure 36, Brazil
increased its absolute trade volume in green
products in almost all categories from 1995

until the 2011-2015 period. Between then andthe 2015-2019 period, total trade volumes
dropped in Brazil’s top 5 categories: Efficient
Consumption of Energy Technologies andCarbon Capture and Storage, Renewable
Energy, Wastewater Management andPotable Water Treatment, Air Pollution
Control, and Noise and Vibration Abatement.

` Fig. 36: Export value over time by environmental category, Brazil
5000
4500

Trade value ($ millions)

4000
3500
3000
2500
2000
1500
1000
500
0
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).
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Predictors of Success in a Greening World

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Over the same period, from 1995 onward,
the average proximity of green products to
Brazil’s productive capabilities has declined,
as is shown in Figure 37. This implies thatgreen growth opportunities might be harder
to attain than was once possible. The steepest
declines occurred between the 20032007 and 2011-2015 time periods, whichcorresponds to the time frame of the great

financial crisis and its recovery period. The
US is by far the largest importer of Brazilian
green products, importing almost 30% of
the total. A breakdown of other countries
importing more than 2% of Brazil’s export isvisualised in Figure 38. The second largest
importer is Argentina with just over 9% of
the total, followed by the Netherlands which
imports 7.8% of Brazil’s green exports.

` Fig. 37: Average proximity over time by environmental category, Brazil
0.22

Average proximity

0.2
0.18
0.16
0.14
0.12
0.1
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World

116` Fig. 38: Largest importers of Brazilian green exports. Only countries that import >2%of Brazilian exports are shown separately.

Argentina
9.2%

USA
29.6%

Others25.6%

Netherlands
7.8%

Chile
4.2%

Germany
4.6%

Mexico4.4%

Columbia
3.3%

South Korea
3.4%

China
2.7%

Paraguay
2.7%

Indonesia
2.5%` Fig. 39: Largest importers of Brazilian overall exports. Only countries that import >2%of Brazilian exports are shown separately.

China
27.6%

USA
13.2%

Others41.8%

Argentina
4.3%

Netherlands
4.0%

Japan
2.4%

Chile
2.3%
Germany
2.2%

Mexico2.2%

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

The distribution of importer shares for Brazil’s overall exports differs from those for its green
exports (Figure 39). China constitutes a much more significant share of overall exports, at
27.6%, while the US’s and Argentina’s shares are much smaller (13.2% and 4.3%, respectively).
Overall, green exports seem to be more locally concentrated and a much smaller share iscaptured by countries with a share of 2% or less (25.6%, compared to 41.8% for overall exports).
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Lombard Odier · December 2021

Predictors of Success in a Greening World

117

Trends in green energy

Brazil has very large renewable energy
potential and some of the highest levelsof renewable energy generation in theindustrialised world thanks to their investment
in hydropower7 and quotas on biofuels fortransport8. Brazil is second only to China in its
hydropower generation capacity, and second
only to the US in bioenergy generation (Figure40). The Brazilian government has invested
significantly in growing a domestic windturbine manufacturing capability which has

supplied much of its current wind capacity.
Solar PV has also begun to grow significantlyin Brazil mainly due to utility-scaleinstallations, but with significant distributed
solar coming online thanks to increasing
competitiveness of the net-metering
regulation throughout the country9. Newly
added solar capacity amounted to 390 MW
in 2018. This doubled in 2019 and almost
doubled again in 2020 despite the COVID-19
pandemic.

` Fig. 40: Brazil’s renewable energy generation capacity by source

Renewable energy capacity (GW)

160 000
140 000
120 000
100 000
80 00060 00040 000
20 000
0

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

Year
Total renewable energy
Total renewable energy
Wind
Solar
Liquid biofuels

Hydropower
Hydropower
Solar
Bioenergy
BiogasMarineWind
Bioenergy
Liquid biofuels
BiogasMarineSource: IRENA (2021), Renewable Capacity Statistics 2021; & IRENA (2020), Renewable Energy
Statistics 2020, The International Renewable Energy Agency, Abu Dhabi.
7 Eduardo Von Sperling, ‘Hydropower in Brazil: Overview of Positive and Negative Environmental Aspects’, Energy Procedia, 18(2012), 110–18 <https://doi.org/10.1016/j.egypro.2012.05.023>.
8 Searle and Malins, 2015.
9 IRENA, Future of Solar Photovoltaic: Deployment, Investment, Technology, Grid Integration and Socio-Economic Aspects (AGlobal Energy Transformation: Paper), International Renewable Energy Agency, 2019, NOVEMBER <https://www.irena.org/-/
media/Files/IRENA/Agency/Publication/2019/Oct/IRENA_Future_of_wind_2019.pdf>; SolarPower Europe, ‘Solar Power2019–2023’, Global Market Outlook, 2018, 94.

Predictors of Success in a Greening World

118

Brazil’s highest potential in the short-term is from wind (Table 4), which would explain its
significant investment in wind capacity over the last decade. Solar potential is limited in part due
to large sections of the country (particularly the Amazon basin) being excluded from the level 1
zonation used to determine solar potential (Figure 41).

� Table 6: Estimates of Brazil's current technical potential for annual renewable energy
generation which is used to calculate its per capita renewable energy potential incomparison with its current average annual per capita usage.
BrazilOnshore wind generation potential (EJ/yr)

80

Offshore wind generation potential (EJ/yr)

25

Solar PV generation potential (EJ/yr)

15

Hydro generation potential (EJ/yr)

3

Bioenergy generation potential (EJ/yr)

14

Est. Total generation potential (EJ/yr)

123

Population (millions)

213

Average annual energy usage per person (MWh/yr/cap)

17

Total generation potential per person (MWh/yr/cap)

161

Source: See Appendix for Data Sources` Fig. 41: Estimates of solar photovoltaic potential (kWh/kWp) and practical potential
zonation used to determine Brazil’s economic potential for solar.

Source: Appendix for Data Sources

Photovoltaic power output (Practical potential, Level 0)
2.0

3.0

4.0

5.0

6.0 kWh/kWp N/APratical potential zonation:
LCOE average (country range)

Source: https://globalsolaratlas.info/
Please read the important information at the end of the document.
Lombard Odier · December 2021

Level 2

Level 1

Level 0

Predictors of Success in a Greening World

119

Policy and economic environment

Brazil’s own development bank, BNDES, is
one of the largest state-owned developmentbanks in the world and works quite efficiently.
Its presence in the country has been called anindustrial policy asset10. It has played a majorrole in many industrial policy strategies in
the past. However, the implementation of anindustrial policy is a particularly difficult task
in Brazil, due to a litany of past failures andthe resistance of many actors11. Such problems
were only exacerbated by the recent Lava Jato
investigation into corruption, involving thegovernment and state-owned enterprises,
notably its energy firm Petrobras12.
A stable factor in Brazil’s industrial policy ofthe past twenty years has been local content
requirements (LCRs)13 for the renewables
market. Brazil is one of the largest markets
for renewables that has a LCR14, and has thelargest wind energy potential in the region15.
Brazil implemented its LCR by restricting
access to low-cost financing from BNDES to
those manufacturers that use local inputs.
Since then, about 70% of Brazilian windand solar power capacity has been financed
through BNDES16. The LCRs started in 2002,
when the industry was still in its infancy,and have become more and more stringent
over time. For wind turbines, as of 2006 all
generating components (nacelle) must be
sourced locally, and the blades and tower must
contain at least 60% local content. These
rules were changed again in 2019 with a lower
LCR percentage but a renewed focus on otherpriorities, such as jobs and exports.
Many studies, including by the OECD and
IRENA, have pointed out the effectivenessof the Brazilian LCRs in creating a local

10 Felipe Silveira Marques João Carlos Ferraz David Kupfer, ‘Industrial Policy as an Effective Development Tool: Lessons from
Brazil’, in Transforming Economies: Making Industrial Policy Work for Growth, Jobs and Development, ed. by José M. SalazarXirinachs, Irmgard Nübler, and Richard Kozul-Wright (Geneva: ILO publishing, 2014), pp. 291–305 <http://www.ilo.org/global/
publications/books/WCMS_315675/lang--en/index.htm> [accessed 19 August 2021].
11 Wilson Suzigan, Renato Garcia, and Paulo Henrique Assis Feitosa, ‘Institutions and Industrial Policy in Brazil after Two Decades:
Have We Built the Needed Institutions?’, Economics of Innovation and New Technology, 29.7 (2020), 799–813 <https://doi.org/1
0.1080/10438599.2020.1719629>.
12 Eliza Massi and Jewellord Nem Singh, ‘Industrial Policy and State-Making: Brazil’s Attempt at Oil-Based Industrial
Development’, Third World Quarterly, 39.6 (2018), 1133–50 <https://doi.org/10.1080/01436597.2018.1455144>.
13 LCRs are used in many jurisdictions, in various forms and degrees. Brazil, India, and South Africa are the largest markets forrenewables that have LCR policies in place Morgan Bazilian, Victoria Cuming, and Thomas Kenyon, ‘Local-Content Rules for
Renewables Projects Don’t Always Work’, Energy Strategy Reviews, 32 (2020), 100569 <https://doi.org/10.1016/J.
ESR.2020.100569>.
14 Bazilian, Cuming, and Kenyon. 2020.
15 Andrew S. David and Dennis Fravel, U.S. Wind Turbine Export Opportunities in Canada and Latin America, Office of Industries
Working Paper, 2012 <https://www.usitc.gov/publications/332/ID-032_final.pdf> [accessed 19 August 2021].
16 Bazilian, Cuming, and Kenyon, 2020.

Predictors of Success in a Greening World

120

manufacturing base for wind and solar
power17. Local players were able to capture alarge market share for less sophisticated partsof the supply chain, but Brazil continued torely on foreign companies with local factories
to produce high-end parts, such as the windturbine’s nacelle18. Partly to comply with
the LCRs, many of these foreign companies
have established subsidiaries in Brazil,
spurring local manufacturing19. A downsideof LCRs might be that realisation rates ofrenewable energy projects are lower in Brazil
compared to other countries, which some havespeculated is due to higher costs caused by
LCRs20.

However, as can be seen in Figure 42, Brazil
does not currently have a competitive
advantage in any of them. It did havesignificant comparative advantage (close to 4)
in steel towers; however, RCA in this producthas seen a steep decline since 1995 and is
now below 1. RCA for other components has
fluctuated somewhat, but all remain below 1.
This suggests that while LCRs have somewhat
boosted local production, jobs, and evenexports in these products, they have not yet
enabled Brazil to become internationallycompetitive. The same is true for the solar
energy products that are included in ourdataset.

In our export dataset we find that Brazil has
increased its export values in five of the key
intermediate products we track that can beused for wind turbines over time21.

17 U. E. Hansen and others, ‘The Effects of Local Content Requirements in Auction Schemes for Renewable Energy in Developing
Countries: A Literature Review’, Renewable and Sustainable Energy Reviews, 127 (2020), 109843 <https://doi.org/10.1016/J.
RSER.2020.109843>.
18 Bazilian, Cuming, and Kenyon, 2020.
19 David and Fravel, 2012.
20 Benedict Probst and others, ‘The Short-Term Costs of Local Content Requirements in the Indian Solar Auctions’, Nature Energy,
5.11 (2020), 842–50 <https://doi.org/10.1038/s41560-020-0677-7>.
21 848360 Clutches, shaft couplings, universal joints; 848340 Gearing, ball screws, speed changers, torque converters; 841381
Pumps n.e.s.; 841290 Parts of hydraulic/pneumatic/other power engines; 730820 Towers and lattice masts, iron or steel. Notethat we do not track all components that can be part of wind turbines.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

121

� Fig. 42: Five wind turbine intermediate products and their RCA through time for

Brazil. Note that all intermediate products are generic and can be used for end uses
other than wind turbines, and that not all wind turbine parts are covered.

Revealed Comparative Advantage (RCA)

4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
1995-1999

2000-2004

2005-2009
Time period

2010-20142015-2019848360 Clutches, shaft couplings, universal joints
848340 Gearing, ball screws, speed changers, torque converters
841381 Pumps n.e.s.
841290 Parts of hydraulic/pneumatic/other power engines
730820 Towers and lattice masts, iron or steel

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World

122

Environmental credentials and policy ambition

Climate Action Tracker reports that Brazil’s
current policies are not consistent with
its NDC and its 2060 net zero target, nor
its Paris Agreement commitment to stop
illegal deforestation in the Amazon by 2030.
President Bolsonaro claims ambition toachieve carbon neutrality by 2050 rather than
2060, although official policy has not been yet
amended22. Its NDC was updated in 2020 andconfirmed its aim to reduce emissions by 37%
by 2025 and by 43% by 2030, but by updating
its carbon accounting for 2005, it increased
its base year emission calculations, making
the target less, rather than more, ambitious
in practice. In fact, Brazil now allows itself
to emit a third more greenhouse gases by
203023. As mentioned above, solar and wind
generation capacity are steadily increasing,which may be cause for some optimism;
however, energy infrastructure planning
continues to include fossil fuels such as coaland gas24.

Deforestation in the Brazilian Amazon, which
had been slowly creeping up from a low pointin 2011, has accelerated dramatically since
President Jair Bolsonaro took office in 2019.
Prioritising economic gains from mining
and agriculture, the current government hasrolled back protective policies and weakened
enforcement mechanisms against illegal
deforestation25. In 2019, Norway and Germany
halted their contributions to the Brazilian
government’s Amazon Fund, whose objectives
were seen to have been undermined by
the government’s actions. Earlier this year,
President Bolsonaro appeared to change
his stance, declaring his intention to protect
the Amazon, subject to receiving financial
contributions amounting to around 20 billion
US dollars from the international community.
This has been widely met with criticism26, but
Brazil did surprisingly join the 100 nations
that signed the global deforestation pledge
at COP26, pledging to end and reverse
deforestation by 2030.

22 Reuters, Jake Spring, and Lisandra Paraguassu, ‘Brazil’s Bolsonaro, under U.S. Pressure, Vows Climate Neutrality by 2050’,
Reuters (Brasilia, 22 April 2021) <https://www.reuters.com/business/environment/bolsonaro-says-brazil-will-reach-climateneutrality-by-2050-2021-04-22/>.
23 The Economist, ‘How Climate Targets Compare against a Common Baseline’, The Economist (London, 7 August 2021).
24 CAT, ‘Country Summary: Brazil’, Climate Action Tracker, 2020 <https://climateactiontracker.org/countries/brazil/> [accessed
27 July 2021].
25 cf. Jonathan Watts, ‘Amazon Rainforest “Will Collapse If Bolsonaro Remains President”’, The Guardian (London, 14 July 2021);
Ernesto Londoño, ‘Bolsonaro’s Sudden Pledge to Protect the Amazon Is Met With Skepticism’, New York Times (New York, 21
April 2021) <https://www.nytimes.com/2021/04/21/world/americas/bolsonaro-climate-amazon.html>.
26 Londoño, Ernesto, ‘Bolsonaro’s Sudden Pledge to Protect the Amazon Is Met With Skepticism’, New York Times (New York, 21
April 2021) <https://www.nytimes.com/2021/04/21/world/americas/bolsonaro-climate-amazon.html>

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

123

Green strengths and opportunities

Over 15% of Brazil’s energy demand is met by
ethanol. While not originally a green policy
but a sugarcane and energy price stabilisation
tool, Brazil’s ethanol industry was rebranded
as an environmentally friendly industry in theearly 2000's27. Brazil now accounts for 25% of
global ethanol production. Flex-fuel cars, thatcan use gasoline, ethanol, or a mixture of thetwo, accounted for over half of Brazil’s totalcars by 2012. While biofuels have negativeside effects, including potentially crowding
out food crops, and in Brazil may indirectly
contribute to deforestation of the Amazon
rainforest, Brazilian sugarcane ethanol is seen
as having one of the lowest carbon intensities
of commercially available biofuels28. Becauseof its credentials as a low-carbon fuel, ethanol
is also part of our list of green products.
With a PCI of -1.12, it is the third mostimportant green product of Brazil by revealed
comparative advantage (RCA), behind sisal/
agave binder twine (PCI: -1.73) and hydraulicturbines and water wheels > 10,000 kW (PCI:0.08).
One challenge to flex-fuel cars might be
the projected future dominance of electricvehicles, which appears to be the winninggreen vehicle strategy in much of Europe
and the US29. While ahead of the green
transportation curve right now, Brazil might
struggle to reduce transportation emissions
further and leverage its ethanol technology if
it delays its EV development and deployment.
This is doubly problematic as, in contrast
to biofuels, batteries are expected to bringsignificant future energy efficiency and costsavings30,31. Sugarcane ethanol fuel could
however, have potential for net-zero aviation32.

27 Green Industrial Policy: Concept, Policies, Country Experiences, ed. by Tilman Altenburg and Claudia Assmann (Geneva, Bonn:
UN Environment; German Development Institute / Deutsches Institut für Entwicklungspolitik (DIE), 2017) <https://www.
die-gdi.de/buchveroeffentlichungen/article/green-industrial-policy-concept-policies-country-experiences/> [accessed 19
August 2021].
28 Altenburg and Assmann, 2017.
29 Ewa Krukowska and Tara Patel, ‘EU Aims to Have 30 Million Electric Cars on the Road by 2030’, Bloomberg, 3 December 2020.
30Way and others, 2021.
31 M. Grubb and others, ‘Induced Innovation in Energy Technologies and Systems: A Review of Evidence and Potential Implications
for CO 2 Mitigation’, Environmental Research Letters, 2021 <https://doi.org/10.1088/1748-9326/abde07>.
32 Deepak Kumar, Stephen P. Long, and Vijay Singh, ‘Jet Fuel from Sugarcane? It’s Not a Flight of Fancy’, The Conversation, 21
November 2017 <https://theconversation.com/jet-fuel-from-sugarcane-its-not-a-flight-of-fancy-84493>.

Predictors of Success in a Greening World124` Fig. 43: Brazil’s green export products divided into current strengths and potential
opportunities. Size of product indicates country’s current RCA, colours represent
product categories (see legend)33
Brazil: Current Strengths
Compressors forregrigerating equipment

1

0

-1

-2

Manganese oxide
other thanmanganese dioxide

Ethanol>80% pure2
Product Complexity Index

2

Product Complexity Index

Brazil: Potential Strengths

0.14

0.16

0.18

0

-1
Towers andlattice masts,
iron or steel

0.06

Proximity to Country

Management of Solid and Hazardous Waste and Recycling Systems
Natural Resource Protection
Energy Efficiency
Heat and Energy Management
Gas Flairing Emission Reduction
EfficientConsumptionof EnergyTechnologiesandCarbonCaptureandStorage
Environmental Monitoring, Analysis and Assessment Equipment
Renewable Energy
Noise and Vibration Abatement
Resources and Pollution Management

Phenolic resins,in primary forms

1-2

Binder or baler twine,of sisalor agave

0.12

Profileprojectors, nes

0.08

Anhydrous
ammonia

0.10

0.12

Proximity to Country

0.14

0.16

Waste Water Management and Potable Water Treatment
Air Pollution Control
Natural Risk Management
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
OthersEnvironmentalPreferableProductsbasedonEnd-UseorDisposalCharacteristics
Waste Management, Recycling and Remediation
Water supply
Bubbles are sized by RCA

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

33 For an in-depth explanation of how to read this figure, please refer to the section Green strengths and opportunities within the
China case study.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

125

Summary` Brazil’s green competitiveness has seen a declining trend in recent decades: its global rankin Green Complexity Index fell from 48 to 93, while its Green Complexity Potential rank
dropped from 43 to 72.

` The decline in Green Complexity Potential and average proximity to products across all

green categories suggests that reversing this negative trend in green competitiveness will
become increasingly difficult.

` Absolute export values in green products increased between 1995 and 2011-2015, but havesince declined.

` Brazil’s government has been subject to international criticism for its failure to combat
deforestation in the Amazon region, which has increased dramatically since 2019.

` Brazil has considerable green energy potential and renewable energy capacity has grownsignificantly in the last decade, particularly in wind.

` Financing from Brazil’s development bank for renewable energy projects has been

contingent on Local Content Requirements, which are thought to have contributed to theestablishment of a local manufacturing base for renewable generation equipment. This has
led to an increase in local manufacturing and jobs, but our analysis indicates that Brazil has
lost, rather than gained, international competitiveness in these components.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

127

Australia
Policy ambition and green complexity
Australia, once self-referenced as the “smart
country1”, has seen a dramatic decline
in its economic complexity (ECI) with aconcurrent decline in GCI - currently ranking
125th in ECI, 157th in GCI and 112th in GCP.
Australia’s reliance on the extractive industry
for its economic growth is a likely driverbehind its low ranking in green complexity.
Australia’s rank in ECI, GCI and GCP has
been on a downward trajectory since the startof our analysis: in the 1995-1999 period it
ranked 60th for ECI and 57th for both GCI
and GCP.
In its updated COP26 Nationally Determined
Contribution (NDC) to the UNFCCC,
Australia has committed to loweringgreenhouse gas emissions by 26-28% below
2005 levels by 2030, confirming its previous
2015 submission2, but with little explanationof how it will meet these reductions.
Australia’s prime minister, Scott Morrison,has very reluctantly agreed to a nationwide
net zero target by 2050, but remains noncommittal to actual climate change action3.
Many of Australia’s states and territories,

however, have set binding net-zero targets
and in general have set more ambitious goalsof their own4.
Only 1.6% of Australia’s exports can bedeemed green, capturing a total of just 0.23%
of the global export market in green products,
a share which has almost halved since ourdataset began; it was 0.44% in the 1995-1999
period. Russia and Brazil, also resource richcountries with a similar sized economies,
capture about double Australia’s share.
Spain, which has an equally sized but morediversified economy, has captured 1.55% of
the global export market in green products.
Australia’s energy consumption is still
dominated by coal, accounting for about
56% of electricity production in 20195.
However, renewables are rapidly gaining
through residential and community adoption,
generally becoming a disruptive force
for change. More than 27% of Australia’s
electricity is now sourced from renewables,up from 17% only four years ago, with fallingelectricity prices causing financial difficulties
for incumbent technologies6.

1 https://medium.com/@ashleyhamiltonrice/australia-the-smart-country-48dc740aca39 .
2 UNFCCC, ‘Australia’s First Nationally Determined Contribution towards Achieving the Objective of the United Nations
Framework Convention on Climate Change (Updated Submission)’, 2020 <https://www4.unfccc.int/sites/ndcstaging/
PublishedDocuments/Australia First/Australia NDC recommunication FINAL.PDF>.
3 RNZ, ‘Australia PM Refuses to Set “net Zero by 2050” Climate Target as Global Warning Issued’, Radio New Zealand, 10 August2021 <https://www.rnz.co.nz/news/world/448880/australia-pm-refuses-to-set-net-zero-by-2050-climate-target-as-globalwarning-issued>.
4 Don Henry and Sangeetha Chandra-Shekeran, ‘State Leadership on Emissions Reduction Is Crucial’, University of Melbourne
Pursuit, 3 May 2021 <https://pursuit.unimelb.edu.au/articles/state-leadership-on-emissions-reduction-is-crucial>.
5 Energy.gov.au, ‘Australian Electricity Generation - Fuel Mix’, Department of Industry, Science, Energy and Resources Website.
<https://www.energy.gov.au/data/australian-electricity-generation-fuel-mix>.
6 Clean Energy Council, Clean Energy Australia Report 2021, https://assets.cleanenergycouncil.org.au/documents/resources/
reports/clean-energy-australia/clean-energy-australia-report-2021.pdf

Predictors of Success in a Greening World

128

Australia at a glance

25,6871,330,900

Population (thousands)

GDP (current US$, millions)

52,518GDP / capita (US$, PPP)

157

125
ECI rank

GCI rank

112
GCP rank

1.60 %
0.20 %

Share of green in
total exports

Global share of green
exports

Aluminium Hydroxide
Highest RCA green product

Electric signal, safetycontrols
Most complex competitive

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Lombard Odier · December 2021

Predictors of Success in a Greening World

129

none

1.1°C

Net zero target

Temp change since 1961

0.31 (rank: 31/230)

64

CO2 intensity (kg/PPP$ GDP)

3,408

Avg energy use(MWh/yr/cap)

19

Global Energy Potential(MWh/yr/cap)

Climate risk index rank

121
Extreme risk index rank

9.2% (143/213)%
Renewable energy consumption

2%
Share of green in covid recovery

Predictors of Success in a Greening World

130

Trends in green competitiveness

While its green complexity ranking dropped,
Australia’s absolute trade value did increase
in almost all green product categories until
the 2011-2015 period and declined sincethen for some. Its top three largest export

categories are efficient consumption ofenergy technologies and carbon captureand storage, wastewater management andpotable water treatment, and renewableenergy, as shown in Figure 44.

` Fig. 44: Export value over time by environmental category, Australia
1750

Trade value ($ 1,000)

1500
1250
1000
750
500
250
0
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version)
Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World131

The average proximity of Australia’s
production capabilities to green products has
been declining for all green categories since
the early 2000s (Figure 45). This is reflected

in its losses in GCI and GCP rank and implies
that it is becoming increasingly harder forAustralia to take advantage of the greening
global economy.

` Fig. 45: Average proximity over time by environmental category, Australia
0.25
0.23

Average proximity

0.21
0.19
0.17
0.15
0.13
0.11
0.09
0.07
0.05
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World132` Fig. 46: Largest importers of Australian green exports. Only countries that import >2%of Australian exports are shown separately.

Papa New
Guinea
5.2%

China
6.6%
USA
16.2%

Singapore
3.9%

Japan
5.0%

Others28.7%

New Zealand
11.6%

Indonesia
4.5%

UK
3.4%

Nether_
lands
2.9%

South
Germany
Korea
2.5%
2.5%

Thailand
2.6%

MalaysiFrancea2.2%
2.3%` Fig. 47: Largest importers of Australian overall exports. Only countries that import>2% of Australian exports are shown separately.

Others
15.3%

China
39.1%

Japan
14.6%

South
Korea
6.7%

India
5.4%

UK
3.7%

USA
3.6%

New
Ma_ Singa_
Hong_
Zealanlaysia porekongd2.2% 2.2%
2.0%
2.0%

Source:Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

The US is the largest buyer of Australia’s green exports, followed by New Zealand, China,
Japan, and other countries in the Asia Pacific region, as well as some European countries.
Figure 47 visualises this breakdown.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

133

Trends in green energy

Australia is a large, sparsely populated andmostly dry land mass that lies predominantlyin the tropics and hence has an abundance ofsunshine. However, it also has an abundanceof land available for mining and large coaland gas resources. A significant percentageof the population are supportive of action on
climate change, but the current conservative
federal government appears to be prioritising
the local fossil fuel industry, which provides
significant export income. This has led todelays in investment to capitalise on the
country’s abundant renewable potential,with only a few independent states declaring
binding net zero goals and supporting largescale renewable projects.
Most of the growth of renewables over thelast decade has been due to expansion ofhydropower, with some wind and mostly
distributed solar (Figure 48). Australia has
only limited additional hydropower capacity,
but abundant wind resources in the south; anaverage LCOE of less than 10c/kWh (USD)
for solar; and continuing public pressure foraction on climate change following someextreme national-scale wildfire events.

� Fig.48: Australia’s renewable energy generation capacity by source

Renewable energy capacity (Gw)

25

20

15

10

5

0

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

Year
Totalenergy
renewable energy
Total renewable
Hydropower
MarineSolar
Bioenergy
Solar

Hydropower
MarineWind
Liquidbiofuels
BioenergyWind
Biogas

Source: IRENA (2021), Renewable Capacity Statistics 2021; & IRENA (2020), Renewable Energy
Statistics 2020, The International Renewable Energy Agency, Abu Dhabi.

Predictors of Success in a Greening World134

It will therefore be difficult to stem thetide of investment in renewables given
the improving economics, growing local
markets for green energy in Asia and thecountry’s huge green energy potential (Table
7). With a high potential and relatively

small population, Australia has the highest
total generation potential per person of
any country evaluated in this report, and istherefore one of the countries best placed tobuild a significant export industry for green
energy.

` Table 7. Estimates of current economic potential of renewable resources per personcompared with current average annual per capita usage for Australia.

Australia
Onshore wind generation potential (EJ/yr)

230

Offshore wind generation potential (EJ/yr)

89

Solar PV generation potential (EJ/yr)

8

Hydro generation potential (EJ/yr)<1

Bioenergy generation potential (EJ/yr)

8

Est. Total generation potential (EJ/yr)

327

Population (millions)26

Average annual energy usage per person (MWh/yr/cap)

64

Total generation potential per person (MWh/yr/cap)

3,496

Source: See Appendix for Data Sources` Fig. 49: Estimates of solar photovoltaic potential (kWh/kWp) and practical potential
zonation used to determine Australia’s economic potential for solar.

Photovoltaic power output (Practical potential, Level 0)
2.0

3.0

4.0

5.0

6.0 kWh/kWp N/APratical potential zonation:
LCOE average (country range)

Source: https://globalsolaratlas.info/
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Lombard Odier · December 2021

Level 2

Level 1

Level 0

Predictors of Success in a Greening World

135

Policy and economic environment

Australia’s economy has grown every year
from 1992 up until 2019, only to suffer arecession again in 2020 of just 2.4% in the
COVID-19 pandemic7. Australia's extraction
economy was fuelled to a large degree byhigh economic growth in China which has
also seen a decline during the pandemic.
Fossil fuels and other commodities
accounted for nearly three quarters ofAustralia’s export growth between 1995 and20208.
Its current government has a lacklustre policy
record on climate change action and greening
its economy. Australia was one of thesignatories to the 1998 Kyoto protocol, but
for a long time opposed the ideas embodied
in the climate action plan. It did not ratify the
Kyoto protocol until 2007, an indication of
the partisan nature of the country’s actions
on climate. A proposal to implement a
carbon tax in 2008 faced criticism because
it might lower Australia’s competitiveness,but an emissions trading scheme was finallyadopted in 2012 during a labour government.
However, after just one year of operation it
was repealed in 2013 by the newly electedconservative Abbot Coalition9. In the2019 election that re-elected the Liberalconservative party into government, theopposition labour party proposed plans to cut
emissions by 45% in 2030, and the Liberalparty’s strong rejection of that plan has been
partly credited for their win10.
In 2020, China, the largest importer ofAustralia’s resources, imposed an unofficial
ban on the use of Australian coal in its power
plants11. While China has struggled to source
its coal elsewhere, Australia has diverted
shipments to other large coal users, including
India and Brazil, after an initial slump inexports following the ban12. However, India's
coal ministry has also recently claimed that it
plans to eliminate coal imports by 202413.

7 Austrade, Why Australia Benchmark Report 2021, 2021 <https://www.austrade.gov.au/benchmark-report/resilient-economy>.
8 Connor MacDonald and Peter Sloman, ‘Resource Extraction, Economic Growth, and the Climate Dilemma in Canada andAustralia’, The Political Quarterly, 91.4 (2020), 780–85 <https://doi.org/10.1111/1467-923X.12902>.
9 Kate Crowley, ‘Up and down with Climate Politics 2013–2016: The Repeal of Carbon Pricing in Australia’, Wiley Interdisciplinary
Reviews: Climate Change, 8.3 (2017), e458 <https://doi.org/10.1002/WCC.458>.
10 MacDonald and Sloman.
11 Su-Lin Tan, ‘China-Australia Relations: US Coal Continues to Fill Void Left by Ban on Australian Exports, Canberra Report Says’,
South China Morning Post (Hong Kong, 30 June 2021).
12 Rory Simington, ‘Australian Coal Exports Bounce Back from China’s Ban’, Wood Mackenzie, 4 March 2021 <https://www.
woodmac.com/news/opinion/australian-coal-exports-bounce-back-from-chinas-ban/>.
13 S&P Global Platts, https://www.spglobal.com/platts/en/market-insights/latest-news/coal/101321-coal-crisis-a-litmus-test-forindias-resolve-to-eliminate-imports.

Predictors of Success in a Greening World

136

Environmental credentials and policy ambition

Australia’s CO2 emissions per capita areamong the highest in the world and, in 2018,
were the highest among OECD countries
together with Canada14.
In its NDC and accompanying policy,
Australia stresses the need for technologicalinnovation to combat climate change. Its Low
Emissions Technology Statement points tofive priority areas for investment in Australia:
clean hydrogen, energy storage, low carbon
materials (steel and aluminium), carbon
capture and storage, and soil carbon15. Manyof these technologies are still in development
and not yet tested at large scale, although

it seems possible that clean hydrogen cantake off on a relatively short term, given the
country’s renewable potential16.
Australia has made plans to spend more thanmost countries on post-COVID-19 recovery,
nearly 10% of GDP. That is the 4th largest
in the University of Oxford Global Recovery
Observatory dataset, behind only Spain,
South Korea, and the UK. However, only afraction of that has been allocated to green
projects. Because of its low GCI and GCP
scores, this means Australia has ended up in
our missed opportunities section.

14 Tan, Su-Lin, ‘China-Australia Relations: US Coal Continues to Fill Void Left by Ban on Australian Exports, Canberra Report
Says’, South China Morning Post (Hong Kong, 30 June 2021)
15 UNFCCC, ‘Australia’s First Nationally Determined Contribution towards Achieving the Objective of the United Nations
Framework Convention on Climate Change (Updated Submission)’.
16 Note that the production of green ammonia can be done with seawater using desalination which represents only a small fractionof the ammonia production costs.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

137

Green strengths and opportunities

Australia’s current strengths andopportunities are highlighted in Figure
5017. Australia only has few green strengths.
Most of the higher PCI products that are
Australia’s strengths are either wastewater
management and potable water treatment
products or are a cleaner or more resource
efficient alternative to mainstream practices.
The green product with the largest revealed
comparative advantage (RCA) in Australia,
aluminium hydroxide, can be used inchemical recovery systems for wastewater
management18. Australia’s opportunities havevery low proximity to the country's current
capabilities, indicating a low probability ofdeveloping a competitive advantage, barring
decisive action. In addition, opportunities
with a high PCI have the lowest proximity.

This means that products that are closest
to Australia’s current strengths, suchas undenatured ethyl alcohol, could becomparatively easier to develop locally
but are unlikely to provide significant
future growth in product complexity andsophistication.
Even though Australia only has few green
product export strengths, and a large shareof its exports relies on fossil fuels and lowcomplexity resource extraction, Australia
is seen by many as a potential green
energy powerhouse. Its large land area,
long coastline and abundant sunshine are
significant assets for harnessing cheap wind
power and solar energy. Indeed, there aremajor plans in place to make the northernstates green energy hubs for export.

17 For an in-depth explanation of how to read this figure, please refer to the section Green strengths and opportunities within the
China case study.
18 Aluminium hydroxide also has other end uses, such as in medicine and as a precursor for other aluminium products. We do nottrack the specific usage in every case. See Section 2. What is a green product? on page 15, for the definition of a green product.

Predictors of Success in a Greening World138` Fig. 50: Current green strengths and opportunities of Australia.19
Australia: Potential Strengths

Australia: Current Strengths
Electric signal safety& traffic controls, nes

2

-0.5

Product Complexity Index

Product Complexity Index

0.5
Aluminiumhydroxide

0.0

Machines andmechanicalappliances nes

Photogrammetricalsurveying instruments
appliances

-1.0

1

0

-1

Undernatured
ethyl alcohol>80% byvolume

-2

-1.5
0.08

0.10
0.12
Proximity to Country

0.14Management of Solid and Hazardous Waste and Recycling Systems
Natural Resource Protection
Energy Efficiency
Heat and Energy Management
Gas Flairing Emission Reduction
EfficientConsumptionof EnergyTechnologiesandCarbonCaptureandStorage
Environmental Monitoring, Analysis and Assessment Equipment
Renewable Energy
Noise and Vibration Abatement
Resources and Pollution Management

0.02

0.04

0.06
0.10
0.08
Proximity to Country

0.12

Waste Water Management and Potable Water Treatment
Air Pollution Control
Natural Risk Management
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
OthersEnvironmentalPreferableProductsbasedonEnd-UseorDisposalCharacteristics
Waste Management, Recycling and Remediation
Water supply
Bubbles are sized by RCA

Source:Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

19 For an in-depth explanation of how to read this figure, please refer to the section Green strengths and opportunities within the
China case study.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

139

Summary` Australia has seen a significant decline in both its economic complexity and green
complexity over the last two decades.

` Australia relies heavily on the export of fossil fuels and minerals for its economic growth,particularly exports to China.

` Australia is a high-income country, but has increasingly relied on low-complexity exports

and therefore ranks low on the economic complexity index as well as the green complexity
index and potential.

` Australia’s current conservative government has a track record of stalling action on climatechange.

` However, because of its vast land mass, ample wind resources, and low average solar costs,
Australia has the highest green potential of all the countries evaluated in this report, andtherefore has the potential to become a powerhouse for renewable energy exports in the
future.

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Lombard Odier · December 2021

Predictors of Success in a Greening World141

United Arab Emirates case study
Policy ambition and green complexity
As a major exporter of petroleum, theUnited Arab Emirates relies primarily
on its extractive industry and therefore
has relatively low manufacturing
competitiveness. Accordingly, its green
complexity ranking is low, with a GCI of
59 and a GCP of 75. However, both indiceshave seen a positive trend over the study
period, suggesting that the UAE’s productive
capabilities are moving closer to thoserequired to competitively produce complex
green products.
The UAE’s per capita emissions areamong the world’s highest. In 2020, theUAE submitted a nationally determined

contribution (NDC) target of decreasing
emissions by 23.5% by 20301. As of 2019,fossil fuels still accounted for nearly 97% of
the country’s energy mix2.
The UAE was the third-largest petroleum
producer in OPEC in 2019 behind Saudi
Arabia and Iraq and plans to continue
increasing production of petroleum3.
This strategy may backfire in the coming
decade, increasing the country’s risk of
stranded assets in a future low-carbon global
economy.

1 CAT, ‘CAT Climate Target Update Tracker: UAE’, Climate Action Tracker, 2020 <https://climateactiontracker.org/climatetarget-update-tracker/uae/> [accessed 19 August 2021].
2 Ritchie and Roser, ‘Energy’.
3 EIA, ‘Country Analysis Executive Summary: United Arab Emirates’, Independent Statistics & Analysis, 2020.

Predictors of Success in a Greening World

142

United Arab Emirates at a glance

9,890

421,124

Population (thousands)

GDP (current US$, millions)

69,957GDP / capita (US$, PPP)

59

104
ECI rank

GCI rank

75
GCP rank

3.52 %
0.46 %

Share of green in
total exports

Global share of green
exports

Limestone materials
Highest RCA green productDistilling or
rectifying plant
Most complex competitivePredictors of Success in a Greening World

143

none

1.6°C

Net zero target

Temp change since 1961

0.30 (rank: 32/230)

89

CO2 intensity (kg/PPP$ GDP)

94

Avg energy use(MWh/yr/cap)

130

Global Energy Potential(MWh/yr/cap)

Climate risk index rank163
Extreme risk index rank

0.1% (196/213)%
Renewable energy consumption

2%
Share of green in covid recovery

Predictors of Success in a Greening World

144

Trends in green competitiveness

The United Arab Emirates rank relatively
low in green competitiveness and overall
complexity, but have increased their position
considerably over the course of the study
period. GCI has risen from its initial rank of
117 to its current rank of 59; GCP increased
from 120 to 75.

Over the same period, overall ECI rose fromrank 138 to 104. This is thought to be result ofa long-term strategy for the UAE's led mostpublicly by Dubai, which has consistently
progressed a pronounced diversification
strategy4.

` Fig. 51: Export value over time by environmental category, United Arab Emirates
3500

Trade value ($ 1,000)

3000
2500
2000
1500
1000
500
0
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year
Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).
4 Seric & Tong, 2019, Progress and the future of economic diversification in the UAE, https://iap.unido.org/articles/progress-andfuture-economic-diversification-uae.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

145

Absolute trade values in most green
categories have also increased at anaccelerating rate since the early 2000’s.
The largest categories in terms of absolute
trade are efficient consumption of energy
technologies and carbon capture andstorage; renewable energy, wastewater
management and potable water treatment;
and air pollution control. The share of green
products in the UAE’s overall exports has also
risen, from 1.9% to 3.5%.

` Fig. 52: Average proximity over time by environmental category,
United Arab Emirates.
0.18

Average proximity

0.16
0.14
0.12
0.1
0.08
0.06
0.04
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year
Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World

146

Average proximity of the UAE’s productive
capabilities to products within each category
fluctuated between the start of the period
and the early 2000s, but has been on a clear
upwards trajectory since 2009-13. This trend
is especially pronounced in the category“Natural Risk Management”, which contains
products the UAE seem to be particularly
well suited to produce.
The largest importers of the UAE’s green
products are Saudi Arabia (15.3%) and Oman(14%), followed by India (8.5%) (Figure 53).
Nearly a third of the UAE’s green products
are imported by countries with a share of lessthan 2% of its green exports.

Notably, the distribution of imported sharesfor the UAE’s overall exports differs from thatfor green exports, with India (10.8%), Japan
(9.7%) and Switzerland (6.1%) as the largest
importers (Figure 54). This is likely driven
by the large share of petroleum in overall
exports, which Oman and Saudi Arabia
have little need to import. The geopolitical
implications of trade relations may thereforechange if the UAE shift their export basket
towards non-extractive, and especiallytowards green, industries.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

147` Fig. 53: Largest importers of the UAE green exports. Only countries that import >2% of
the UAE's exports are shown separately.

India
8.5%

Saudi Arabia
15.3%

Others
31.7%

Iraq
8.3%

USA
6.2%

China
4.3%

Bah_
rain
2.6%

Koweit
4.8%

Iran
2.3%

Egypt
2.1%

Oman
14.0%

` Fig. 54: Largest importers of the UAE overall exports. Only countries that import >2%of the UAE's exports are shown separately.

Saudi Arabia
7.2%

Switzerland
6.1%

India
10.8%

China
5.9%

Others
34.7%

Japan
9.7%

Iraq
5.5%

Oman
4.4%

South
Korea
3.5%

Singapore
4.3%

Iran
2.9%

Thai_
land
2.6%

Pakistan
2.4%

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World

148

Trends in green energy` Table 8. Estimates of current technical potential of renewable resources per personcompared with current average annual per capita usage for the UAE.

United Arab Emirates
Onshore wind generation potential (EJ/yr)<1

Offshore wind generation potential (EJ/yr)-

Solar PV generation potential (EJ/yr)

3

Hydro generation potential (EJ/yr)-

Bioenergy generation potential (EJ/yr)-

Est. Total generation potential (EJ/yr)

3

Population (millions)

10

Average annual energy usage per person (MWh/yr/cap)

89

Total generation potential per person (MWh/yr/cap)

94

Source: See Appendix for Data Sources

The UAE has the seventh largest supplyof proven oil reserves in the world5 and so
stands to lose much from a rapid transition
away from fossil fuels. They are not as
blessed in renewable resources, but havesufficient solar potential to meet their current
high average annual energy usage per person.

5

It is possible that the UAE will try to develop
a green energy export capacity, given its
high irradiance levels and consequent low
average costs for solar (Figure 55); its need toeventually diversify away from fossil fuels;
and its proximity to the large increasingly
green market of Europe.

UAE facts and figures, https://www.opec.org/opec_web/en/about_us/170.htm

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Lombard Odier · December 2021

Predictors of Success in a Greening World149` Fig. 55: Estimates of solar photovoltaic potential (kWh/kWp) and practical potential
zonation used to determine the UAE’s economic potential for solar

Photovoltaic power output (Practical potential, Level 0)
2.0

3.0

4.0

5.0

6.0 kWh/kWp

Source: https://globalsolaratlas.info/

Pratical potential zonation:
LCOE average (country range)

Level 2

Level 1

Level 0

Predictors of Success in a Greening World

150

Policy and economic environment

The United Arab Emirates have historicallyrelied largely on petroleum extraction as
the main component of economic activity.
However, the government’s economic agenda
includes stated aims to grow manufacturing
capacity in sectors such as plastics,
machinery, renewable energy equipment
and others6. As a major oil producer, theUAE face a considerable threat of stranded
assets in a world of declining renewableand electric vehicle costs and increasing
ambition to transition to net zero around theworld, rendering industrial diversification
and upgrading an essential and pressing
challenge.

6 UAE, ‘Operation 300bn, the UAE’s Industrial Strategy’, The United Arab Emirates’ Government Portal, 2021 <https://u.ae/en/
about-the-uae/strategies-initiatives-and-awards/federal-governments-strategies-and-plans/the-uae-industrial-strategy>[accessed 19 August 2021].
7 UAE, ‘Operation 300bn, the UAE’s Industrial Strategy’, The United Arab Emirates’ Government Portal, 2021 <https://u.ae/en/
about-the-uae/strategies-initiatives-and-awards/federal-governments-strategies-and-plans/the-uae-industrial-strategy>[accessed 19 August 2021].

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Predictors of Success in a Greening World

151

Operation 300bn
Operation 300bn, the UAE government’s main industrial strategy, was launchedin March 2021 with the stated aim to develop the UAE’s industrial sector and“raise [its] contribution to the GDP from AED 133 billion to AED 300 billion by2031”. The plan has 6 objectives, which include creating an attractive businessenvironment for local and foreign investors in industry; supporting industrialisationand international competitiveness; and stimulating innovation. Its 11 target sectors
include agriculture, pharmaceuticals, electronics, petrochemicals, and machinery,
as well as hydrogen. The strategy is to be implemented by the Ministry of Industry
and Advanced Technology and relies on the Emirates Development Bank (EDB) to
provide financing to its target sectors7.

Predictors of Success in a Greening World

152

Environmental credentials and policy ambition

The UAE emitted about 190 million tonnesof CO2 in 2019; a notable drop from its
peak of nearly 240 million tonnes in 2015.
In contrast, the United States emitted over
5 billion tonnes, and China, the world’s
largest emitter, over 10 billion tonnes in 2019.
However, its per capita emissions are among
the highest in the world. In 2016 it emittedroughly 21 tonnes of CO2 per person, putting
it well ahead of the US (14.8 tonnes), let alone
the global average of 4.9 tonnes8.

by 203012. In 2019 (the most recent year forwhich data could be collected), renewables
and nuclear energy accounted for only about
3% of the UAE’s energy mix13, suggestingthat this target was not reached. The UAE’s
Energy Strategy 2050’s stated aim is toincrease the share of clean energy, which
includes renewables as well as nuclear, to
50% of the energy mix by 2050, and to reduceenergy consumption by 40% over the same
timeframe14.

The UAE is not an Annex-1 country9 andtherefore is not required to reduce its
emissions as rapidly under the United
Nations Framework Convention on Climate
Change (UNFCC). However, it has ratified
the Paris Agreement and pledged to takeaction to reduce emissions10. The UAE’s NDC
to the Paris Agreement originally contained
no overall emissions reduction target, but
merely a target to increase the share of
renewables and nuclear in the energy mix
to 24% by 202111. It was updated in 2020
with a target to reduce emissions by 23.5%

The UAE has been slow to spend on green
recovery after the COVID-19 pandemic. Even
though it is a high income country, it has only
made plans to spend around 0.1% of GDP on
recovery, none of which has been deemedgreen by the University of Oxford’s Global
Recovery Observatory. This is potentially amissed opportunity, as the UAE has shown
clear progress in increasing its GCI rank
and its stated intentions to upgrade its
manufacturing capabilities.

8 Ritchie and Roser, ‘CO2 and Greenhouse Gas Emissions’.
9 Within the UNFCCC regime, the term “Annex I countries” refers to a list of countries that includes members of the Organisation
for Economic Co-operation and Development (OECD) as well as economies in transition.
10 UAE, ‘The UAE’s Response to Climate Change’, The United Arab Emirates’ Government Portal, 2021 <https://u.ae/en/
information-and-services/environment-and-energy/climate-change/theuaesresponsetoclimatechange> [accessed 19 August2021].
11 CAT, ‘Country Summary: UAE’.
12 CAT, ‘CAT Climate Target Update Tracker: UAE’.
13 Ritchie and Roser, ‘Energy’.
14 UAE, ‘UAE Energy Strategy 2050’, The United Arab Emirates’ Government Portal, 2021.

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Lombard Odier · December 2021

Predictors of Success in a Greening World153

The number of green strengths for the UAE
are significantly exceeded by the number ofpotential opportunities (Figure 56). Overallproximity of its productive capabilities
to green products is low, and there is anegative correlation between proximity andcomplexity. This implies an industrial policy
trade-off between aiming for sophisticatedproducts and aiming for those with a highchance of success. Nevertheless, the trends
are encouraging.
A high complexity product the UAE exports
competitively is distilling or rectifying
equipment, which includes distilling
apparatus for desalination systems, biogas
refinement equipment and solvent recycling
plants. The green product which the UAE
export most competitively are limestonematerials for manufacture of lime or cement,
used in chemical recovery systems for
wastewater management. This, however,is a product with a low complexity rank.
One of the easiest new opportunities for the
UAE to transition into would be methanol
made from renewable sources, which is
low in technological sophistication but
has huge growth potential. By contrast,
machines, and mechanical appliances, which
includes those used in a range of areas ofenvironmental management such as waste,
wastewater, drinking water production andsoil remediation, ranks significantly higher incomplexity. However, it is also very far fromthe UAE’s existing capabilities and would bea more difficult and riskier prospect.

Predictors of Success in a Greening World154` Fig. 56: The UAE’s green export products divided into current strengths and potential
opportunities. Size of product indicates the UAE’s current RCA; colours represent
product categories (see legend)15
UAE: Potential Opportunities

Distilling or rectifying
plant

Machines andmechanicalappliances nes

0.5

2Parts andaccessories forsurveying etc
instruments

0.0

-0.5

-1.0

Product Complexity Index

Product Complexity Index

1.0

UAE: Current Strengths

0.12

0.18
0.16
0.14
Proximity to Country

0

-1

-2

Limestone materials for
manufacture of lime or
cement0.10

Methyl alcohol

1

0.20

Management of Solid and Hazardous Waste and Recycling Systems
Natural Resource Protection
Energy Efficiency
Heat and Energy Management
Gas Flairing Emission Reduction
EfficientConsumptionof EnergyTechnologiesandCarbonCaptureandStorage
Environmental Monitoring, Analysis and Assessment Equipment
Renewable Energy
Noise and Vibration Abatement
Resources and Pollution Management

Parts/accessories
for optical/electric
instrument

0.050

0.075

0.100
0.125
0.150
Proximity to Country

0.175

Waste Water Management and Potable Water Treatment
Air Pollution Control
Natural Risk Management
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
OthersEnvironmentalPreferableProductsbasedonEnd-UseorDisposalCharacteristics
Waste Management, Recycling and Remediation
Water supply
Bubbles are sized by RCA

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

15 For an in-depth explanation of how to read this figure, please refer to the section Green strengths and opportunities within the
China case study.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

155

Summary` The United Arab Emirates is one of the world’s largest oil producers and, not surprisingly,
scores relatively low in green (and overall) economic complexity.

` The country has one of the highest levels of per capita emissions globally, but due to its
small population only accounts for a limited share of emissions overall.

` The UAE have seen gains in both green complexity and green complexity potential

over time, suggesting the country’s productive structure is becoming more suited tocompetitively producing complex green goods.

` The government’s “Operation 300bn” industrial strategy aims to develop the country’s
manufacturing capabilities, including for renewable energy production.

` The UAE only has sufficient solar potential to meet their current high average annual energy

usage per person, but it is possible it will try to develop a green energy export capacity given
its low production costs; a need to diversify away from fossil fuels; and proximity to the large
greening market of Europe.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

157

Singapore case study
Policy ambition and green complexity
Singapore is one of the wealthiest placeson earth, with a sophisticated economy(Economic Complexity Index - ECI rankof 2), but a much lower ranking in green
complexity.

Financial Times2. One of the reasons forthis lack of progress is its limited renewableenergy potential. Consequently, the country
relied on natural gas for about 96% of its
electricity generation in 20193.

Singapore’s nationally determined
contribution (NDC) to the UNFCCC states
the country’s aim to peak its emissions by
20301. Based on data up to 2017, Singapore
was the worst performing rich country
regarding action on climate change, andone of the worst overall, according to the

Despite its strong response to the COVID-19
pandemic, none of Singapore's recovery
spending spending was deemed green by the
Oxford University recovery tracking project.

1 UNFCCC, ‘Singapore’s Update of Its First Nationally Determined Contribution (NDC) and Accompanying Information’, 2020
<https://www4.unfccc.int/sites/ndcstaging/PublishedDocuments/Singapore First/Singapore’s Update of 1st NDC.pdf>[accessed 19 August 2021].
2 Steven Bernard, ‘Singapore Fails to Keep Pace with Wealthy Peers on Carbon Emissions’, The Financial Times, 12 March 2021
<https://www.ft.com/content/a60e9464-a55d-4066-a839-46e334fde094> [accessed 19 August 2021].
3 CAT, ‘Country Summary: Singapore’, Climate Action Tracker, 2020.

Predictors of Success in a Greening World

158

Singapore at a glance

5,686

340,000

Population (thousands)

GDP (current US$, millions)

98,526
GDP / capita (US$, PPP)40

2
ECI rank

GCI rank

64
GCP rank

7.80 %
1.44 %

Green exports of total

Global share of green
exports

Chromatographs,
electrophoresis
Highest RCA green product

Profile projectors
Most complex competitivePredictors of Success in a Greening World

159

none

1.4°C

Net zero target

Temp change since 1961

0.08 (rank: 160/230

60

CO2 intensity (kg/PPP$ GDP)53

Avg energy use(MWh/yr/cap)

130

Global Energy Potential(MWh/yr/cap)

Climate risk index rank

159
Extreme risk index rank

0.7% (191/213)%
Renewable energy consumption

2%
Share of green in covid recovery

Predictors of Success in a Greening World

160

Trends in green competitivenessSingapore’s GCI rank has increased
marginally over the course of the study
period – from 45 in 1995-99 to 40 in 2015-19.
However, its GCP rank fell from 53 to 64.
This stands in stark contrast to its ECI rankof 2 – which has risen from 43rd. Singapore
has thus drastically improved its capability
in producing complex products, but not,according to this analysis, complex green
products. Absolute trade values increased
over time, especially in the green categories
of Renewable Energy; Environmental
Monitoring, Analysis and Assessment
Equipment; Efficient Consumption ofEnergy Technologies and CCS; Waster
Water Management and Potable Water` Fig. 56: Export value over time by environmental category, Singapore.
10000
9000

Trade value ($ 1,000)

8000
7000
6000
5000
4000
3000
2000
1000
0
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

161

Treatment; Management of Solid andHazardous Waste and Recycling Systems;
and Air Pollution Control. The share of green
products in Singapore’s overall exports has
also increased, from 5.1% to 7.8% (Figure56). However, this increase is smaller than
the rise in green products as a share of global
trade. The average proximity of Singapore’s

production capabilities to green products has
been declining for all green categories since
the early 2000s (Figure 57). This is reflected
in its losses in GCI and GCP rank, andimplies that it is becoming harder, rather thaneasier, for Singapore to develop a competitive
advantage in the green economy.

` Fig. 57: Average proximity over time by environmental category, Singapore
0.2
0.19

Average proximity

0.18
0.17
0.16
0.15
0.14
0.13
0.12
0.11
0.1
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year

Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

Predictors of Success in a Greening World162

The largest importers of Singapore’s green
products are China (18.8%) and the UnitedStates (12.1%). Several countries account for
about 2-5% of Singapore’s green exports,
while only 18.1% of green export value goesto countries with less than a 2% share(Figure 58).

The distribution looks slightly different for
overall export values: China (15.2%) remains
the largest importer, but is followed by Hong
Kong (13%), while Malaysia (9.4%) accounts
for a slightly larger share than the US (8.2%)(Figure 59).

` Fig. 58: Largest importers of Singapore's green exports. Only countries that import>2% of Singapore's exports are shown separately.

China
18.8%

Others18.1%

Indonesia
5.8%South Korea
5.8%

USA
12.1%

Malaysia
8.2%

Japan
5.4%

Hongkong
4.4%

India
4.9%

Thai_
land
2.9%

Ger_
many
3.0%

Philippines
2.4%
Philippines
2.2%

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

163` Fig. 59: Largest importers of Singapore's overall exports. Only countries that import>2% of Singapore's exports are shown separately.

Others18.0%

Hongkong
13.0%

India
4.7%

China
15.2%

Malaysia
9.4%

Indonesia
6.6%

USA
8.2%

Japan
3.6%

Thailand
3.0%
South
Korea
2.7%
Australia
2.7%

Viet Nam
2.8%
Philip_ Ger_
pines many
2.5% 2.1%
Netherlands
2.1%

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World

164

Trends in green energy

Singapore is a country that clearly has poor
renewable energy potential relative to its
population size. It has a high population
density (8,400 people per km2), relatively
high average energy use per person (60MWh/yr/cap), quite limited access torenewable resources, and consequently
very little current renewable generation(Figure 60).
Singapore and its surrounding waters do
not experience winds consistently above 4
mph and so it is not considered to have any
current economic wind energy potential.
Moreover, it has no hydropower, and onlya small bioenergy industry. There is somepotential for solar energy, (Figure 61) but
with limited available land it is unlikely muchof this solar potential will be realised. Even if
all of its green energy potential of 53 MWh/yr/cap were utilised it would still not be able
to meet its current energy demands withouta significant improvement in the energy
efficiency of solar.
Consequently, Singapore is looking to securesignificant amounts of green energy from
Australia in the near future. As mentioned in
Section 2. G, two major projects currently intheir planning phases - the Asian Renewable
Energy Hub and the Australia–ASEAN
Power Link - are set to deliver around 20GW
of green energy, or 20% of Singapore’s
current energy demand, in the form ofgreen ammonia (hydrogen) or as electricity
transferred through high voltage direct
current underwater cables.

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Lombard Odier · December 2021

Predictors of Success in a Greening World165` Fig. 60: Singapore’s renewable energy generation capacity (GW) by energy source

Renewable energy capacity (MW)

600
500
400
300
200
100
0
2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

Year

Totalrenewable
renewableenergy
energyTotal

Hydropower
Hydropower

MarineSolar

Bioenergy

Liquid biofuels

Wind

Solar

MarineWind
Bioenergy

Biogas

Source: IRENA (2021), Renewable Capacity Statistics 2021; & IRENA (2020), Renewable Energy Statistics
2020, The International Renewable Energy Agency, Abu Dhabi.

` Table 9. Estimates of current technical potential of renewable resources per personcompared with current average annual per capita usage for Singapore.

Singapore
Onshore wind generation potential (EJ/yr)<1

Offshore wind generation potential (EJ/yr)<1

Solar PV generation potential (EJ/yr)

1

Hydro generation potential (EJ/yr)-

Bioenergy generation potential (EJ/yr)<1

Est. Total generation potential (EJ/yr)

1

Population (millions)

6

Average annual energy usage per person (MWh/yr/cap)

60

Total generation potential per person (MWh/yr/cap)

53

Source: See Appendix for Data Sources

Predictors of Success in a Greening World

166

� Fig. 61: Estimates of solar photovoltaic potential (kWh/kWp) and practical potential
zonation used to determine Singapore’s economic potential for solar

Photovoltaic power output (Practical potential, Level 0)
2.0

3.0

4.0

5.0

6.0 kWh/kWp

Pratical potential zonation:
LCOE average (country range)

Source: https://globalsolaratlas.info/

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Lombard Odier · December 2021

Level 2

Level 1

Level 0

Predictors of Success in a Greening World

167

Policy and economic environment

As one of the four "Asian tigers" – alongwith Hong Kong, Taiwan, and South
Korea – Singapore has seen rapid economic
development since the 1990’s. Taking
advantage of its strategic position next to
the Malacca Strain through which passes
perhaps 40% of global trade, Singapore is aninternational trade success story, rising torich country status in just a few decades after
it gained independence in 19654.
Fairly soon after the Asian Financial Crisis,
China took over as the Asian growth
powerhouse. Consequently, Singapore
has used its strong institutions and liberalpolicies to become a financial bridge between
China and the rest of the world5. This exposes
Singapore to the ups and downs of China’s
fortunes, and its policies toward international
finance.
Singapore has also grown into a knowledge
economy with some of the top universities
in Asia. It prides itself on its advanced
research, including in renewable energy
technologies and other green innovation.
Such innovations, however, are not reflectedin the green complexity index or potential
unless local companies are able to capitaliseon these and export their products globally.

4 https://www.economist.com/the-economist-explains/2015/03/26/why-singapore-became-an-economic-success
5 https://www.economist.com/special-report/2019/12/05/after-half-a-century-of-success-the-asian-tigers-must-reinventthemselvesPredictors of Success in a Greening World

168

Environmental credentials and policy ambition

In its NDC, Singapore seeks to peakemissions by 2030 below 65 Mt of CO2e,
giving it ample room to increase emissions
from their 2018 levels of 46 Mt6. Even
without new policies these emission targets
could be easily met, showing a clear lack ofambition7.
Singapore explains its recent lack of ambition
to earlier progress in shifting from oil tonatural gas for electricity generation in theearly 2000s, and a limited and eventuallyzero growth rate in the number of carsand motorbikes. Singapore is also densely
populated and lacks natural renewableenergy resources. Singapore has introduced
a carbon tax in 2019 for industrial facilities as
the first Southeast Asian nation. However, at
5 Singapore dollars (approximately 3.7USD)
per ton, this is one of the lowest carbon
prices in the world8. The price is expected
to rise to about 10 or 15 Singapore dollars(approximately 7.5 – 11 USD) by 2030,
but that has also been criticised by actiongroups and members of parliament as being
unambitious9.

Singapore’s post-COVID-19 pandemic
spending echoes its recent slow progress.
According to the University of Oxford’s
Global Recovery Observatory, Singapore’splans so far have revealed less than 0.1% of
GDP spending on recovery in total, noneof which can be deemed green. One reason
for its low green spending might be that
this does not include Singapore’s recently
unveiled Green Plan 2030, which aims to
get Singapore on track for meeting its Paris
agreement goals. While the details of theGreen Plan 2030 are still to be worked out,
and without a net zero date pledge, nor any
best-in-class ambition, it has nonethelessbeen welcomed as a good starting point10,11.
Among other elements, the Green Plan 2030
includes increased solar energy deployment
and investment in EV infrastructure, as
well as investment in trees, parks, waste
management, and green finance. Discussing
the plan, Grace Fu, Minister for Sustainability
and the Environment of Singapore, declareda need to incorporate sustainability ineverything, including the COVID-19
recovery 12,13.

6 World Bank, ‘Total Greenhouse Gas Emissions (Kt of CO2 Equivalent)’, World Bank Data, 2020 <https://data.worldbank.org/
indicator/EN.ATM.GHGT.KT.CE> [accessed 19 August 2021].
7 CAT, ‘Current Policy Projections: Singapore’, Climate Action Tracker, 2020 <https://climateactiontracker.org/countries/
singapore/current-policy-projections/> [accessed 19 August 2021].
8 Maria Hofbauer Pérez and Carla Rhode, ‘Carbon Pricing: International Comparison’, Ifo DICE Report I, Spring Volume 18 (2020).
9 Winston Chow, ‘Singapore’s Climate Action: It Is Time to Be More Ambitious’, Research Collection School of Social Sciences.
Paper 3173., 2020, 19–19 <https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=4430&context=soss_research> [accessed
19 August 2021]; John Koh, ‘Singapore MPs Call for Minimum 15-Fold Carbon Tax Increase by 2040’, IHS Markit Net-ZeroBusiness Daily News Research & Analysis, 2021 <https://ihsmarkit.com/research-analysis/singapore-mps-call-for-minimum15fold-increase-in-carbon-tax-b.html> [accessed 19 August 2021].
10 Carnell and Sakpal.
11 Carnell and Sakpal.
12 Paritta Wangkiat, ‘Green Recovery’, Bankok Post (Bankok, 21 June 2021) <https://www.bangkokpost.com/business/2135711/
green-recovery>.
13 Wangkiat.

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Lombard Odier · December 2021

Predictors of Success in a Greening World

169

Green strengths and opportunities

Singapore’s green strengths are vastly
exceeded by the number of potential
opportunities, as can be seen in Figure 6214.
While there is a positive association between
proximity and complexity, implying that themost technologically sophisticated products
are also the ones it can transition into with thegreatest ease, proximity overall is low, whichis reflected in its relatively low GCP rank. The
plot in Figure 62 highlights two of Singapore’s
competitive strengths: chromatographs andelectrophoresis instruments, which are used
for measurement and analysis of air- andwater quality; and equipment for measuring

electrical flow, used to identify electronicand electrical problems in equipment. New
products which Singapore could develop
a competitive advantage in with relative
ease (compared to other green products)
include exposure meters for controlling
light sources and for measurements inagriculture, horticulture, and other natural
resources applications; regulating/controlling
equipment which includes solar heliostats;and parts for solar heliostats (labelled “parts
and accessories of optical appliances”).

14 For an in-depth explanation of how to read this figure, please refer to the section Green strengths and opportunities within the
China case study.

Predictors of Success in a Greening World170` Fig. 62: Singapore's green export products divided into current strengths and potential
opportunities. Size of product indicates Singapore’s current RCA, colours represent
product categories (see legend).15
Singapore: Current Strengths

Singapore: Potential Strengths

2.5 Chromatographs,

1.5
1.0
Parts andaccessories,
electrical measuring
instruments

0.5
0.0
-0.5

Exposure
meters1

Parts andaccessoriesof opticalapplicances nes

0

-1

-2

-1.0
-1.5

Automatic
regulating/controlling
equipment nes

2

Product Complexity Index

Product Complexity Index

2.0

electrophoresis
instruments

0.125

0.150

0.175

0.220

0.225

0.250

0.075 0.100

Management of Solid and Hazardous Waste and Recycling Systems
Natural Resource Protection
Energy Efficiency
Heat and Energy Management
Gas Flairing Emission Reduction
EfficientConsumptionof EnergyTechnologiesandCarbonCaptureandStorage
Environmental Monitoring, Analysis and Assessment Equipment
Renewable Energy
Noise and Vibration Abatement
Resources and Pollution Management

0.125

0.150

0.175 0.220

0.225

Proximity to Country

Proximity to Country

Waste Water Management and Potable Water Treatment
Air Pollution Control
Natural Risk Management
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
OthersEnvironmentalPreferableProductsbasedonEnd-UseorDisposalCharacteristics
Waste Management, Recycling and Remediation
Water supply
Bubbles are sized by RCA

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org.

15 For an in-depth explanation of how to read this figure, please refer to the section Green strengths and opportunities within the
China case study.

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World

171

Summary` Singapore's economic growth can be attributed in no small part to its strategic position on
major trade routes and its strong institutions.

` Singapore scores low on green complexity compared to its economic complexity ranking.
` While it has made progress in the past, Singapore’s current climate action policies have been
criticised for lacking ambition.

` Singapore has high-ranking universities and prides itself on its green innovations, but suchinnovations are yet to be reflected in green complexity rankings as they require an ability tocapitalise on these knowledge gains.

` With very limited green energy resources, Singapore is already looking to import green
energy from other countries.

Predictors of Success in a Greening World

172

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Lombard Odier · December 2021

Predictors of Success in a Greening World

173

Switzerland
Policy ambition and green complexity
Switzerland1 is one of the highest income
countries on earth with a GDP per capita ofover 70,000 USD1. This is also reflected in its
high economic complexity (ECI) ranking of
5th.

Switzerland’s nationally determined
contribution to the UNFCCC (NDC) was
updated in December 2020 and includes a2030 target of 50% GHG reduction below
1990 levels.

It does not score as well on GCI and GCP andhas, in fact, been dropping in the ranks2.

This contribution is slightly more ambitious
than previous submissions, in that a larger
share of this goal will come from domestic
reductions4 rather than through thesomewhat controversial purchase of overseas
offsets.

Switzerland’s legislature adopted a goal of
net zero GHG emission by 2050 in 20193; yeta key piece of legislation was voted down in areferendum in 2021.

1 Switzerland GCI, GCP and RCA includes Liechtenstein due to their being combined in the underlying export trade data.
2 At price point parity.
3 CAT, ‘Country Summary: Switzerland’, Climate Action Tracker, 2020 <https://climateactiontracker.org/countries/
switzerland/> [accessed 14 September 2021].
4 UNFCCC, ‘Switzerland’s First Nationally Determined Contribution towards Achieving the Objective of the United Nations
Framework Convention on Climate Change (Updated Submission)’, 2020 <https://www4.unfccc.int/sites/ndcstaging/
PublishedDocuments/Switzerland First/Switzerland_Full NDC Communication 2021-2030 incl ICTU.pdf>.switzerland/>[accessed 14 September 2021].

Predictorsofof
Predictors
Success
Successin ainGreening
a Greening
WorldWorld174

Switzerland at a glance

8,637

747,969

Population (thousands)

GDP (current US$, millions)

71,352GDP / capita (US$, PPP)

23

5
ECI rank

GCI rank

47
GCP rank

6.90 %
1.30 %

Share of green in
total exports

Global share of green
exports

Railway & tramway &Bissel -bogies
Highest RCA green product

Machines & Mechanicalappliances
Most complexe competitive

PleasePlease read
read thethe important
important information
information at
at thethe endend ofof thethe document.
document.
LombardLombard Odier
Odier ·· December
December 2021
2021

Predictors
Predictorsof Successof Successin ainGreening
a GreeningWorld
World

175

2050

2.3°C

Net zero target

Temp change since 1961

0.06 (rank: 177/230)

64

CO2 intensity (kg/PPP$ GDP)130

Avg energy use(MWh/yr/cap)

96

Global Energy Potential(MWh/yr/cap)

Climate risk index rank

155
Extreme risk index rank

25.3% (90/213)%
Renewable energy consumption

54 %Share of green in covid recovery

Predictors of Success in a Greening World

176

Trends in green competitivenessSwitzerland has been declining in
GCP since the mid-1990s and in GCI
since the early 2000s. While the UK
was on a similar trajectory in GCI fromthe mid 1990s until the mid 2000s,
Switzerland was not able to keep its top 10
position. It now ranks 23rd in GCI
and 47th in GCP.

Over the same period, absolute tradevalue went up in all green productcategories, although many have slightly
declined since a peak in the early 2010s.
The largest export product by value
are products in the category Efficient
Consumption of Energy Technologies andCCS (see Figure 63). In line with its declining` Fig 63: Export value over time by environmental category, Switzerland.
12000

Trade value ($millions)

10000
8000
6000
4000
2000
0
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year
Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Please read the important information at the end of the document.
Lombard Odier · December 2021

Predictors of Success in a Greening World177

GCI and GCP, the proximity of many green
product categories to the Swiss economy has
fallen, as is shown in Figure 64. There has,
however, been a slight uptick in the category“Others” in recent years. This includes
distilling apparatus for desalination systems,
biogas refinement equipment and solvent
recycling plants and machinery for treatment

by temperature change, whose applications
include biogas reactors and refinement
equipment, among other environmentally
relevant uses.

` Fig 64: Average proximity over time by environmental category, Switzerland.
0.4

Average proximity

0.35
0.3
0.25
0.2
0.15
0.1
1995-1999

1999-2003

2003-2007

2007-20112011-2015

2015-2019Year
Air Pollution Control
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Heat and Energy Management
Management of Solid and Hazardous Waste and Recycling Systems

Natural Resource Protection
Natural Risk Management
Noise and Vibration Abatement
OthersRenewable Energy
Resources and Pollution Management
Waste Management, Recycling and Remediation
Waste Water Management and Potable Water Treatment
Water supply

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World178` Fig 65: Largest importers of Switzerland and Liechtenstein’s green exports. Only countries
that import >2% of Switzerland and Liechtenstein’s exports are shown separately.

China
6.4%

USA
11.0%

Others30.7%

Germany
27.5%

France
5.6%

UK
4.1%

Italy
3.9%

Austria
3.1%

Netherlands
3.4%

Japan
2.1%

South
Korea
2.1%

` Fig 66: Largest importers of Switzerland and Liechtenstein’s overall exports. Only countries
that import >2% of Switzerland and Liechtenstein’s exports are shown separately.

Germany
15.5%

France6.2%

Others
24.6%

USA
13.7%

China
7.0%

UK
7.9%

Italy
4.7%

Japan
2.6%
India
24.6%

Spain
2.3%

Hongkong
3.1%

Austria Belgium
2.0%
2.1%
Singapore
2.0%

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

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Predictors of Success in a Greening World179

At 27.5%, Germany is the most significant
importer of Switzerland4’s green exports.
This is not surprising, given the twocountries’ geographic and cultural proximity,
as well as the size of the German economy
relative to that of other countries in theregion. However, an analysis of overall
import shares suggests that Germany is aparticularly significant trading partner ingreen goods – more so than overall.
The United States account for the secondlargest share at 11%, followed by China with
6.4%. Nearly a third of Switzerland’s green
exports are imported by countries with ashare of less than 2%.

Importers’ shares of Switzerland’s overall
exports differ somewhat from green exports.
Germany remains the largest importer, but
accounts for only 15.5%, which is only slightly
more than half of its share of green exports.
This indicates that Switzerland’s green
exports are significantly more dependent on
Germany as a trading partner than is the caseoverall.4
The United States are still the second-largest
importer, but account for a marginally higher
percentage of 13.7%. They are followed by
the United Kingdom (close to 8%) and China(7%). Countries with small import shares(less than 2%) account for about a quarter of
Switzerland’s exports.

Predictors of Success in a Greening World

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Trends in green energy

Hydropower is the most important domestic
source of renewable energy in Switzerland,with 59% (36.3 TWh/year) of domestic
electricity production currently sourced fromhydropower. Being a land-locked country,
Switzerland has no offshore wind potential, so
the next largest renewable resources available
are solar, onshore wind, and bioenergy. Thisis reflected in the recent growth in solar PV
shown in Figure 5, which is also indicative ofrelatively low costs and the reasonably large
solar potential shown in Figure 67.

� Fig 67: Switzerland’s renewable energy generation capacity by source.

Renewable energy capacity (GW)

25 000

20 000

15 000

10 000

5 000

0

2000

2002

2004

2006

2008

2010
Year

2012

2014

Total renewable energy

Hydropower

Marine

Wind

Solar

Bioenergy

Liquid biofuels

Biogas

2016

2018

2020

Source: IRENA (2021), Renewable Capacity Statistics 2021; & IRENA (2020), Renewable Energy
Statistics 2020, The International Renewable Energy Agency, Abu Dhabi.

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Switzerland’s average annual energy usage
per person is quite low compared to othercountries of similar income, which isconsistent with the European region (Table
10) . Hence the country’s renewable percapita generation potential per person ismuch higher than current per capita demand,
despite the country having only relatively low

renewable potential. A scale up of renewables
spending to match that of key regional
competitors such as Germany could provide
Switzerland with even greater energy security
and the potential to export green energy to
the growing EU market.

` Fig 68: Estimates of solar photovoltaic potential (kWh/kWp) and practical potential
zonation used to determine Switzerland’s economic potential for solar.

Photovoltaic power output (Practical potential, Level 0) Pratical potential zonation:
2.0

3.0

4.0

5.0

6.0 kWh/kWp

Level 2

Level 1

Level 0LCOE average (country range)

Source: https://globalsolaratlas.info/` Table 10. Estimates of Switzerland's current technical potential for annual renewableenergy generation which is used to calculate its per capita renewable energy potential
in comparison with its current average annual per capita usage.

Switzerland
Onshore wind generation potential (EJ/yr)<1

Offshore wind generation potential (EJ/yr)-

Solar PV generation potential (EJ/yr)

3.7

Hydro generation potential (EJ/yr)<1

Bioenergy generation potential (EJ/yr)<1

Est. Total generation potential (EJ/yr)

4.0

Population (millions)

9

Average annual energy usage per person (MWh/yr/cap)

34

Total generation potential per person (MWh/yr/cap)

130

Source: See Appendix for Data Sources

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Policy and economic environment

Switzerland’s economy is highly servicesbased, with a large financial industry and astrong tourism sector. On the manufacturingside, Swiss companies have a strong presencein the pharmaceutical industry, and foodproducts via Nestlé, as well as niche high-end
manufacturing such as watches and jewellery.
While Switzerland is not part of the EU,
its relationship is governed via various
treaties. Although Switzerland pulled out ofnegotiations of a landmark deal with the EU

to formalise these bilateral treaties into asingle agreement4, the EU and Switzerland
are largely aligned on their climate goals5.
The European Green Deal, which wasannounced in late 2019 and is still being
defined in detail, will impact Switzerland
through many of its regulations. However,since both jurisdictions have emissions
trading schemes in place that have been
coupled since the beginning of 2020,
Switzerland is exempt from a potential EU
border adjustment tax6.

4 Hans von der Burchard, ‘EU-Switzerland Relations Head for Trouble as Partnership Deal Unravels’, Politico, 26 May 2021
<https://www.politico.eu/article/eu-switzerland-relations-head-for-trouble-as-partnership-deal-unravels/>.
5 Mission of Switzerland to the EU, ‘Environment and Climate – Stepping up Cooperation on Shared Challenges’, 2021 <https://www.eda.admin.ch/missions/mission-eu-brussels/en/home/key-issues/enviroment-climate.html>.
6 Mission of Switzerland to the EU, ‘Environment and Climate – Stepping up Cooperation on Shared Challenges’, 2021 <https://www.eda.admin.ch/missions/mission-eu-brussels/en/home/key-issues/enviroment-climate.html>.

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Environmental credentials and policy ambition

Switzerland’s updated NDC in 2020 was
written with the amended CO2 act in mind
as a key piece of legislation to help get
Switzerland on a Paris agreement aligned
pathway. It included, among other things,
higher fossil fuel taxes and more expensive
flight tickets. In June 2021, voters rejected thisbill in a referendum, leaving Switzerland´senvironmental minister to state that thiswould make reaching net zero in 2050
"very difficult7".
To reach its goal to decrease GHG emissions
by 50% in 2030, Switzerland has madedeals with Peru and Ghana to fund partof the reductions there that would counton Switzerland´s balance8. The deal with
Peru was hailed as the first international
agreement of its kind. This practice isallowed and governed by Article 6 of theParis agreement, but still controversial andunderutilised as exact rules for Article 6 werestill being negotiated a deal on its formal
rules was reached at the recent Glasgow
COP26)9.
Due in part to its natural endowments ofrenewable energy sources, Switzerland
has an electricity system that is very low incarbon intensity. Almost 60% of domestic
electricity production comes from its morethan 600 hydroelectric power plants. Mostof the remainder is accounted for by nuclear
power plants.
In early 2020, almost 10% of vehicles soldwere EVs, with the ambition to raise thisto 15% by 2022. This is more than the EU
average, although richer peers of Switzerland
such as the Nordics are further ahead.

7 Peter Stubley, ‘Swiss Voters Reject New Climate Law to Help Cut Carbon Emissions’, The Independent (London, 14 June 2021)<https://www.independent.co.uk/climate-change/news/switzerland-referendum-climate-change-emissions-b1865193.html>.
8 Joe Lo, ‘Peru and Switzerland Sign “World First” Carbon Offset Deal under Paris Agreement’, Climate Home News, 21 October
2020 <https://www.climatechangenews.com/2020/10/21/peru-switzerland-sign-world-first-carbon-offset-deal-parisagreement/>.
9 IISD, Delivering Climate Ambition Through Market Mechanisms: Capitalizing on Article 6 Piloting Activities, 2021 <https://sdg.
iisd.org/commentary/policy-briefs/delivering-climate-ambition-through-market-mechanisms-capitalizing-on-article-6piloting-activities/>.

Predictors of Success in a Greening World

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Green strengths and opportunities

Figure 69 shows that Switzerland has a larger
number of green opportunities than green
strengths, and relatively low proximity togreen production capabilities. However, themost proximate green products tend to behigher in complexity, which implies there islittle tradeoff between complexity and theease of transitioning .

Switzerland’s green strengths include anumber of railway parts, one of which ishighlighted on the plot. High complexity
green opportunities include parts forwind turbines (such as clutches, shaft
couplings and universal joints) and cleaner
vehicles, such as hybrids and EVs, in which
Switzerland currently has very low RCA.

� Fig 69: Switzerland’s green export products divided into current strengths andpotential opportunities. Size of product indicates Switzerland’s current RCA, colours
represent product categories (see legend)10.
Switzerland: Current Strengths
2.5

Product Complexity Index

1.5
1.0
0.5
0.0
Railway &tramway driving
bogies & bisselboggies

-0.5
-1.0
0.150

0.175
0.200
0.225
Proximity to Country

Product Complexity Index

Machine andmechanicalappliances nes

2.0

-1.5
-1.5

Switzerland : Potential Strengths

0.250Management of Solid and Hazardous Waste and Recycling Systems
Natural Resource Protection
Energy Efficiency
Heat and Energy Management
Gas Flairing Emission Reduction
EfficientConsumptionof EnergyTechnologiesandCarbonCaptureandStorage
Environmental Monitoring, Analysis and Assessment Equipment
Renewable Energy
Noise and Vibration Abatement
Resources and Pollution Management

2

Othe vehicles
including Gas Turbine
Powered1

Clutches, shaft
couplings, universal
joints0Machines forbalancingmechanicals
parts, nes

-1

-2

0.075

0.100

0.125
0.150 0.175
Proximity to Country

0.220

Waste Water Management and Potable Water Treatment
Air Pollution Control
Natural Risk Management
Clean UP or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
OthersEnvironmentalPreferableProductsbasedonEnd-UseorDisposalCharacteristics
Waste Management, Recycling and Remediation
Water supply
Bubbles are sized by RCA

Source: Andres, P and Mealy, P (2021) Green Transition Navigator. Retrieved from www.green-transitionnavigator.org..
10 For an in-depth explanation of how to read this figure, please refer to the section Green strengths and opportunities within the
China case study.

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Summary` Switzerland ranks highly in overall economic complexity, with a global ECI rank of 5th.
` However, its competitiveness in producing complex green products has declined

dramatically over the period of this study, with GCI falling from 6 to 23 and GCP from 18 to
47 between 1995-1999 and 2015-2019.

` Products which Switzerland (and Liechtenstein) export competitively include railway partsand equipment used for biogas production.

` Switzerland (and Liechtenstein)’s green exports are highly concentrated: Germany accounts
for close to 30%, which is almost twice its share in the region’s overall exports.

` Switzerland has set a goal to reach net zero GHG emissions by 2050. However, given its
current trajectory and policies it is difficult to argue it is on track to reach this goal.

` Switzerland has a much greater renewable energy potential than current energy demandneeds and so a scale up of renewables spending to match that of key regional competitors
such as Germany could provide Switzerland with even greater energy security and thepotential to export green energy to the growing EU market.

` The country has put in place international agreements to outsource emission reductions
to countries in the Global South, specifically Ghana and Peru, which is an unusual andcontroversial practice.

Predictors of Success in a Greening World187

5. What could
this mean forcompanies andtheir investors?

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188

Investment opportunities in wind and solar
Is the transition to blame for the current energy crisis?
As countries have begun to recover from the COVID-19 pandemic, an energy crisis has
gripped Europe. By October 2021, European gas prices had increased by about 500% from the
beginning of the year. In the UK, prices of 60p per therm1 at the beginning of the year rose 37%
in 24 hours to trade at 400p per therm1. Energy bills are forecasted to rise by up to 30% nextyear, whilst by the 18th October sixteen smaller energy providers had gone out of business in
the UK market as they struggled with rising costs.
While some have blamed this energy crisis on the energy transition, it is most likely a resultof multiple factors including supply and demand dynamics, geographic and political factors,
rather than merely the rising cost of carbon2. Such additional factors include low gas storage
stocks, reduced gas supplies from certain geographies, a shortage in Liquified Natural Gas(LNG) deliveries linked to high demand from Asia following China's decision to ban importsof Australian coal following a political dispute, as well as lower than normal renewable output
in Europe due to meteorological factors. Asian gas demand has risen due to cold weather andnew policies on imports of coal, whilst LNG shipments have been sent to South America as
droughts caused hydroelectric production to fall. In Europe, where natural gas demand fell
by 1.9% in 2020, demand has rebounded post-pandemic as lockdowns have eased. Delayed
maintenance at other European production facilities has further exacerbated supply chain
shortages, as have lower wind energy production due to reduced wind speeds. Finally, andcrucially, gas supplies from Russia have fallen. This is in part due to high Asian demand. Some
commentators have suggested that Russia may also be purposefully limiting gas flows to therest of Europe to strengthen its case for starting flows through the new Nord Stream 2 pipeline
to Germany. In October this year, President Putin claimed that Russia “could deliver 10%
more gas if Nord Stream 2 was approved”3, hinting at the existence of additional stockpiles thatwere being deliberately withheld.
Some have argued that the excessive price rises are simply the result of a market responding toan “unusual confluence of economic forces”4, and should soon reverse course. However, thecrisis also presents an inflection point in the energy transition, as policymakers need to choose
between two different responses.
The first response, that will likely be supported by many incumbent energy providers, is toblame renewables, encouraging a “popular revolt against climate policies” as households
energy bills rise5. This was observed earlier in 2021, when the electricity grid in Texas failed
due to freezing temperatures. Republican leaders blamed freezing wind turbines, when
1 One therm is equivalent to 100,000 BTUs (British Thermal Unit) – the amount of heat needed to increase the temperature of one
pound of water by one degree Fahrenheit.
2 From January to November 2021 the EU carbon price has doubled (https://ember-climate.org/data/carbon-price-viewer/) while
EU gas prices over this period have quadrupled. (https://www.euronews.com/2021/10/28/why-europe-s-energy-prices-aresoaring-and-could-get-much-worse)3 https://www.ft.com/content/e5f74353-73e5-4273-ae13-cc3d0985e606
4https://www.ft.com/content/f2ca6690-0390-4374-a9d5-29caf2d651dd

5 https:////www.economist.com/leaders/2021/10/16/the-first-big-energy-shock-of-the-green-era

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freezing components in thermal sources were also a major contributing factor; renewables
only contributed 13% of power outages, according to analysis from the Electric Reliability
Council of Texas6. In the current crisis, some argue that the phasing out of coal increases
volatility, reducing the grid’s capacity to draw on reliable sources of backup power when thewind does not blow, or when gas supplies run low. There is some credence to this view; as
the energy transition towards renewables accelerates, coal and other sources of fossil fuelenergy, traditionally seen as reliable sources of primary and backup power, are indeed being
phased down. Under such pressure, some countries have considered controversial measuresagainst renewables. For instance, Spain's now watered-down levy on "excess profits" fromelectricity companies would have taken from companies with a larger share of renewables(thus comparatively unaffected by rising gas prices yet benefiting from rising electricity costs)
to "shield" consumers from rising electricity prices7. Meanwhile, many countries, including theUK8, are temporarily ramping up coal output to alleviate short-term pressure.
The second possible response would be to stay the course on the transition and recognise that
there will likely be short-term growing pains as the world undergoes a major transformationof the energy system. Gas might be needed as a bridge fuel to smooth the transition awayfrom coal, especially across Asia, but this can lead to greater stranded assets, carbon lock-in9,
and unless there is further investment in ramping up LNG capacity to meet growing demand,
the global shortfall in LNG capacity could rise from 2% of demand to 14% by 203010. It could
therefore be argued that extreme volatility in gas prices is a result of too little investment inclean energy and associated energy storage technologies. The more renewables and storage
capacity is increased, the less need there is for fossil fuel sources such as LNG or coal tosmooth the transition. Therefore, the speed of the transition from fossil fuels to green energy
will determine the volatility of the energy supply-demand balance in the EU. Finally, in termsof long-term energy security, such volatility in fossil fuel prices is one key reason to transition
to domestically generated renewable energy sources plus more transmission and storage11
capacity which has shown to result in increased resilience in power systems and electricity
grids12,13,14.
Policymakers could therefore choose to address the gas crisis with even more aggressive

6 https://www.reuters.com/article/uk-factcheck-texas-wind-turbines-explain-idUSKBN2AJ2EI
7 https://www.ft.com/content/7d38b7da-0e33-4379-bffa-470b74e82a3f
8 https://www.bbc.com/news/business-58469238
9 Linus Mattauch, Felix Creutzig, and Ottmar Edenhofer, ‘Avoiding Carbon Lock-in: Policy Options for Advancing Structural
Change’, Economic Modelling, 50 (2015), 49–63 <https://doi.org/https://doi.org/10.1016/j.econmod.2015.06.002>.
10 https://www.economist.com/leaders/2021/10/16/the-first-big-energy-shock-of-the-green-era
11 https://www.ren21.net/renewable-energy-resilient/
12 Dakota J. Thompson, Wester C.H. Schoonenberg, and Amro M. Farid, ‘A Hetero-Functional Graph Resilience Analysis of the
Future American Electric Power System’, IEEE Access, 9 (2021), 68837–48 <https://doi.org/10.1109/ACCESS.2021.3077856>.
13 https://www.sciencedaily.com/releases/2021/05/210511123634.htm
14 NREL, 2019, Renewable Energy to Support Energy Security, https://www.nrel.gov/docs/fy20osti/74617.pdf

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investment in the wind and solar industries. Renewables are no longer an expensive source ofenergy. On the contrary, wind and solar costs have dropped by 60% and 80%, respectively,
over the past 10 years, owing to larger, more efficient wind turbines and the automation ofsolar product manufacturing (Figure 70). Such cost declines are expected to continue, andcould prove to be profoundly disruptive for the global energy system15. Increased wind andsolar capacity can support a wholesale shift away from gas towards electrification in domestic
heating, industry, and power generation, as well as supporting the growing green hydrogen
industry.
As the global economy ramps up its efforts to align with net zero, renewable sources of energy
such as wind and solar are increasingly becoming deflationary forces. New modelling fromthe Oxford Institute for New Economic Thinking suggests a fast transition to a global energy` Fig 70: Long-run useful energy costs and prices of major energy supply technologies.

Useful energy cost ($/MWh)

105

104

103

102

101

100
1880

1900

1920

1940

1960

1980

2000

2020

2040

Year
Oil (primary)
Coal (primary)
Coal electricity
Gas (primary)Gas electricity
Nuclear electricity
Wind electricity

Solar PC electricity
Solar PV forecast (Decisive Transition scenario)
Batteries (cost per cycle)

Source: Ives et al. 202114. Primary oil, coal and gas paths are based on price data; all other technology
paths are based on cost data. Costs and prices are scaled by technology-specific useful energy conversion
factors. The dashed yellow line and shaded area show the cost forecast for the LCOE of solar PV in theFast (Decisive) Transition scenario (median and 95% confidence interval).

15 Ives et al. 2021, www.energychallenge.info/report

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system based on renewables plus storage could save the world trillions and result in much
lower energy costs for all – creating a positive dynamic that could drive rapid change16.
The International Energy Agency’s (IEA) latest research on the topic sends a similar message.
Under its Net Zero scenario, the IEA estimates that in the next 10 to 30 years,
the cost of electricity from gas would likely rise across geographies, while a further drop in
costs for solar and offshore wind is also likely (Figure 71). There is no doubt that wind andsolar capacity must be scaled up to reach Net Zero by 2050. According to BNEF, 505 gigawattsof new wind power globally need to be provided each year to 2030 (5.2 times the 2020 total) as
well as 455 gigawatts of solar PV (3.2 times the 2020 total). Such an electrification
process could lower household energy and fuel bills by up to 50% over business as usual17.

` Fig 71: Levelized cost of electricity (LCOE)18 by technology (varies by geography)
300

LCOE ($/MWh))

250
200
150
100
50

LCOE ($/MWh) 2020

China

LCOE ($/MWh) 2030

Wind offshore

Solar PV

Wind onshore

Gas CCGT

Coal

NuclearWind onshore

Wind offshore

Solar PV

Coal

Gas CCGT

NuclearWind offshore

Solar PVEUWind onshore

Coal

US

Gas CCGT

NuclearWind offshore

Solar PV

Wind onshore

Gas CCGT

Coal

Nuclear0

India

LCOE ($/MWh) 2050

Source: IEA. Note: there is no data for coal in 2030 and 2050 or gas CCGT in 2050 as these energy sources
are assumed to have been phased out under a Net Zero scenario.
16 Rupert Way, Matthew C. Ives, and others, Empirically Grounded Technology Forecasts and the Energy Transition, 2021 <https://www.inet.ox.ac.uk/publications/no-2021-01-estimating-the-costs-of-energy-transition-scenarios-using-probabilisticforecasting-methods/>.
17 Alberto Gandolfi and others, 'Energy costs and affordability: who pays for Net Zero?' Goldman Sachs Research, 5.9 (2021), 56.
18 LCOE calculations are based on a levelized average lifetime cost approach, using the discounted cash flow (DCF) method. Costs
are calculated at the plant level, and therefore do not include transmission and distribution costs but include costs induced into
the system by the variability of wind and solar PV at higher penetration rates.

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The energy transition requires a long-term perspective. In accordance with the Paris
agreement, governments could enable more clean energy by redesigning energy markets, forexample by scaling up storage technologies which have shown consistent cost declines similar
to those of wind and solar19, or by investing in greater transmission capacity, rather thaninvesting further in fossil assets. Recent negotiations as part of COP26 in Glasgow identified
how some developing countries (India and China) may rely on fossil fuel assets longer thanothers. In developed regions as well, legacy fossil fuel assets may also need need support toact as a backstop in periods of crisis. Nonetheless, if we are to successfully mitigate climatechange, new fossil fuel investment without some clear carbon takeback obligation20 needs tobe stopped and redirected towards renewables.
Overall, renewables are poised to provide an increasing share of global energy consumption
in a way that is cleaner and more cost competitive, compared to fossil-based sources ofenergy. As per the IEA’s Net Zero scenario, by 2030 we need to see a significant slow-down(or contraction in a net zero scenario) in the demand for oil and gas energy (requiring around
US$3trn in annual investments in industry, buildings, and transport) and a rapid increase in
the production of wind and solar based energy.
This pathway will create winners and losers across the global economy. Countries which are
well-positioned to supply high value-added products necessary to the production and supplyof wind and solar energy are likely to benefit enormously with up to 10-fold increases in the
deployment of solar and wind possible over the next decade,21, while those relying on fossil
fuel exports are faced with declining markets and the spectre of stranded assets22. Equally, thecorporate landscape of the energy sector, from the supply of basic materials through energy
production to energy supply, will shift radically.
In the next two sections, we propose to analyse the position of countries and corporates in thisenergy transition and discuss investment implications at the corporate level.

19 Way et al. 2021
20Stuart Jenkins and others, ‘Upstream Decarbonization through a Carbon Takeback Obligation: An Affordable Backstop Climate
Policy’, Joule, 5.11 (2021), 2777–96 <https://doi.org/10.1016/J.JOULE.2021.10.012>.
21 Way et al. 2021
22 J. F. Mercure and others, ‘Macroeconomic Impact of Stranded Fossil Fuel Assets’, Nature Climate Change, 2018 <https://doi.
org/10.1038/s41558-018-0182-1>.

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The macro-picture: wind and solar complexity index andcomplexity potential
As set out in Section 1, this report seeks to ask a central question in a world of evolving
comparative advantages: as the transition to a green economy unfolds, which countries,
regions and economic assets are poised to appreciate, and which are set to decline?
Investors hoping to gain exposure in rapidly growing clean technology industries can draw
upon GCI and GCP scores to better understand which countries are currently nurturing
competitive industries, and which are likely to do so in the future. However, it should be notedthat these scores are only one kind of indicator and are by no means exhaustive or prescriptive
when making investment or policy decisions. We explore here the relationship between
countries' green competitiveness and their corporate structure to better understand thisconnection, with a focus on solar and wind.
GCI and GCP are country level indicators (current and potential) of global greencompetitiveness, which may not easily translate into an assessment of the performance ofindividual companies. To examine the relationship between green competitiveness at thecountry and corporate level, Complexity Index (CI) and Complexity Potential (CP) scores are
re-calculated on a subset of green products that are specific to wind and solar industries23.
Countries are ranked by the subset of complexity scores to identify current and potential
leaders in each renewable energy sector. Major corporations and markets in wind and solar are
subsequently compared at the country level. Comparative analysis based on Complexity Index/ Complexity Potential (CI/CP) scores for solar and wind explores the relationship between
green competitiveness at the country and corporate level, and how this can help investors andpolicymakers to understand and develop strategies and policies in the renewable energy sector
and in the transition to a green economy.
The costs of wind and solar have been above fossil fuel alternatives for most countries
for much of the last two decades. During this time, deployment was primarily driven by
government support in the form of feed-in tariffs, subsidies, quotas, and other such measures.
However, countries that have had the greatest deployment of renewables in terms of installedcapacity, including China, Germany, and India, now have some of the lowest levelised costs
for renewables, (Figure 72)24 despite not having the best sun or wind available resources25 –suggesting the benefits to be gained from learning-by-doing.

23 These scores include multiple products beyond wind turbines and solar panels, as well as accounting for the complexity of theseproducts.
24 IRENA, Renewable Power Generation Costs in 2018, International Renewable Energy Agency, 2019 <https://doi.org/10.1007/
SpringerReference_7300>.
25 By the best sunlight and wind resources we are referring to the technical potential for renewable energy generation in thesecountries, which is measured as the geographical potential energy generation (irradiance or wind) after the losses of theconversion from the extractable primary energy flux to secondary energy carriers or forms (electricity, fuel) are taken into
account - de Vries et al. 2007.

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195` Fig 72: Breakdown of utility scale solar PV installed costs by country (2019).
2'500.0

2'000.01'500.0

1'000.0

500.0

0.0

Modules

Inverters

Racking and mounting

Grid connection

Cabling/ wiring

Safety and security

Monitoring and control

Mechanical installation

Electrical installation

Inspection

MarginFinancing costs

System design

Permitting

Incentive application

Costumer acquisition

Source: IEA. IRENA Renewable Cost Database. © IRENA 2019

Predictors of Success in a Greening World

196` Table 11: Ranking of countries by GCI and Wind and Solar CI

Country

GCICountry

Wind and Solar CI

Germany

4.74

Germany

4.53

Italy

3.57

China

3.72

Austria

3.36

USA

3.65

USA

3.36

Denmark

3.44

China

3.23

Japan

3.38

Japan

3.12

Austria

2.76

Denmark

3.04

Romania

2.71

Czechia

2.78

South Korea

2.67

United Kingdom

2.65

Hungary

2.64

France2.48

Finland

2.63

High deployment does not automatically imply that a country has the capacity to competitively
produce the equipment necessary to generate energy from renewable sources. However,research in the field of economic geography suggests that agglomeration economies, including
knowledge spillovers, economies of scale and better access to supply chains and skilled
labour, may lead to a positive reinforcement cycle for cultivating technologically sophisticatedproduction capabilities, which can provide a supportive environment for companies toflourish26. Moreover, Mealy and Teytelboym (2020)27 have shown that a high GCI is correlatedwith high indicators of environmental policy stringency. A high CP score in wind and solar
industries implies that a country is likely to increase its competitiveness in those technologies
in the future, which may be interpreted as indicating a comparatively attractive investment
environment.
Among renewable energy technology, the development of wind and solar products provides
one of the largest contributions to a country’s green competitiveness, as they involve thegreatest number of specific green products as inputs in the construction of facilities. From295 products analysed in this report, 75 products have been identified as technologies andrelated goods used in the renewable energy sector28. Of the 75 unique products, 22 products are
specific to the construction of wind facilities, and 15 specific to solar facilities29. There are an
additional 9 products that have overlapping usage for both wind and solar facilities.
26 Stuart S. Rosenthal and others, ‘Evidence on the Nature and Sources of Agglomeration Economies’, 4 (2004), 2119–71 <https://
econpapers.repec.org/RePEc:eee:regchp:4-49> [accessed 20 November 2021]; Glenn Ellison, Edward L. Glaeser, and William R.
Kerr, ‘What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns’, American Economic Review, 100.3(2010), 1195–1213 <https://doi.org/10.1257/AER.100.3.1195>.
27 Mealy and Teytelboym, 2020, "Economic Complexity and the Green Economy", Research Policy.

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Predictors of Success in a Greening World197` Table 12: Ranking of Countries by Wind CI and Solar CI

Country

Wind CICountry

Solar CI

Germany

5.16

Japan

4.93

Denmark

3.8

South Korea

4.2

USA

3.63

Other Asia

4.11

Romania

3.34

Germany

3.85

Finland

3.12

China

3.82

Japan

2.83

Austria

3.37

Hungary

2.78

Denmark

3.31

Austria

2.66

Finland

3.25

Italy

2.58

USA

2.54

Sweden2.54

Switzerland

2.53

Taking the subset of green products relevant to wind and solar industries, complexity
index and complexity potential scores are re-estimated, and countries are ranked in order
to illustrate how complexity scores can be used to understand countries’ comparative andpotential strengths in the renewable energy sector. Table 11 shows the ranking of the top 10
countries by their CI within wind and solar, as well as their relative overall GCI. It is important
to note that, to the authors’ knowledge, this is the first time a technology-specific aggregate
complexity score has been constructed in this manner. While the Green Complexity Index
and the Green Complexity Potential are measures introduced in Mealy and Teytelboym(2020) and have undergone a number of validation exercises, as well as academic peer review,
the wind and solar specific indices discussed in this section are not based on peer-reviewed
research and should be interpreted with greater caution. Future research may investigate theconstruction and implications of technology-specific complexity scores.
There are some notable changes in countries that have a higher complexity rating in wind andsolar production compared to their overall GCI rank (Table 11) China, Denmark, and South
Korea show higher rankings in CI for wind and solar relative to their GCI rank overall. In
contrast, although Italy, Austria, Czechia, and the United Kingdom rank highly in their overalllevel of green complexity, they do not rank as highly in wind and solar complexity.

28 The list of products in renewable energy is taken from the International Centre for Trade and Sustainable Development 2008
mapping study: Wind, Izaak. HS Codes and the Renewable Energy Sector. ICTSD programme on Trade and Environment, 2008.
29 Of the remaining 29 green products, 15 are for biomass, 7 are for hydropower, 5 are for geothermal. There are an additional 2
products that are not specific to any particular type of renewable energy industry.

Predictors of Success in a Greening World198` Table 13: Ranking of countries by GCP and Wind and Solar CP

Country

Total GCP

CountryWind
Windand
andSolar
SolarGCP
CP

China

3.92

Italy

4.43

Italy

3.89

China

3.99

Spain

3.33

Spain

3.69

France2.85

Turkey2.93

Germany

2.75

France2.88

Turkey

2.55

India

2.86

Poland2.5

Poland

2.61

India

2.4

Portugal

2.48

Austria

2.38

Czechia

2.25

Netherlands

2.3

USA

2.23

Despite differences in the ranking of countries by CI for wind and solar manufacturing relative
to their overall ranking in green complexity, countries still face very different comparative
positions within these technologies. As noted earlier, there are more green products thatare specific to solar or wind than products with overlapping usage between the two or withother types of renewable energy. Therefore, while a country might have a similar CI for windand solar relative to their overall GCI, countries may be more specialised in one renewable
technology. Table 12 shows a ranking of countries by CI for wind and solar separately.
Comparing the country rankings in Table 12, countries demonstrate some specialization
between their green complexity in wind or solar, but not equally for both. Germany, Denmark,the United States, and Romania are more specialised in wind relative to solar. In contrast,
Japan, South Korea, and China are more specialised in solar compared to wind. This indicatesa significant difference in a country’s specialisation in renewable energy that may otherwise beoverlooked by the ranking of countries in Table 11. This is evident in the case of the US, whichis ranked 3rd in wind and solar complexity combined, but has higher specialisation in solar
product complexity. South Korea ranks 8th for combined wind and solar complexity, while in
Table 12 South Korea is ranked second in solar but is not ranked in the top 10 for wind.

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Predictors of Success in a Greening World199` Table 14: Ranking of countries by Wind CP and Solar CP

CountryWind
WindGCPCPCountry

Solar
SolarGCP
CP

China

4.56

China

4.92

Italy

4.2

Italy

3.67

Spain

3.95

Poland

3.58

Turkey

3.13

Spain

3.48

France2.83

Germany

3

India

2.66

France2.97

Portugal

2.65

India

2.81

Croatia

2.62

USA

2.72

Poland

2.54

Turkey2.63

Netherlands

2.39

Czechia

2.46

To get a sense of future wind and solar trajectories, re-calculations of CP for a subset of windand solar products have been similarly compiled and included in Table 13. From the rankings,
the same countries that rank highly in green complexity under CI do not rank as highly
under CP, suggesting that the countries that already have a high degree of complexity haveless potential. The ranking of countries by CP overall and for the subset of wind and solar
technology are similar, with the top 2 positions occupied by the same two countries. Asidefrom countries that are consistently ranked highly overall and for a subset of wind and solar
potential CP, those that demonstrate a better position in wind and solar products relative totheir overall GCP are Turkey, India, Portugal, and Czechia. This suggests that these countries
are well positioned with a high potential complexity in wind and solar manufacturing, relative
to other forms of green product development.
Similarly, Table 14 illustrates the CP ranking of countries by wind and solar separately. The
disaggregated rankings for wind and solar illustrate different specializations for a country’s
potential in either wind or solar production. Although Spain does not appear in the top 10 for
any measure of CI, it consistently appears in the top 10 for CP scores under wind and solar.
While Turkey appears as the fourth ranked country by CP for the combined wind and solar
products, it has greater potential in wind manufacturing compared to solar. In contrast, while
Poland is ranked seventh for the combined wind and solar products, it has greater potential insolar, where it is ranked third.

Predictors of Success in a Greening World200

To compare the relative position of countries according to their CI and CP in wind and solar
for the seven countries studied in this report, along with Italy, Figure 73 and Figure 74 illustrate
the relationship between countries’ current complexity and their potential. They illustrate
which countries have higher potential compared to their current levels of complexity inwind and solar, and in relation to other countries. From the figures, the correlation between
a country’s CI and a country’s CP in wind or solar is clearly positive, but not perfect. Thisis particularly true for countries that score highly according to either measure30, broadly
indicating that countries that have a high level of complexity in wind or solar currently are not
the same countries that have the highest potential.
The comparative rankings and position of countries according to their green complexity inwind and solar suggests potential future leaders in the production of these renewable energy
products. Knowing which countries are specialised in the production and manufacture ofwind and solar products compared to other types of green products adds to the information
available to investors as they strategically develop their portfolios in the renewable energy
sector.

30Wind correlation coefficient: 0.642, solar correlation coefficient: 0.535.

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Predictors of Success in a Greening World

201` Fig 73: A scatterplot of wind CP and wind CI (2015-2019) for all countries withthe seven case study countries and Italy highlighted

4Wind CP Score

3
2

1

0
-1
0

1

2
Wind CI Score

3

4

5

` Fig 74: A scatterplot of solar CP and solar CI (2015-2019) for all countries with theseven case study countries and Italy highlighted
54Solar CP Score

3
2

1

0

-1
0

1

2
Solar CI Score

3

4

5

Source: Authors' own calculations based on Gaulier, G. and Zignago, S., 2010. Baci: international trade
database at the product-level (the 1994-2007 version).

Predictors of Success in a Greening World

202

The micro and meso picture: wind and solar companies
Wind and solar capacity could increase ten-fold in just 20 years as part of global efforts toachieve the Paris goals and reach net zero by mid-century, according to Way et al. 202131. This
research also suggests that future global solar capacity is set to be at least triple future global
wind capacity. Using both export competitiveness data and corporate level data at both thecountry and corporate level can help investors navigate the rapidly changing global wind andsolar landscape.
Institutional investors will play a key role in facilitating growth in wind and solar capacity –pension funds, insurance companies and other long-term asset owners and managers form asubstantial pool of private capital that is increasingly being directed at the renewables sector.
Pureplay wind and solar companies, making up a complex value chain that operates acrossglobally integrated supply chains, are an increasingly central focus for investors who want togain exposure to the clean energy transition. This section analyses some of the implicationsof such increases in wind and solar investments at the corporate level, to complement to theprevious wind and solar investment implications at the national level.
To combine both a country-level and company-level perspective, a global sample of major
wind and solar companies was constructed. The selection sought to capture specialized,
pureplay companies with the greatest exposure to wind and solar industries. The windand solar product value chain was examined (Figure 75), unpacking the various activities
associated with each technology, ranging from upstream materials production to downstream
electricity generation. This value chain acted as a starting point in constructing a datasetof publicly listed companies with a high level of purity to wind and solar industries. The
methodology used to derive our sample of wind and solar corporates follows industry bestpractices - however, it is not based on peer-reviewed research and should be interpreted withcaution.
Firstly, the value chain activities in Figure 2 were mapped onto the S&P Global Trucost
Climate Impact Sectors Classification (CISC). The CISC defines corporate revenue streams
based on 447 underlying high climate impact sub-industries. High climate impact in thiscontext refers to sub-industries that are key to a low-carbon transition, as defined in the
EU Low Carbon Benchmarks Regulation (2019/2089). Relevant CISC sub-industries wereselected and mapped to the most relevant activity in the wind and solar value chains. In total,
32 CISC sub-industries were selected (16 Upstream, 12 Midstream, and 4 Downstream).
Secondly, each of the 32 CISC sub-industries was assigned an Exposure Score (ranging from0 to 1), using expert judgement and engagement with industry professionals (Figure 76).
The Exposure Score was calculated using two considerations – specialisation and relevance.
31 Way, Rupert, Matthew C. Ives, Penny Mealy, and J.Doyne Farmer, Empirically Grounded Technology Forecasts and the Energy
Transition, 2021 https://www.inet.ox.ac.uk/publications/no-2021-01-estimating-the-costs-of-energy-transition-scenariosusing-probabilistic-forecasting-methods/

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Lombard Odier · December 2021

Predictors of Success in a Greening World203

� Fig 75: Wind and solar value chain
Downstream

Generationand distribution

Wind turbine components
Blades, towers, nacelle,bearings, castings
Metals and minerals
CopperAluminium
Rare Earth

Upstream
InputsMidstream

Construction and installation

Midstream

Wind farm

Product manufacturing

Cabling,
engineering
design,construction,lease andinsurance,
commissioning,development,
finance,
O&M

Wind energy
generation

Solar Power
Plant
Solar energy
generation

Mixed windand solar
developers
Chemicals
Plastics
PolysiliconAncillary services
All non-module hardware(inverters, trackers, steel structures, cabling)
Monitoring and controls
PV manufacturing equipment

Mixed windandsolar generation
Solar Panel
Components
Wafer, cell, module` Fig 76: Exemplifying the scoring process employed to score companies

Company

Revenuebreakdown
Sectors

100%

SIEMENS GAMESAWind turbine
manufacturer

Turbine and turbine generator
set units manufacturing

20%

CANADIA SOLAR
Solar panel
components
manufacturer

Revenuebreakdown
Exposure scores for sub

1

Semiconductor and related
device manufacturing

1

1%

0.8

29%

0.6

Solar Power Generation
Other non residential structures

Final Purity Score

1

0.88

Predictors of Success in a Greening World

204

The first was the specialisation of the sub-industry, capturing how much the sub-industry
exclusively contributes to the wind and solar value chain; pureplay activities were assigned
higher scores than generic, diversified sub-industries whose activities play less of a directrole in driving wind and solar growth. Secondly, the relevance of the sub-industry to windand solar products specifically was analysed; this assigned higher scores to midstream (coremanufacturing) activities that involved component manufacturing and installation, whilst
reducing the emphasis on upstream and downstream activities. Overall, for example, thesub-industry “Turbine and turbine generator set units manufacturing” was given a highscore (specialisation = high, relevance = high), as it sits in the relevant midstream productcomponent manufacturing section of the value chain, whilst also being quite exclusive in
its link to wind turbine manufacturing. “Custom computer programming services”, on theother hand, whilst being a relevant sub-industry to product manufacturing, scored low on
specialisation as wind and solar activities likely only comprise a small segment of the subindustry.
On average, upstream and downstream sub-industry exposure scores were low (0.33 and0.5 respectively), whilst midstream sub-industry scores were higher (0.8). This focus on
midstream manufacturing activities also attempts to encapsulate the range of products, as
opposed to services and inputs.
A further keyword analysis was performed using company descriptions, filtering out
companies with little relevance to wind or solar value chains. Furthermore, all companies withpurity scores below 0.3 were excluded from the sample, to maintain high average purity towind and solar industries.
The framework produced a sample of 93 companies, providing an indication of the corporate
landscape for the wind and solar industries. Table 15 shows summary statistics; the sample
contained companies from nineteen countries, with a strong presence in China and the US in
terms of headquarter location, primarily in midstream activities.

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Predictors of Success in a Greening World205` Table 15: Summary statistics on solar and wind companies in 19 major economies
Midstream

Upstream
Company Location(Headquarters)
China

Inputs4

Product
Manufacturing

Downstream

Construction
andInstallation

Generation andDistribution

16

11

5

5

4

2

1

8

Canada

1

3

1

5

India

2

2

1

5

Japan

2

2

USA
GermanySouth Korea

1

1

Spain

1

Taiwan3

France

1

Italy

2

1

4

3

1

4
3

1

2

1

2

1

Sweden1

Switzerland

4
4

1
1

1

32
10

3

ThailandNorway1

TotalCompanies

2
1

2

1

2

Denmark

1

1

Greece11Israel1

United Kingdom
Total Companies

1
7

40

1
1

36

10

93

Predictors of Success in a Greening World

206` Table 16: Top 10 countries for each category of sample revenue(W+S = wind and solar)32

Portion of sample
Country

revenue – WindCountryand Solar (%)

Portion of sample
revenue – Solar (%)

Portion of sample
Country

revenue – Wind
(%)

China

33

China

23.6

China

13.7

USA

14.1

USA

11.5

USA

6.8

Japan

6.7

Japan

5.9

India

4.4

India

6.3

Thailand

3.6

Germany

3.1

Germany

4.5

India

3.0

Japan

2.2

Thailand

3.6

Canada2.5

Canada2.2

South Korea

3.2

South Korea

2.5

Italy

1.9

Canada2.7

Germany

2.2

Sweden

1.5

Spain

2.6

Spain

2.2

United Kingdom

1.2

Italy

2.4

Taiwan2.0

France

1.1

Other

20.9

Other

34.0

Other

54.9

For each company, data was retrieved on revenue breakdown by country. Table 16 shows the
top 10 countries in terms of revenue generated from wind and solar companies in the sample.
For example, when all revenues generated for each company in the sample were aggregated,
33% were drawn from wind and solar products sold in China. The dominance of China andthe US markets in this regard mirrored the number of companies from each country present
in the sample, with 32 and 10 companies based in China and the US respectively. The top 10
countries in each category of Table 16 differ somewhat from Table 12, which shows the top 10
ranked countries by wind and solar CI. China features lower on CI compared to the size of its
corporate level influence. Thailand, Spain, and Canada, have lower CI ranks, yet all feature
more prominently in the corporate level data. Germany, which has the highest wind CI rank,
fails to come close to China in terms of the number of leading wind and solar companies inthe sample. The corporate data does not have any company representation from Denmark,Finland, Romania, or Austria in the top ten rankings, which all feature prominently in the
rankings of countries based on CI (both combined wind and solar and individually).

32

Some revenue classifications apply to both wind and solar which explains the discrepancies between the total wind and solar
revenue share, and the sum of the solar and wind revenue shares.

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Predictors of Success in a Greening World207` Table 17: Revenues (%) generated by country. Seller country are shown in rows andbuyer country in columns.

Headquater location

Revenues (%) generated by country

CanadaChina

Germany

India

Italy

Japan

Spain

ThailandUSA

Canada

36%

3%

6%

0%

0%

23%

1%

0%

5%

China

0%

85%

1%

1%

0%

1%

0%

0%

4%

Germany

1%

10%

33%

1%

4%

2%

1%

0%

16%

India

0%

0%

0%

97%

0%

0%

0%

0%

2%

Italy

0%

0%

7%

0%

67%

1%

1%

0%

2%

Japan

1%

4%

1%

2%

0%

69%

0%

2%

5%

Spain

2%

1%

2%

2%

7%

0%

40%

0%

20%

Thailand

0%

0%

0%

0%

0%

13%

0%

79%

0%

USA

4%

7%

1%

1%

0%

4%

0%

0%

67%

Other

1%

6%

4%

2%

1%

3%

3%

0%

19%

It thus appears that the countries that are most competitive and complex in wind and solar
exports do not necessarily dominate the wind and solar industry in the corporate sample. What
drives the apparent discrepancies between CI rank and corporate level representation? First,
the sample of companies used in this analysis is relatively small and may not be representativeof country’s corporate landscapes relating to wind and solar. Secondly, the Green Complexity
Index (GCI) measures the number and complexity of green products that a country has
exported competitively. It is thus aimed at measuring exports, and in the context of Wind andSolar CI, specifically in products related to these areas. Moreover, competitiveness measures
based on trade data are based on the relative importance of each product in a country's
exports, whereas the corporate level analysis in this section may well be coloured by the sizeof each country's economy. This highlights the importance of considering multiple factors
and indicators when navigating the landscape of green competitiveness. It is also important
to note that the location of a company's headquarters can often be different from the locationof its manufacturing activities. Table 17 provides evidence of this disconnect. In general, areasonable proportion of a company’s revenues in the sample are generated from the country
in which the company is headquartered. For example, companies that are headquartered in
Canada on average generate 36% of their revenues within Canada. Interestingly, this pattern is
far more pronounced for Asian companies.
Companies from China, India, Japan, and Thailand all generate well over half of theirrevenues domestically, whilst for Western companies the values are considerably lower.

Predictors of Success in a Greening World

208

Overall, these results seem to explain the differences between CI and corporate level rankings.
Germany, with the highest Wind and Solar CI ranking, seems to be the most competitive inexporting wind and solar products; unsurprisingly, companies headquartered in the country
only generate 33% of revenue domestically. The fact that Chinese companies generate 85%of revenue at home suggests that China has a very strong domestic wind and solar market.
Overall, countries with lower Wind and Solar CI rankings may still be interesting for investors;
corporate expertise may just be directed inwards, to the domestic market. Further analysis
could draw upon national production data to complement export data, in order to better
understand this dynamic.
As China is poised to become the largest market for wind and solar energy, comparing thefinancial characteristics of its companies with other countries reveals interesting results.
Table 18 provides more detail on the company profiles, in both midstream and downstream
segments of the value chain (upstream activities were left out due to their limited presencein the sample). Chinese wind and solar component manufacturers seem to be, on average,
larger than similar companies from other countries, whilst also trading at higher premia basedon price-to-earnings (P/E) ratios. However, Chinese wind and solar companies involved indownstream operations operate with higher capitalisation ratios than in other regions.

` Table 18: Summary information on the profiles of Chinese solar and wind companies
vs Rest of World.

Solar

Wind

Wind and Solar

China

Rest of World

China

Rest of World

Average Market Cap. (US$bn)

13.2

9.6

2

3.5

Average price/earnings (PE) ratio

108

16.2

17

58.4

0.38

0.42

0.72

0.58

16

25

12

32

Average capitalisation ratio(debt/equity)
Number of companies

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Lombard Odier · December 2021

Predictors of Success in a Greening World

209

Predictors of Success in a Greening World

210

Discussion
Several more specific investment implications can be drawn out from the CI/CP scores andcorporate level analysis. Firstly, opportunities across the wind and solar value chain vary acrossboth the relevance and the specialization of activities. Midstream activities that manufacturesolar panel and wind turbine components, and the construction of wind and solar farms
that are connected to the grid via specialized cabling and equipment, operate as the engineof growth for both industries. Materials inputs and downstream electricity generation offer
less pure play exposure to the wind and solar products theme. China, Germany, Japan, South
Korea, Taiwan, and the United States have the highest number of product manufacturing
companies in the sample; many of these are concentrated in the solar panel components
sector. China, the US, and Japan (already with the highest solar CI ranking) are simultaneously
set to consolidate country-level complexity in solar products, all with high CP rankings.
China is clearly playing an increasingly central role in the wind and solar landscape. Our
corporate level analysis revealed than Chinese companies on average generate 85% of theirrevenue from within China, and so whilst its wind and solar capabilities are clearly substantial
at the corporate level, they may yet be able to further capitalise on export opportunities.
China has the highest solar CP rank of any country, suggesting that product complexity will
likely increase; this could lead to technological innovation in other areas and push corporate
performance towards increased profitability in the future. In conclusion, the Chinese market
seems to offer the highest growth market for both wind and solar products – both at the export
level and the corporate level. As its strong domestic wind and solar market is well placed to
expand internationally, both areas can benefit substantially.
The US is likely to continue playing a key role in terms of trade as well as at the corporate level,
based on wind and solar CI and CP scores, and because American wind and solar companies
have the largest average market capitalization out of any country in the sample. This isespecially true in its solar capabilities; its companies are more profitable than Chinese rivals,
and it ranks highly under both solar CI and solar CP. However, its dependence on Chinese raw
materials for wind and solar products, combined with ongoing trade tensions, imply supply
chain risks that could hamper both export and corporate competitiveness into the future. The
United States is 100% reliant on foreign sources of arsenic, gallium, and indium, all of which
are crucial components in solar cells. China dominates the global supply of many of these
metals, as well as other rare-earth metals32, aluminium, and refined copper that are used inwind turbine manufacturing and other renewable energy products. In recent months, Chinese

31 "Zhang, L., Wang, J., Wen, H., Fu, Z. and Li, X., 2016. Operating performance, industry agglomeration and its spatial
characteristics of Chinese photovoltaic industry. Renewable and Sustainable Energy Reviews, 65, pp.373-386.

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Lombard Odier · December 2021

Predictors of Success in a Greening World211

magnesium production, which is responsible for 87% of global supply, has slowed significantly
due to power cuts and reduced energy consumption in China, forcing plants to close or halt
production. Magnesium is critical in aluminium production, which in turn is a key material inboth solar panels and wind turbines. China’s dominance in supplying such materials presents
significant supply chain risks for companies in the US and Europe, who rely on Chinese
imports to drive production. The recent US-China climate agreement at COP26 to jointly
accelerate the low-carbon transition and climate technology innovation has been received withcautious optimism33.
Finally, perhaps the most interesting investment trend is the increasing role European
countries will play in the energy transition. Italy, Spain, France, Turkey, and Poland all havevery high CP ranks across both wind and solar products and could present attractive markets
for private sector investment if this is followed by the development of trailblazing domestic
wind and solar companies. Policy must also identify where opportunities for growth lie in thecontext of their countries' capabilities. For example, Switzerland’s wind and solar productmanufacturing capabilities are relatively weak, and thus return low CI and CP scores. Thiswas recognised by State Secretary for International Finance Daniela Stoffel during a panelat COP26 in Glasgow; she argued that Switzerland’s strong financial services industry andexpertise in sustainable finance could play a key role in providing the necessary capital toaccelerate the energy transition, thus contributing via a different route.

32The EU’s Critical Raw Materials framework sets out a comprehensive review of many of the materials used in wind and solar
products. Available at: https://ec.europa.eu/growth/sectors/raw-materials/areas-specific-interest/critical-raw-materials_en
33 https://www.state.gov/u-s-china-joint-glasgow-declaration-on-enhancing-climate-action-in-the-2020s/

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Conclusion

The world is in the midstof a new industrial revolution,and industries, investors and governmentsthat actively invest in and foster high-growth climate
compatible industries have much to gain.

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6. Conclusion

Megatrends are shifting the global competitiveness landscape. Even if the politics of climatechange mitigation can, at times, appear intractable, it is unlikely to stop the processes that havealready been set in motion with consistent declines in the cost of renewable energy, batteries,
electrolysers, and other clean technologies. Technological change is supporting automation,mechanisation, electrification, and dynamic optimisation, all of which are helping to drive theclean energy transition. While the long-term picture is clear, the path to this new green economy
will be littered with tales of winners and losers: those who are able to seize the opportunities
arising from the transition, and those who are left behind holding stranded assets. The aim of
this report is to help investors navigate this changing landscape, by not only illuminating themegatrends, but also analysing which countries and industries are well-placed in terms of theircurrent and future green competitiveness.
At the national level one can already see that some countries have captured value fromfast growing green sectors. China is a case in point, having emerged as a global solar PV
manufacturing powerhouse. The US has similarly captured value within its own large domestic
market. The laggards are also visible: Australia and, to a lesser extent, the UAE, have only mostrecently shown signs of providing a favourable environment for green investment.
Clean energy financing is not without its challenges: renewable energy projects generally
have high capital costs and carry significant risk in many developing countries. Yet, thesetechnologies have also exhibited remarkable learning rates which have led to cost declines andremarkable growth. It is likely that products that are complementary to renewable energy, suchas batteries and electrolysers for green hydrogen, will also grow substantially in the years tocome. The fate of the hydrocarbon sector is also clear. Most hydrocarbon power generators, if
not already uneconomic, are set to become more expensive than low-carbon alternatives in thenext 5-10 years.
Given this, investors aiming to curate portfolios that will maximise value would do well todisentangle short-term noise from long-term trends. As this report shows, a global green raceis underway; a race in which early movers will be rewarded and laggards will risk losing global
competitiveness.

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7. Appendix

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7. Appendix
A. Measuring green competitiveness
Empirical evidence has shown that industrial development is often path-dependent: countries
and regions are significantly more likely to develop competitiveness in products and services
which require similar capabilities to those they already produce1,2. There is further evidence tosuggest that countries which specialise in more technologically sophisticated products tend toenjoy greater income and growth3,4,5.
We employ the approaches introduced by Hidalgo and Hausmann (2007a)6 and Mealy andTeytelboym (2020)7 to measure competitiveness in exporting green products. Using CEPII’s
BACI database of bilateral international trade8 we construct a panel of country-level exports in
products at the 6-digit level from 1995-2019. This data provides bilateral trade flows between
more than 200 countries for over 5,000 products. To prevent our analysis from being skewed byshort-term fluctuations in trade, we use annual average values over rolling 5-year periods (19951999, 1996-2000, etc).

We first calculate “Revealed Comparative Advantage” (RCA), which is a product p’s share ina country c’s exports, divided by this product’s share in global trade. We then define a binary
variable m which takes the value 0 or 1. If RCA > 1, we say that a country exports “more than its
fair share” in this product; it exports the product competitively and m=1. If RCA is below 1, thecountry does not have competitiveness in the product and m=0.

1 Hidalgo, C.A., Klinger, B., Barabási, A.L. and Hausmann, R., 2007. The product space conditions the development of nations.
Science, 317(5837), pp.482-487.
2 Frank Neffke, Martin Henning, and Ron Boschma, ‘How Do Regions Diversify over Time? Industry Relatedness and theDevelopment of New Growth Paths in Regions’, Economic Geography, 87.3 (2011), 237–65 <https://doi.
org/10.1111/J.1944-8287.2011.01121.X>.
3 Hidalgo, C.A. and Hausmann, R., 2009. The building blocks of economic complexity. Proceedings of the national academy ofsciences, 106(26), pp.10570-10575.
4 Hidalgo and Hausmann 2017
5 Ricardo Hausmann & Jason Hwang & Dani Rodrik, 2007. "What you export matters," Journal of Economic Growth, Springer, vol.
12(1), pages 1-25, March.
6 Hidalgo and Hausmann.
7 Mealy, Penny, and Alexander Teytelboym, ‘Economic Complexity and the Green Economy’, Research Policy, 2020, 103948<https://doi.org/10.1016/j.respol.2020.103948>
8 Guillaume Gaulier and Soledad Zignago, ‘BACI: International Trade Database at the Product-Level (the 1994-2007 Version)’,
SSRN Electronic Journal, 2010 <https://doi.org/10.2139/ssrn.1994500>.

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Using RCA, we calculate the probability that a country exports product p’ if it also exports
product p: this is the proximity (or similarity) of product p and product p’. We then define theproximity of product p to country c as the average proximity of product p to other products
which the country exports with RCA>1 (cf. Hidalgo and Hausmann, 2007a). We also use thealgorithm developed by Hidalgo and Hausmann (2007a) to calculate the Product Complexity
Index (PCI), which is a proxy for technological sophistication. For more detail on themathematical interpretation of PCI, please refer to Mealy et al (2019)9.

9 Penny Mealy, J. Doyne Farmer, and Alexander Teytelboym, ‘Interpreting Economic Complexity’, Science Advances, 14.2 (2019)<https://doi.org/10.1126/SCIADV.AAU1705/SUPPL_FILE/AAU1705_SM.PDF>.

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B. Green Goods and the EU taxonomy
To see how our green goods classification compares to other definitions of sustainability,
we map our 19 categories to the six environmental goals set out in the “EU taxonomy forsustainable activities”. The EU taxonomy is a classification system created for the purpose ofidentifying which investments are “sustainable” and consistent with the European Green Deal.
It was published in June 2020 and entered into force the following month. The following tablelists the categories included in the EU taxonomy and maps them against all corresponding
categories within our list of traded green products.
EU taxonomy

Corresponding category green trade

Climate change mitigation

Cleaner or More Resource Efficient Technologies and Products
Efficient Consumption of Energy Technologies and Carbon Capture and Storage
Energy Efficiency
Environmental Monitoring, Analysis and Assessment Equipment
Gas Flairing Emission Reduction
Heat and Energy Management
Renewable Energy

Climate change adaptation

Environmental Monitoring, Analysis and Assessment Equipment
Natural Risk Management

The Sustainable use andprotection of water andmarine resources

Clean up or Remediation of Soil and Water
Environmental Monitoring, Analysis and Assessment Equipment
Natural Resource Protection
Resources and Pollution Management
Wastewater Management and Potable Water Treatment
Water supply

The transition toa circular economy

Environmentally Preferable Products based on End-Use or Disposal Characteristics
Management of Solid and Hazardous Waste and Recycling Systems
Waste Management, Recycling and Remediation
Wastewater Management and Potable Water Treatment

Pollution prevention control

The protection andrestauration of biodiversity
and ecosystems

Air Pollution Control
Clean up or Remediation of Soil and Water
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Gas Flairing Emission Reduction
Management of Solid and Hazardous Waste and Recycling Systems
Noise and Vibration Abatement
Renewable Energy
Resources and Pollution Management
Waste Water Management and Potable Water Treatment
Clean up or Remediation of Soil and Water
Cleaner or More Resource Efficient Technologies and Products
Environmental Monitoring, Analysis and Assessment Equipment
Environmental Preferable Products based on End-Use or Disposal Characteristics
Management of Solid and Hazardous Waste and Recycling Systems
Noise and Vibration Abatement
Resources and Pollution Management

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C. Data Sources` Green Complexity and Trade

All measures based on trade data are the authors' own calculations based on Gaulier, G.
and Zignago, S., 2010. Baci: international trade database at the product-level (the 19942007 version). Some, though not all, were originally published in Andres, P and Mealy, P(2021) Green Transition Navigator. Retrieved from www.green-transition-navigator.org.
Those measures, which include GCI, GCP, country-to-product proximity, and others, can beobtained from the Green Transition Navigator website.

` Recovery spending

Recovery spending information was sourced from the observatory database downloaded on
25 June from https://recovery.smithschool.ox.ac.uk/tracking/GDP data was sourced from World bank GDP data 2019 or latest in current US dollars on 25
June 2021 from https://data.worldbank.org/indicator/NY.GDP.MKTP.KD
The Recovery dataset used in this chapter distinguishes between different categories:
Covid spending ⊇ Recovery spending ⊇ Green recovery spending ⊇ Renewable
recovery spending• Covid spending is all fiscal spending of the past year or so• Recovery spending is that part of Covid spending that is intended for the long term(e.g. excluding liquidity support or direct cash transfers, including infrastructure
investment)• Green recovery spending is that part of Recovery spending that is deemed green• Renewable recovery spending is that part of Recovery spending that is part of fiscal
spending archetype 'eta': Clean energy infrastructure investment
The Recovery Observatory recognises 5 typologies, 40 archetypes and 158 sub-archetypesof fiscal spending. Renewable energy is archetype eta (𝜂): Clean energy infrastructure
investment. It is part of typology Recovery: investment measures. Sub-archetypes include
the construction of new renewable generation facilities (𝜂1), upgrades to the transmission
infrastructure (𝜂4), and building of CCS installations (𝜂8).
It is important to note that these figures indicate spending plans, not actuals, and may
therefore not correspond to how governments have actually allocated funds. In this analysis
we have focussed solely on long-term recovery spending which has the potential to impact an
economy’s competitiveness, and not on short-term rescue spending.

Predictors of Success in a Greening World222` Current green energy resources

The time trends in electricity generation capacity for each country shown in this report weresource from IRENA (2021), Renewable Capacity Statistics 2021; & IRENA (2020), Renewable
Energy Statistics 2020, The International Renewable Energy Agency, Abu Dhabi. https://www.irena.org/publications/2021/March/Renewable-Capacity-Statistics-2021` Future green energy potential

The availability of green energy sources varies over time and locations. This variation is
not only caused by the climatic or resource characteristics, but also by land use, labourcosts, access to finance, and political support. Some of these factors cannot or can only beapproximately quantified. As shown in Figure 1, estimates for global technical potential fromrenewable resources vary by orders of magnitude. Therefore, a full and precise assessment of
the long-term role of renewable energy sources for each country is not viable.

` Figure 1: Ranges of global technical potentials of RE sources derived from studies

presented in Chapters 2 through 7. Biomass and solar are shown as primary energy due
to their multiple uses10.
Electricity

Heat

Primary energy

10 IPCC, 2012, Renewable Energy Sources and Climate Change Mitigation, Special Report of the Intergovernmental Panel on
Climate Change, https://archive.ipcc.ch/pdf/special-reports/srren/SRREN_Full_Report.pdf , p39

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Understanding the potential of harnessing solar energy is particularly important given
the geographic potential is 3 to 100 times more than current global energy supply and it
is available in virtually every country on earth. Capturing the energy of sunlight is subject
to a diversity of constraints related to the solar irradiance in a certain area; geographicalconstraints such as the slope and the existing use of the land; practical constraints, such as
proximity to human settlement; and regulatory constraints, e.g., the protected status of theland, often related to ecosystem and wildlife preservation.
In this study we focus on a country’s technical potential for all such renewable resources,
which is a subset of a country’s geographical potential. The geographical potential is theenergy flux theoretically extractable in areas that are considered suitable and available forthis production i.e. in areas which are not excluded by other incompatible land cover/use
and/or by constraints set on local characteristics such as elevation and minimum averagewind speed. The technical potential is the geographical potential after the losses of theconversion from the extractable primary energy flux to secondary energy carriers or forms(electricity, fuel) are taken into account11.
There is unfortunately little consensus in the global scientific community on how best tomeasure the technical potential for the various renewable resources available. As notedby the IPCC Working Group III, “a variety of practical, land use, environmental, and/or economic constraints are used in estimating the technical potential of RE, but withlittle uniformity across studies in the treatment of these factors, including costs.12” Thereis, however, consensus that “technical potentials will not be the limiting factors for the
expansion of renewable energy on a global scale.13”
Total country renewable resources were calculated by combining onshore and offshore windand hydro resources with either solar or biomass totals depending on which provided the
maximum potential. This simplified methodology ensures a conservative total that assumes
biomass and solar resources are mutually exclusive, which will not always be the case.
Every effort was made to source the green energy potential data from reliable, peerreviewed sources that apply a single methodology to the broadest possible list of countries
used in this report. These are listed below by energy resource. In the cases where countries
were not covered by the main data source the additional sources are also listed.

11 Bert J.M. de Vries, Detlef P. van Vuuren, and Monique M. Hoogwijk, ‘Renewable Energy Sources: Their Global Potential for theFirst-Half of the 21st Century at a Global Level: An Integrated Approach’, Energy Policy, 35.4 (2007), 2590–2610 <https://doi.
org/10.1016/j.enpol.2006.09.002>.
12 Clarke L. and others, Transformation Pathways. In: Climate Change 2014: Mitigation of Climate Change, 2014 <https://www.
ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_chapter6.pdf>.
13 IPCC, 2012, Renewable Energy Sources and Climate Change Mitigation, Special Report of the Intergovernmental Panel on
Climate Change, https://archive.ipcc.ch/pdf/special-reports/srren/SRREN_Full_Report.pdf , p796

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224` Solar resources

Solar resource potential by country was sourced entirely from the World Bank, 2020, Solar
Photovoltaic Power Potential by Country, https://documents.worldbank.org/en/publication/
documents-reports/documentdetail/466331592817725242/global-photovoltaic-powerpotential-by-country and associated resources found online at https://globalsolaratlas.info/
Extensive information on the methodology used to generate solar potential which included
geographic potential (irradiance, terrain effects, cloud cover, temperature, etc) are available
at https://globalsolaratlas.info/support/methodology. For our measure of technical potential
we used “Practical potential (PVOUT Level 1, kWh/kWp/day), long-term” values. These
values were than multiplied by the PV equiv area (m2) for each country to produce a total
technical potential. All of these data are available for download at https://globalsolaratlas.
info/global-pv-potential-study. Note that Level 1 excludes unsuitable land, using of relevant
global datasets, due to physical/technical constraints, such as rugged terrain, presence ofurbanized/industrial areas, forests, and areas that are too distant from the centres of humanactivity.

` Wind resources

The primary source for wind resources for this report was Eurek, Kelly, Patrick Sullivan,
Michael Gleason, Dylan Hettinger, Donna Heimiller, and Anthony Lopez, ‘An Improved
Global Wind Resource Estimate for Integrated Assessment Models’, Energy Economics, 64(2017), 552–67 https://doi.org/10.1016/j.eneco.2016.11.015 as well as as well as Dujardin,
Jérôme, Annelen Kahl, and Michael Lehning, ‘Synergistic Optimization of Renewable Energy
Installations through Evolution Strategy’, Environmental Research Letters, 16 (2021) https://doi.org/10.1088/1748-9326/abfc75 and Swiss Energy Scope, https://www.energyscope.ch/en/questions/what-is-switzerlands-wind-energy-potential/

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The methodology employed by Eurek et al. excluded areas primarily based on geographic
limitations, such as water, excessive elevation or slope for onshore resources; water depth,
sea ice, and distance from shore for offshore resources; as well as land use suitability andregulation limits such as protected areas.

` Hydro resources

Hydro resource potentials were primarily sourced from Rogner, Hans-Holger, Roberto F.
Aguilera, Cristina L. Archer, Ruggero Bertani, S.C. Bhattacharya, Maurice B. Dusseault,
and others, ‘Energy Resources and Potentials’, Global Energy Assessment (GEA), 2012,
425–512 https://doi.org/10.1017/cbo9780511793677.013 with additional information sourced
from Von Sperling, Eduardo, ‘Hydropower in Brazil: Overview of Positive and Negative
Environmental Aspects’, Energy Procedia, 18 (2012), 110–18 https://doi.org/10.1016/j.
egypro.2012.05.023 and https://en.wikipedia.org/wiki/Electricity_sector_in_Norway` Biomass resources

Biomass resource potentials were primarily sourced from Deng, Yvonne Y., Michèle Koper,
Martin Haigh, and Veronika Dornburg, ‘Country-Level Assessment of Long-Term Global
Bioenergy Potential’, Biomass and Bioenergy, 74 (2015), 253–67 https://doi.org/10.1016/j.
biombioe.2014.12.003 and Rogner, Hans-Holger, Roberto F. Aguilera, Cristina L. Archer,
Ruggero Bertani, S.C. Bhattacharya, Maurice B. Dusseault, and others, ‘Energy Resources
and Potentials’, Global Energy Assessment (GEA), 2012, 425–512 https://doi.org/10.1017/
cbo9780511793677.013

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Itatum nam quatusti tem eiur? Ximos
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