JANUARY 2018
đ ď Đ ėBroad-Based Upturn,but for How Long?

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ISSN: 1014-8906
ISBN (paper): 978-1-4648-1163-0
ISBN (electronic): 978-1-4648-1245-3
DOI: 10.1596/978-1-4648-1163-0
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The cutoff date for the data used in this report was December 19, 2017.

Summary of Contents
Chapter 1

Global Outlook: Broad-Based Upturn—Will It Last? ...................................... 1

Special Focus 1

With the Benefit of Hindsight: The Impact of the 2014-16 Oil Price
Collapse ......................................................................................................... 49

Chapter 2

Regional Outlooks ......................................................................................... 73

Chapter 3

Building Solid Foundations: How to Promote Potential Growth ................. 157

Special Focus 2

Education Demographics and Global Inequality .......................................... 217

Boxes

Box 1.1

Is the global economy turning the corner? ........................................8

Box 1.2

Low-income countries: Recent developments and outlook ..............24

Box 1.3

Regional perspectives: Recent developments and outlook ..............30

Box 2.1.1 Potential growth in East Asia and Pacific ........................................82
Box 2.2.1 Potential growth in Europe and Central Asia ..................................97
Box 2.3.1 Potential growth in Latin America and the Caribbean ..................111
Box 2.4.1 Potential growth in the Middle East and North Africa..................123
Box 2.5.1 Potential growth in South Asia .....................................................132
Box 2.6.1 Potential growth in Sub-Saharan Africa ........................................144
Box 3.1

What is potential growth? .............................................................161

Box 3.2

Understanding the recent productivity slowdown: Facts andexplanations..................................................................................168

Box 3.3

Moving together? Investment and potential output ......................173

Box 3.4

The long shadow of contractions over potential output .................178

Box 3.5

Productivity and investment growth during reforms .....................188iii

Table of Contents
Foreword ...................................................................................................................................... xi
Acknowledgments .......................................................................................................................xiii
Executive Summary ..................................................................................................................... xv
Abbreviations............................................................................................................................. xvii
Chapter 1

Global Outlook: Broad-Based Upturn—Will It Last? .......................................... 1
Summary ................................................................................................................ 3
Major economies: Recent developments and outlook .............................................. 7
United States .................................................................................................... 7
Euro Area ....................................................................................................... 13
Japan .............................................................................................................. 13
China ............................................................................................................. 14
Global trends ........................................................................................................ 15
Global trade ................................................................................................... 15
Financial markets ........................................................................................... 16
Commodities ................................................................................................. 17
Emerging market and developing economies: Recent developments and outlook .. 19
Recent developments ...................................................................................... 19
Commodity-exporting EMDEs ............................................................... 19
Commodity-importing EMDEs............................................................... 21
Low-income countries ............................................................................. 22
EMDE outlook .............................................................................................. 22
Risks to the outlook .............................................................................................. 28
Upside risk: Stronger-than-expected growth in large economies...................... 28
Downside risk: Disorderly adjustment of financial market conditions ............ 29
Downside risk: Policy uncertainty and geopolitical risks ................................. 33
Downside risk: Increased restrictions to trade ................................................. 34
Downside risk: Sharper-than-expected slowdown in potential growth ............ 34
Region-specific downside risks ........................................................................ 35
Policy challenges ................................................................................................... 35
Challenges in major economies....................................................................... 35
Challenges in emerging market and developing economies ............................. 38
References ............................................................................................................. 44
Box 1.1 Is the global economy turning the corner? .................................................. 8
Box 1.2 Low-income countries: Recent developments and outlook ....................... 24
Box 1.3 Regional perspectives: Recent developments and outlook ........................ 30v

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Special Focus 1 With the Benefit of Hindsight: The Impact of the 2014-16 Oil Price Collapse ..... 49
Introduction ........................................................................................................... 51
What were the main drivers of the oil price plunge? ................................................ 52
U.S. shale oil production ................................................................................. 52
The role of OPEC policies .............................................................................. 54
The role of demand conditions ........................................................................ 54
The oil price collapse: The relative importance of supply and demand ............. 55
How did the recent oil price collapse impact the global economy? .......................... 56
Impact on oil exporters .................................................................................... 56
Impact on oil importers ................................................................................... 57
What was the policy response in oil exporters and oil importers? ............................ 59
Policy response in oil exporters ........................................................................ 59
Monetary policy ........................................................................................ 59
Fiscal policy ............................................................................................... 60
Structural policy ........................................................................................ 61
Policy response in oil importers ....................................................................... 63
Monetary policy ........................................................................................ 63
Fiscal policy ............................................................................................... 63
Structural policy ........................................................................................ 63
Concluding remarks and implications for the future ............................................... 64
Annex SF1.1 Decomposition of supply and demand shocks to oil prices:
Bayesian structural vector autoregressive model approach ................................ 67
References............................................................................................................... 68
Chapter 2

Regional Outlooks ............................................................................................... 73
East Asia and Pacific................................................................................................ 75
Recent developments ....................................................................................... 75
Outlook .......................................................................................................... 78
Risks................................................................................................................ 79
Box 2.1.1 Potential growth in East Asia and Pacific ................................................ 82
Europe and Central Asia .......................................................................................... 91
Recent developments ....................................................................................... 91
Outlook .......................................................................................................... 93
Risks................................................................................................................ 93
Box 2.2.1 Potential growth in Europe and Central Asia ......................................... 97
Latin America and the Caribbean .......................................................................... 105
Recent developments ..................................................................................... 105
Outlook ........................................................................................................ 107
Risks ............................................................................................................. 108
Box 2.3.1 Potential growth in Latin America and the Caribbean .......................... 111

vi

Chapter 2

Middle East and North Africa ............................................................................. 117
Recent developments ................................................................................... 117
Outlook ...................................................................................................... 118
Risks............................................................................................................ 120
Box 2.4.1

Potential growth in the Middle East and North Africa .................... 123

South Asia .......................................................................................................... 127
Recent developments ................................................................................... 127
Outlook ...................................................................................................... 128
Risks............................................................................................................ 130
Box 2.5.1

Potential growth in South Asia ....................................................... 132

Sub-Saharan Africa ............................................................................................ 137
Recent developments ................................................................................... 137
Outlook ...................................................................................................... 139
Risks ............................................................................................................ 141
Box 2.6.1 Potential growth in Sub-Saharan Africa ........................................... 144
References ......................................................................................................... 149
Chapter 3

Building Solid Foundations: How to Promote Potential Growth .................... 157
Introduction ...................................................................................................... 159
Evolution of potential growth: What happened? ................................................ 164
Drivers of the slowdown in potential growth ...................................................... 166
Total factor productivity growth .................................................................. 166
Physical capital accumulation ....................................................................... 172
Labor supply ................................................................................................ 176
Prospects for potential growth: What could happen? .......................................... 181
Policy options to lift potential growth ................................................................ 183
Raising physical capital ................................................................................ 183
Raising human capital .................................................................................. 184
Raising labor supply ..................................................................................... 185
Raising productivity ..................................................................................... 186
Reforms for growth: More important should history repeat itself ...................... 190
Box 3.1

What is potential growth? ............................................................... 161

Box 3.2

Understanding the recent productivity slowdown: Facts andexplanations .................................................................................... 168

Box 3.3

Moving together? Investment and potential output ......................... 173

Box 3.4

The long shadow of contractions over potential output ................... 178

Box 3.5

Productivity and investment growth during reforms ....................... 187

Annex 3.1 Potential output estimates using the production function approach 193
Annex 3.2 Potential output estimates using statistical filters ............................ 199

vii

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Chapter 3

Annex 3.3 TFP and potential output growth during investment booms
and busts........................................................................................... 203
Annex 3.4 Long-term effects of output contraction............................................. 204
Annex 3.5 Impact of reforms .............................................................................. 205
References ............................................................................................................ 206

Special Focus 2 Education Demographics and Global Inequality ................................................ 217
Introduction ......................................................................................................... 219
Recent evolution of global inequality ............................................................. 220
Education wave and the global labor market .................................................. 221
Education wave and global inequality ............................................................ 222
Conclusions .......................................................................................................... 225
Annex SF2.1 Methodology, data, and measures of inequality................................ 226
References............................................................................................................. 227
Statistical Appendix...................................................................................................................... 231
Figuresviii

1.1

Summary - Global prospects ......................................................................... 5

1.2

Global risks and policy challenges ................................................................. 6

1.3

Advanced economies..................................................................................... 7

1.4

United States .............................................................................................. 13

1.5Euro Area ................................................................................................... 14

1.6

Japan .......................................................................................................... 14

1.7

China ......................................................................................................... 15

1.8

Global trade ................................................................................................ 16

1.9

Global finance ............................................................................................ 17

1.10

Commodity markets ..... …………………………………………………..18

1.11

Activity in EMDEs ..................................................................................... 19

1.12

Activity in EMDE commodity exporters..................................................... 20

1.13

Activity in EMDE commodity importers excluding China ......................... 21

1.14

EMDE growth prospects ............................................................................ 23

1.15

Global growth forecasts: Uncertainty and the balance of risks .................... 28

1.16

Upside risks of stronger-than-expected growth in large economies .............. 29

1.17

Financial market risks ................................................................................. 32

1.18

Policy uncertainty and geopolitical risks...................................................... 33

1.19

Trade protectionism ................................................................................... 34

1.20

Slowing potential growth ........................................................................... 35

1.21

Monetary and fiscal policies in advanced economies ................................... 36

1.22

Structural policy in advanced economies ..................................................... 37

1.23

Policy challenges in China .......................................................................... 37

Figures

1.24

EMDE monetary policy ............................................................................ 38

1.25

EMDE fiscal policy ................................................................................... 39

1.26

EMDE structural policy ............................................................................ 40

1.27

Education and inequality .......................................................................... 41

SF1.1

The oil price plunge of 2014-16 in perspective ......................................... 51

SF1.2

U.S. shale oil activity and OPEC policy .................................................... 53

SF1.3

Oil demand trends .................................................................................... 54

SF1.4

Oil supply and demand shock decomposition ........................................... 55

SF1.5

Global activity .......................................................................................... 56

SF1.6

Activity in oil-exporting EMDEs .............................................................. 57

SF1.7

Activity in oil-importing economies .......................................................... 58

SF1.8

Policy response in oil-exporting EMDEs................................................... 60

SF1.9

Oil dependency in oil-exporting EMDEs .................................................. 62

SF1.10 Reforms and Doing Business scores ......................................................... 63
SF1.11 Policy response in oil-importing economies .............................................. 64
SF1.12 Long-term outlook ................................................................................... 65
2.1.1

EAP: Recent developments ....................................................................... 76

2.1.2

China ....................................................................................................... 77

2.1.3

EAP: Outlook and risks ............................................................................ 78

2.2.1

ECA: Recent developments....................................................................... 92

2.2.2

ECA: Outlook and risks ............................................................................ 94

2.3.1

LAC: Recent developments ..................................................................... 106

2.3.2

LAC: Outlook and risks .......................................................................... 107

2.4.1

MENA: Recent developments ................................................................. 118

2.4.2

MENA: Outlook and risks ...................................................................... 119

2.5.1

SAR: Recent developments ..................................................................... 128

2.5.2

SAR: Outlook and risks ......................................................................... 129

2.6.1

SSA: Recent developments ...................................................................... 138

2.6.2

SSA: Outlook and risks ........................................................................... 140

3.1

Global growth......................................................................................... 160

3.2

Evolution of potential growth ................................................................. 164

3.3

Regional potential growth ....................................................................... 165

3.4

Drivers of potential growth ..................................................................... 166

3.5

Total factor productivity growth ............................................................. 167

3.6

Investment growth .................................................................................. 176

3.7

Demographics......................................................................................... 177

3.8

Potential growth prospects ...................................................................... 182

3.9

Policies to stem declining potential growth ............................................. 184

3.10

Growth and crisis scenarios ..................................................................... 191
ix

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Figures

Annex A3.2.1 Global output gap .......................................................................... 201
Annex A3.3.1 Potential growth around investment booms and busts in EMDEs:
Alternative measures ....................................................................... 203

Tables

SF2.1

Globalization and inequality ........................................................... 220

SF2.2

Evolution of inequality, 1988-2013 ................................................ 221

SF2.3

Future supply of skilled workers ..................................................... 222

SF2.4

Global inequality in 2012 and 2030 ............................................... 223

1.1

Real GDP ........................................................................................... 4

1.2

List of emerging market and developing economies ......................... 43

Annex SF1.1 Country classification ....................................................................... 66
2.1.1

East Asia and Pacific forecast summary ............................................. 80

2.1.2

East Asia and Pacific country forecasts .............................................. 81

2.2.1

Europe and Central Asia forecast summary ....................................... 95

2.2.2

Europe and Central Asia country forecasts ........................................ 96

2.3.1

Latin America and the Caribbean forecast summary ....................... 109

2.3.2

Latin America and the Caribbean country forecasts ........................ 110

2.4.1

Middle East and North Africa forecast summary ............................ 121

2.4.2

Middle East and North Africa economy forecasts ........................... 122

2.5.1

South Asia forecast summary .......................................................... 131

2.5.2

South Asia country forecasts ........................................................... 131

2.6.1

Sub-Saharan Africa forecast summary ............................................. 142

2.6.2

Sub-Saharan Africa country forecasts .............................................. 143

Annex 3.1.1 Country and year coverage.............................................................. 197
Annex 3.1.2 Regression results of total factor productivity ................................. 197
Annex 3.1.3 Regression results of labor force participation rates ......................... 198
Annex 3.2.1 Country and year coverage.............................................................. 202
Annex 3.3.1 Potential growth, TFP growth, and investment ............................. 203
Annex 3.4.1 Impulse response of potential growth to contraction events ........... 204

x

Foreword“Cinema,” Martin Scorsese once said, “is a matterof what’s in the frame and what’s out.” The same
could be said about economic growth, as thisJanuary 2018 edition of Global Economic Prospects(GEP) illustrates. On the one hand, the GEP
points out that, for the first time since the global
financial crisis, all major regions of the world areexperiencing an uptick in economic growth. The
current, broad-based growth acceleration is awelcome trend and could be self-reinforcing.
On the other hand, stepping outside the frame ofshort-term forecasting, the GEP observes thatgrowth in investment and in total factor
productivity (TFP) has been declining over the
past five years. Thanks to demographic trends,
labor force growth has also been slowing in many
parts of the world. This means that potential
output—the amount the economy can produce iflabor and capital were fully employed—wouldgrow at a subdued pace in the future. The current
demand-led recovery is likely to run up against
supply constraints. The decline in TFP growth isparticularly troubling since this has been a key
source of rising living standards in many countries
in the past.
The combination of what’s in the original frame
and what’s outside—the movie, if you like—is aclarion call for public action. To arrest andpossibly reverse this decline in potential growth,
emerging market and developing economies needto accelerate investment in both physical andhuman capital, especially if TFP growth is likely toremain anemic. This may sound like the standard
prescriptions of development economics. There’s areason for that: they are fundamental to economic
growth. Today, the costs of neglecting theseprinciples have gone sky-high.
Stepping even further outside the original frame,
the GEP and other research suggest ways topromote investment in physical and human capitalby examining what limits them now. For example,
private investment is often constrained by the lackof infrastructure. And infrastructure investment
has been limited because governments lacked“fiscal space.” But as the section in the GEP on the
recent oil price decline shows, oil-importing

countries missed the opportunity to rebuild fiscal
space by reducing energy subsidies; some of themdid, but not nearly enough. Similarly, according
to the 2018 World Development Report, Learning
to Realize Education’s Promise, while developing
countries have been investing in school
enrollment, learning outcomes—what reallymatters for human capital accumulation—havebeen woefully inadequate.
Taken together, these findings point to what isconstraining investment in human and physicalcapital: politics. Energy subsidy reform is difficultin an oil-importing country where, say, 8 percentof the firms are highly energy-intensive, but 45
percent of the politically-connected ones are.
Learning can be difficult in countries where
teachers, who run the campaigns of local
politicians, are absent 25 percent of the time.
What can be done to overcome these constraints?
If a majority of the population stand to benefit
from reforms that promote physical and humancapital accumulation, then they should be able tobring pressure to bear on politicians, who may becatering to special interests, for broad-based
reform. To do this, citizens need to be informed
about the costs and benefits of reform (and of notreforming). Publications like the GEP contributeto this effort by putting objective, rigorous analysis
in the hands of the public. Not only does theJanuary 2018 Global Economic Prospects identify
the problem of limited potential growth, it is alsopart of the solution.
Among these measures, efforts to invest in
infrastructure and education, health and otherhuman skills and wellbeing, as well as initiatives topromote economic diversification and liberalize
trade, will boost growth prospects and improvestandards of living. The international community
has an important role to play in the pursuit ofthese goals.
Shantayanan Devarajan
Senior Director
Development Economics
The World Bank GroupxiAcknowledgments
This World Bank Group Flagship Report is a product of the Prospects Group in the Development Economics Vice
Presidency. The project was managed by M. Ayhan Kose and Franziska Ohnsorge, under the general guidance of
Shantayanan Devarajan.
Chapters 1 and 2 were led by Carlos Arteta. Chapter
1 (Global Outlook) was prepared by Carlos Arteta
and Marc Stocker, with contributions from
Ekaterine Vashakmadze and Collette M. Wheeler.
Additional inputs were provided by John Baffes,
Sinem Kilic Celik, Delfin S. Go, Gerard Kambou,
Eung Ju Kim, Csilla Lakatos, Hideaki Matsuoka, Y.
Modeste Some, and Dana Vorisek.
Chapter 2 (Regional Outlooks) was supervised by
Carlos Arteta, Anna Ivanova, and Franziska
Ohnsorge. The authors were Ekaterine Vashakmadze(East Asia and Pacific), Yoki Okawa (Europe andCentral Asia), Dana Vorisek (Latin America and the
Caribbean), Lei Sandy Ye (Middle East and North
Africa), Temel Taskin (South Asia), and Gerard
Kambou (Sub-Saharan Africa).
Chapter 3 (Building Solid Foundations: How toPromote Potential Growth) was prepared by Sinem
Kilic Celik, M. Ayhan Kose, Franziska Ohnsorge, and
Y. Modeste Some.
The first Special Focus, With the Benefit ofHindsight: The Impact of the 2014–16 Oil Price
Collapse, was prepared by Marc Stocker, John
Baffes, and Dana Vorisek, with contributions from
Carlos Arteta, Raju Huidrom, Atsushi Kawamoto,Seong Tae Kim, Y. Modeste Some, Shane S. Streifel,
and Collette M. Wheeler.
The second Special Focus, Education Demographics
and Global Inequality, was prepared by Marcio Cruz,
Delfin S. Go, Franziska Ohnsorge, and Israel OsorioRodarte.
Boxes in Chapters 1, 2, and 3 were prepared by
Carlos Arteta, Ergys Islamaj, Gerard Kambou, Sinem
Kilic Celik, M. Ayhan Kose, Franziska Ohnsorge,
Yoki Okawa, Y. Modeste Some, Temel Taskin,Ekaterine Vashakmadze, Dana Vorisek, and Lei
Sandy Ye.

Research assistance was provided by Mai Anh Bui,
Ishita Dugar, Xinghao Gong, Shituo Sun, andJinxin Wu.
Modeling and data work were provided by Mai Anh
Bui, Xinghao Gong, Rajesh Kumar Danda, andJinxin Wu.
The online publication was produced by Graeme
Littler and Mikael Reventar. Mark Felsenthal andPhillip Hay managed media relations anddissemination. Mark Felsenthal, Graeme Littler, andDaniel Nikolits provided editorial support, with
contributions from Adriana Maximiliano.
The print publication was produced by Maria Hazel
Macadangdang, Adriana Maximiliano, Quinn John
Sutton, and Rosalie Singson Dinglasan, in
collaboration with Aziz Gökdemir, Michael Harrup,
Patricia Katayama, and Jewel McFadden.
Many reviewers offered extensive advice andcomments. These included: Kishan Abeygunawardana, Sara Alnashar, Camilo Amezquita, Paloma
Anos Casero, Rabah Arezki, Dilek Aykut, Luca
Bandiera, Daniel Barco, John Adrian Barham,
Ulrich Bartsch, Davaadalai Batsuuri, Robert Carl
Michael Beyer, Guillermo Raul Beylis, Fernando
Blanco, Monika Blaszkiewicz-Schwartzman, Florian
Michael Blum, Elena Bondarenko, Eduardo
Borenzstein, Stefanie Brodmann, Cesar Calderon,
Jasmin Chakeri, Derek Chen, Yew Keat Chong, Ajai
Chopra, Ibrahim Chowdhury, Punam Chuhan-Pole,
Kevin Clinton, Fabiano Colbano, Tito Cordella,
Stefano Curto, Brahima Coulibaly, Barbara Cunha,
Simon Davies, Annette De Kleine Feige, Agim
Demukaj, Allen Dennis, Tatiana Didier, Viet Tuan
Dinh, Makhtar Diop, Ndiame Diop, Anton Dobronogov, Mariam Dolidze, Jozef Draaisma, Bakyt
Dubashov, Kim Alan Edwards, Khalid El
Massnaoui, Olga Emelyanova, Wilfried Engelke,David Evans, Jorge Familiar Calderon, Antonio

xiii

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Fatás, Francisco H. G. Ferreira, Manuela V. Ferro,
Erik Feyen, Cornelius Fleischhaker, Frederico Gil
Sander, Fernando Giuliano, Maria De los Angeles
Cuqui Gonzalez Miranda, Poonam Gupta, Gohar
Gyulumyan, Graham Hacche, Kiryl Haiduk, Lea
Hakim, Birgit Hansl, Zahid Hussain, Wissam
Harake, Zeina Hasra, Faya Hayati, Thomas
Helbling, Sandra Hlivnjak, Bert Hofman, Sahar
Sajjad Hussain, Elena Ianchovichina, Stella Ilieva,
Fernando Im, Amina Iraqi, Yoichiro Ishihara, Ivailo
V. Izvorski, Evans Jadotte, Atsushi Kawa-moto,
Majid Kazemi, Vera Kehayova, Tehmina S. Khan,
Naoko Kojo, Ewa Korczyc, Sibel Kulaksiz, Jean
Pierre Lacombe, Christoph Lakner, Sumir Lal, Eric
Le Borgne, Daniel Lederman, Nathalie Lenoble,
Tenzin Lhaden, John Litwack, Julie Saty Lohi, J.
Humberto Lopez, Gladys Lopez-Acevedo, Sanja
Madzarevic-Sujster, Ashwaq Natiq Maseeh, Andrew
D. Mason, Gianluca Mele, Elitza Mileva, Deepak K.
Mishra, Florian Moelders, Shabih Mohib,
Mahmoud Mohieldin, Lars Moller, Lili Mottaghi,
Evgenij Najdov, Nur Nasser Eddin, Jean-Pascal
Nganou, Ha Nguyen, Antonio Nucifora, Eduardo
Olaberria, Harun Onder, Kamer K. Ozdemir,
Catalin Pauna, Steven Michael M. Pennings,

xiv

Samuel Jaime Pienknagura, Emmanuel Pinto
Moreira, Ruslan Pionkivsky, Rong Qian, Martin G.
Rama, Rita Ramalho, Nadir Ramazanov, Richard
Record, Christine Richaud, David Robinson, Paul
Romer, David Rosenblatt, Pablo Saavedra, Miguel
Eduardo Sanchez Martin, Apurva Sanghi, Ilyas
Sarsenov, Cristina Savescu, Marc Schiffbauer, Philip
Schuler, Claudia Paz Sepúlveda, Luis Serven, Lazar
Sestovic, Smriti Seth, Sudhir Shetty, Altantsetseg
Shiilegmaa, Emilia Skrok, Karlis Smits, Abdoulaye
Sy, Congyan Tan, Ashley Taylor, Fulbert Tchana
Tchana, Jonathan Temple, Hans Timmer,
Christopher Towe, Eskender Trushin, Christoph
Theodor Friedrich Ungerer, Ralph Van Doorn, Axel
van Trotsenburg, Carlos Vegh, Julio Velasco,
Mathew Verghis, Ekaterina Vostroknutova, Georgia
Wallen, Jan Walliser, Christina Wood, Hoda
Youssef, Albert Zeufack, Luan Zhao, and Bakhrom
Ziyaev.
Regional projections and write-ups were producedin coordination with country teams, country
directors, and the offices of the regional chief
economists.

Executive Summary
The global economy is experiencing a broad-based cyclical upturn, which is expected to be sustained over the
next couple of years, although with downside risks. In contrast, growth in potential output (full-employment
output) is flagging, languishing below its longer-term and pre-crisis average both globally and among emerging
market and developing economies (EMDEs). The forces depressing potential output growth will continue unlesscountered by structural policies. In oil-exporting economies, the 2014-16 oil price collapse has already prompted
some reforms. Nevertheless, across all EMDEs, room for policy improvements remains. Policy initiatives to lift
physical and human capital, encourage labor force participation, and improve institutions could help raisepotential growth and reduce inequality.
Global Outlook. A broad-based cyclical global
recovery is underway, aided by a rebound ininvestment and trade, against the backdrop of
benignfinancingconditions,generally
accommodative policies, improved confidence,and the dissipating impact of the earlier
commodity price collapse. Global growth isexpected to be sustained over the next couple ofyears—and even accelerate somewhat in emerging
market and developing economies (EMDEs)
thanks to a rebound in commodity exporters.
Although near-term growth could surprise on theupside, the global outlook is still subject tosubstantial downside risks, including thepossibility of financial stress, increased protectionism, and rising geopolitical tensions.
Particularly worrying are longer-term risks andchallenges associated with subdued productivity
and potential growth. With output gaps closing or
already closed in many countries, supporting
aggregate demand with the use of cyclical policies
is becoming less of a priority. Focus should now
turn to the structural policies needed to boost
potential growth and living standards.
Regional Perspectives. Growth in most EMDE
regions with large numbers of commodity
exporters recovered in 2017, with the notable
exception of the Middle East and North Africa,
mainly due to oil production cuts. These regions
are generally expected to see faster growth during
the forecast horizon, as commodity prices rise andthe impact of the earlier terms of trade shockdiminishes. The robust pace of expansion in

EMDE regions with a substantial number ofcommodity importers is expected to continue.
Risks to the outlook have become more balanced
in some regions, but continue to tilt down in all ofthem.
This edition of Global Economic Prospects includes
a chapter on the sources of slowing global
potential growth and policy options to raise it, as
well as two special focus pieces—on the impact ofthe 2014-16 oil price collapse and the potential
implications of improving education for inequality.
Building Solid Foundations: How to Promote
Potential Growth. Despite a recent acceleration of
global economic activity, potential output growthis flagging. At 2.5 percent, 2013-17 potential
growth was 0.5 percentage point below its longerterm average and 0.9 percentage points below its
average a decade ago, with an even steeper decline
in EMDEs. More than one-half of thedeceleration reflects weaker-than-average rates ofcapital accumulation, but weaker total factor
productivity growth and demographic trends havealso played a role. These forces are not expected todiminish over the next decade and, unless counterred, will depress global and EMDE potential
growth further by 0.2 and 0.5 percentage point,respectively, over the next decade. Policy
initiatives to lift physical and human capital,
encourage labor force participation, and improve
institutions could help reverse this trend.

xv

EMBARGOED: NOT FOR PUBLICATION, BROADCAST, OR TRANSMISSION UNTIL TUESDAY, JANUARY 9, 2018 AT 4:00 PM EDT (9:00 PM GMT/UTC)

With the Benefit of Hindsight: The Impact of the
2014-16 Oil Price Collapse. The 2014-16 collapse
in oil prices was one of the largest in modern
history, but failed to provide an expected boost to
global growth. The short-term benefits of falling
oil prices to global growth were muted by several
factors, including the low responsiveness ofactivity in key oil-importing emerging markets,
economic rebalancing in China, and thedampening impact of a sharp contraction inenergy investment and a rapid appreciation of the
U.S. dollar on growth in the United States.
Among oil-exporting countries, those with flexible
exchange rates, more diversified economies, andlarger fiscal buffers fared better than others. Since
2014, many countries have taken advantage of

xvi

lower prices to reduce energy subsidies, and somehave implemented broader structural reforms.
Education Demographics and Global Inequality.
An expected shift in the skill composition of the
global labor force will have importantconsequences for the future of global inequality.
Specifically, a better-educated labor force fromemerging market and developing economies will
likely reduce inequality between countries. It
could mitigate, especially in EMDEs, thedeterioration of within-country inequality that
may result from other developments, including
increasing urbanization, skill-biased technologicalchange, labor market frictions that cause persistent
unemployment, or trade that raises skill premia.

Abbreviations
ADB
AE
Bbbl
bbl
BIS
CEMAC
CGE
CPEC
EAP
EBRD
EC
ECA
ECB
EIA
EM
EMDE
EM7
EU
FDI
FOMC
GE(0)
G20
GCC
GDP
GEP
GIDD
GNFS
GSP+
GST
GTAP
GVC
IDB or IADB
IEA
IFC
ILO
IMF
LAC
LIC
MVF
MENA or MNA
Mb/dAsian Development Bank
advanced economies
billion barrels per literbarrels per liter
Bank for International Settlements
Central African Economic and Monetary Community
computable general equilibrium
China-Pakistan Economic Corridor
East Asia and Pacific
European Bank for Reconstruction and Development
European Commission
Europe and Central Asia
European Central Bank
U.S. Energy Information Administration
emerging market economies
emerging market and developing economy
seven largest emerging markets
European Union
foreign direct investment
Federal Open Market Committee
mean log deviation
Group of Twenty
Gulf Cooperation Council
gross domestic product
Global Economic Prospects
Global Income Distribution Dynamics
goods and non-factor services
Generalized System of Preferences Plus
goods and services tax
Global Trade Analysis Project
global value chain
Inter-American Development BankInternational Energy Agency
International Finance Corporation
International Labor Organization
International Monetary Fund
Latin America and the Caribbean
low-income country
multivariate filter
Middle East and North Africa
million barrels per day

xvii



EMBARGOED: NOT FOR PUBLICATION, BROADCAST, OR TRANSMISSION UNTIL TUESDAY, JANUARY 9, 2018 AT 4:00 PM EDT (9:00 PM GMT/UTC)

NAFTA
OECD
OPEC
PF
PMI
PPP
R&D
RBI
SAR
SAR
SF
S&P
SSA
SVAR
SWF
TFP
UCM
UN
UNCTAD
UNIDO
VAT
WAEMU
WHO
WTO

xviii

North American Free Trade Agreement
Organisation for Economic Co-operation and Development
Organization of the Petroleum Exporting Countries
production function approachpurchasing managers’ index
purchasing power parity
research and development
Reserve Bank of India
South Asia
special Administrative Region
Special Focus
Standard & Poor’s
Sub-Saharan Africa
structural vector autoregressive
sovereign wealth funds
total factor productivity
unobserved components model
United Nations
United Nations Conference on Trade and Development
United Nations Industrial Development Organization
value-added tax
West African Economic and Monetary Union
World Health Organization
World Trade Organization

CHAPTER 1

GLOBAL OUTLOOKBroad-Based Upturn—Will It Last?

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1

A broad-based cyclical global recovery is underway, aided by a rebound in investment and trade, against the
backdrop of benign financing conditions, generally accommodative policies, improved confidence, and thedissipating impact of the earlier commodity price collapse. Global growth is expected to be sustained over the
next couple of years—and even accelerate somewhat in emerging market and developing economies (EMDEs)
thanks to a rebound in commodity exporters. Although near-term growth could surprise on the upside, theglobal outlook is still subject to substantial downside risks, including the possibility of financial stress, increased
protectionism, and rising geopolitical tensions. Particularly worrying are longer-term risks and challenges
associated with subdued productivity and potential growth. With output gaps closing or closed in many
countries, supporting aggregate demand with the use of cyclical policies is becoming less of a priority. Focus
should now turn to the structural policies needed to boost longer-term productivity and living standards. A
combination of improvements in education and health systems; high-quality investment; and labor market,
governance, and business climate reforms could yield substantial long-run growth dividends and thus contributeto poverty reduction. Among commodity-exporting EMDEs, oil exporters in particular should take advantage ofan incipient recovery to pursue policies that support diversification.

Summary
The global economy is experiencing a cyclicalrecovery, reflecting a rebound in investment,
manufacturing activity, and trade. This
improvement comes against the backdrop of
benign global financing conditions, generallyaccommodative policies, rising confidence, andfirming commodity prices. Global GDP growth isestimated to have picked up from 2.4 percent in2016 to 3 percent in 2017, above the June forecastof 2.7 percent (Figure 1.1). The upturn is broadbased, with growth increasing in more than half of
the world’s economies. In particular, the reboundin global investment growth—which accounted
for three quarters of the acceleration in global
GDP growth from 2016 to 2017—was supported
by favorable financing costs, rising profits, andimproved business sentiment across both advanced
economies and emerging market and developing
economies (EMDEs). This synchronous, investment-led recovery is providing a substantial boost
to global exports and imports in the near term.

Note: Prepared by Carlos Arteta and Marc Stocker, with
contributions from Ekaterine Vashakmadze and Collette M. Wheeler.
Additional inputs were provided by John Baffes, Sinem Kilic Celik,
Delfin Go, Gerard Kambou, Eung Ju Kim, Csilla Lakatos, Hideaki
Matsuoka, Yirbehogre Modeste Some, and Dana Vorisek. Research
assistance was provided by Anh Mai Bui, Ishita Dugar, Xinghao
Gong, and Jinxin Wu.

In advanced economies, growth in 2017 isestimated to have rebounded to 2.3 percent,driven by a pickup in capital spending, aturnaround in inventories, and strengthening
external demand. While growth accelerated in all
major economies, the improvement was markedly
stronger than expected in the Euro Area.
Growth among EMDEs is estimated to haveaccelerated to 4.3 percent in 2017, reflecting
firming activity in commodity exporters andcontinued solid growth in commodity importers.
Most EMDE regions benefited from a recovery inexports. The improvement in economic activity
among commodity exporters took place as key
economies—such as Brazil and the RussianFederation—emerged from recession, prices ofmost commodities rose, confidence improved, thedrag from earlier policy tightening diminished,
and investment growth bottomed out after aprolonged period of weakness. Nonetheless, theestimated pace of growth in commodity exporters
in 2017, at 1.8 percent, was still subdued and notenough to improve average per capita incomes,
which continued to stagnate after two consecutive
years of contraction.
Global growth is projected to edge up to 3.1
percent in 2018, as the cyclical momentum
continues, and then slightly moderate to an
average of 3 percent in 2019-20. This broadly

3CHAPTER 1

4

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

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2LOSULFH
1RQHQHUJ\FRPPRGLW\SULFHLQGH[Source: World Bank.
Notes: PPP = purchasing power parity; e = estimate; f = forecast. World Bank forecasts are frequently updated based on new information and changing (global) circumstances.
Consequently, projections presented here may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any given moment intime. Country classifications and lists of emerging market and developing economies (EMDEs) are presented in Table 1.2. BRICS include: Brazil, Russia, India, China, and South Africa.
1. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights.
2. GDP growth values are on a fiscal year basis. Aggregates that include these countries are calculated using data compiled on a calendar year basis. Pakistan’s growth rates are based on
GDP at factor cost. The column labeled 2017 refers to FY2016/17.
3. The column labeled 2016 refers to FY2016/17.
4. World trade volume of goods and non-factor services.
5. Simple average of Dubai, Brent, and West Texas Intermediate.
For additional information, please see www.worldbank.org/gep.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1

steadyforecast masks marked differences betweenthe outlook for advanced economies and EMDEs.
Growth in advanced economies is projected toslow, as labor market slack diminishes andmonetary policy accommodation is gradually
unwound, moving closer to subdued potential
growth rates, which remain constrained by aging
populations and weak productivity trends.

FIGURE
1.1 Summary - Global prospects
Conversely, growth in EMDEs is expected toaccelerate, reaching 4.5 percent in 2018 and an
average of 4.7 percent in 2019-20. This mainlyreflects a further pickup of growth in commodity
exporters, which is forecast to rise to 2.7 percent
in 2018 and to an average of 3.1 percent in 201920, as oil and other commodity prices firm andthe effects of the earlier commodity price collapse
dissipate. Growth in commodity importers is
projected to remain stable, averaging 5.7 percent
in 2018-20, as a gradual slowdown in China isoffset by a pickup in some other large economies.
Within the broader group of EMDEs, growth in
low-income countries is projected to rise to 5.4
percent in 2018 and to 5.6 percent on average in
2019-20, as conditions gradually improve in oiland metals-exporting economies.

A. Growth

Nonetheless, there remain important downside
risks. Disorderly financial market movements,
such as an abrupt tightening of global financing

C. Export growth, by EMDE region

D. Investment growth incommodity-exporting EMDEs,
by region

Percent
8

Percent
20

ECA

LAC

2018

Decreasingg

2017

Unchanged

2016

2020

2019

2018

2017

0

2016

0

2015

25

2014

2

2013

50

2012

4

2011

75

2010

6

Increasing

2015

100

2014

EMDEs

2013

Percent
Advanced economies

2012

B. Share of countries withincreasing/decreasing growth

Percent
World
8

SSA

15

6

10
4

5
0

2

-5
-10

Percent
10

2020

2019

EMDE commodity
importers20172018-27

EMDE commodity
exporters

2018

0

2017

2

-2
2016

4

0
2020

6

2

2019

8

3

2018

5

TFP
CapitalLabor
Potential growth

2013-17

Real GDP per capita

2003-07

Percent
6

F. Contribution to EMDE potential
growth

1998-2017

E. EMDE growth

2016

MNA

2015

2016
2017
2018

SSA

2014

2016
2017
2018

LAC

2013

2016
2017
2018

EAP

2012

2016
2017
2018

SAR

2011

2016
2017
2018

ECA

-15

2010

2016
2017
2018

0

2017

Although risks to the global outlook continue tobe tilted to the downside, they are more balanced
than in previous forecast exercises (Figure 1.2).
This is mainly due to the possibility of strongerthan-expected growth in the largest advanced
economies and EMDEs—reflecting, for instance,a more pronounced investment-led recovery in the
United States and the Euro Area, or a fasterrebound in large commodity exporters. If these
positive surprises were to materialize, they could
have beneficial international spillovers.

Global growth picked up in 2017, supported by a broad-based recovery
encompassing more than half of the world’s economies. A substantial
acceleration in global trade translated into strengthening export growth inmost EMDE regions. As headwinds eased in commodity exporters,
investment and activity bottomed out in 2017, but income per capita wasstagnant. Despite the cyclical recovery, potential growth is likely to decline
further, reflecting subdued capital deepening, slowing productivity growth,and less favorable demographics.

2016

Despite the projected firming of activity among
EMDEs over the forecast horizon, theirunderlying potential growth—which has fallen
considerably over the past decade—appears likely
to further decline over the next 10 years, reflecting
a more subdued pace of capital accumulation,
slowing productivity growth, and less favorable
demographic trends.

5

Source: World Bank.
Notes: EMDEs = emerging market and developing economies. Data for 2017 are estimates.
A. -C. E. F. Shaded areas indicate forecasts.
A. B. E. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights.
C. D. EAP = East Asia and Pacific, ECA = Europe and Central Asia, LAC = Latin America and the
Caribbean, MNA = Middle East and North Africa, SAR = South Asia, and SSA = Sub-Saharan Africa.
B. Increasing/decreasing growth are changes of at least 0.1 percentage point from the previous year.
Countries with a slower pace of contraction from one year to the next are included in the increasing
growth category. Sample includes 36 advanced economies and 146 EMDEs.
C. Exports measured as the volume of goods and services.
F. GDP-weighted averages of production function-based potential growth as described in Chapter 3.
TFP is total factor productivity growth. Sample includes 49 EMDEs.

CHAPTER 1

6

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.2 Global risks and policy challenges
Risks to the outlook remain tilted to the downside, despite the possibility ofstronger-than-expected growth in large economies and associated positive
international spillovers. Financial market volatility has been unusually low
and asset prices have become highly valued, suggesting the risk of
sudden market adjustments. Large negative output gaps in commodity
exporters would suggest the need for accommodative policies, but fiscal
space is limited. Structural reforms are essential to stem a further decline inpotential growth in EMDEs.
A. Probability distribution aroundglobal growth forecasts

B. Impact of 1-percentage-point
increase in G7 and EM7 growth on
growth in other EMDEs after one year

Percent
550 percent
80 percent
90 percent
4
Baseline

Percentage points
2

3
1
2
1
0
2016

0
2017

2018

G7

2019

EM7

C. U.S. equity prices and volatility

D. Output gaps

Index, 3-month
Ratio, 3-monthmoving average
moving average
Volatility
70
35
Price-to-earnings
ratio
(RHS)
60
30
50
25
40

Percent of potential GDP

30
20
10
0

Advanced economies
EMDE commodity exporters
EMDE commodity importers

4

2
0

20

E. Fiscal sustainability gaps in
EMDEs

F. EMDE potential growth underreform scenarios

Percent of GDP
10

Percent
5.2

EMDE commodity exporters
EMDE commodity importers

6

4.8

2018

2016

2014

2012

2010

2008

2006

2000

2004

-4

2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018

10

-2

2002

15

Labor market reforms
Education and health improvements
Fill investment needs
Baseline

2
4.4

-2
-6

4.0

2016

2014

2012

2010

2008

2006

2004

2002

2000

-10
3.6
2013-172018-27

Reform impact

Sources: Federal Reserve Bank of St. Louis, Shiller (2015), World Bank.
A. The fan chart shows the forecast distribution of global growth using time-varying estimates of thestandard deviation and skewness extracted from the forecast distribution of three underlying risk
factors (oil price futures, the S&P 500 equity price futures, and term spread forecasts). Each of therisk factor’s weight is derived from the model described in Ohnsorge, Stocker, and Some (2016).
Values for 2018 are computed from the forecast distribution of 12-month ahead oil price futures, S&P
500 equity price futures, and term spread forecasts. Values for 2019 are based on 24-month-ahead
forecast distributions. Last observation is December 2017.
B. Cumulative impulse responses of a 1-percentage-point increase in EM7 and G7 growth on growthin other EMDEs. Solid bars represent medians, and orange bars represent 16-84 percent confidence
intervals.
C. Volatility is measured by the VIX implied volatility index of option prices on the U.S. S&P 500.
Price-to-earnings ratio is the cyclically-adjusted ratio as described in Shiller (2015). Last observationis December 2017. Data for December 2017 are estimates.
D. GDP-weighted average of 15 advanced economies and 23 EMDEs. Shaded area indicates
forecasts.
E. Simple averages. Sustainability gaps are measured under current conditions. The year of global
recession (2009) is shaded in gray.
F. GDP-weighted averages of production function-based potential growth under different policy
scenarios as described in Chapter 3. Shaded area indicates forecast.

conditions
or a sudden rise in financial market
volatility, could trigger financial turbulence andpotentially derail the expansion. The adverse
effects of rising borrowing costs could beparticularly acute for those EMDEs with large
external financing needs, fragile corporate balance
sheets, and significant fiscal sustainability gaps. In
addition, escalating trade protectionism or risinggeopolitical risk could also negatively affectconfidence, trade, and overall economic activity.
Over the longer term, a more pronounced
slowdown in potential output growth in bothadvanced economies and EMDEs would make theglobal economy more vulnerable to shocks andworsen prospects for improved living standards.
This outlook underscores the need forpolicymakers in both advanced economies and
EMDEs to shift their focus toward boosting
potential growth in the longer term. With
unemployment rates returning to pre-crisis levels
and recoveries firming in advanced economies,
monetary and fiscal policy accommodation
become less of a priority, and productivityenhancing reforms have become increasingly
urgent as the pressures on underlying growth from
population aging intensify. Among EMDEs,
output gaps are near zero in commodity importers
but still negative in commodity exporters,suggesting a continued need to nurture the cyclicalrecovery in the latter, even though fiscal spaceremains constrained.
Beyond cyclical considerations, EMDEs face thechallenge of an expected further decline inpotential growth. This argues strongly for theurgency of implementing structural policies, suchas improvements in education and health systems;
high-quality investment; and labor market,
governance, and business climate reforms. All ofthese efforts will be critical to boost long-term
growth prospects, alleviate poverty, and, if
accompanied by a rising number of skilled workers
in EMDEs thanks to better education outcomes,
to help reduce global inequality. In addition tothese challenges, oil-exporting EMDEs—whichsuffered large losses in actual and potential output
due to the 2014-16 oil price collapse—need topursue policies that bolster diversification andresilience to oil price fluctuations.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Consumption growth was stable, as continued
labor market improvements offset the dampening
impact of a rebound in energy prices. The
recovery was substantially stronger than expectedin the Euro Area and, to a lesser degree, in the
United States and Japan. Despite thestrengthening of activity, inflation in advanced
economies remained subdued in 2017.
Over the forecast horizon, advanced-economy
growth is expected to moderate slightly in 2018,
to 2.2 percent, and to average 1.8 percent in
2019-20—close to the upper bound of potential
growth estimates. This path reflects the unwindingof a cyclical upturn in investment and further
normalization of monetary policy, as advancedeconomy output gaps close (Box 1.1).
United States
Growth picked up in 2017 to an estimated 2.3
percent, supported by strengthening private investment. The recovery reflected a diminisheddrag from capacity adjustments in the energy
sector, rising profits, a weakening dollar, and

A. GDP and demand components
growthB. Growth

Percent
4.5

Percent
2.5

June 2017

June 2017

2.0
3.0

1.5
1.0

1.5

0.5
2016
2017
2018
2019
2020

2016
2017
2018
2019
2020

GDP

2016
2017
2018
2019
2020

0.0
2016
2017
2018
2019
2020

0.0

2016
2017
2018
2019
2020

Growth in advanced economies strengthened in2017, reaching an estimated 2.3 percent—0.4
percentage point above previous forecasts—helped
by a recovery in capital spending and exports(Figure 1.3). The pickup in investment reflected
increased capacity utilization, favorable financing
conditions, and rising profits and businesssentiment. Confidence was supported by the factthat policy uncertainty, albeit still elevated,diminished during the year.

Growth in advanced economies strengthened in 2017, helped by arecovery in capital spending and exports. The recovery was markedly
stronger than expected in the Euro Area and, to a lesser degree, in the
United States and Japan. Advanced-economy growth will gradually slow
toward potential over the forecast horizon, as the cyclical upturn
moderates.

Consumption Investment

Exports

United States

Euro Area

Japan

2016
2017
2018
2019
2020

Growth in advanced economies gained significant
momentum in 2017. The recovery was markedly
stronger than expected in the Euro Area and, to alesser degree, in the United States and Japan. As
economic slack diminishes and monetary policy
becomes less accommodative, growth is expected togradually moderate toward low potential growth
rates in 2018-20. Growth in China continues to beresilient, with drivers of activity shifting away fromstate-led investment.

7

FIGURE
1.3 Advanced economies


2016
2017
2018
2019
2020


Major
economies: Recent
developments and outlook

CHAPTER 1

Source: World Bank.
A. B. Green diamonds correspond with the June 2017 edition of the Global Economic Prospects
report. Shaded areas indicate forecasts.
A. Aggregate growth rates and contributions calculated using constant 2010 U.S. dollar GDP weights.

robust external demand (Figure 1.4). Economic
activity was little disrupted by major hurricane
landfalls in September, and reconstruction efforts
are likely to offset any negative effects over time
(Deryugina, Kawano, and Levitt 2014). Private
consumption continued to grow at a robust pacedespite modest real income gains and moderate
wage growth, as the personal savings rate fell
further. Households’ income expectations continued to recover following a prolonged period of
weakness.
Labor market slack diminished further andemployment growth slowed. With the economy
moving closer to full employment, and despite
inflation running below target, the U.S. Federal
Reserve continued to normalize monetary policy
in 2017, raising interest rates and starting togradually reduce the size of its balance sheet(FOMC 2017). Recently legislated corporate andpersonal income tax cuts are expected to provide alift to activity over the forecast horizon—
particularly to investment, by lowering thestatutory corporate tax rate and by allowing full
expensing of new equipment. The benefits of fiscal
stimulus will likely be constrained because theeconomy is already operating at near full capacity
and the pace of monetary policy normalization
might slightly accelerate (Gale and Samwick 2016;
Gemmell, Kneller, and Sanz 2011; Kose et al.

CHAPTER 1

8

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX 1.1 Is the global economy turning the corner?


The year 2018 will likely mark a turning point for the global economy because, for the first time since 2008, the negative global
output gap is expected to be closed. Among EMDEs, helped by the recent recovery in commodity markets, and advanced
economies, output gaps should approach zero. The closing gaps in major advanced economies would allow a normalization ofmonetary policy after a decade of exceptional easing. With the anticipatedfurther withdrawal of stimulus by advanced economies,
EMDE policymakers need to remain alert to the potential for adverse spillovers even while pursing policies to support strong,sustained growth.
The global financial crisis tipped the global economy intoa deep recession that affected first the advanced economies
but spread—especially with the subsequent collapse ofcommodity prices—to emerging market and developing
economies (EMDEs). Recoveries have been slow, but by
2018 the global economy is expected to return to its
potential for the first time in a decade as the global output
gap is expected to be closed. This in turn could mean acontinued withdrawal by advanced economies of theextraordinary policy accommodation that was provided
during the crisis, with important spillovers to EMDEs
through trade and financial linkages.1
Against this backdrop, this box addresses three questions.
xWhy do we care about the global output gap?

xWhat are the main challenges associated with themeasurement of output gaps?

xHow have output gaps evolved since 2000?

Why do we care about the global output gap?
The global output gap captures the difference between thelevel of actual global output and its “potential,” scaled bypotential output. A positive global output gap indicates
global excess demand, where economies are operating
above the level that is sustainable at full employment.
Conversely, a negative global output gap indicates weak
demand and the presence of global spare capacity.
Negative global output gaps can weigh on global inflationand depress global commodity and financial markets,
especially in a world where trade and financial flows arehighly integrated (Carney 2017b).

Note: This box was prepared by M. Ayhan Kose, Franziska Ohnsorge,and Modeste Yirbehogre Some.
1 Some major central banks have already undertaken or signaled
measures to shift their monetary policy stance. For potential implicationsof changes in advanced-economy monetary policies for emerging market
economies, see Arteta et al. (2015, 2016). For a discussion of cross-border
spillovers from major advanced and emerging market economies, see
Huidrom, Kose, and Ohnsorge (2017).



The global output gap is relevant for policies at theindividual country level, especially so for smaller and more
open economies. A negative global output gap could be asign of weak external demand that may depress importprices and inflation.2 The existence of a large negative
global output gap may amplify the potential benefits frominternational policy coordination. For example, the G20
commitments to fiscal stimulus in 2009 were founded ona consensus that the global economy had sizable slack in
the wake of the financial crisis and that unemployment
and deflationary pressures would continue to rise absent
coordinated policy action (G20 2009). In contrast, when
output gaps are diverging, lack of policy coordination
becomes more likely.

Measuring the global output gap: Navigating
through the haze
Measuring output gaps at the national level is complex
since the output gap is an unobserved variable. This iscompounded when doing so at the global level.3 National
output gaps can be estimated using a range of methods.4x

Production function methods involve the estimation of
the aggregate production capacity from factors of
production (labor and capital) and measures of totalfactor productivity.

xLong-term growth expectations, such as five-year-ahead
growth forecasts from Consensus Economics,
incorporate expert judgment about long-term growthpotential.

2 The evidence is still mixed on the link between the global output gap
and domestic inflation. Several studies find that the global output gap is
an important determinant of domestic inflation (Borio and Filardo 2007;
Eickmeier and Pijnenburg 2013; Auer, Borio, and Filardo 2017; Bianchi
and Civelli 2015). Others find little support for the role of the global
output gap in driving domestic inflation (Calza 2009; Mishkin 2009;
Ihrig et al. 2010; Irena and David 2016).
3 Only two studies focus on the empirical properties of the global
output gap (Tanaka and Young 2008; Gerlach 2011). These studies
document the major conceptual issues and measurement challenges, andexamine the evolutions of a few measures of the global output gap.
4 These methodologies are discussed and compared in greater detail in
Box 3.1.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1

BOX 1.1 Is the global economy turning the corner? (continued)x

Statistical filters include univariate or multivariate
filters. Univariate filters decompose quarterly output
series into a trend and a cycle. Multivariate filters
expand on the univariate filters by ensuring that theresulting output gap estimates are consistent withmultiple indicators of domestic demand pressures,such as inflation and unemployment.

The use of any of these methods presents tradeoffs and theappropriate choice usually depends on the purpose athand. The production function approach, in principle,
captures the supply-side drivers of long-term growth, but
in practice relies on estimates and projections of theseunderlying factors that are themselves subject toconsiderable measurement error. The resulting output gaps
are not necessarily consistent with other indicators ofdomestic demand pressures. Long-term growth expectations
may reflect additional information to complement models
but may also rest on biased judgments on the part of theforecasters. Univariate filters for GDP growth essentiallyinvolve a moving average of actual past growth. While
their calculation is possible even in data-poor environments, they tend to correlate closely with actual growth.
As a result, the filter will likely underestimate both the true
extent of output losses stemming from unemployment andthe associated disinflationary pressure.5
Multivariate filters are sensitive to model specification, andin practice can be heavily influenced by financial andcommodity market cycles. They do, however, have theadvantage of being consistent with multiple indicators ofdemand pressures. Since they incorporate additional
information, they tend to be less susceptible to the endpoint problem. Given their ability to capture multiple
dimensions of cycles, the analysis in the rest of this box
relies on the results from the multivariate filter.
Database and methodology. The sample includes 15
advanced economies (AEs) and 23 emerging market anddeveloping economies (EMDEs) with quarterly data overthe period 2000-16. The countries in the sample together
accounted for about 85 percent of global GDP, on
average, since 2000. National output gaps of each country
are estimated using nine different methods.6 National

5 Statistical filters also suffer from end-point problems and large
revisions after data updates which tend to be most pronounced at cyclicalturning points (Coibion, Gorodnichenko, and Ulate 2017).
6 These include five univariate filters (Hodrick-Prescott, Baxter-King,
Christiano-Fitzgerald, Butterworth filters, and the unobserved
components model), the multivariate filter, the production function
approach and two expectations-based measures (five-year-ahead World

output gaps are then aggregated into a global output gap
using GDP weights.7 Group- and region-specific output
gaps are similarly aggregated.
Results from different methods. While different methods
produce broadly consistent trends in national output gaps
in the majority of countries and periods, they also show
sizable variation across these measures in some periods(Figure 1.1.1). Output gap estimates during 2008-09
illustrate this variation. All estimates pointed to negative
output gaps but with a wide range. In EMDEs,
the estimated gaps for these years from different
methodologies vary from -0.1 to -0.9 percent.

How have global output gaps evolved?
Following the global slowdown in 2001-02, the recovery
in advanced economies in the first half of the 2000s was
accompanied by narrowing negative global output gaps
(Figure 1.1.2). Although growth slowed in EMDEs in theearly years of the decade with recessions in Mexico andTurkey and the legacies of the late 1990s Asian financial
crisis, by mid-decade the estimates for EMDEs as well as
for advanced economies indicated positive gaps. At their2007 peak, estimated output gaps for both groups were ata positive 2-3 percent.
The global financial crisis of 2008-09 led to significant
economic slack in the majority of countries and a wide
global output gap (captured unanimously by all
methodologies). During 2010-2014, the global output gap
remained large and only narrowed during 2015-17 to bestatistically indistinguishable from zero. There were
substantial differences in the output gaps of different
country groups and regions.
Advanced economies. Even well after the global financial
crisis, output gaps in most advanced economies remained
negative, averaging about -1 percent of potential GDP
during 2011-16. By 2015, the gap had narrowed, and wasstatistically indistinguishable from zero. In 2018, theoutput gap for advanced economies is expected to turnslightly positive.

Economic Outlook and Consensus forecasts). Details of the methodologies
are provided in Annexes 1 and 2.
7 The estimated weighted average global output gap is broadly consistent
with a global output gap estimated directly using global variables, such as
GDP-weighted average global GDP, median global inflation, labor forceweighted average employment and oil prices.

910

CHAPTER 1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX 1.1 Is the global economy turning the corner? (continued)


FIGURE 1.1.1 Output gap estimates
The trends in the estimates of the output gap from different methodologies are broadly similar. For example, they signal thesame timing of peaks and troughs. However, at times the point
 estimates show considerable differences, even in sign.
A. Coincidence of signs of output gaps
Percent ofcountry-year pairs

PFA(Funda- MVF
mentals)HP

BK

B. Global output gap estimates (range across methodologies)

CF

BW

Exp. Exp.
(WEO) (CF)Percent of potential GDP
0.4

PFA(Fundamentals)
0

MVF

73

HP

65

76

BK

70

79

92

CF

58

63

74

76

-0.4

BW

61

73

91

88

82

Exp. (WEO)

65

64

59

64

55

56

Exp. (CF)

76

69

63

67

58

61

Alt. (WEO)

70

76

74

76

64

72

-0.8

84
69

72

-1.2
2002-05

2008-09

2012-152017-18

C. Advanced economies output gap estimates (range acrossmethodologies)

D. EMDE output gap estimates (range across methodologies)

Percent of potential GDP
1

Percent of potential GDP

0

0.5

-1

0.0

-2

-0.5

-3

-1.0

1.0

-4

-1.5
2002-05

2008-09

2012-152017-18

2002-05

2008-09

2012-152017-18

Source: World Bank staff estimates.
Notes: Global, regional, and group output gaps are calculated using constant 2010 U.S. dollar GDP as weights. The sample includes 15 advanced economies (Australia,
Canada, Denmark, Finland, France, Germany, Italy, Japan, New Zealand, Norway, Spain, Sweden, Switzerland, United Kingdom, and United States) and 23 EMDEs(Argentina, Bolivia, Brazil, Bulgaria, Chile, China, Colombia, Croatia, Hungary, India, Indonesia, Kazakhstan, Malaysia, Mexico, Peru, Poland, Romania, Russia, Serbia,
South Africa, Thailand, Turkey, and Vietnam). 2018 data is forecast.
A. Table shows the share of country-year pairs during 2000-16 in which two different measures of output gap have the same signs. Red represents greater than 80
percent, orange represents 60-80 percent, and yellow represents 50-60 percent. “Exp. (WEO)” stands for five-year-ahead WEO expectations, “Exp. (CF)” stands forfive-year-ahead Consensus forecast, “Alt. (WEO)” stands for output gap from WEO.
B. -D. Blue bars denote multivariate filter-based estimates. Vertical orange lines indicate range of all six filter-based estimates. The five univariate filters (HP, BK, CF,
BW, UCM), the multivariate filter (MVF), and the production function approach (PFA). “HP” stands for Hodrick-Prescott filter, “BK” stands for Baxter-King filter, “CF”
stands for Christiano-Fitzgerald filter, “BW” stands for Butterworth filter, “UCM” stands for unobserved components model.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1



BOX 1.1 Is the global economy turning the corner? (continued)


FIGURE 1.1.2 Global and group-specific output gaps
The global financial crisis of 2008-09 opened up a considerable degree of slack in the majority of countries. Post-crisis, awide divergence in output gaps emerged between advanced economies, which were at the center of the crisis, and EMDEs
as well as between commodity-exporting and importing EMDEs.

2016

2018

2017

2016

LAC

2010-15

2018

2015

2012

2009

2006

2003

2000

-5

2010-15-4EMDEs
EMDE commodity exporters
EMDE commodity importers

-3

2018

-2

2018

-1

2015

0

2018

1

2015

Percent of potential GDP
2

2012

Percent of potential GDP
3

2009

Percent of potential GDP
4
World
Advanced economies
3
EMDEs
2
1
0
-1
-2
-3
-4
-5

2006

F. Range of regional output gaps

2003

E. Output gaps in EMDE commodity
exporters and importers

2000

D. Output gaps in advanced economies
and EMDEs

2017

2012

95% confidence bandOutput gap

2009

2006

2003

2000

2018

2015

2018

2015

2012

2009

2006

2003

2000

2012

Percent of potential GDP
4
3
2
1
0
-1
-2
-3
-4
-5

2009

Percent of potential GDP
495% confidence bandOutput gap
3

2006

C. Output gaps in EMDEs

Percent of potential GDP
495% confidence bandOutput gap
3
2
1
0
-1
-2
-3
-4
-5
2003

B. Output gaps in advanced economies

2000

A. Global output gap

2
1
0
-1
-2
-3
-4
-5

SSA

Source: World Bank staff estimates.
Notes: Output gaps calculated using multivariate filter. Global, regional, and group output gaps are calculated using constant 2010 U.S. dollar GDP as weights. The
sample includes 15 advanced economies (Australia, Canada, Denmark, Finland, France, Germany, Italy, Japan, New Zealand, Norway, Spain, Sweden, Switzerland,
United Kingdom, and United States) and 23 EMDEs (Argentina, Bolivia, Brazil, Bulgaria, Chile, China, Colombia, Croatia, Hungary, India, Indonesia, Kazakhstan,
Malaysia, Mexico, Peru, Poland, Romania, Russia, Serbia, South Africa, Thailand, Turkey, and Vietnam). 2018 GDP is forecast.
A. -C. Dashed lines are 95 percent confidence interval bounds computed from the Kalman smoother state variances. Global lower and upper bounds are obtained as
GDP-weighted averages of individual country lower and upper bounds.
E. “EMDE commodity exporters” include Argentina, Bolivia, Brazil, Chile, Colombia, Indonesia, Kazakhstan, Malaysia, Peru, Russia, and South Africa. “EMDE commodity
importers” include China, Hungary, India, Mexico, Poland, Romania, Serbia, Thailand, Turkey, and Vietnam.
F. Blue bars denote multivariate filter-based estimates. Vertical orange lines indicate one standard deviation error bands. LAC = Latin America and the Caribbean,
SSA = Sub-Saharan Africa.

EMDEs. Output gaps in EMDEs varied widely between
commodity-exporting and importing EMDEs (Figures
1.1.2 and 1.1.3).
x



11

For commodity exporters (accounting for two-thirdsof EMDEs), the slide in commodity prices since thefirst quarter of 2011 and, especially, the sharp drop in
oil prices in mid-2014, as well as weaknesses among
their major trading partners, led to an unwinding of
their large positive output gaps. By 2016, their gaps
had turned negative (below -1 percent), on average,
and are expected to remain marginally negative (-0.8
percent) in 2018.

x

By contrast, wide negative output gaps emerged
among the commodity-importing EMDEs during the
global financial crisis and narrowed quickly in the
post-crisis rebound. With EMDEs growth remaining
steady during 2011-17 at around potential growth,
their gaps remained near zero during this period.

x

Output gaps in EMDE regions broadly reflected theprevalence of commodity exporters in each region.
Notwithstanding a gradual narrowing, LAC and SSA(represented in the sample by South Africa)—two
regions with large commodity-exporting economies—
are expected to have sizable (and statistically12

CHAPTER 1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX 1.1 Is the global economy turning the corner? (concluded)
significant) negative output gaps in 2017 and 2018.
Elsewhere, output gaps have been near zero.

FIGURE 1.1.3 Output gap synchronization
The majority of advanced economies had positive output
gaps pre-crisis and negative output gaps post-crisis. In
EMDEs, there was greater heterogeneity.
A. Share of economies with positive output gaps: Advanced
economies
Percent
100

75

50



Heterogeneity in output gaps. Common shocks andcyclical spillovers through cross-country linkages cangenerate homogeneity and comovement in output gaps.
Since 2000, output gaps in the advanced economies havebeen less diverse than in EMDEs. Excepting the years ofthe 2001-02 U.S. recession and the 2011 Euro Area crisis,
at least two thirds of advanced economies had output gapsof the same sign. In contrast, in the large majority of years
since 2000, around half of EMDEs had positive output
gaps (Figure 1.1.3). This heterogeneity among EMDEs
has largely reflected the divergences between commodityexporting and -importing economies.

Implications for EMDEs
25

0

2003-072008-09

2012-152017-18

B. Share of economies with positive output gaps: EMDEs
Percent
100

75

50

25

0

2003-072008-09

2012-152017-18

Source: World Bank staff estimates.
Notes: Output gaps calculated using multivariate filter approach. The
sample includes 15 advanced economies (Australia, Canada, Denmark,Finland, France, Germany, Italy, Japan, New Zealand, Norway, Spain,
Sweden, Switzerland, United Kingdom, and United States) and 23 EMDEs(Argentina, Bolivia, Brazil, Bulgaria, Chile, China, Colombia, Croatia,
Hungary, India, Indonesia, Kazakhstan, Malaysia, Mexico, Peru, Poland,
Romania, Russia, Serbia, South Africa, Thailand, Turkey, and Vietnam).
2018 GDP is forecast.

Output gap measures are subject to uncertainty as reflectedin large variations across methods and wide confidence
bands. Policymakers need to account for this uncertainty
when assessing and implementing cyclical policies.
That said, for the first time in a decade, the global output
gap is expected to approximately close in 2018, with
important implications for EMDEs. On the one hand, theexpected closing of the global output gap signals a returnto health of the world economy after a prolonged period of
weak growth, which holds the promise of favorable
spillovers to EMDEs, including through trade channels.
However, it also means that the coming years may witness
an unprecedented shift in the stance of cyclical policies
among the advanced economies, with an attendant risk of
missteps or disorderly financial market adjustments. This
underscores the importance for EMDEs to continue tofocus on measures to enhance prospects for strong,sustained growth, but also the need for measures to ensure
the resilience of their domestic financial markets andbroader macroeconomic policy frameworks in the face of
external shocks.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1

2017a).
Other policy initiatives of the U.S.
administration, including in the areas of healthcare and infrastructure, have made limited
headways, while the outcome of renegotiations of
the North American Free Trade Agreement(NAFTA) remains uncertain.

FIGURE
1.4 United States

A. Investment and profit growth

B. Expected wage growth

Barring major additional policy changes, U.S.
growth is expected to reach 2.5 percent in 2018,
above previous expectations, and then to moderate
to an average of 2.1 percent in 2019-20—toward
the upper range of potential output growthestimates (Congressional Budget Office 2017;
OECD 2017a; Federal Reserve Board 2017). Low
labor participation and weak productivity trends
remain the most significant drag on U.S. growthover the longer term (Fernald et al. 2017).

Percent, year-on-year
Percent, year-on-year
60
30Profit Investment (RHS)

Percent, 3-month moving average
4

Euro Area

Investment growth picked up in 2017, households’ wage growth
expectations improved, and labor market slack continued to diminish, evenas employment growth slowed. Although productivity has improved
recently, it is still weak and remains a major constraint to growth.

40

20

20

10

0

0

-20

-10

-40

-20

3

1
0

1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2017

2016
2017

2014

2012

2010

2008

2006

2004

2002

2000

2

C. Employment growth

D. Hourly labor productivity growth

Change, thousands of persons
280
6-month moving average

Percent
3

2010-14 average

250

220

2

190
160
1

130
100

Jan-14Apr-14Jul-14Oct-14Jan-15
Apr-15
Jul-15Oct-15Jan-16
Apr-16
Jul-16Oct-16
Jan-17
Apr-17
Jul-17Oct-17Growth gained substantial momentum in 2017,
reaching an estimated 2.4 percent—0.7 percentage
point higher than previously expected—with
broad-based improvements across member countries spurred by policy stimulus and strengthening
global demand. In particular, private sector credit
continued to respond to the stimulative stance of
the European Central Bank (ECB; Figure 1.5),
and both domestic demand and import growth
were robust.

13

0
1995-2005 2006-11

2012-162017

Sources: Federal Reserve Bank of St. Louis, Haver Analytics, Survey of Consumers University ofMichigan, U.S. Bureau of Economic Analysis, World Bank.
A. Real private fixed capital formation and nominal before-tax profit growth. Last observation is
2017Q3.
B. Expected wage growth is the median increase in expected household income during the next year.
Last observation is October 2017.
C. Employment is private nonfarm payroll. Last observation is November 2017.
D. Hourly labor productivity measured as output per hour worked in the nonfarm private sector. Data
for 2017 estimated by averaging 2017Q1 to 2017Q3. Last observation is 2017Q3.

The unemployment rate reached its lowest level
since 2009, and labor shortages became
increasingly prevalent in some countries. However,wage growth remained subdued, and theappreciation of the euro during 2017 is likely tofurther delay a pickup in inflation in 2018, as it
puts downward pressure on import prices (ECB2016). With inflation remaining below target, the
ECB is expected to keep interest rates unchanged
during 2018, but to gradually scale back asset
purchases. The aggregate fiscal stance of the EuroArea was somewhat expansionary in 2017
(European Commission 2017).

notably stronger than previously projected. It isthen foreseen to average 1.6 percent in 201920—around the upper end of estimates ofpotential output growth—as labor market slack
dissipates. Over the longer term, growth prospects
remain constrained by the shrinking of theworking-age population in the majority of EuroArea economies and persistent productivity andcompetitiveness gaps among the peripheral
members (Díaz del Hoyo et al. 2017).

The cyclical upturn is expected to continue in2018, albeit at a more restrained pace, as domestic
demand loses some momentum following strong
gains in 2017, and policy stimulus is gradually
unwound. GDP growth is expected to be 2.1
percent in 2018, down from the previous year but

Growth picked up in 2017 to an estimated 1.7
percent. Domestic demand firmed, supported bya gradual recovery in consumer spending andinvestment, as well as the implementation of a
fiscal stimulus package (Figure 1.6.). Exports
accelerated in response to strengthening global

Japan

CHAPTER 1

14

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.5 Euro Area
Credit recovered further in 2017, as the balance sheet of the European
Central Bank continued to expand, albeit at a slightly slower pace.
Domestic demand, exports, and imports strengthened. Labor shortages
have become increasingly prevalent, although wage growth remains
subdued. The appreciation of the euro is likely to put downward pressure
on import prices and inflation.
A. Private credit and ECB balance
sheet

B. Contribution to growth

Euros, trillions
Euros, trillions
13.5
6.0
Credit to nonfinancial sector
ECB balance sheet (RHS)

Percentage points
Domestic demand
6
Imports4

13.0

Exports
GDP growth

4.5

demand,but the net trade contribution to growthremained unchanged as imports picked up as well.
Labor market conditions continued to tighten,
with the unemployment rate at a 22-year low
amid growing labor shortages. However, wage
growth remained moderate and inflation below 1
percent. In this context, the Bank of Japan left
policy rates unchanged in 2017 and continued tocalibrate its bond purchases to stabilize long-termbond yields around zero.

2
12.5

3.0

12.0

1.5

0

2018

2017

2016

2015

2014

2013

-4

2012

Jun-17

Dec-17

Jun-16

Dec-16Jun-15

Dec-15Jun-14

Dec-14Jun-13

Dec-13Jun-12

Dec-12-2

C. Labor shortages

D. Import prices and euro exchange
rate

Percent, balance of answers
15
Historical medianIndex, 100=Jan. 2005
Index, 100=Jan. 2005
110
85
Import prices
Euro exchange rate (RHS, inverted)
90
106

10

95
102
100

5

98

105
110

2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017

94
0
2013Q1 2015Q1 2017Q1 2017Q3 2017Q4

Sources: European Central Bank, European Commission, Federal Reserve Bank of St. Louis, Haver
Analytics, World Bank.
A. Last observation is November 2017 for ECB balance sheet and October 2017 for credit tononfinancial sector.
B. Shaded area indicates forecast.
C. Factors limiting output growth based on the European Commission business sentiment surveys.
Median value is computed over the period from 2000Q1 to 2017Q4.
D. Last observation is November 2017 for the euro exchange rate and October 2017 for import prices.

FIGURE 1.6 Japan
Domestic demand strengthened in 2017, but wage growth remainedmoderate and inflation low despite some increase.
A. Contribution to growth

B. Wage growth and CPI inflation

Percentage points
3

Percent, year-on-year
Inflation Wage growth
2.5

Domestic demand
Exports
Imports
GDP growth2

Bank of Japan target

2.0
1.5

1

1.0

0.5

0

2018

2017

2016

2015

2014

2013

-1.0

2012

-0.5

-2

Jan-11
Jul-11
Jan-12
Jul-12
Jan-13
Jul-13Jan-14Jul-14Jan-15
Jul-15Jan-16
Jul-16
Jan-17
Jul-17Jan-180.0-1Growth is expected to slow to 1.3 percent in
2018, as fiscal stimulus is withdrawn and export
growth moderates. In 2019, growth is forecast at
0.8 percent, in line with average potential growthestimates. The planned consumption tax hike in
October 2019 is expected to have a negative effecton growth in 2020, which is projected to slow
temporarily to 0.5 percent. Population aging and ashrinking labor force continue to weigh on longterm growth prospects (Japan Cabinet Office2017; Kawamoto et al. 2017).

Sources: Haver Analytics; Japan Ministry of Health, Labor, and Welfare; Japan Ministry ofInternational Affairs and Communications; World Bank.
A. Shaded area indicates forecast.
B. The Bank of Japan's (BoJ) inflation target is 2 percent. CPI inflation is the headline rate adjusted
for changes in the consumption tax rate. Last observation is October 2017.

China
Growth in China is estimated to have reached 6.8
percent in 2017—an upward revision from June
forecasts, reflecting continued fiscal support andthe effects of reforms, as well as a stronger-thanexpected recovery of exports and a slight positive
contribution from net trade (World Bank 2017a;
Figure 1.7). Domestic rebalancing continued, withdrivers of activity shifting away from state-led
investment. China’s trade flows recovered
markedly in 2017, partly reflecting rising commodity imports amid tightly enforced production
cuts as well as strengthening foreign demand.
Consumer price inflation increased steadily
throughout the year but remained below target,
while producer price inflation was stable, supporting a recovery of industrial profits. House
price growth continued to slow, reflecting tighter
regulations in larger cities. Despite further
monetary and regulatory tightening in 2017, thetotal stock of non-financial sector debt, at about
260 percent of GDP, continued to expand on a
year-on-year basis (BIS 2017; World Bank 2017a).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Growth in China remains solid, with drivers of activity shifting away fromstate-led investment. China’s trade flows recovered markedly in 2017.
Tighter enforcement of capital flow management measures helped ease
capital outflows and exchange rate pressures and reverse a reduction inforeign reserves.
A. Contribution to growth
Percentage points
10
Consumption

B. Investment growth

D. Balance of payments

Percent
10

Percent of GDP
8

Exports

Imports

Global trade
Global goods trade volumes have gatheredsignificant momentum since mid-2016, following
two years of pronounced weakness. A cyclicalrebound in investment contributed to strong
growth of trade in machinery, electronics and,semiconductors (Figure 1.8). Momentum wassustained throughout 2017, and global trade
growth is estimated to have reached a strongerthan-expected 4.3 percent, thanks to synchronous
recovery in import demand from both advanced
economies and EMDEs. Export growth accelerated in most EMDE regions. However, it
decelerated in the Middle East and North Africa,

Jul-17

Nov-17

Current accountNet capital flows
Change in reserves

4
0

0

-4

2017Q3

2017H1

2016H2

2016H1

2015H2

2015H1-8
2010-14

2017Q3

2017Oct

2017Q1

2016Q3

2016Q1

2015Q3-5

2015Q1

Global trade strengthened significantly in 2017,
benefiting from a cyclical recovery in global
manufacturing and investment growth. This
momentum is expected to diminish in 2018-20, as
the upturn in advanced economies moderates andgrowth in China continues to decelerate. Global
financing conditions remain benign, despite prospectsof further normalization of monetary policy in majoradvanced economies, but are likely to tighten going
forward. Energy and metals prices recovered in 2017,
while agricultural prices remained stable.

Mar-17Mar-15

2017Q3

C. Export and import growth5

Global trends

Jul-16

-5

2016

0

-2

Nov-16

50

Mar-16

10

8

Jul-1542

Net exports

Nov-15

6

Percent, year-on-year, 6-month moving average
25
State
20
Private15

Investment

2015

Chinese growth is projected to edge down in 2018
to 6.4 percent as policies tighten, and average 6.3
percent in 2019-20. Key downside risks to theoutlook stem from financial sector vulnerabilities,
the possibility of increased protectionist policies inadvanced economies, and rising geopoliticaltensions. Long-term fundamental drivers ofpotential growth point to a further slowdown in
China’s growth over the next decade, as
population aging is expected to depress labor
supply.

15

FIGURE
1.7 China
2010-14On the external side, the current account surplus
continued to narrow but, with a moderation of
net capital outflows, foreign exchange reserves
recovered in 2017. In the second half of the year,
the renminbi reversed some of its previous
nominal appreciation following the removal ofreserve requirements for foreign currency trading.

CHAPTER 1

Sources: China National Bureau of Statistics, Haver Analytics, World Bank.
A. Investment refers to gross capital formation, which includes change in inventories. Lastobservation is 2017Q3.
B. Last observation is November 2017. October 2017 and November 2017 deflators are estimated.
C. Data include only goods and reflect contributions to year-on-year 12-month moving average
growth. Horizontal lines indicate 2010-14 averages. Last observation is October 2017.

partly reflecting cuts in oil production agreed by
OPEC members.
The recovery in global trade has been tightly
connected to a cyclical upturn in global manufacturing, which in turn was encouraged by stronger
capital spending. Services trade also recovered in2017, albeit at a slower pace than goods trade, as
the former is generally less affected by short-term
inventory and production cycles (OECD 2017b).
Global trade growth is set to moderate somewhat
in 2018-19, at an average of 4 percent, in line withthe projected deceleration of capital spending in
advanced economies and China.
Besides the effects of maturing recoveries, global
trade is expected to remain constrained bystructural forces, including the slower pace of
global value chain integration and trade liberali-

CHAPTER 1

16

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.8 Global trade
Global trade has gathered momentum, supported by firming capital goods
trade. Robust import demand from major advanced economies was adriving force, while export growth accelerated in most EMDE regions.
However, structural factors continue to dampen trade, including stalling
global value chain integration. The number of newly introduced
protectionist measures in the largest economies stabilized in 2017.
B. Contribution to global import
growthPercent, year-on-year
Percent, year-on-year
6 Goods trade (real)
25
Goods trade (nominal, RHS)
20
5 Semiconductors (nominal, RHS)
15
4
10
3
5
0
2
-5
1
-10
0
-15

Percentage points

2020

2019

2018

2016

EMDE commodity exporters
EMDE commodity importers
Advanced
ed economies
World

2017

5
4
3
2
1
0
-1
-2

2015

Jan-12
Jul-12
Jan-13
Jul-13Jan-14Jul-14Jan-15
Jul-15Jan-16
Jul-16
Jan-17
Jul-17Jan-18

A. Global goods trade growth

C. Export growth, by EMDE region

D. Ratio between global goods tradeand global industrial production

Percent
8

Index, 100=Jan. 2000, 6-month moving average
125

6

120

4

115
110

2

105

2018

2016

2014

100
2012

MNA

2010

2016
2017
2018

SSA

2008

2016
2017
2018

LAC

2006

2016
2017
2018

EAP

2004

2016
2017
2018

SAR

2002

2016
2017
2018

ECA

2000

2016
2017
2018

0

E. Evolution of global value chains(GVC)

F. New trade restrictions

Percent
9

Flow of measures
G4 (China, EU, Japan, United States)
1,200
Others
1,000

7

800

6

600

5

400

4

200

3

Jul-17Jan-18

Jul-16
Jan-17

Jul-15Jan-16

Jan-15

Jul-14Jan-14Jul-13Jan-13

2013
2014

2011

2009

2007

2005

2003

2001

1999

1997

Jan-12
Jul-120

2
1995

The number of newly introduced protectionist
measures in 2017 stabilized in the largest
economies and declined in the rest of the world.
However, the stock of these measures continues togrow. It is estimated that close to three-quarters of
G20 exports face some type of trade distortion indestination markets (Evenett and Fritz 2017).
Anti-dumping duties and other tariffs accounted
for close to half of recently introduced protectionist measures, followed by financial grants andpublic procurement localization measures. Exporters of iron and steel, electrical energy and metal
products remain disproportionately affected bytrade restrictions (Evenett and Fritz 2017).
Financial markets

Traditional trade
Simple GVCs
Complex GVCs

8

value
chains (GVCs) has stabilized—and even
dropped slightly for more complex production
processes where value added crosses borders
multiple times, which is typical for high-value
sectors such as motor vehicles, computers, andmachinery. Although simple GVCs (where value
added crosses borders only once) are about two
times larger than complex GVCs in terms of total
value added, the latter contribute disproportionately to trade flows and are particularly sensitive tochanges in trade costs and trade policy uncertainty(World Bank et al. 2017).

Sources: CPB Netherlands Bureau for Economic Policy Analysis, Global Trade Alert, Semiconductor
Industry Association, Wang et al. (2017), World Bank, World Trade Organization.
A. Goods trade data are 3-month moving averages. Last observation is October 2017.
B. C. Shaded areas indicate forecasts.
C. Exports measured as the volume of goods and services. EAP = East Asia and Pacific, ECA =Europe and Central Asia, LAC = Latin America and the Caribbean, MNA = Middle East and North
Africa, SAR = South Asia, and SSA = Sub-Saharan Africa.
D. Last observation is October 2017.
E. Share of total value added. In simple GVCs, value added crosses national borders only once
during the production process. In complex GVCs, value added crosses national borders at least twice.
F. Data are 12-month sums. Last observation is October 2017.

zation. Even during a period of marked
acceleration since mid-2016, global goods trade
only kept pace with global industrial productionlevels, prolonging a plateau observed since themid-2000s. Since 2011, participation in global

Global financing conditions remain benign,
benefiting from an improved global growth
outlook and historically low interest rates, despite
prospects of further monetary policy normalization in major advanced economies. The U.S.
Federal Reserve hiked policy interest rates threetimes in 2017, and by a cumulative 125 basis
points since the start of its tightening cycle in
December 2015. It also began to gradually reduce
the size of its balance sheet in October 2017,
although the target level over the medium-term
has not been specified yet. In addition, the ECB
announced a further reduction of its asset
purchase program starting in January 2018.
Despite prospects of tighter monetary policy, U.S.
and Euro Area bond yields remained at historically
low levels throughout 2017 (Figure 1.9), reflecting
subdued inflation trends and expectations ofstructurally low real interest rates (Rachel andSmith 2017). Amid low nominal and real interest

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Although cross-border bank lending to EMDEs
recovered, it remained subdued, partly reflecting
past de-risking from banks in the Euro Area,
United Kingdom, and United States (IFC 2017).
Capital inflows to EMDEs are expected tocontinue to be sustained in 2018, supported by
improved growth prospects, but are likely tomoderate thereafter as global financing conditions
tighten.

A. U.S. and German long-term bondyieldsB. U.S. dollar exchange rates

Percent
7
6

Index, 100=Jan. 2, 2014
Euro/US$
Trade weighted
130
1.0
Bilateral against the euro (RHS)

United States
Germany

120

5

0.9

4
110

3
2

0.8

100

1
0
-1

Jul-17

C. EMDE sovereign bond spreads

D. International bond issuances

Basis points
450

US$, billions
150

400

125

350

100

300

75

250

Jan-18

Jul-16

Jan-17

Jul-15Jan-16

Jul-14Jan-150.7

Jan-14

2018

2016

2014

2012

2010

2008

2006

2004

2002

90

General government
Financial corporations
Non-financial corporations

50

200

25

E. Capital inflows to EMDEs

F. FDI inflows to EMDEs

US$, billions
1,500

US$, billions
EAP
700 SAR

2

300

1

2017

-1
2016

-300

2015

0

2014

0

2017

2016

40
30
20

10
0

2017

600

50

2016

3

600
500
400
300
200
100
0

2015

900

Percent, share of global FDI
ECA
LAC
Other
Total (RHS) 60

2014

1,200

2013

Percent of GDP
FDI
6
Portfolio
5
Other
Total (RHS)
4

2015

2014

2013

2012

2011

0
2010

Jan-18

Jul-17Jan-17

Jul-16

Jan-16

Jul-15Jan-15

Jul-14150

2013

Overall, capital inflows rose as a share of EMDE
GDP in 2017, recovering further from their postcrisis low in 2015. The increase was particularly
notable in Asia and Eastern Europe and Central
Asia, while flows into Latin America remained
weak. A rise in portfolio and bank lending flows
were the main drivers of the overall improvement.
Although foreign direct investment (FDI) flows
were broadly stable in aggregate, the experiencevaried across regions. FDI flows to Asia remained
strong, supported by a robust growth outlook andpolicy efforts to attract foreign investment (e.g.,
India, Indonesia, Vietnam). FDI flows to SubSaharan Africa rose only slightly in the wake of amoderate rise in commodity prices and an increasein non-commodity investments, and FDI inflows
to Middle East and North Africa also posted
modest growth, supported by privatization plans
and improvements in business regulations (e.g.,
Algeria, the Arab Republic of Egypt, Tunisia).

Despite prospects of tighter monetary policy, U.S. and Euro Area bondyields remained low in 2017, while the U.S. dollar generally depreciated. A
continued search for yield helped lower bond spreads for EMDEs and spurrobust capital inflows.

2000

Highly accommodative financing conditions inmajor advanced economies supported a search foryield and strong demand for EMDE assets in2017. This was reflected in declining bondspreads, particularly for EMDE investment grade
borrowers, and an increase in capital flows,
including portfolio and international bondissuances. Among commodity-exporting EMDEs,
the waning effect of the terms-of-trade shock,combined with moderating inflation and external
imbalances, helped support market sentiment.

17

FIGURE
1.9 Global financeJan-14rates,
financial market volatility remained subdued

despite policy and geopolitical uncertainties.
Stronger-than-expected growth in the Euro Area
combined with a relatively stable outlook for the
U.S. economy has contributed to some weakeningof the U.S. dollar, following three years ofsignificant appreciation.

CHAPTER 1

Sources: Bank for International Settlements, Bloomberg, Dealogic, Federal Reserve Bank of St.
Louis, Haver Analytics, International Monetary Fund, J.P. Morgan, World Bank.
A. 10-year government bond yields. Last observation is December 19, 2017.
B. An increase indicates an appreciation of the U.S. dollar. Last observation is December 15, 2017.
C. Data exclude Venezuela. Last observation is December 18, 2017.
D. Last observation is 2017Q4.
E. F. Based on top 28 recipients of capital flows. “Other” investment category includes all financialtransactions not covered in direct investment, portfolio investments, or reserve assets. Data for 2017
are estimates.
F. EAP = East Asia and Pacific, ECA = Europe and Central Asia, LAC = Latin America and the
Caribbean, and SAR = South Asia.

Commodities
Energy and metals prices recovered in 2017 while
agricultural prices remained broadly stable, in linewith June expectations (Figure 1.10). Oil prices
averaged $53 per barrel (bbl) in 2017, up 24
percent from 2016, but were volatile throughout

CHAPTER 1

18

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.10 Commodity markets
Crude oil prices increased in 2017, despite a further rebound in U.S. rig
counts and growing efficiency gains in shale oil production. Metals pricesrose sharply, on the back of China’s strong demand and supply
restrictions. Agricultural commodity prices, which stabilized in 2017, areanticipated to make only marginal gains in 2018 as global stocks remain at
multi-year highs.
A. Commodity price indexes

B. U.S. oil rig count and oil prices

Index, 100=2010
180

US$/bbl150

EnergyMetalsAgriculture160

Oil price, WTI
U.S. oil rig count (RHS)

Rig count
1,800
1,500

125

140
120

1,200

100

900

100

75

600

80

2017

2016

2015

2014

2013

2012

2011

2010

2017

2016

2014

2015

0

2013

25

2012

300

40

2011

50
2010

60

C. U.S. shale break-even oil prices

D. Global oil consumption growth

US$/bbl90
70

mb/d, year-on-year
OECD
4
China
Other Non-OECD
3

60

2

Range
Average U.S. shale

80

50
40

1

30

0

E. Global metals consumption growth
OECD
China
Other non-OECD

mmt, year-on-year
3

2018

2017

2016

F. Stocks-to-use ratios of main grains
Percent
40

Maize
Rice
Wheat

35

2

2015

2014

2013

2012

2011

-1

2010

2017Q1

2016Q3

2016Q1

2015Q3

2015Q1

2014Q3

2014Q1

2013Q3

2013Q1

20

30
1

25
20

0

15

2016
2017

2014

2012

2010

2008

2006

2004

2002

10

2000

2017

2016

2015

2014

2013

2012

2011

2010

-1

Sources: Baker Hughes, Bloomberg, International Energy Agency, Rystad Energy NASWellCube
Premium, U.S. Department of Agriculture, World Bank, World Bureau of Metal Statistics.
A. Index based on nominal U.S. dollars. Last observation is November 2017.
B. Weekly data. Last observation is December 15, 2017.
C. Does not include test activity, where well was shut-down after completion. The average and range
are calculated over Bakken, Eagle Ford, Permian Delaware, and Permian Midland basins. Lastobservation is 2017Q2.
D. Shaded area (2017Q4-2018Q4) represents IEA projections.
E. Last observation is 2017Q2.
F. USDA December 2017 update.

the year. Despite an agreement by someOrganization of Petroleum Exporting Countries(OPEC) and non-OPEC producers to cut
production, oil prices dropped to $46 in mid2017, reflecting a rebound in U.S. crude oil
output and rising production from Libya andNigeria,
which were exempted from production
targets. The price dip temporarily halted the
upturn in U.S. shale drilling. Prices then increased
to around $60/bbl toward the end of 2017, amid
strengthening demand, falling stocks, and an
agreement in late November to extend production
cuts until the end of 2018.
Oil prices are projected to average $58/bbl in
2018—a slight upward revision from June
forecasts—and edge up to $59/bbl in 2019. These
projections reflect expectations of an increase in
U.S. production due to continued efficiency gains
in the shale oil industry, moderate non-OECD
demand growth, and very limited OECD demand
growth. Downside risks for oil prices arise mainly
from the resilience of the U.S. shale industry andfrom weak compliance to the agreed production
cuts. Conversely, upside risks to prices include thepossibility of supply disruptions among politicallystressed oil producers (e.g., Iraq, Libya, Nigeria),
as well as stronger demand growth.
Metals prices gained 22 percent in 2017 partly
due to robust demand from China. Low stocks forsome metals, notably aluminum and zinc, andChina’s efforts to reduce surplus production
capacity and limit industrial pollution, also helped
lift prices in the second half of 2017. In response
to tightening conditions, the base metals priceindex is expected to edge up in 2018 and 2019.
Downside risks to the price forecast include thepossibility of slowing demand and less-thanexpected production cuts in China. Upside risks
include stronger global demand, falling stocks, anda further reduction in Chinese capacity.
Agricultural prices weakened marginally in 2017and are projected to remain stable in 2018 and2019. Weighing on prices is the fact that
improved growing conditions have pushed stocksto-use ratios of key grains to multi-year highs.
Moreover, fears of supply disruptions (notably,
wheat in North America), which temporarily
boosted some grain prices, have diminished. Low
energy prices have helped reduce grain andoilseeds costs, given that their production isrelatively energy-intensive, and have also reduced
incentives to divert land to the production of
biofuels. Indeed, biofuel production, which grewat 15 percent per annum during the past 10 years,

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Commodity-exporting EMDEs
Growth in commodity exporters is estimated tohave accelerated in 2017 to a still subdued rate of
1.8 percent—broadly in line with previous
forecasts and up from 0.8 percent in 2016, asvarious large economies (e.g., Argentina, Brazil,
Nigeria, Russia) emerged from recession (Figure

Percent
9Percentage points
Commodity importers ex. China
6
Commodity exporters
5
China
4

6
3

3

1

0
2018

2017

C. GDP and demand component
growthD. Export and import growth

Percentage points
Net exports
6

Percent
12

4

EMDEs

Commodity
exporters

Commodity
importers ex.
China

2016

2013
2014
2015
2016
2017
2018

0
-4

2013
2014
2015
2016
2017
2018

0
-2

EMDEs

EMDE
commodity
exporters

E. Industrial production growth

F. Manufacturing PMIs

Percent, year-on-year
EMDE commodity exporters
6
EMDE commodity importers ex.China

Index
53

2016

8

2

Imports

2017

4

Exports

2016

Investment

2017

Consumption

2017

EMDE
commodity
importers ex.
China

2016

EMDE
commodity
exporters

2015

2015
2016
2017
2018

EMDEs

2

2010-14

2015
2016
2017
2018

0

EMDE
commodity
importers ex.
China

EMDE commodity exporters
EMDE commodity importers ex. China

52

4

51
50

2

49

0

48

Nov-17

Nov-16May-17

Nov-15May-16May-15

Nov-14

Nov-17May-17

Nov-16May-16

Nov-15May-1447-2
May-15EMDE growth accelerated to an estimated 4.3
percent in 2017, in line with June projections(Figure 1.11). A cyclical upturn continued incommodity exporters, raising their contribution
to overall EMDE growth. The recovery in commodity exporters reflected an upturn in private
consumption and investment amid improved
confidence and diminishing drag from earlier
policy tightening. The contribution of net exports
declined in commodity exporters, as import
growth rebounded substantially. In commodity
importers, growth remained robust in 2017,supported by solid domestic demand and strong
exports. Recent activity data have been solid, anda number of high-frequency indicators—such asindustrial production and purchasing managers’
indexes (PMIs)—are at multi-year highs, suggesting continued momentum across EMDEs,
particularly among commodity exporters.

B. Contribution to EMDE growth
1990-2008 average
2003-08 average
200age

Nov-14

Recent developments

A. Growth

2015
2016
2017
2018

EMDE growth accelerated in 2017 to 4.3 percent,reflecting a recovery in commodity exporters amid
continued robust activity in commodity importers.
EMDE growth is projected to further strengthen to
4.5 percent in 2018 and to an average of 4.7 percent
in 2019-20—close to potential—as headwinds tocommodity exporters dissipate. However, potential
growth over the next decade is likely to decline,reflecting the lagged effect of recent investment
weakness, slowing productivity growth, andunfavorable demographic trends.

EMDE growth strengthened in 2017, as activity recovered in commodity
exporters and remained solid in commodity importers. In particular, firming
private consumption and investment supported growth in commodityexporting EMDEs. A number of high-frequency indicators suggest
continued momentum across EMDEs.

2013
2014
2015
2016
2017
2018

Emerging market anddeveloping economies:
Recent developments
and outlook

19

FIGURE
1.11 Activity in EMDEs


May-14is expected to grow at 3 percent only in the next 3
years, and stabilize thereafter.

CHAPTER 1

Sources: Haver Analytics, World Bank.
A. -C. Shaded areas indicate forecasts. Data for 2017 are estimates.
C. Based on sample of 155 EMDEs for which demand components are available and projected.
Aggregate GDP growth numbers can differ from those presented in Table 1.1 due to the smaller
country sample.
D. Data include goods and services. Blue and red horizontal lines indicate 2006-17 averages. Data
for 2017 are estimates.
E. Blue and red horizontal lines indicate January 1995-October 2017 averages. Last observation
is October 2017.
F. Values above 50 indicate expansion. Last observation is November 2017, with South Africa data
as of May 2017.

1.12). Although the recovery was led by a reboundin Brazil and Russia (the largest economies in thisgroup), it was broad-based, and seen in more than
50 percent of commodity exporters.
Domestic demand in 2017 continued to benefit
from improved confidence and greater macroeco-

CHAPTER 1

20

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.12 Activity in EMDE commodity exporters
While the recovery in commodity exporters reflected improvements in Brazil
and Russia, it was broad based, with growth increasing in more than 50
percent of countries. Investment in commodity exporters bottomed out,
reflecting stabilizing commodity prices, improved confidence, anddiminishing drag from past policy tightening. However, energy exporters
continued to lag behind.
A. Contribution to growth incommodity exporters

B. Share of commodity exporters withincreasing/decreasing growth

Percentage points
5

Percent
Increasing
100

RussiaBrazilOthers4

3

Unchanged

Decreasing
g

75

2
1

50

0
-1

25
2018

C. Investment growth
Percent
20

ECA

2018

2017

2016

2015

2014

2013

0

2012

2017

2016

2010-142015-2

D. Growth

LAC

Percent
8

SSA

15

6

10

4

5

2

0

0

2017

2016

2015

2014

2013

2012

2011

2010

2010-15
2016
2017

-15

2010-1520162017

2010-15
2016
2017

-5
-10

2010-15
2016
2017

-2

Commodity Energy
Metals Agricultural
exporters exporters exporters exporters

Source: World Bank.
A. B. Shaded area indicates forecasts. Data for 2017 are estimates.
B. Increasing/decreasing growth are changes of at least 0.1 percentage point from the previous year.
Countries with a slower pace of contraction from one year to the next are included in the increasing
growth category. Sample includes 85 commodity-exporting EMDEs.
C. ECA = Europe and Central Asia, LAC = Latin America and the Caribbean, and
SSA = Sub-Saharan Africa. Data for 2017 are estimates.
D. Simple average of GDP growth. Orange lines indicate interquartile ranges of growth in each group.
Data for 2017 are estimates.

nomic, currency, and price stability. The dragfrom earlier policy tightening diminished, anddeclininginflation
allowedformoreaccommodative monetary policy (e.g., Brazil,
Chile, Colombia, Kazakhstan, Russia, South
Africa, Zambia). Lower inflation and greater
monetary policy accommodation supported
private consumption growth in large economies(e.g., Brazil, Kazakhstan, Russia, South Africa,
Zambia; World Bank 2017b).
Investment recovered in 2017 after a period ofcontraction (e.g., Argentina, Colombia, theIslamic Republic of Iran, Nigeria, Russia,
Zambia). In about 65 percent of commodity
exporters investment growth rose. The turnaroundreflected
a response to the stabilization of globalcommodity prices and improved domestic
conditions, which contributed to a reduction in
financing costs and a recovery in capital inflows.
In resource sectors, corporate profits picked up
supported by higher commodity prices, stronger
currencies, and increased global demand, which
helped improve balance sheets. After a substantial
decline in 2014-2016, upstream energy
investment
rebounded
modestly
acrosscommodity exporters, with gains in large energy
producers in the Europe and Central Asia andMiddle East and North Africa regions (e.g.,
Kazakhstan, Libya, Russia) offsetting continued
contraction in large producers in the Latin
America and Caribbean and Sub-Saharan Africa
regions (International Energy Agency 2017).
Positive industry-wide trends in mining andmetals markets, including rising demand andprices, encouraged investment in metals producers(e.g., Armenia, Mongolia, Zambia; World Bank
2017c).
Trade volume flows in commodity exporters
recovered markedly. A significant rebound inimport growth reflected strengthening private
consumption and investment. Export growth was
supported by firming foreign demand; however, itremained moderate, as production cuts in some oil
exporters offset accelerating export flows in othercommodity exporters. More generally, export
growth was modest in countries with undiversified
export bases.
Among the largest commodity exporters, growthin Brazil rebounded to an estimated 1 percent in2017 following two years of contraction—above
previous forecasts, reflecting a recovery ofdomestic demand supported by easier monetaryconditions and improved confidence (World Bank
2017d). In Russia, activity in 2017 was stronger
than previously expected, with growth reaching an
estimated 1.7 percent, in response to higher oil
prices, banking sector support, targeted fiscal
stimulus, and reduced external imbalances amid
exchange rate flexibility (World Bank 2017e).
Growth in Nigeria picked up to an estimated 1
percent—below previous forecasts, mainly due tosofter-than-expected recovery of oil production(World Bank 2017f).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Growth in commodity importers was solid in 2017, supported by acontinued strong contribution from India. About 50 percent of countries
experienced increasing output growth. Investment growth in commodity
importers generally strengthened, although it varied across regions. Export
and import growth accelerated.
A. Contribution to growth incommodity importers excluding China

B. Share of commodity importers withincreasing/decreasing growth

Percentage points
6
India

Percent
Increasing
100

TurkeyMexicoOthers4

Commodity-importing EMDEs
Growth in commodity importers remained robust
at an estimated 6 percent in 2017. Excluding
China, estimated growth in 2017 was 5.1 percent,in part reflecting a continued strong contribution

Decreasing

75

3
50

2
1

25

2016

2015

2014

2013

2018

2017

2016

2015

2013

2012

2017

2
2010

2017

4

2015

6

Imports

2014

8

Exports

2013

10

Percent
16
14
12
10
8
6
4
2
0
2011

1990-2008 average

2010

Investment

2012

D. Export and import growth

2014

Percent
12

2016

C. Investment growth

0

2012

2018

2017

2016

2015

0

0

More generally, stronger initial conditions andfundamentals helped some countries recover fromthe commodity price shock more quickly thanothers (World Bank 2017g). For example, initialconditions among oil producers accounted forabout half of the cross-country variations in theimpact of the oil price shock (Grigoli, Herman,
and Swiston 2017). More broadly, key
determinants of the speed of recovery in commodity exporters included greater macroeconomic
policy space and more adequate reserve buffers(e.g., Indonesia, Kazakhstan, Malaysia, Russia);
more effective policy frameworks such as flexible
exchange rate regimes (e.g., Colombia, Malaysia,
Kazakhstan, Russia; Werner, Adler, and Magud2017), and more diversified export bases (e.g.,
Albania, Indonesia, Malaysia).

Unchanged

5

2010-14

In contrast, adjustment to low commodity prices
has proven more protracted than initially expectedin some energy exporters (Special Focus 1).
Countries with sluggish performance in 2017
include those that implemented oil production
cuts (e.g., Iraq, Kuwait, Saudi Arabia). They also
include countries that began to undertake belated
policy adjustment in Sub-Saharan Africa (e.g.,Chad, Republic of Congo), Latin America and the
Caribbean (e.g., Trinidad and Tobago), Europe
and Central Asia (e.g., Azerbaijan), and East Asia
and Pacific (e.g., Timor-Leste). In some cases,
these difficulties were compounded by countryspecific challenges, such as exchange rate
misalignments, social tensions, political challenges,
and security issues.

21

FIGURE
1.13 Activity in EMDE commodity importers
excluding China

2011

Activity
in 2017 remained solid in a number ofmore diversified economies and agriculture
exporters (e.g., Benin, Burkina Faso, Côte
d’Ivoire, Ethiopia, Indonesia, Malaysia, Morocco,
Senegal, Tanzania). Growth generally improved
among metals exporters (e.g., Armenia, Mongolia,
Zambia), reflecting higher metal prices andimproved domestic conditions.

CHAPTER 1

Source: World Bank.
A. B. Shaded area indicates forecasts. Data for 2017 are estimates.
B. Increasing/decreasing growth are changes of at least 0.1 percentage point from the previous year.
Countries with a slower pace of contraction from one year to the next are included in the increasing
growth category. Sample includes 57 commodity-importing EMDEs.
C. Data exclude China and refer to fixed investment. Data for 2017 are estimates.
D. Data exclude China and refer to goods and services. Horizontal lines indicate 1990-2008
averages. Data for 2017 are estimates.

from India (Figure 1.13.). About 50 percent ofcountries in this sub-group experienced increasing
GDP growth. Accommodative policies, amid
benign global financing conditions and low
inflation, supported domestic demand, which
offset the diminishing windfalls from the earlier
decline in commodity prices. In particular,
investment growth in commodity importers
generally strengthened, although it varied acrossregions—picking up sharply in Europe andCentral Asia, edging down in South Asia due toongoing softness in India’s private investment, andstagnating in Latin America and the Caribbean
amid policy uncertainty. Meanwhile, export andimport growth accelerated, reflecting firming
global and domestic demand, respectively.

22

CHAPTER 1

Many
commodity importers in the Europe andCentral Asia and Middle East and North Africa
enjoyed positive trade and financial spillovers
from strengthening activity in the Euro Area andthe recovery in Russia (e.g., Belarus, Georgia,
Jordan, Montenegro, Poland, Romania, Tunisia,
Turkey). Idiosyncratic factors that had held backgrowth in several large commodity importers in
the ECA region in 2016 diminished in 2017. For
instance, absorption of EU structural funds
strengthened in some Central European countries(e.g., Hungary, Poland). In addition, fiscal andmonetary policy support in Turkey contributed toa much stronger-than-expected rebound ingrowth. However, geopolitical and domestic challenges in some economies (e.g., FYR Macedonia,
Lebanon, Serbia) continued to weigh on activity.
In Latin America, growth in Mexico was slightly
better than expected, supported by solid services
sector activity, despite challenges related to therenegotiation of NAFTA and natural disasters.
Commodity importers across Asia continued toregister solid growth, in line with potential rates,
supported by robust domestic demand andstrengthening exports. Growth in large commodity importers accelerated (e.g., Pakistan,Thailand, Vietnam), or remained strong (e.g.,
Bangladesh, India, the Philippines), despite some
disruptions related to idiosyncratic factors (e.g.,
adjustment to the new Goods and Services Tax inIndia, floods in Bangladesh, slower progress in theimplementation of public investment projects in
the Philippines; World Bank 2017h). Smaller
Asian economies continued to benefit from robust
growth in China and India, including resurging
trade and substantial infrastructure investment(e.g., Afghanistan, Cambodia, Maldives, Sri
Lanka). New infrastructure investment supported
by China-led Belt and Road projects also
benefitted a number of commodity importers inNorth Africa (e.g., Djibouti).
Low-income countries
Within the broader group of EMDEs, growth in
low-income countries (LICs) is estimated to havestrengthened to 5.1 percent in 2017, from 4.5
percent in 2016, reflecting an increase incommodity prices and a recovery in agriculture

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018sectors
from earlier droughts (Box 1.2). Mining
output and investment rebounded in metalsexporting LICs (e.g., Democratic Republic ofCongo) as metals prices recovered. The uptick inoil prices helped oil exporters exit recession (e.g.,Chad). Non-resource intensive LICs expanded ata solid pace, supported by infrastructure
investment and higher crop production. Favorable
monsoon rains, a pickup in reconstruction works,
and the normalization of trade with India
underpinned a strong recovery in Nepal.
However, growth was softer than expected in
LICs dealing with heightened political uncertainty(e.g., Democratic Republic of Congo), highgovernment debt (e.g., Chad), large external
imbalances (e.g., Rwanda), and weak execution of
fiscal plans (e.g., Tanzania). Most LICs reported amodest decrease in the poverty headcount in2017. For almost a third of LICs, per capita
growth was negative (e.g., Burundi, Chad,
Democratic Republic of Congo, Haiti) or
stagnant (e.g., Afghanistan, Comoros, The
Gambia, Liberia).
EMDE outlook
EMDE growth is projected to strengthen to 4.5
percent in 2018 and to an average of 4.7 percent
in 2019-20, in line with June forecasts (Figure1.14). This outlook is predicated on improved
global manufacturing activity and robust global
trade, broadly favorable financing conditions, andfirming commodity prices, amid an investmentled recovery in advanced economies.
The projected acceleration for EMDEs as a wholereflects a continued recovery in commodity
exporters, whose growth is expected to pick up
from 1.8 percent in 2017 to 2.7 percent in 2018,as the cyclical rebound continues, and to an
average of 3.1 percent in 2019-20, as output gaps
close and labor market slack gradually diminishes.
The rebound in commodity exporters is expected
to be broad-based, so long as the prices of oil andother commodities continue to rise. Domestic
demand is expected to further strengthen,reflecting the positive effects of currency and pricestability on consumer and business confidence.
As the cyclical recovery continues, large negative output gaps are expected to narrow.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Growth in low-income countries is projected torise to 5.4 percent in 2018 and to an average of
5.6 percent in 2019-20, as commodity prices
firm. These forecasts are lower than in June, andreflect a reassessment of the pace of recovery in
oil—and metals-exporting LICs that experienced
sharp slowdowns or recession in 2016-17. Nonresource-intensive LICs in Sub-Saharan Africa are
expected to continue to expand at a solid pace,supported by infrastructure investment andexports. However, growth is projected to moderate in countries adjusting to high public debt
(e.g., Ethiopia), large external imbalances (e.g.,Mali, Rwanda), and rising fiscal deficits (e.g.,
Zimbabwe). As for the non-resource-intensive
LICs in South Asia, activity is expected to expand

A. Growth

B. Output gaps

Percent
9

1990
1990-2008
averageverage2003-08 average
2003
rage

Percent of potential GDP
3
2

6

1
3

0

0

C. EMDE potential growth

2018

2016

2014

2012

2010

2008

-4

D. Contribution to EMDE potential
growthPotential growth
Actual growth
1998-2017 potential growth
growt

Percent
8

EMDEs
EMDE commodity exporters
EMDE commodity importers

-3

2006

EMDE
commodity
importers ex.
China

2004

EMDE
commodity
exporters

2002

2015
2016
2017
2018
2019
2020

EMDEs

-2

2000

2015
2016
2017
2018
2019
2020

-1

Percent
10

TFP
CapitalLabor
Potential growth

8

6

6

4

4
2

2

2018-272013-17

2003-070

1998-20172018-272013-17

2008-120

2003-07

Forecasts for both groups are, on average, broadly
in line with June projections. In commodity
exporters, an upward revision to the largest
economies (e.g., Brazil, Russia) offsets a downgrade to the near-term growth forecast in several large energy-producing economies related tohigher-than-expected production cuts. In commodity importers excluding China, a small
downgrade to growth projections in 2018 reflects
a slight downward revision to India’s still-fast paceof expansion due to a softer-than-envisioned
recovery in investment and lingering effects of recent policy changes, as well as moderating growth
in Turkey following a sharp rebound in 2017.

In the near term, EMDE growth is projected to pick up, as cyclicalheadwinds in commodity exporters, where negative output gaps remain
large, gradually dissipate. Absent significant policy changes, EMDE
potential growth—which has already fallen since the onset of the global
financial crisis—is likely to further decline over the next decade, reflecting amore subdued pace of capital accumulation, slowing total factor
productivity growth, and population aging.

2015
2016
2017
2018
2019
2020

Growth in commodity importers is projected toremain broadly stable in 2018-20, averaging 5.7
percent—in line with its potential rate. Strengthening exports are expected to offset the impact ofdiminishing policy support in the face of
emerging price pressures and waning windfalls
from earlier commodity price declines. A gradualslowdown in China is expected to be offset by amodest pickup in the rest of the group during theforecast horizon. Excluding China, growth incommodity importers is foreseen to be 4.8 percent
in 2018 and to accelerate to an average of 5.1
percent in 2019-20, reflecting the diminishingrole of idiosyncratic factors weighing on activity
in some large economies (e.g., India, Mexico).

23

FIGURE
1.14 EMDE growth prospects

1998-2002

Consequently,
growth in most EMDE regions
with large numbers of commodity exporters is
projected to accelerate (Box 1.3; Chapter 2).

CHAPTER 1

Source: World Bank.
A. -D. Shaded area indicates forecasts.
B. Output gaps calculated using multivariate filter. Groups output gaps is the GDP-weighted averageof individual country output gap estimates using, as weights, real GDP at 2010 prices and market
exchange rates. The 23 EMDEs in the sample include Argentina, Bolivia, Brazil, Bulgaria, Chile,
China, Colombia, Croatia, Hungary, India, Indonesia, Kazakhstan, Malaysia, Mexico, Peru, Poland,
Romania, Russia, Serbia, South Africa, Thailand, Turkey, and Vietnam.
C. D. GDP-weighted averages of production function-based potential growth as described in Chapter
3. Sample includes 49 EMDEs.
D. TFP stands for total factor productivity growth.

at a modest pace in Afghanistan, as the security
situation continues to weigh on investment.
In Nepal, growth is expected to moderate owing
to infrastructure bottlenecks and regulatory
challenges.
EMDE potential growth has declined considerably
over the past two decades, notwithstanding an
investment-driven boost during the pre-crisis surge
in commodity prices. This slowdown reflectedsoftening total factor productivity (TFP) growthand, to a lesser extent, recent investment weakness
as well as less favorable demographic trends(Chapter 3). These factors were compounded by
the slow post-crisis recovery and, in commodity

24

CHAPTER 1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX 1.2 Low-income countries: Recent developments and outlook
Economic activity in low-income countries (LICs) strengthened, as commodity prices improved and the agricultural sector
recovered. Growth in LICs is estimated to have picked up to 5.1 percent in 2017, and is projected to rise to 5.4 percent in 2018
and 5.6 percent in 2019-20, as commodity prices firm. However, these forecasts are lower than in June, due to a slower-thanpreviously-anticipated pace of recovery in oil and metals exporters.
Risks to the outlook remain skewed to the downside, includingthe possibility of lower commodity prices, weaker-than-expected implementation of needed policy reforms, and a deterioration inpolitical and security situations. On the upside, stronger-than-expected recoveries in large advanced economies and EMDEs could
support stronger LIC growth through higher exports, investment, and remittances.

Recent developments
Growth rebounded. Growth in low-income countries(LICs) is estimated to have picked up to 5.1 percent in2017 from 4.5 percent in 2016, reflecting gains incommodity prices and a recovery in agricultural sectors
from droughts (Figure 1.2.1).1 Mining output andinvestment rebounded in some metals-exporting LICs(e.g., Democratic Republic of Congo) as metals prices
recovered. The uptick in oil prices helped slow the pace ofcontraction in some oil exporters (e.g., Chad). Nonresource-intensive LICs expanded at a solid pace,supported by infrastructure investment and higher crop
production. Favorable monsoon rains, a pickup inreconstruction works, and the normalization of trade with
India underpinned a strong recovery in Nepal. However,growth was softer than expected in LICs dealing withheightened political uncertainty (e.g., Democratic
Republic of Congo), high government debt (e.g.,
Mozambique), large external imbalances (e.g., Rwanda),
and weak execution of the capital expenditure budget (e.g.,
Tanzania).
Currencies stabilized, inflation slowed. The uptick incommodity prices, along with foreign aid inflows andcentral bank interventions, helped mitigate currencypressures. In some LICs (e.g., Mozambique), currencies
strengthened as rising export receipts boosted the supply of
foreign exchange. Exchange rate stability and an easing offood price inflation, due to improved rainfalls, helped
lower headline inflation across LICs. However, in somemetals-exporting LICs (e.g., Democratic Republic ofCongo, Liberia), a slow recovery of foreign direct
investment and the inability to access other sources ofexternal financing resulted in a rapid depreciation of theircurrencies, which exacerbated inflationary pressures. Othercases of high inflation reflected rising fuel prices and theNote: This box was prepared by Gerard Kambou. Research assistance
was provided by Xinghao Gong.
1 For the 2018 fiscal year, low-income economies are defined as thosewith a gross national income per capita, calculated using the World Bank
Atlas method, of $1,005 or less in 2016.



effects of natural disasters on domestic food supplies (e.g.,
Haiti). In LICs where inflation eased, some central banks(e.g., Tanzania) were able to cut interest rates to support
domestic demand.
Current account deficits narrowed. The median current
account deficit in LICs is estimated to have narrowed by
0.6 percentage points to 8.8 percent of GDP in 2017,reflecting an improvement in their terms of trade. Current
account deficits narrowed in oil-exporting LICs (e.g.,Chad), as imports decreased amid weak domestic demand,
but remained elevated in metals-exporting LICs, as
imports of capital equipment for mining projects
continued. Deficits widened in non-resource-intensive
LICs, due to a rise in capital goods imports forinfrastructure development and natural disaster-related
reconstruction work (e.g., earthquake in Nepal), and infuel and food imports (e.g., Haiti). Although some current
account deficits could be financed through Eurobond
issuance and remittances (e.g., Senegal), capital flows to
LICs remained soft and foreign reserves generally declined.
Declining fiscal deficits, still-elevated government debt.
The median fiscal deficit in LICs is estimated to havenarrowed to 4.3 percent of GDP in 2017 from 4.8 percent
in 2016. The fiscal balance in some oil-exporting LICs
turned into a surplus, in response to drastic spending cuts,and the fiscal deficits narrowed in non-resource-intensive
countries, owing in some cases to delayed public
investment spending. However, the fiscal deficits in metals-exporting LICs widened, as they continued to struggle
to mobilize domestic revenue, while reconstruction-related
spending increased the fiscal deficit in LICs hit by natural
disasters (e.g., Nepal, Haiti).
Government debt remained elevated, reflecting the slow
progress in reducing fiscal deficits, with the median debtto-GDP ratio edging down to 53.3 percent from 53.8
percent in 2016. Government debt fell in oil-exporting
LICs, but remained high in metals-exporters and the nonresource-intensive countries. Between 2016 and 2017,
government debt increased by 5 percentage points toabove 50 percent of GDP in some non-resource-intensive

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1



BOX 1.2 Low-income countries: Recent developments and outlook (continued)


FIGURE 1.2.1 Recent developments in low-income countries
Growth strengthened in low-income countries in 2017, reflecting a pickup in some metals exporters. Non-resource-intensive
LICs continued to expand at a solid pace. Headline inflation  slowed across LICs, as food inflation fell. Current account andfiscal deficits narrowed in oil-exporting LICs as they implemented measures to contain spending, but remained elevated inmetals exporters and non-resource-intensive countries as investment spending remained high. Government debt remained
elevated across LICs, reflecting still-high fiscal deficits. While most LICs reported a decrease in the poverty headcount, it isexpected to increase in metals exporters and, particularly, in oil exporters.
B. Inflation-4

Non-resourceintensive LICs

Metalsexporting
LICs

Oil-exporting
LICs

-6

2016

Percent of GDP
70
60
50
40
30
20
10
0

2017

2018

Share of countries
100

Increasing

Non-resourceintensive LICs

Decreasing

75
50
25

0

Non-resourceintensive LICs

0

F. Share of countries with increasing/decreasing poverty rate

Metalsexporting LICs

2018

Oil-exporting
LICs

2017

LICs

2016

-2

LICs

LICs

E. Government debt

D. Fiscal balance
Percent of GDP
2

0

Jan-15Mar-15May-15
Jul-15
Sep-15
Nov-15Jan-16
Mar-16May-16
Jul-16
Sep-16
Nov-16
Jan-17Mar-17May-17
Jul-17
Sep-17
Nov-17

2016

2015

2017

2016

2015

-5

2017

OilMetalsNonexporting exporting resourceLICs
LICs
intensive
LICs

2016

2017

LICs

5

2015

2017

10

2018

Non-resourceintensive LICs

15

Metalsexporting
LICs

20

2017

Metalsexporting LICs

25

2016

Oil-exporting
LICs

Percent of GDP
0
-5
-10
-15
-20
-25
-30

UgandaChad
Mozambique
Nepal
Haiti
LICs

Oil-exporting
LICs

Percent
30

2003-08 average

2016

2015

Percent
16
12
8
4
0
-4
-8

C. Current account balance

LICs

A. Growth

Sources: Haver Analytics, International Monetary Fund, World Bank.
Note: Non-resource-intensive countries consist mostly of agricultural exporters.
A. Data for 2017 are estimates.
C. D. E. Data for 2017 are estimates and data for 2018 are forecasts.
F. Based on the international poverty line of $1.90 a day, at 2011 purchasing power parity (PPP) exchange rates.

LICs (e.g., Burundi) and metals-exporters (e.g., Niger,
Sierra Leone). Although government debt increased less in
Benin and Ethiopia, it still rose above the median debt
ratio, as they continued to borrow to finance ambitious
investment plans. Debt servicing costs remained
unsustainable in Chad and Mozambique, highlighting theneed for governments in these and other LICs to continue
their efforts to mobilize domestic revenue and rationalize
public spending.
Slow progress in poverty reduction. Most LICs reported amodest decrease in the poverty headcount in 2017, basedon the international poverty line ($1.90 in 2011 PPP). Per
capita growth improved on average from 1.5 percent in2016 to 2.1 percent in 2017, but was negative or flat for

25

about a third of LICs. The international headcountpoverty rate is estimated to have edged up in oil- andmetals-exporting LICs (e.g., Chad, Democratic Republicof Congo), as well as in fragile countries (e.g., Afghanistan,
Burundi) as they continued to experience low GDP
growth rates.

Outlook
Softer-than-expected outlook. Growth in LICs is
projected to pick up further, rising to 5.4 percent in 2018
and to 5.6 percent on average in 2019-20, as commodity
prices firm (Figure 1.2.2). These forecasts are lower thanin June, reflecting a more gradual pace of recovery in a
number of oil and metals-exporting LICs that experienced

26

CHAPTER 1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX 1.2 Low-income countries: Recent developments and outlook (continued)


FIGURE 1.2.2 Outlook
Economic activity in LICs is projected to pick up further,with growth rising to 5.4 percent in 2018 and to 5.6
percent on average in 2019-20 as commodity prices
firm. However, these forecasts are lower than in June,
reflecting a more gradual pace of recovery among oil
and metals exporters. While per capita growth will edge
up in LICs as a whole, it will remain negative or low in a
number of oil and metals exporters and in fragile
countries. Growth, including in per capita terms, is
expected to remain robust in non-resource-intensive
LICs, although it will ease in some countries.

Growth in non-resource-intensive LICs is expected toremain robust. Non-resource-intensive LICs in SubSaharan Africa are expected to continue to expand at asolid pace, supported by expanding infrastructure
investment. However, growth is projected to moderate incountries adjusting to high public debt (e.g., Ethiopia) andlarge external imbalances (e.g., Mali, Rwanda).
Among non-resource-intensive LICs in South Asia, activity
is expected to expand at a modest pace in Afghanistan, as
the security situation limits investment. In Nepal,
following the strong recovery in 2017, growth is expected
to moderate owing to infrastructure bottlenecks,
regulatory challenges, and lower agricultural output.
Elsewhere, after a slowdown in 2017, growth in Haiti is
expected to rebound, as improving political stability helps
lift investment.

A. Growth forecasts
Percent14

a significant slowdown or recession in 2016-17. Moreover,while per capita growth is expected to edge up in LICs as awhole, it will still remain negative or low in several oil andmetals-exporters and in fragile countries.

2003-08 average

12

10
8
6
4
2
0
-2
-4

Risks

-6

LICs

Oil-exporting
LICs

Metals-exporting Non-resourceLICs
intensive LICs

B. Per capita GDP growth projections for selected LICs
Percent
6

2017

2018

4

2
0
-2
-4
-6

Chad

BurundiCongo,
Dem. Rep.

Afghanistan-8

Ethiopia

2019

2018

2017

2016

2019

2018

2017

2016

2019

2018

2017

2016

2019

2018

2017

2016

-8

Source: World Bank.
A. Data for 2017 are estimates; data for 2018 and 2019 are forecasts.
Shaded areas indicate forecasts.
B. Data for 2017 are estimates; data for 2018 are forecasts.

Risks still skewed to the downside. A key downside risk toactivity in LICs is the possibility of weaker-than-expectedcommodity prices, due for instance to softer Chinesedemand. Renewed slides in commodity prices would strain
fiscal and current account balances in commodity
exporters. Foreign direct investment in mining andinfrastructure, which is essential for long-term growth,would be curtailed. Metals-exporting LICs in Sub-SaharanAfrica are particularly vulnerable to negative terms-of-trade
shocks. Other downside risks include the possibility of a
sharp reduction in foreign aid or of a large decline inremittances due to stricter immigration policies inadvanced economies, which would harm investment andconsumption in many LICs. On the upside, stronger-thanexpected growth in the Euro Area—a major trading
partner for many LICs—could lead to a stronger-thanexpected pickup in activity in LICs through trade,investment and remittance channels. Faster-than-expected
recoveries in EMDEs could have positive spillover effects
on neighboring LICs.
On the domestic front, weak economic and financial
policies remain the main risk to the LICs outlook. Thisrisk is especially important among oil- and metalsexporting LICs, where sustained measures are needed tocontain fiscal deficits, stabilize government debt, andrebuild buffers. In contrast to oil and metals exporters, theGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1



BOX 1.2 Low-income countries: Recent developments and outlook (concluded)

TABLE 1.2.1 Low-income country forecastsa

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Source: World Bank.
Notes: e = estimate; f = forecast. World Bank forecasts are frequently updated based on new information and changing (global) circumstances. Consequently,
projections presented here may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any given
moment in time.
a. Central African Republic, Democratic People’s Republic of Korea, Somalia, and South Sudan are not forecast due to data limitations.
b. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars.
c. GDP growth based on fiscal year data. For Nepal, the year 2017 refers to FY2016/17.
For additional information, please see www.worldbank.org/gep.

non-resource-intensive LICs (e.g., Ethiopia, Senegal)—
which are relatively more diversified—have expanded at arobust pace. Their high pace of expansion has, however,been accompanied by a rising debt burden, as they
continued to borrow, including on international capital
markets, to finance ambitious public infrastructure27

programs. Excessive external borrowing, in the absence ofsound forward-looking budget management, could worsen
debt dynamics and cause economic instability. In addition,
droughts, heightened policy uncertainty, conflicts, andworsening security conditions could weigh heavily on
economic activity in LICs, especially in fragile countries.

28

CHAPTER 1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.15 Global growth forecasts: Uncertainty andthe balance of risks
Uncertainty around global growth prospects remains elevated and risks
still tilted to the downside, despite the possibility of stronger-than-expected
growth in large economies.
A. Probability distribution aroundglobal growth forecasts

B. Balance of risks to one-year-ahead
global growth forecasts

Percent
550 percent
80 percent
90 percent
4
Baseline

Percentage point
0.0

Historical median

-0.1

3
-0.2

2
1

2018

2019

Dec-172017

May-17-0.3
Dec-160
2016

Source: World Bank.
A. B. The fan chart shows the forecast distribution of global growth using time-varying estimates ofthe standard deviation and skewness extracted from the forecast distribution of three underlying risk
factors (oil price futures, the S&P 500 equity price futures, and term spread forecasts). Each of therisk factor’s weight is derived from the model described in Ohnsorge, Stocker, and Some (2016).
Values for 2018 are computed from the forecast distribution of 12-month ahead oil price futures, S&P
500 equity price futures, and term spread forecasts. Values for 2019 are based on 24-month-ahead
forecast distributions. Last observation is December 2017.
B. Balance of risks to 12-month global growth forecasts measured as the time-varying skewness ofglobal growth forecasts, computed from the forecast distribution of the three underlying risk factors.
Dates in horizontal axis correspond to cutoff dates for the January 2017, June 2017, and January
2018 editions of Global Economic Prospects. Median value is computed over the period January
2006 to October 2016.

exporters, the decline in commodity prices. Absent
significant policy changes to boost potential
growth, long-term fundamental drivers of EMDE
growth are expected to continue to weaken overthe next decade, including a subdued pace ofcapital accumulation, slowing productivity, andpopulation aging. Demographic trends are
expected to particularly worsen in East Asia andPacific (e.g., China, Thailand) and Europe andCentral Asia (e.g., Poland, Russia), while they willremain especially supportive to potential growth inSouth Asia.

Risks to the outlook
Risks to global growth have become more balanced,
following a stronger-than-expected cyclical upturn in
2017. A further pickup in investment growth inmajor economies could strengthen the recovery, withpositive spillover effects for trading partners.
However, risks remain predominantly on thedownside, especially over the medium term. With
interest rates and financial market volatility at
exceptionally low levels, the outlook is vulnerable tosudden changes in market sentiment or unexpected

policyshifts that could lead to financial instability.
Also, increased trade protectionism and risinggeopolitical tensions could weigh on sentiment anddisrupt the recovery. Over the longer term, a sharperthan expected slowdown in potential output growth
could reduce the resilience of the global economy toadverse shocks and damage prospects for gains inliving standards and poverty reduction.
Global growth estimates for 2017 have beenrevised up to 3 percent, reflecting a broad-based
recovery in advanced economies and faster-thanexpected growth in some major EMDEs. The
pace of global investment and export growth wasstronger than previously projected, which
benefited in particular more trade-dependent
EMDE regions (e.g., Europe and Central Asia,
East Asia and Pacific). While global growth isforecast to edge up to 3.1 percent in 2018, it isprojected to slightly moderate later in the forecasthorizon, given the anticipated normalization ofmonetary policy in major advanced economies in
the face of closing output gaps, an expectedslowing of growth in China, and limited mediumterm prospects for substantial further acceleration
among commodity-exporting EMDEs.
This said, the better-than-expected outcome in2017 illustrates the possibility of a continued
pickup in global investment and GDP growth if
financing conditions continue to be benign,
policy uncertainty recedes, and confidence
improves further. Risks to the outlook havetherefore become more balanced in 2018-19,
although they remain tilted to the downside(Figure 1.15). Major risks include the possibilityof disorderly financial market movements,
unexpected policy changes, rising tradeprotectionism, heightened geopolitical tensions,and, over the longer run, a sharper-than-expected
slowdown in potential output growth.
Upside risk: Stronger-than-expected growthin large economies
In the Euro Area, the dampening effect on activityof household and firm deleveraging has
diminished, and capital spending is recovering(Figure 1.16). With investment rates still well
below pre-crisis levels, the recovery could

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

In commodity-exporting EMDEs, a stabilization ofcommodity prices and policy adjustments havegenerally helped restore confidence. Investment
bottomed out in 2017, and diminished currencypressures allowed monetary policy to be eased. A
faster pickup in commodity prices amid strengthening global growth could contribute to a more
rapid revival in near-term activity and investment
than currently expected, particularly in some of
the largest commodity exporters (e.g., Brazil,
Russia). Faster growth in these economies would
have positive spillover effects on neighboring
countries (World Bank 2016b).
More generally, a further strengthening ofinvestment in the largest advanced economies and
EMDEs could stimulate global trade andmanufacturing activity, benefiting in particularmore trade-dependent EMDEs (Freund 2016).
Developments in major advanced economies
continue to generate the largest international
spillovers, but systemically important EMDEs areplaying an increasing role as well. In addition, astronger-than-expected cyclical recovery, in theselarge economies and elsewhere, could generate
its own momentum, encouraging greater
investment and boosting productivity. Consequently, if this growth spurt were to materialize
and be sustained, it could in turn support
potential growth (Chapter 3).

Investment has been recovering across the Euro Area and the return on
capital is at historically high levels in the United States. A stronger-thanexpected recovery in these and other major economies, including thelargest commodity-exporting EMDEs, could provide a boost to trading
partners.
A. Share of Euro Area countries withincreasing/decreasing investment
growthB. U.S. business investment rate
and return on capital

Percent of Euro Area countries
Increasing
Unchanged
100

Percent
10

Decreasing

Percent of GDP
Return on capital
18
Investment rate (RHS)

9
16

75

8
14

7

50

6

12

25

5
10

1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2015

2017

2016

2015

4

2014

0

2013

In the United States, the real return on businesscapital recovered from the global financial crisis,
reaching historically high levels. Investment rates
have rebounded but remain below previous
cyclical highs, and they could recover more
quickly than expected if rising business confidence
or growth-enhancing policies unlock pent-up
demand for capital spending. In particular,
removing distortions that discourage capitalspending could help spur stronger-than-expected
activity (Auerbach et al. 2017; Toder 2017;
Devereux, Lockwood, and Redoano 2008).

29

FIGURE
1.16 Upside risks of stronger-than-expected
growth in large economies

2012

continue
to strengthen in 2018 as monetary policyremains highly accommodative and confidence
improves further. The cyclical upturn could be
reinforced by targeted structural reforms, which
could create additional space for fiscal support
measures in the short term (Banerji et al. 2017).

CHAPTER 1

C. Average impact of 1-percentagepoint growth increase on neighboring
economies

D. Impact of 1-percentage-point
increase in EM7 and G7 growth
on global growth

Percentage point
0.9

Percentage points
3
EM7

0.6

2

0.3

1

0.0

G7

0
RussiaBrazilOn impact

1 year

2 years

Sources: Federal Reserve Bank of St. Louis; Gomme, Ravikumar, and Rupert (2011); World Bank.
A. Increasing/decreasing investment growth are changes of at least 0.1 percentage point from theprevious year. Countries with a slower pace of contraction from one year to the next are included in
the increasing investment growth category.
B. Business capital data are calculated using constant U.S. dollars, following the methodology from
Gomme, Ravikumar, and Rupert (2011). Investment as a share of GDP measured in current U.S.
dollars.
C. Based on estimates of a structural VAR. Average cumulative impact response after two years ofneighboring country’s real GDP growth to a 1-percentage-point decline in Russia’s or Brazil’s growth.
Orange bars reflect the 16th-84th percentile confidence bands. For Russia, the list of affectedneighboring countries is Armenia, Kazakhstan, Poland, Romania, Slovak Republic, Turkey, andUkraine. For Brazil, it is Argentina, Chile, Colombia, Ecuador, Paraguay, and Peru. For each country,
the variables included in the model are: G7 growth, EMBI, growth of source country, trade-weighted
average commodity prices, growth of the affected countries, the real effective exchange rate of theaffected countries. The model includes a dummy that captures the global financial crisis of 2008-09.
D. EM7 includes Brazil, China, India, Indonesia, Mexico, Russia, and Turkey. Cumulative impulse
responses of a 1-percentage-point increase in EM7 and G7 growth on global growth. The impact is
the GDP-weighted average of the responses of EM7, other EMDEs, and G7 countries. Solid bars
represent medians, and error bars represent 16-84 percent confidence intervals.

Downside risk: Disorderly adjustmentof financial market conditions
A disorderly adjustment of financial market
conditions could be triggered by several factors,
including a sudden correction in asset valuation, amarket reassessment of the pace of monetary
policy normalization in advanced economies, or
financial stress in major EMDEs such as China.

30

CHAPTER 1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018


BOX 1.3 Regional perspectives: Recent developments and outlook
Growth in most EMDE regions with large numbers of commodity exporters recovered in 2017, with the notable exception of the
Middle East and North Africa mostly due to oil production cuts. These regions are generally expected to see faster growth during
the forecast horizon, as commodity prices rise and the impact of the earlier collapse in those prices dissipates. The robust pace of
expansion in EMDE regions with a substantial number of commodity
importers is expected to continue. Risks to the outlook have
become more balanced in some regions, but continue to tilt down in all of them.

East Asia and Pacific. Regional growth in 2017 edged
up to an estimated 6.4 percent in 2017, up 0.2
percentage point from previous forecasts, reflecting an
improving external environment. Notwithstanding thiscyclical upturn, growth is projected to moderate to 6.2
percent in 2018 and to an average of 6.1 percent in
2019-20, as a structural slowdown in China offsets amodest pickup in the rest of the region. Risks to theforecast have become more balanced, as near-term
growth in advanced-economy trading partners may bestronger than expected. However, downside risks still
predominate, including rising geopolitical pressures, anabrupt tightening of global financing conditions,increased global protectionism, and a steeper-thanenvisaged slowdown in China or other major
economies.
Europe and Central Asia. Growth in the region isestimated to have accelerated to 3.8 percent in 2017,
1.3 percentage points above June projections, reflecting
a stronger-than-envisioned recovery across the region—
including in Poland, Russia, and particularly Turkey—
mainly due to firming domestic demand. Growth isprojected to decelerate to 2.9 percent in 2018, as therecovery in Turkey moderates, and settle at 3 percent in
2019-20. This stable outlook reflects continued
recovery in the eastern part of the region, driven bycommodity exporters, which is offset by a gradualslowdown in the western part of the region amid
moderating activity in the Euro Area toward the end of
the forecast horizon. Risks are more balanced than inprevious forecasts, with stronger-than-expected growthin advanced economies in the upside and increased
policy uncertainty and a renewed slide in oil prices inthe downside.
Latin America and the Caribbean. The region emerged
from a two-year contraction in 2017, growing by an
Note: This box was prepared by Carlos Arteta with contributions from
Gerard Kambou, Lei Ye, Yoki Okawa, Temel Taskin, Ekaterine
Vashakmadze, and Dana Vorisek. Research assistance was provided by
Jinxin Wu.

estimated 0.9 percent, slightly up from the June
forecast. Growth in the Caribbean sub-region was
significantly lower than projected in mid-2017,
however, reflecting the impact of two major hurricanes
in September. The pickup in overall regional activity
was supported by private consumption and, to a lesser
degree, by net exports. Growth is expected to accelerate
during the forecast period, reaching 2.7 percent in
2020, as conditions in commodity exporters improvefurther. However, the materialization of several
downside risks could derail the recovery. They include
economic spillovers from domestic policy uncertainty,
additional disruptions from natural disasters, negative
spillovers from international financial market
disruptions or a rise in U.S. trade protectionism, and afurther deterioration in fiscal conditions.
Middle East and North Africa. Growth in the region isestimated to have slowed markedly to 1.8 percent in2017, 0.3 percentage point below previous projections.
OPEC oil production cuts and heightened geopoliticaltensions led to deterioration in growth of oil exporters,
more than offsetting improving growth in oil importers.
Regional growth is forecast to pick up over the medium
term, as reforms across the region gain momentum andas fiscal adjustments ease amid a projected rise in oil
prices. Improved competitiveness and external conditions are expected to further support growth in oil
importers. Key risks to the regional outlook are tilted tothe downside, including continued geopolitical conflicts
and weakness in oil prices.
South Asia. Regional growth decelerated but remained
strong in 2017, at an estimated 6.5 percent—below
June forecasts, mainly due to temporary disruptions
associated with the adjustment in India to the newGoods and Services Tax. Growth is expected to pick up
to 6.9 percent in 2018 and stabilize around 7.2 percent,on average, in 2019-20, as consumption remains strong,exports recover, and investment revives with ongoingpolicy reforms and infrastructure improvements. Main
downside risks to the outlook include fiscal slippages(e.g., Bangladesh, Maldives, Pakistan), a setback inGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1



BOX 1.3 Regional perspectives: Recent developments and outlook (concluded)
Growth in most EMDE regions with substantial numbersof commodity exporters is expected to accelerate ascommodity prices rise and the impact of the earlier
collapse in those prices dissipates. The robust pace of
expansion in EMDE regions with a large number ofcommodity importers is expected to continue.
A. Regional growth, weighted average
Percent

Jun 2017

1990-2008 average

2003-08 average

10

8
6
4
2
0
2016
2017
2018
2019
2020

2016
2017
2018
2019
2020

2016
2017
2018
2019
2020

2016
2017
2018
2019
2020

2016
2017
2018
2019
2020

-2
2016
2017
2018
2019
2020

East Asia Europe and
Latin
Middle East South Asia
and Pacific Central Asia America and Northand theAfricaCaribbean

SubSaharanAfricaB. Regional growth, unweighted average
Percent

Jun 2017

1990-2008 average

2003-08 average

10
8
6
4
2

2016
2017
2018
2019
2020

2016
2017
2018
2019
2020

2016
2017
2018
2019
2020

2016
2017
2018
2019
2020

0
2016
2017
2018
2019
2020

Sub-Saharan Africa. Regional growth is estimated tohave strengthened to 2.4 percent in 2017, 0.2
percentage point below the June forecast, partly
reflecting a softer-than-expected recovery in Nigeria. An
uptick in metals prices, along with a recovery in the
agricultural sector, supported a modest rebound inmetals exporters, while growth was stable in nonresource-intensive countries as infrastructure investment
continued. Despite these improvements, regional
growth remained negative in per capita terms in 2017.
The region is projected to see a moderate pickup in
activity, with growth rising to 3.2 percent in 2018 andan average of 3.6 percent in 2019-20, turning slightly
positive in per capita terms. These forecasts assume that
commodity prices will firm and reforms to address
economic imbalances will be implemented. Downside
risks include lower commodity prices, inadequate fiscal
adjustment, and a faster tightening of global financing
conditions.

FIGURE 1.3.1 Regional growth

2016
2017
2018
2019
2020

implementation of reforms to improve corporate andfinancial sector balance sheets (e.g., Bangladesh, India),an abrupt rise in global financial market volatility, anddisruptions due to natural disasters. On the other hand, stronger-than-expected global growth in the near term
could result in positive spillovers to the more open
economies in the region.

31

East Asia Europe and
Latin
Middle East South Asia
and Pacific Central Asia America and Northand theAfricaCaribbean

SubSaharanAfricaSource: World Bank.
A. B. Bars denote latest estimates and forecasts; diamonds correspond to
Global Economic Prospects June 2017 forecasts. Average for 1990-2008
is constructed depending on data availability. For Europe and Central Asia,
the long-term average uses data for 1995-2008 to exclude the immediate
aftermath of the collapse of the Soviet Union. Shaded areas indicate
forecasts.
A. Since the largest economies account for almost 50 percent of regional
GDP in some regions, the weighted average predominantly reflects thedevelopment in the largest economies in each region.
B. Unweighted average regional growth is used to ensure broad reflectionof regional trends across all countries in the region.

CHAPTER 1

32

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.17 Financial market risks
Asset valuations are elevated and compensation for credit risks is at low
historical levels. A market reassessment of policies by major central banks
or financial stress in systemically large EMDEs such as China, could cause
a sudden increase in financial market volatility and borrowing costs for
EMDEs. The impact of a sharp reversal in capital inflows could be
amplified by elevated corporate sector vulnerabilities and growing debt
redemptions in coming years.
A. U.S. equity prices and long-term
interest rates

B. Risk-adjusted bond spreads

Ratio
50

Basis points
500

Percent
20

40

15

Basis points
1,200

United States
EMDEs (RHS)

400

1,000
800

300

30

10
20

600

200

2018

2017

2016

2015

2014

2013

2012

2011

0

2010

1920
1927
1934
1941
1948
1955
1962
1969
1976
1983
1990
1997
2004
2011
2018

200

0

2009

0

0

400

100

2008

5

10

2,000

1,000

1,000
2017

2015

2013

2011

2009

2007

2005

0
2003

0

Japan (1996)

3,000

2,000

China (2016)

3,000

Thailand (1997)

4,000

Poland (2016)

4,000

Malaysia (1997)

Percent of GDP
250
200
150
100
50
0

Indonesia (1998)

Euro, billions
US$, billions
European Central Bank
5,000 U.S. Federal Reserve (RHS)
5,000

Turkey (2016)

D. Corporate credit-to-GDP ratios
during past credit boom episodes

South Africa (2008)

C. Asset holdings by the U.S. Federal
Reserve and the European Central
Bank

Spain (2010)

Price-to-earnings ratio
Long-term interest rate (RHS)

E. EMDE corporate vulnerability

F. Value of international EMDE bonds
maturing

Index
0.20

US$, billions
Percent of GDP
1.0
280 Total maturing bond amount
Share of GDP (RHS)

0.16

0.8

210

0.6

0.12

140
0.4

0.08
70

0.04

0.2

2020

2019

2018

2017

2016

2015

2014

2013

2017

2014

2010

0.0

2012

0

0.00

Sources: Bank for International Settlements, Bloomberg, Dealogic, Federal Reserve Bank of St.
Louis, Feyen et al. (2017), Shiller (2015), World Bank.
A. Price-to-earnings ratio is the cyclically-adjusted ratio as described in Shiller (2015). Long-term
interest rates are the nominal 10-year Treasury constant maturity rates. Last observation is
December 2017. Data for December 2017 are estimates.
B. Based on option-adjusted spreads calculated from early redemptions of government and corporate
bonds. The option-adjusted spreads are used as a measure of credit risk compensation. Lastobservation is December 18, 2017.
C. Last observation is November 2017.
D. Ranges shows the highest private non-financial debt to GDP ratios across advanced economies
and EMDEs over the period 1996Q1-2016Q4. Red bars denote EMDEs and blue bars are advanced
economies.
E. The Corporate Vulnerability Index (CVI) tracks financial conditions of the non-financial corporate
sector in 69 EMDEs. The CVI uses firms' balance sheet information covering seven indicators:
interest coverage ratio, leverage ratio, net debt-to-EBIT ratio, current-to-long term liabilities ratio,
quick ratio, return to assets, and market-to-book ratio. The CVI ranges from 0 (i.e., firms in aparticular country are not financially vulnerable in any of the 7 indicators) to 1 (i.e., all firms in aparticular country are financially vulnerable in all 7 indicators). The CVI is calculated using data from
14,207 firms. For more details, see Feyen et al. (2017). The 2017 numbers are an average of the firsttwo quarters.
F. Horizontal axis shows maturity date.

Asset
valuations have continued to rise amid
persistently low interest rates and improved
growth prospects (Lansing 2017). Equity prices
are elevated and compensation for credit risks forlower-graded borrowers has reached historical lowsin both advanced economies and EMDEs (Figure1.17). While they could help support the recovery
in the short term, stretched asset valuations andcompressed risk premiums raise the risk ofdestabilizing corrections. The combination ofdeteriorated credit quality, corporate balance sheet
leverage, and diminished compensation for credit
risks make corporate bond markets susceptible tosudden reversals (IMF 2017a).
Both the U.S. Federal Reserve and the ECB haveannounced measures to unwind or cap the size of
their balance sheets in the short term. During thepost crisis period, the expansion of these central
banks’ balance sheets helped compress global longterm interest rates and volatility (Gagnon 2016;
Christensen and Rudebusch 2016; Altavilla,
Carboni, and Motto 2015). This spurred demand
for riskier assets, supporting capital inflows in
EMDEs (Arteta et al. 2015). While a gradual andwell-anticipated reversal of balance sheet policies
should be manageable, unexpected changes, ormarket reassessment of these policies and ofunderlying inflation dynamics, could lead to an
abrupt rise in global bond yields and risk
premiums. In addition, uncertainty surrounding
the outlook for inflation and equilibrium interest
rates has contributed to diverging views between
market participants and monetary authorities on
the path for policy rates, particularly in the UnitedStates. A sudden market reassessment of this path
could generate financial stress.
China continues to face vulnerabilities associatedwith high corporate indebtedness, particularly insectors with overcapacity and deteriorating
profitability (IMF 2017b). Credit growth still
outpaces nominal GDP growth, despite monetaryand regulatory tightening. The total stock of nonfinancial sector debt is above levels observed at thepeak of previous credit booms in other major
EMDEs, although still below those of advanced
economies. The materialization of financial stresscould have significant adverse repercussions on
activity, with negative effects on other EMDEs,

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1

particularlycommodity exporters (Huidrom,
Kose, and Ohnsorge 2017). However, policy
buffers remain substantial in China and are likely
to provide space to support growth if risksmaterialize.

FIGURE
1.18 Policy uncertainty and geopolitical risks


EMDEs would be particularly susceptible to thematerialization of these and other financial risks,
which can result in a sudden increase in externalfinancing conditions, a reversal of capital flows
and slowing activity. These reversals could
exacerbate default risks, which have so far been
mitigated by a long period of exceptionally low
global interest rates (Reinhart, Reinhart, andTrebesch 2017). The adverse effects would be
most acute for countries with large externalfinancing needs, fragile corporate balance sheets,and significant fiscal sustainability gaps. During
the post-crisis period, corporate vulnerability has
increased substantially in a number of EMDEs,
driven by a rise in leverage ratios and adeterioration in profitability and debt service
capacity (Feyen et al. 2017). Credit-to-GDP ratios
have continued to increase in recent years incommodity exporters, while they remain elevated,albeit stable or declining, in commodity importers(World Bank 2016b).

A. Global economic policy uncertainty

B. Global economic policy
uncertainty, geopolitical risks,and financial market volatilityIndex, 100=2000-17 median, 6-month average
250

Index, 100=2000-17 median
200

200

150

Although profitability of banks in EMDEs isgenerally solid, credit losses could continue toerode capital buffers (e.g., India, Russia, South
Africa). A large volume of international debt
redemptions scheduled in 2019-20 could also
make some EMDEs vulnerable to a sudden
increase in borrowing costs around that period.
Rising public-sector risks are an important sourceof concern across EMDEs, affecting in particular asubstantial number of low-income countries(World Bank 2017g).
Downside risk: Policy uncertainty andgeopolitical risks
Global policy uncertainty moderated in the courseof 2017, reflecting diminished risks from key
electoral outcomes in Europe and perceptions of areduced likelihood of major policy shifts in the
United States. However, uncertainty remains
elevated and could intensify again, potentiallyweighing on confidence and growth (Figure 1.18).
Negotiation around the exit of the United

33

Global policy uncertainty moderated in the course of 2017, but remains
elevated. Geopolitical risks spiked during 2017, mainly reflecting tensions
on the Korean peninsula, and is also above historical norms. Despite theseconcerns, financial market volatility reached new lows.

150

100

100

50

Nov-17

Jul-17

Sep-17May-17Jan-17Mar-17

Nov-16

Jul-16

Sep-16May-16

Jan-16

Mar-16500Policyuncertainty

Geopoliticaluncertainty

Volatility(VIX)

Sources: Baker, Bloom, and Davis (2015); Bloomberg; Caldara and Iacoviello (2017); World Bank.
A. B. Policy uncertainty is the Economic Policy Uncertainty index computed by Baker, Bloom, andDavis (2015) and is based on the frequency of articles in domestic newspapers mentioning economic
policy uncertainty. The index is normalized to equal 100 at its 2000-17 median. Orange horizontal line
denotes 2000-17 median.
A. Last observation is November 2017.
B. Geopolitical uncertainty is the Geopolitical Risk Index computed by Caldara and Iacoviello (2017)and is based on the frequency of words related to geopolitical tensions in international newspapers.
Volatility is measured by the VIX. All indexes are normalized to equal 100 at their 2000-17 medians.
Blue bars denote 2017 averages. The last observation is December 2017 for geopolitical uncertainty
and volatility (VIX), and November 2017 for policy uncertainty.

Kingdom from the European Union, calls for
greater regional autonomy, or governancechallenges for the Euro Area could impact
investment decisions in Europe and beyond. In
the United States, there remains substantial
uncertainty about possible changes to trade,
immigration, and other policies, and there areconcerns that fiscal brinkmanship could
contribute to market turmoil, as it did in 2011
(U.S. Treasury 2013).
Similarly, geopolitical risks spiked during 2017
and remain above historical averages, mainlyreflecting tensions on the Korean peninsula,border disputes and territorial claims in Asia, andstrains in the Middle East. A renewed andsustained rise in geopolitical tensions, especiallythose involving systemically large economies,
could dampen confidence and lead to bouts offinancial market volatility, both in the affected
countries and their major trading partners. If thesetensions escalate into high-intensity interstate
conflict, the result could be a significant loss of
lives, assets, and productive capacity, particularly
in more vulnerable countries. In the Middle East,
they could also result in rising migrant flows

CHAPTER 1

34

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.19 Trade protectionism
An increase in tariffs up to WTO bound rates could significantly raise costs
and reduce trade volumes, particularly for some EMDE regions. The
reduction of tariff and non-tariff barriers between NAFTA countries has
been associated with rising trade, which could reverse if the agreement isundone.
A. Applied and bound tariffs
Percent
50

B. Tariffs and trade within NAFTA

Applied

Percent
5

Bound

EU

U.S.

0

China

1

0

EAP

10

ECA

2

LAC

20

MNA

3

SSA

4

30

SAR

40

1993

2015
Tariffs

1993

2015
Trade

Sources: U.S. Bureau of Economic Analysis, World Bank.
A. Bound tariffs are maximum tariffs under WTO rules. Data as of 2015. EAP = East Asia and Pacificexcluding China, ECA = Europe and Central Asia, LAC = Latin America and the Caribbean,
MNA = Middle East and North Africa, SAR = South Asia, and SSA = Sub-Saharan Africa.
B. Trade between NAFTA countries in percent of their combined GDP.

across the region (World Bank 2017i). This could
be further amplified by regional instability,
displacement, and violence (Rodrik 1999,
Polachek and Sevastianova 2012, Institute for
Economics and Peace 2017).
Downside risk: Increased restrictions to
trade
Despite the recent stabilization in the number of
newly introduced barriers to trade, the threat ofprotectionism is still a major concern. This was
highlighted by the failure of G20 economies torenew their long-standing commitment to free
trade and pledge to resist all forms ofprotectionism.
Even isolated attempts to resort to beggar-thyneighbor policy measures by large economies
could be met with retaliatory responses andtranslate into wide-ranging negative effects forparticipating countries as well as the rest of theworld (Bouët and Laborde 2017). While awithdrawal of commitments from unilateralpreferential schemes and trade agreements could
have a significant negative impact on trade, a trade
war that would result in a worldwide increase intariffs up to legally allowed WTO bound rates
would have much larger effects (Figure 1.19). Dueto their reliance on trade flows, an increase inbarriers to trade would likely impact low-income

countries(LICs) substantially. Measures that
negatively affect the economic interest of LICs
subsided in recent years, but that trend could
reverse, as was observed in the immediate postcrisis period.
Apart from potential upticks in protectionist
measures, the renegotiation of several free trade
agreements—notably, NAFTA—casts uncertainty
over trade and investment flows between major
trading partners. NAFTA was accompanied by asignificant deepening of trade relationships
between the United States, Canada, and Mexico.
Given the depth of the agreement, the undoing of
NAFTA could result in an appreciable decline intrade among member countries. Due to theinterconnectedness of NAFTA countries with theglobal economy, major changes in their trade
policies could affect the rest of world (Bergsten
and de Bolle 2017).
Downside risk: Sharper-than-expected
slowdown in potential growth
There is considerable uncertainty regarding
underlying rates of potential growth. The risk
remains for both advanced economies and
EMDEs of a more pronounced weakness in
productivity growth and investment. This would
amplify a broad-based further deterioration ofpotential growth expected in coming years amid
demographic pressures (Figure 1.20). In bothadvanced economies and EMDEs, demographic
trends will become an increasing headwind topotential growth. More than 84 percent of global
GDP is currently produced by countries whose
working age population shares are expected toshrink by 2030. Population aging is expected todampen global potential growth by around 0.2
percentage point over 2018-27 on averagecompared to the average of 2013-17, as it
depresses labor supply and total factor
productivity growth.
A sharper-than-expected slowdown in potential
growth could reduce the resilience of the global
economy to adverse shocks and, in the longer
term, damage prospects for gains in living
standards and poverty reduction. Slowing longterm growth in large economies—particularly inadvanced economies, which are the destination forGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1

35

about
60 percent of EMDE exports, and China,which has substantial trade and commodity
linkages with other EMDEs—would haveimportant negative spillovers (World Bank
2016b).

FIGURE
1.20 Slowing potential growth

In EMDEs, past investment busts have generally
been associated with subsequent slowdowns in
potential growth (Chapter 3). The post-crisis
slowdown in investment growth has had lingering
effects on EMDEs, and renewed weakness ininvestment would further damped potential
growth. Adjustments in commodity-exporting
EMDEs caused by a slump in commodity prices
could leave a particularly long legacy for thisgroup of countries. More generally, there is a riskthat the anticipation of lower future growth may
have a larger-than expected effect on current
investment, leading to a negative feedback loopthat further amplifies the slowdown.

A. Share of economies and GDP withpotential growth below 1998-2017
average

B. Share of global GDP of countries
with rising working-age population(WAP) share

Percent
100

Percent
100

A large number of advanced economies and EMDEs have experienced adeterioration in potential growth in recent years. More than 84 percent of
global GDP is currently produced by countries whose working-age
population shares are expected to shrink in the coming decade.

Share of countries
Share of GDP

75

OthersCountries with rising WAP

75

50

50

25
25

A worsening of security conditions and conflict,and the associated displacement of people, could
weigh substantially on growth in some economies
in Europe and Central Asia, the Middle East andNorth Africa, South Asia, and Sub-Saharan Africa.
A greater incidence of natural disasters andextreme weather events—such as hurricanes,
earthquakes, droughts, or floods—could exert
further economic disruption in regions such as
Latin America and the Caribbean (particularly in
the Caribbean sub-region), South Asia, and SubSaharan Africa.
Finally, a renewed weakness in the price of oil andother commodities could derail the recovery in

2018-272013-17

Source: World Bank.
A. B. Shaded areas indicate forecasts.
A. Number of economies and their share of global GDP among 80 advanced economies and EMDEs
with potential growth in each period below its long-term average (1998-2017).
B. Period averages are simple averages of the shares. Sample includes 37 advanced economies and
148 EMDEs.

Region-specific downside risks
In addition to global risks, there are various
region-specific downside risks (Box 1.3; Chapter2). For instance, heightened domestic policy
uncertainty within EMDE regions may
compound the effects of uncertainty emanatingfrom major economies, as discussed above, andadversely affect confidence and investment.
EMDE regions where policy uncertainty remains
elevated in some large economies include Europe
and Central Asia, Latin America and the
Caribbean, and Sub-Saharan Africa.

2008-12

2003-07

EMDEs

1998-2002

2018-272013-17

2003-072018-272013-17

2003-07

Advanced
economies0

1993-97World

2018-272013-17

2003-070

regions with large numbers of commodity
exporters—Europe and Central Asia, Latin
America and the Caribbean, the Middle East andNorth Africa, and Sub-Saharan Africa. In
particular, oil exporters in these regions remain
vulnerable to a renewed slide in oil prices (Special
Focus 1).

Policy challenges
Challenges in major economies
In advanced economies, monetary policy is graduallynormalizing but still faces important challenges,
including stubbornly low inflation. Fiscal policy has
become generally more supportive to growth, but
fiscal space remains limited in many advanced
economies. Amid rising demographic pressures,productivity-enhancing reforms are urgently needed.
In China, further reforms could help reallocate
factors of production toward more productive sectors.
Monetary and financial policies in advanced
economies
Monetary policy normalization is underway in the
United States and, to a lesser extent, in the EuroArea, as the recovery continues. However, despite

CHAPTER 1

36

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.21 Monetary and fiscal policies in advanced
economies

accommodation
despite diminishing economic
slack.

Challenges for monetary policy normalization include continued low
inflation despite declining unemployment. The U.S. Federal Reserve has
repeatedly revised down its medium-term policy rate expectations.
Expansionary fiscal policies were undertaken in a growing number ofcountries in 2016-17, while fiscal sustainability gaps have narrowed.
A. Policy rate, inflation, andunemployment in major advanced
economies
Policy rate
CPI inflation
Unemployment (RHS)

Percent
6

B. Median forecast of U.S. federal
funds rate by FOMC members

Percent
10

Percent
4
3

8

2

6

0

4

2014
2015
2016
2017

1

2019

2018

2017

2016

2015

2014

0

2017

2014

2011

2008

2005

2002

1999

2

C. Share of advanced-economy GDP
with expansionary/contractionary
fiscal policy

D. Fiscal sustainability gaps

GDP-weighted share of countries
Expansionary Unchanged Contractionary
100

Percent of GDP
6

Long
run

4

4
2

75

0

50

-2
25

-4

The extraordinary monetary stimulus of recent
years has raised concern that it may haveencouraged excessive financial risk-taking. For thisreason, it will be important that central banks
carefully manage the unwinding of policy
accommodation, including the normalization ofbalance sheets. Financial market reforms andmeasures to improve the loss-absorbing capacity ofmajor financial institutions have improved theresilience of the financial system (Yellen 2017;
Firestone, Lorenc, and Ranish 2017). However,there still are risks to financial stability, including
possible asset price overvaluation, rising leverage,
and a concentration of risks in non-bank financial
institutions. Financial regulation and supervision
should continue to be reinforced, including
further improvements in bank resolution frameworks and improved supervision of non-banks.
Macroprudential policies could play a more activerole to curb leverage cycles and mitigate risks
associated with low interest rates (European
Systemic Risk Board 2016; Rubio and Yao 2017;
Claessens 2015).

2017

2015

2013

2011

2009

2007

2005

2003

2017

2016

2015

2014

2013

2012

2001

-6

0

Sources: Federal Reserve Board, Haver Analytics, International Monetary Fund, World Bank.
A. Weighted averages for Euro Area, Japan, and the United States. Last observation is November
2017 for policy rates and October 2017 for CPI inflation and unemployment.
B. Forecasts for each year correspond to the December FOMC meeting.
C. Expansionary fiscal policy defined as a decline in the cyclically-adjusted primary balance of morethan 0.2 percentage point of potential GDP. Contractionary fiscal policy is defined as an increase in
the cyclically-adjusted primary balance of more than 0.2 percentage point of potential GDP.
D. Sustainability gap is measured as the difference between the primary balance and the debtstabilizing primary balance, assuming historical median (1990–2016) interest rates and growth rates.
A negative gap indicates that government debt is on a rising trajectory; a positive gap indicatesgovernment debt is on a falling trajectory. Figure shows median in advanced economies. Dashed bluelines denote the interquartile range, while solid blue line is the median. Sample includes 34 advanced
economies.

strengthening activity, inflation remains below
central banks’ objectives (Blanchard, Cerutti, andSummers 2015; Ciccarelli and Osbat 2017; Figure1.21). Both transitory and structural factors
appear to be at play, making central banks’ tasks
particularly difficult as uncertainty about the
trajectory of inflation and real equilibrium interest
rates remains elevated (Carney 2017; Bobeica et al.
2017; Miles et al. 2017). The U.S. Federal Reserve
has continued to revise down its medium- to longrun policy interest rate expectations, while the
ECB continues to highlight the need for policy

Fiscal policy in advanced economies
In recent years, the role of counter-cyclical fiscal
policy has regained prominence in the policy
debate, especially when monetary policy isconstrained (Auerbach and Gorodnichenko 2017;
Jordà and Taylor 2016; Christiano, Eichenbaum,and Rebelo 2011). Marking a significant shift
from previous years, expansionary fiscal policies
were undertaken in countries representing morethan 50 percent of advanced-economy GDP in
2016, and more than 25 percent in 2017. The
share of countries implementing contractionary
fiscal policies dropped drastically, from more than70 percent in 2015 to 12 percent in 2017.
However, fiscal space is limited in some
economies, notwithstanding some improvements(Kose et al. 2017b). Since the need for fiscal
stimulus has become less urgent as economic slack
diminishes in most advanced economies, growthenhancing tax and expenditure reforms shouldplay a more prominent role in policy discussions(Barbiero and Cournède 2013; IMF 2017c).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1

37

In the Euro Area, closer fiscal coordination could
further enhance resilience to domestic and external
shocks (Dabrowski 2015). Stricter compliancewith common fiscal and macroeconomic
surveillance rules could help make a central fiscal
authority more acceptable to all (Juncker et al.
2015). In the United States, public infrastructure
programs and comprehensive tax reforms coulddeliver growth dividends over time.

FIGURE
1.22 Structural policy in advanced economies
Structural policies in advanced economies

1

Structural reforms could offset the impact of demographic aging on
potential output growth. Reform spurts tend to be followed by improvements in productivity growth.
A. Potential growth and reform
scenarios

B. TFP growth during reform episodes

Percent
Education, health, and labor market reforms
2
Fill investment needs
Baseline

Percentage points
1.4
1.0
0.6

Policy challenges in China
China has initiated a wide range of reforms inrecent years. Efforts have focused on excess

2013-172018-27

Spurt

Reform impact

Setback

Source: World Bank estimates.
A. GDP-weighted averages of production function-based potential growth under different policy
scenarios as described in Chapter 3. Shaded area indicates forecast.
B. Simple averages of TFP (total factor productivity) growth. TFP growth refers to potential TFP
growth, as estimated in Chapter 3. Data use Worldwide Governance Indicators (WGI): Basedon an event study of 26 statistically significant events for 38 advanced economies during 1996-2015.
A detailed methodology is available in Chapter 3.

FIGURE 1.23 Policy challenges in China
In China, efforts have focused on excess capacity reduction, as well as
fiscal and financial reforms. Fiscal policy remained expansionary in 2017,supporting growth but contributing to rising public debt.
A. Employment in overcapacity
sectors

B. General government debt andstructural balance

Million people
Coal mining & dressing
Nonmetallic mineral product25
Chemical material & productFerrous metal smelting & pressing
20

Percent of GDP

Percent of GDP

General government gross debt
General government structural balance (RHS)

50

0

45

-1

40

-2

5

35

-3

0

30

-4

2017

2016

2015

2014

2013

2012

2011

2017

2015

2013

2011

2009

2007

10

2010

15

2005

To offset the impact of population aging on
potential growth in coming years, reforms willneed to be geared toward boosting productivity
growth and labor participation. Policies that raise
the quality of education and training; further
improve female, youth, and senior labor market
attachment; and match changing labor market
needs would be particularly beneficial (Figure1.22). In addition, investment needs could be
filled through high-quality public infrastructure,better regulation, and well-designed R&D
incentives. Encouragingly, reform spurts canreinforce growth prospects. In some advanced
economies, most notably in the Euro Area,
facilitating debt restructuring and strengtheningbank balance sheets could help facilitate private
investment and encourage the relocation of capital
toward higher-productivity firms.

-0.6

0

2003

The slowdown in productivity growth across advanced economies pre-dated the global financial
crisis. It was most visible in the United States,
where the benefits of the information and technology revolution had been the largest from themid-1990s to mid-2000s (Foda 2016). However,the deceleration in productivity has also been
noticeable in other major economies, including
the Euro Area after the global financial crisis.

-0.2

2001

Persistently weak productivity gains in coming
years could lead to a further slowdown in potential
growth amid rising demographic pressures. This
would further constrain wage growth, and make it
more difficult to reduce inequality and sustainsocial safety nets.

0.2

Sources: CEIC, China National Bureau of Statistics, International Monetary Fund.
A. Data for 2017 are as of October 2017.
B. Gross debt is as a percent of GDP; structural balance is the cyclically-adjusted fiscal balance as apercent of potential GDP. General government gross debt ratios in 2016 and 2017 are estimates.

capacity reduction (Figure 1.23), as well as fiscal
and financial reforms to contain financial sector
vulnerabilities. Fiscal policy remained expansionary in 2017, supporting growth but contributing
to rising public debt. Tighter enforcement of
capital flow management measures has helped ease
capital outflow pressures. Regulatory efforts havegained momentum since the October Party
Congress, as new rules were announced to lift caps
on foreign ownership of financial institutions and38

CHAPTER 1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.24 EMDE monetary policy
Inflation in EMDEs generally eased in 2017, most notably in some largecommodity exporters, and is within target bands in most EMDEs with
inflation targets. Policy interest rate actions in commodity exporters andimporters were reflective of cyclical positions. Continued monetary policy
accommodation among commodity exporters would be consistent with stillnegative output gaps in 2018.
A. Inflation versus target range
Percent
100

B. Output gaps and policy interest
rates

Commodity
importers

2017

2016

2011-15

2017

2016

2011-15

Commodity
exporters

Commodity
exporters

2018

-2

2017

-2

2016

0

0

2015

0

20

2018

2

80

2017

2

Above

2016

40

Within2015

60

Percent of potential GDP
Number of actions
6
6
Policy rate hikes (RHS)
Po
RHS)
Policy rate cuts (RHS)
Po
HS)
4
4
Output gap
O

Below

Commodity
importers

Sources: Haver Analytics, National Bureau of Statistics of the Republic of Moldova, World Bank.
A. Sample includes 15 commodity exporters and 10 commodity importers. Bars for 2017 consider
actual versus target range (year-on-year) inflation in November. Bars for other years consider actual
versus target inflation in December of the respective years. Bars for 2011-15 are simple averages.
B. Sample includes 11 commodity exporters and 11 commodity importers. Commodity importers
aggregate excludes China. Output gaps and policy interest rates are GDP-weighted averages. Policy
rate data are year-to-date as of December 19, 2017. Shaded areas indicate forecasts.

tighten oversight of commercial banks.
Deleveraging measures need to be intensified toaddress vulnerabilities and improve fiscal
sustainability of subnational governments.
Further financial and corporate sector reforms
could also help reallocate capital and labor toward
more productive firms and sectors. This could
increase the contribution of productivity topotential growth by about 1 percentage point overthe long term (Chapter 2; IMF 2017b). Efforts tobuild human capital through better education andtraining, and reforms that improve theinstitutions and business environment, could also
provide a further boost to productivity andpotential output (World Bank 2017j).

undertakecountercyclical policy, even in the face ofsizable negative output gaps. In the longer term,
structural policies—such as improvements in education and health systems, as well as labor market,
governance, and business climate reforms—may help
stem the expected further decline in potential growth.
Reforms that boost education may also reduce
inequality. In addition to these challenges, oilexporting EMDEs need to pursue policies that bolster
diversification and resilience to oil price fluctuations.
Monetary and financial policies
Headline inflation in EMDEs generally eased
through the second half 2017, most notably insome large commodity exporters (e.g., Brazil,
Russia). Inflation is now within target bands inthe majority of EMDEs that have adopted targets,
including in some large commodity importers
where it was previously below target (Figure1.24). Policy interest rate adjustments during
2017—mostly hikes by commodity importers,
and nearly all cuts by commodity exporters—werereflective of their cyclical positions. Continued
monetary policy accommodation among commodity exporters would be consistent with stillnegative output gaps expected for 2018.

Challenges in emerging market anddeveloping economies

Benign global financing conditions and low
financial market volatility may have lessened
pressures to reform and modernize financial sector
regulations in EMDEs. However, with debt
building and credit growth accelerating in some
EMDEs, strengthened macroprudential policy
frameworks could play an important role inassuring financial stability, especially given thepotential unexpected effects from the unwindingof monetary accommodation in major advanced
economies, as well as higher-than-expected volatility in capital flows.

Inflation in EMDEs generally eased through most of
2017, most notably in commodity exporters,
allowing the latter to pursue a more accommodative
monetary policy stance. Rising debt and rapid credit
growth in some EMDEs highlight the importance ofstrengthening financial stability. Fiscal space remains
constrained across EMDEs, particularly in commodity exporters, which limits their ability to

Macroprudential policies, such as caps on bankloan-to-value and debt-to-income ratios, havebeen found to be particularly effective when credit
growth is high (Cerutti, Claessens, and Laeven2015), while both prudential and targeted capital
inflow management tools can reduce the riskinessof external liabilities (Cardarelli, Elekdag, andKose 2010). The rapid increase of portfolio andother investment flows in 2017, including cross-GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

As revenue growth catches up with expenditure growth across EMDEs,
fiscal deficits are anticipated to narrow. Fiscal policy in commodity
exporters is becoming less procyclical. However, fiscal sustainability gaps
remain large in these economies. Although such gaps are much smaller incommodity importers, government debt as a share of GDP has been rising
for this group. As a result, both commodity exporters and importers facedebt-related vulnerabilities.
A. Fiscal balance

B. Fiscal impulses and output gaps,
commodity exporters

Percent of GDP
0

Percentage-point change
Percent of GDP
2.5
Fiscal impulse
Output gap (RHS)
RHS 4.0

Commodity exporters
Commodity importers

-1

2.0

In commodity importers, fiscal sustainability gaps
are much smaller. However, rapid expenditure
growth in 2016-17 resulted in protracted deficits
and continued increases in public debt, which islikely to have exceeded 55 percent of GDP in
2017. Although interest payments have been
declining despite growing debt, they could risemarkedly if global financing conditions were totighten abruptly. In both commodity exporters
and importers, a substantial share of external debt
(private and public) is denominated in foreign
currency, pointing to vulnerabilities to global

2.0

1.0

1.0

0.5

2018

-2.0

2017

-1.0

-1.0

2016

2018

2017

2016

2015

2014

2013

2012

2011

2010

-5

0.0

-0.5

2015

-4

0.0

2014

-3

C. Fiscal sustainability gaps

D. Government gross debt andinterest payments, commodity
importers

Percent of GDP
2-2

Percent of GDP
Percent of GDP
58
2.2
Gross government debt
Interest payments (RHS)
56
2.1
54

-4

52

-6

50

Commodity
exporters

2017

2016

2015

2014

2017

2016

2015

0

2014

Among commodity exporters, government
revenues are recovering from the earlier terms-oftrade shock and fiscal deficits are narrowing(Figure 1.25). Fiscal policy in commodity
exporters is becoming less procyclical, withnegative output gaps no longer accompanied byfiscal consolidation. Steps are being taken, or arecontemplated, to place their fiscal position on amore sustainable footing. These include
reductions in energy subsidies (e.g., Argentina,
Indonesia, Malaysia, Mexico, Saudi Arabia, theUnited Arab Emirates), cuts in expenditures (e.g.,
the Islamic Republic of Iran, Malaysia, Russia,
Saudi Arabia), and the introduction of valueadded taxes (e.g., GCC countries; Boersma andGriffiths 2016; World Bank 2016a). Despite these
efforts, fiscal sustainability gaps are still large,
which is contributing to growing debt-to-GDP
ratios. While a more accommodative policy stancewould help close negative output gaps incommodity exporters, the necessary fiscal space islimited and debt dynamics continue to be a
critical challenge, including for low-income
countries (World Bank 2017g).

3.0

1.5
-2

2013

Fiscal policy

39

FIGURE
1.25 EMDE fiscal policy
2012borderbank loans, may warrant particularattention, given that their volatility has historically
been much higher than that of foreign direct
investment flows (Pagliari and Hannan 2017).
Macroprudential tools may be particularly usefulfor EMDEs with pegged exchange rates, where
the transmission of global financial shocks todomestic banking sectors and through capital
flows appears to be greater (Obstfeld, Ostry, andQureshi 2017).

CHAPTER 1

Commodity
importers

2.0

1.9
48
1.8

46
2013 2014 2015 2016 2017 2018

Sources: International Monetary Fund, Kose et al. (2017), World Bank.
A. Figure shows median in each country group. Shaded area indicates forecasts. Sample includes
61 commodity importers and 93 commodity exporters.
B. Fiscal impulse is defined as the change in the structural fiscal deficit from the previous year. A
decline in structural deficit (a negative fiscal impulse) is a fiscal consolidation—countercyclical if
implemented while output gaps are positive—while an increase in the structural deficit (positive fiscal
impulse) is a fiscal stimulus—countercyclical if implemented while output gaps are negative. Sample
includes 11 commodity exporters.
C. Sustainability gap is measured as the difference between the primary balance and thedebt-stabilizing primary balance, assuming historical median (1990–2016) interest rates and growth
rates. A negative gap indicates that government debt is on a rising trajectory; a positive gap indicatesgovernment debt is on a falling trajectory. Blue bars denote the interquartile range, while orange
diamonds denote the median for each country group. Sample includes 44 commodity exporters and28 commodity importers.
D. Interest payments reflect general government expenses paid on interest. Sample includes 51
commodity-importing EMDEs.

capital market turbulence and currency
depreciation (Burger, Warnock, and Warnock2017). Indeed, the rapid increase in private-sector
debt across EMDEs suggests the possibility ofgrowing contingent liabilities for the public sector,
given the potential call for bailouts if balance sheet
stresses become systemic (World Bank 2017g). If
realized, contingent liabilities—particularly thosestemming from the financial sector—can lead to
substantial fiscal costs (Bova et al. 2016).

CHAPTER 1

40

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 1.26 EMDE structural policy
Education and health improvements and labor market reforms could
reverse the expected decline in EMDE potential growth over 2018-27
compared with 2013-17. Around reform episodes, EMDE total factor
productivity growth tends to improve.
A. EMDE potential growth

B. EMDE potential growth underreform scenarios

Percent
5.2

Percent
5.2

Baseline
Demographic trends
Other factors

4.8

4.8

4.4

4.4

4.0

4.0

3.6

Labor market reforms
Education and health improvements
Fill investment needs
Baseline

3.6
2013-17

Contribution

2018-272013-172018-27

Reform impact

C. Average change in EMDE TFP
growth during reform episodes

D. Change in EMDE TFP growth afterreform episodes

Percentage points
1.2

Percentage point
1.0

0.9

0.5

0.6
0.3

to
 prioritize and evaluate the efficacy of publicprojects, as well as strengthening institutions tofoster growth given fiscal constraints.
In addition, introducing fiscal rules, stabilization
funds, and medium-term expenditure frameworks
can foster institutional credibility and help restore
fiscal space (Huidrom, Kose, and Ohnsorge2016). These types of reforms can also help
discourage procyclical, asymmetric fiscal responses
to cyclical shocks—that is, increasing current
expenditures during booms but reducing
investment expenditures during busts—that canthreaten fiscal sustainability and undermine
growth (Ardanaz and Izquierdo 2017). Finally, theunusually benign state of global financing
conditions favor debt management operations to
reduce the vulnerability of the public sector toshocks, including by lengthening the maturity of
public debt and shifting debt into local currency.

0.0

0.0
-0.3

Structural policies

-0.5

-0.6
Spurt

Setback

World GovernanceIndicators

Spurt

Setback

Doing BusinessIndicators-1.0
2 years

4 yearsSpurt

2 years

4 years

Setback

Source: World Bank estimates.
A. B. Shaded areas indicate forecasts.
A. GDP-weighted averages of production function-based potential growth as described in Chapter 3.
B. GDP-weighted averages of production function-based potential growth under different policy
scenarios as described in Chapter 3.
C. Simple averages of TFP (total factor productivity) growth. TFP growth refers to potential TFP
growth, as estimated in Chapter 3. Worldwide Governance Indicators (WGI): Based on an event studyof 110 statistically significant events for 77 EMDEs during 1996-2015. Doing Business Indicators(DB): Based on an event study of 29 statistically significant events for 77 EMDEs during 2002-17.
A detailed methodology is available in Chapter 3.
D. TFP growth refers to potential TFP growth, as estimated in Chapter 3. Regression coefficients on
dummies for structural reform spurts and setbacks from local projections model for lags of four years,
for a sample of 77 EMDEs during 1996-2015. Data use Worldwide Governance Indicators. Verticalbars show 90 percent confidence interval. A detailed methodology is available in Chapter 3.

There is still considerable scope for growthenhancing fiscal reforms among EMDEs. Most
notably, tax reforms can be implemented tomobilize revenues and create the fiscal space tofund needed development priorities, as carried out
in a number of countries in recent years (e.g.,
Colombia, India, Kazakhstan, Malaysia, thePhilippines, Russia, Vietnam). Such reforms may
include broadening the tax base, eliminating
loopholes and unnecessary preferences (e.g.,
avoiding base erosion and profit shifting), andstrengthening tax administration and collection to
reduce avoidance (OECD 2017c). Moreover,expenditure reforms could enhance the quality of
public spending, by having mechanisms in place

Long-term trends point to a decline in EMDE
potential growth to 4.3 percent on average over
2018-27, 0.5 percentage point below the 2013-17
average (Figure 1.26). Per capita potential growthis expected to weaken accordingly. A boost to
public and private investment, if implemented
efficiently, can help stem this decline; however, it
will also need to be supplemented by measures toraise labor productivity and labor force
participation (Chapter 3).
Reforms to improve education and healthoutcomes, as well as labor market policies toexpand female labor force participation, could lift
potential growth by raising labor supply andfostering total factor productivity growth. Whileeducation and health outcomes have strengthened
in EMDEs in recent years, there is still room for
substantial improvement. School enrolment rates
and secondary school completion rates are nearadvanced-economy levels in many EMDEs;
however, tertiary school completion rates are, at
13 percent on average in 2013-17, about one-halfof the advanced-economy average. At 74 years on
average in 2013-17, life expectancy in EMDEs iswell below that in advanced economies (82 years).
Similarly, global female labor force participation,

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018at 58 percent on average in 2013-17, remains
three-quarters below that of men (74 percent), andeven less in EMDEs.
Improvements in education and health could also
generate gains in EMDE potential growth.
Stylized scenarios suggest that, of the expected0.5-percentage-point slowdown in EMDE potential growth in 2018-27, about 0.2 percentage
point could be reversed if education and healthoutcomes were improved substantially, and 0.1
percentage point if female labor force participation
were increased through labor market policies. In
regions with large room for improvement and asolid track record of implementing reforms, thesegrowth dividends could be larger.

CHAPTER 1

FIGURE
1.27 Education and inequalityNew entrants of educated workers to the global labor market will comeentirely from EMDEs, contributing to a decline of global inequality by 2030,
largely reflecting income convergence among countries. Although withincountry inequality will rise in importance at the global level, the education
wave—the increase in skilled EMDE workers—will nudge down withincountry inequality in EMDEs, albeit with regional differences.
A. Number of skilled workers

B. Difference in the Gini index
between education wave and no-wave
scenario

Million people
Advanced economies
500
ECA
400
EAP
MNA
300
LAC
SSA
200
SAR

0.1
0.0
-0.1

-0.2
-0.3
-0.4

-0.5

100

-0.6
0

-0.7

-100

-0.8
2020

Furthermore, reforms to improve the businessenvironment and promote good governance—e.g.,
to increase government effectiveness, reduce
corruption, and enhance the rule of law andregulatory quality—could help reverse theslowdown in potential growth. Past experience
illustrates that major governance and businessreforms were associated with higher output, TFP,
and investment growth (Chapter 3; Hodge et al.
2011; Acemoglu, Johnson, and Robinson 2001;
Divanbeigi and Ramalho 2015). Reform spurts
were, on average, associated with higher EMDETFP and investment growth during the two tofour years following such events.1 Conversely, atypical reform setback was accompanied by lower
TFP and investment growth. Improvements inpolitical institutions can also help overcome astatus quo bias that block reform progress (Stuti
2017; World Bank 2017j). Naturally, reform
priorities differ across countries. Depending on
the country context, pre-existing conditions andinteractions between reforms would warrant
careful sequencing to ensure synergies and avoid
possibly politically destabilizing reforms.
In addition to these structural challenges, oilexporting EMDEs—which suffered large losses in
actual and potential output due to the 2014-16 oilprice plunge—need to pursue policies that bolster

1 TFP growth refers to potential TFP growth to capture the longterm impact of reforms.

41

2025

2030

2035

2040

LAC SAR SSA MNA EAP ECA AEs

Source: Ahmed et al. (2017).
A. B. EAP = East Asia and Pacific, ECA = Europe and Central Asia, LAC = Latin America and the
Caribbean, MNA = Middle East and North Africa, SAR = South Asia, and SSA = Sub-Saharan Africa.
A. Skilled is defined as workers with more than nine years of education. Population projections are
based on UN (2015). Education information is from harmonized household and labor surveys for 117
countries, keeping present rates of education attainment in the calculation of the supply of skilledworkers.
B. The population weighted average difference in the Gini index is negative if there is an
improvement in the within-country inequality between the education wave relative to the no-wave
scenario. AEs = advanced economies.

diversification and resilience to oil pricefluctuations, given that prices are unlikely torecover substantially in coming years (Special
Focus 1). Some have started undertaking reforms
to limit their reliance on the energy sector, but
progress has been mixed so far. Both vertical
diversification in oil, gas, and petrochemical
sectors, as well as horizontal diversification beyond
these sectors, should be pursued, with an emphasison technological upgrades and competitiveness(Cherif, Hasanov, and Zhu 2016; Gill et al. 2014;
World Bank 2016c).
Education and inequality
Structural reforms that improve education will
have substantial long-term impacts not only on
potential growth, and thus on poverty reduction,
but also on shared prosperity. In the next two
decades, new cohorts of workers from EMDEs
will enter the global workforce with better skills
from more education (Figure 1.27). As the supplyof skilled workers rises in EMDEs, an expected
shift in the skill composition of the global labor

42

CHAPTER 1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

force
will have important consequences on global
and within-country income inequality.

that
job creation keeps pace to absorb the rising
supply of skilled workers across countries.

The number of skilled workers in global labormarkets is likely to rise from 1.66 billion in 2011
to 2.22 billion by the middle of this century—anincrease of about 33 percent (Ahmed et al. 2017).
Importantly, EMDEs will be wholly responsible
for this increase, since the absolute number ofskilled workers in advanced economies will bedeclining due to population aging. This meansthat the ratio of skilled workers from advanced
economies to those from EMDEs will fall fromone-to-two to one-to-three by 2030.

Although within-country inequality is expected torise in importance at the global level, the“education wave”—i.e., the expected increase in
the supply of skilled workers—will likely mitigate
increases in inequality in EMDEs, driven by
reductions in the wage gap between skilled andunskilled workers. The benefits of the education
wave are likely to be highest in Latin America andthe Caribbean, South Asia, and Sub-SaharanAfrica. Yet, it is critical that the expected
improvements in years of schooling in the labor
force of EMDEs be accompanied with better
learning outcomes, as new technologies may
disproportionally benefit more skilled workers.
More generally, improving learning outcomes in
EMDEs to increase productivity, employment,
earnings, and economic growth will require asystemic change in the educational approach andthe removal of political and technical barriers thatprevent a focus on learning (World Bank 2018).
With better skills from education, the promises of
reduced global inequality can also be realized(Special Focus 2).

Since better skills lead to higher income, this trend
is expected to help lower global income inequality,
largely reflecting income convergence among
countries amid a higher supply of skilled workers
in EMDEs—particularly in populous countries
such as China and India. Consequently, as theaverage income across countries becomes moreequal, the relative contribution of within-country
inequality to global inequality is expected to raise,continuing a trend observed in the last two
decades (Special Focus 2). Critically, this assumes

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 1

43

TABLE
1.2 List of emerging market and developing economies1
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%ROLYLD %RWVZDQD
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*KDQD *XDWHPDOD
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.D]DNKVWDQ .HQ\D
.RVRYR.XZDLW .\UJ\]5HSXEOLF
/DR3'5/LEHULD

0DGDJDVFDU
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0R]DPELTXH
0\DQPDU 
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=LPEDEZH
&RPPRGLW\LPSRUWHUV$IJKDQLVWDQ$QWLJXDDQG%DUEXGD%DKDPDV7KH
%DQJODGHVK%DUEDGRV%HODUXV%KXWDQ%RVQLDDQG+HU]HJRYLQD
%XOJDULD&DER9HUGH
&DPERGLD
&KLQD&RPRURV&URDWLD
'MLERXWL'RPLQLFD'RPLQLFDQ5HSXEOLF
(J\SW$UDE5HS
(O6DOYDGRU(ULWUHD)LML*HRUJLD
*UHQDGD+DLWL
+XQJDU\,QGLD-DPDLFD-RUGDQ.LULEDWL/HEDQRQ/HVRWKR
0DFHGRQLD)<5
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5RPDQLD
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6H\FKHOOHV6RORPRQ,VODQGV
6UL/DQND
6W.LWWVDQG1HYLV
6W/XFLD
6W9LQFHQWDQGWKH*UHQDGLQHV
6ZD]LODQG
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

Energy exporters.
1. Emerging market and developing economies (EMDEs) include all those that are not classified as advanced economies. Advanced economies include Australia; Austria; Belgium; Canada;
Cyprus; the Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Hong Kong SAR, China; Iceland; Ireland; Israel; Italy; Japan; the Republic of Korea; Latvia; Lithuania;
Luxembourg; Malta; Netherlands; New Zealand; Norway; Portugal; Singapore; the Slovak Republic; Slovenia; Spain; Sweden; Switzerland; the United Kingdom; and the United States.
2. An economy is defined as commodity exporter when, on average in 2012-14, either (i) total commodities exports accounted for 30 percent
or more of total goods exports or (ii) exports of any single commodity accounted for 20 percent or more of total goods exports. Economies for which these thresholds were met as a resultof re-exports were excluded. When data were not available, judgment was used. This taxonomy results in the classification of some well-diversified economies as importers, even if they
are exporters of certain commodities (e.g., Mexico).
3. Commodity importers are all EMDEs that are not classified as commodity exporters.
*

44

CHAPTER 1


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SPECIAL FOCUS 1
With the Benefit of Hindsight:
The Impact of the 2014-16 Oil Price Collapse

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018



SPECIAL FOCUS 1

51

With the Benefitof Hindsight:
The Impact of the 2014-16 Oil Price Collapse

The 2014-16 collapse in oil prices was one of the largest in modern history, but failed to provide an expected boost to global
growth and was a missed opportunity for reforms in a number of countries. The decline in oil prices was caused by a boom
and rapid efficiency gains in U.S. shale oil production, a diminished effect of geopolitical risks, the inability of OPEC toregulate global oil supply, and softening demand prospects. The short-term benefits of falling oil prices to global growth were
muted by several factors. These include the low responsiveness of activity in key oil-importing emerging markets, ongoing
economic rebalancing in China, and the dampening impact of a sharp contraction in energy investment and a rapid
appreciation of the U.S. dollar on growth in the United States. Among oil-exporting countries, those with flexible exchange
rates, more diversified economies, and larger fiscal buffers fared better than others. Since 2014, many countries have taken
advantage of lower prices to reduce energy subsidies, and some have implemented broader structural reforms. Limited
prospects of a substantial recovery in oil prices from current levels could have lasting implications for potential growth in oil
exporters. This calls for accelerated reforms to increase diversification.

Note: This Special Focus was prepared by Marc Stocker, John
Baffes, and Dana Vorisek, with contributions from Carlos Arteta,
Raju Huidrom, Atsushi Kawamoto, Seong Tae Kim, Yirbehogre
Modeste Some, Shane S. Streifel, and Collette M. Wheeler. Research
assistance was provided by Anh Mai Bui and Xinghao Gong.

The 2014-16 plunge brought oil prices in line with other industrial
commodity prices, and closer to long-term historical averages. It followed amounting supply glut, supported by surging U.S. shale oil output and laterby the recovery of production in Libya and the Islamic Republic of Iran.
A. Nominal oil and metals priceindexes

B. Real oil prices

Index, 100=Sept. 2010
200

US$/bbl140

Oil
Metals1970-2017 average

120

150

100

80

100

60
40

50

20

2015
2017

2010

2005

2000

1995

1990

1985

1980

1975

0

1970

2016
2017

2014

2012

2010

2008

2006

2004

2002

2000

0

C. World oil balance

D. Oil production, cumulative change
since December 2010

mb/d
2

mb/d
5
4
3
2
1
0
-1
-2
-3

0
-1

2017Q3

2017Q1

2016Q3

2016Q1

2015Q3

2015Q1

2014Q3

2014Q1

2013Q3

2013Q1

2012Q3

2012Q1-2

U.S. shale
Iran, Islamic Rep.
Libya
Net

2011Q1
2011Q3
2012Q1
2012Q3
2013Q1
2013Q3
2014Q1
2014Q3
2015Q1
2015Q3
2016Q1
2016Q3
2017Q1
2017Q3

1

2011Q3

Between mid-2014 and early 2016, the global
economy faced one of the largest oil-price shocks
in modern history. The 70 percent price drop overthat period was one of the three largest declines
since World War II, and the most persistent since
the supply-driven collapse of 1986. The decline—
triggered by a combination of surging U.S. shale
oil production, receding geopolitical risks
involving some key producers, shifts in policies by
the Organization of Petroleum ExportingCountries (OPEC), and weakening global growthprospects—brought oil prices in line with otherindustrial commodities and ended a prolonged
period of historically elevated prices that started in2003 (Figure SF1.1). International prices haverebounded since their early 2016 trough, reachingnearly $60 per barrel at the end of 2017, in partdue to prospects of strengthening demand andextensions of production cuts agreed by OPEC
and non-OPEC producers. In constant U.S. dollar
terms, oil prices are still somewhat above theirlong-term (1970–2017) historical average. The oil
price decline followed a broad-based commodity
price boom that started in the early 2000s andlasted more than a decade. The boom, which

FIGURE SF1.1 The oil price plunge of 2014-16
in perspective

2011Q1Introduction

Sources: Energy Information Administration, International Energy Agency, World Bank.
A. Last observation is November 2017.
B. Real oil prices are calculated as the nominal price deflated by the international manufacturers unit
value index, in which 100=2010. World Bank crude oil average. Last observation is November 2017.
C. Oil supply balance is the difference between global oil production and consumption, in million
barrels per day (mb/d). Last observation is 2017Q3.
D. Last observation is 2017Q3.

52

SPECIAL FOCUS 1

unfolded
after two decades of relatively low and
stable prices, was mainly driven by surging
demand prospects from emerging market anddeveloping economies (EMDEs), especiallyChina.1
The individual factors contributing to the oil priceplunge have been extensively analyzed, but theirrespective roles remain subject to debate.
Moreover, lower oil prices did not provide theexpected boost to global activity, and policy
responses and outcomes have varied considerablyacross countries. To shed light on these issues, thisSpecial Focus addresses three questions:xWhat were the main drivers of the oil priceplunge from mid-2014 to early 2016?

x

How did the recent oil price collapse impact
the global economy?

xWhat was the policy response in oil exporters
and oil importers?

The Special Focus concludes with an assessment of
the outlook for oil prices and its implications foroil-exporting economies.2

What were the main driversof the oil price plunge?
Several key developments in the global oil market
occurred prior to and during the plunge in pricesthat began in mid-2014: A growing role of the
U.S. shale oil industry as the marginal costproducer, a shift in OPEC policy, a reassessmentof geopolitical risks, and deteriorating global
growth prospects. Although supply factors appear
to have been the dominant force in the sudden
price collapse in 2014, weakening demand
1 China’s share of global oil consumption increased from 6 percent
in 2000 to 12 percent in 2014. The increase in China’s metal andcoal consumption share was even larger: increasing from less than 10
percent to almost 50 percent of global consumption during the same
period.
2 A country is classified as an oil exporter when, on average in2012-14, exports of crude oil accounted for 20 percent or more of
total exports. Countries for which this threshold is met as a result of
re-exports are excluded. When data are not available, judgment isused. The list of oil-exporting emerging market and developing economies is presented in Annex Table SF1.1.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

prospects
were also an important contributor,
particularly in 2015–16. The latter could partly
explain why the oil price plunge failed to provide
the anticipated boost to global activity.
U.S. shale oil production
A surge in U.S. shale oil production was one of themain drivers of the global oil supply glut in the
period leading up to the price collapse in thesecond half of 2014. While U.S. shale oil
represents less than 6 percent of world oil output,
it accounted for nearly half of the growth in global
oil production from 2010 to 2014. This rapid
expansion was initially underestimated, as
reflected in repeated upward revisions to theoutlook for U.S. oil production by theInternational Energy Agency (IEA).3 It was also
overshadowed by a series of supply disruptions in
the Middle East, which held back global oil
output. These disruptions included conflict in
Libya, the impact of sanctions on the Islamic
Republic of Iran, and fears of supply outages in
Iraq. Concurrent with the dissipation of some ofthese geopolitical concerns during 2014, shale oil
production continued to grow rapidly, reaching apeak of more than 5 million barrels per day(mb/d) in late 2014. That year, gains in U.S. oil
production alone exceeded those of global oil
demand.
The technology to extract natural gas and oil fromshale formations (hydraulic fracturing andhorizontal drilling) has existed for decades, but its
application became widespread in the oil sector
only in the late 2000s, as oil prices peaked (Wangand Krupnick 2013). Such an endogenous supply
response to elevated oil prices was observed in thepast. In particular, during the early 1980s, highprices led to a similar expansion of oil extraction
from Alaska, Mexico, and the North Sea, which
contributed to a subsequent supply glut and pricecollapse in 1986. During the recent oil priceplunge, however, shale technology proved more
flexible and resilient (Bjørnland, Nordvik, andRohrer 2017). Production from existing U.S. shale
oil wells was sustained during the price collapse
3 From a total of 72 updates, IEA undertook 66 upward revisions to
U.S. production over that period, implying that the organization wasunderestimating the importance of U.S. shale.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

B. Shale oil well productivity

US$/bbl150

b/d per well
1,800

0

0

2007

2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017

C. Average wellhead break-even oil
price

D. Global shale oil resource
assessments

US$/bbl90

Billion barrels
United States
RussiaChina
Argentina
Libya
United Arab Emirates
Chad
Australia
Venezuela
Mexico

80
70
60

50
40

Range
Average U.S. shale

30

2017Q1

2016Q3

2016Q1

2015Q3

2015Q1

2014Q3

2014Q1

2013Q3

20

0

20

40

60

80

E. Brent oil price forecasts around
OPEC decision in November 2014

F. Brent oil price forecasts around
OPEC decision in December 2016

US$/bbl110

US$/bblBefore Nov. 14 announcement
After Nov. 14 announcement

Before Dec. 16 announcement
After Dec. 16 announcement

68

99
2017
88

70

2018

300

25

2017

300

2016

600

50

2015

900

600

75

2014

1,200

900

2013

1,200

100

BakkenEagle Ford
Permian

2012

1,500

2011

1,500

125

2010

Rig count
1,800

2009

Oil price
U.S. oil rig count (RHS)2008

A. U.S. oil rig count and oil prices

2018

2016

2020

66

2019

64

77

62

66

60

55

58

2014-15

2014-15

2014-15

2018

Jun
Aug
Oct
Dec
Feb
Apr
Jun
Aug
Oct
Dec
Feb
Apr
Jun
Aug
Oct
Dec
Feb
Apr

The U.S. shale oil industry is likely to remain themarginal cost producer in coming years, and thus
will continue to cap global oil prices (IEA 2017).
Even if oil prices were at $30/bbl, about 50 percent
of technically recoverable U.S. shale reserves wouldbe economically viable (Smith and Lee 2017). U.S.
shale oil reserves are assessed to be approximately
80 billion barrels (Bbbl), or around 20 percent of
global shale reserves (EIA 2015; BP 2017).
Technological improvements achieved in the
United States could also stimulate fasterproduction elsewhere. Shale reserves in the RussianFederation are close to those in the United States,
at an estimated 75 Bbbl. China and Argentina
follow, with 32 and 27 Bbbl of reserves,
respectively. Although shale oil reserves represent a
relatively small share of global reserves (around 10
percent), greater flexibility in production implies
that shale oil will continue to have a major effecton prices.

Advancement in U.S. shale oil played a significant role in the oil priceplunge from mid-2014 to early 2016. Oil drilling responded flexibly tochanges in oil prices, but production was resilient and efficiency gains
lowered break-even prices considerably in recent years. OPEC’s decision
to abandon price controls in November 2014 led to a significant drop in
current and expected oil prices. Prices also fell following OPEC’s
agreement to reinstate production targets amid ample supply, suggesting
OPEC’s diminishing capacity to stabilize prices.

2013Q1

The resilience of the shale oil industry to lower oil
prices was also echoed in rapid efficiency gains that
became increasingly evident after mid-2014.
Production costs fell considerably, dropping byaround 25 percent since the start of the oil pricedecline, reflecting the improved design of wells,
shorter drilling and completion times, and higher
initial production rates (Curtis 2015). Overall,efficiency gains and technological innovation
helped spur a near tripling of output per well in
the Eagle Ford and Bakken basins (Curtis 2016).
The combined impact of lower production costs
and efficiency gains caused average break-evenprices for the shale oil industry to fall from morethan $70 per barrel (bbl) in 2012 to less than $50/
bbl in 2016–17 (Rystad Energy 2017). The
resilience also reflects the decline in input costs(especially labor and rental equipment), as well as
the ability of shale producers to hedge their entire
production, as the shale oil cycle spans only a few
years (as opposed to conventional oil, which spans
decades).

53

FIGURE
SF1.2 U.S. shale oil activity and OPEC policy


Feb
Jun
Oct
Feb
Jun
Feb
Jun
Oct
Feb
Jun
Feb
Jun
Oct
Feb
Jun

from
mid-2014 to early 2016, but drilling fell
nearly 80 percent, about five times more than theestimated response of conventional oil drillingto price fluctuations (Newell and Prest 2017;
Anderson, Kellogg, and Salant forthcoming; Figure
SF1.2).

SPECIAL FOCUS 1

2016-172016-172016-17

Sources: Baker Hughes, Bloomberg, Consensus Economics, Energy Information Administration,
Rystad Energy NASWellCube Premium.
A. Weekly data. Last observation is December 15, 2017. WTI is West Texas Intermediate.
B. Shaded area indicates forecasts. Data for December 2017 are estimates.
C. Does not include test activity, where well was shut-down after completion. Last observation is
2017Q2.
D. Technically recoverable oil from low permeability tight formations, which includes shale.
E. Median Brent oil price forecasts reported from February 2014 through August 2015.
F. Median Brent oil price forecasts reported from June 2016 through May 2017. 

SPECIAL FOCUS 1

54

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE SF1.3
 Oil demand trends
Evidence of slowing demand prospects became visible around 2011, as
global industrial production growth and major industrial commodity prices
started trending down, and long-term projections for non-OECD oil
consumption continued to be downgraded. The declining oil intensity of
global GDP and increased uptake of technologies that consume less fossil
fuels were also underlying trends.
A. Commodity price indexes andindustrial production growth

B. Non-OECD oil consumption growthforecast, 5 years ahead

Percent, year-on-year
Index, 100=Sept. 2010
Oil
180
12
MetalsIndustrial production (RHS)
150
9
120
6
90
3
60
0
30

Percent
4.0
3.5

3.0
2.5
2.0

2017

Millions
2.5

China
United States
Rest of world

120
2.0

20

2015

2005

1995

1985

1975

1965

10

The role of demand conditions

1.0

60

0.5

40

0.0

2016

30

Amid mounting fiscal pressures and in view of
shale oil’s resilience, several OPEC members,
along with 10 non-OPEC countries led by Russia,
agreed to revert to production cuts to shore up
prices (World Bank 2016a). The initial six-monthagreement, which went into effect in January
2017, was subsequently extended twice: first to
March 2018 and then to December 2018.
Relatively high compliance with the agreed cuts,
especially by Saudi Arabia (the dominant OPEC
member) and Russia (the most important nonOPEC oil producer) contributed to somerebalancing of oil markets during 2017. However,actual and expected prices did not rise following
policy announcements, illustrating the reduced
ability of OPEC to influence market conditions as
U.S. shale oil has effectively become the new
marginal cost producer.5

1.5

2015

80

2012

40

2011

100

2010

50

2014

Index, 100=1965
Oil intensity of energy consumption
Oil intensity of GDP (RHS)60

D. Global stock of electric cars

2013

2016

2015

2014

2013

2012

2011

2010

C. Oil intensity of GDP and energy
consumption
Percent

Jul-07
Jul-08Dec-08Jun-09Jun-10Dec-10Jun-11
Oct-12
May-13Jun-14Feb-15
Feb-16Jun-17-30

strategy
throughout 2015 and 2016, was followedby a large and sustained decline in oil prices.4

Sources: BP Statistical Review of World Energy, International Energy Agency Global EV Outlook,
World Bank.
A. Oil and metals prices are nominal. Last observation is November 2017 for oil and metals andOctober 2017 for industrial production.
B. Last observation is June 2017.
C. Oil intensity of energy consumption measured as oil consumption in percent of total primary energy
consumption. Oil intensity of real GDP measured as oil consumption relative to real GDP. Lastobservation is 2016.
D. Electric car stock includes battery-electric vehicles and plug-in hybrid electric vehicles.

The role of OPEC policies
Despite the shale oil boom, oil prices remained
high over the period 2011–14, supported bysupply disruptions and heightened geopoliticalconcerns involving some key producers, as well as
expectations that OPEC members would continue
to adjust production to stabilize prices. Following
the beginning of the price collapse in mid-2014,
however, OPEC decided against reducing output,
as it had done in the past, including during theprice plunge in 2009. Instead, it announced in
November 2014 that its objective was to retain its
market share; a policy shift that reflected theincreasing clout of shale oil and reduced
cohesiveness within the cartel (Behar and Ritz
2016). That decision, which defined OPEC’s

Changing demand conditions for oil, including
short-run movements in market sentiment andexpectations, play an important role in driving oil
price fluctuations (Lippi and Nobili 2012; Alquist
and Coibion 2014; Jacks and Stürmer 2016). Thiswas particularly visible during the boom years
from 2003–08, when a positive reassessment ofdemand prospects from EMDEs contributed to anear doubling of the real price of oil (Baumeister
and Peersman 2013; Kilian and Hicks 2013).
That process reversed after the global financial
crisis, as long-term prospects for advanced
economies and, later, for EMDEs began to be
downgraded.
Evidence of the slowdown became more visiblearound 2011, as global industrial production,
goods trade, shipping freight, and major industrial
commodity prices all trended down (Figure SF1.3;
Kilian and Zhou 2017). Deteriorating growth

4 This was comparable to OPEC’s decision to reclaim market sharesin 1986, which contributed to a collapse in prices after unsuccessfulattempts to support prices through production cuts (McNally 2017).
5 OPEC’s reduced ability to influence the oil market is also
consistent with the lower price volatility experienced during and after
the 2014 collapse (World Bank 2015a; Baffes and Kshirsagar 2015).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

The oil price collapse: The relative
importance of supply and demand
While changes in underlying supply and demandconditions pre-dated the start of the oil priceplunge in mid-2014, a convergence of geopoliticalfactors triggered a sudden and abrupt pricerealignment, later amplified by OPEC’s policy
shift and signs of a further weakening of global
growth.

6 For example, in the context of identifying the sources of thedecline in CO2 emissions in the U.S. during 1997–2013, Feng et al.
(2015) concluded that the change in fuel mix and productivity
improvements played a key role in the lower use of oil.

Empirical results suggest that the initial drop in oil prices from mid-2014 toearly 2015 was primarily driven by supply factors. However, demand
factors played an increasing role during the second stage of the plunge
from mid-2015 to early 2016.
A. Oil price decomposition

B. Share of oil price decline driven by
supply shocks

Cumulative percent change from Jan. 1992
200
Demand150
SupplyOil price
100

Percent
60
50

40
30

50

20

0

10

-50

May 15 Jan 16

May 14 Jan 15

0

-100

Jun 08 Dec 08

A decline in the average oil intensity of global
GDP, which has nearly halved since the 1970s,
also explains an undercurrent of weakening longterm demand. By 2016, the level of oil consumption in advanced economies, which had begun tofall prior to the global financial crisis, was nearly 7
percent below its 2005 peak. Technologicalimprovements and substitution away from oil havebeen significant driving factors underlying theslowdown in oil consumption since 2005.6 In
non-OECD countries, technology and environmental policies have also started to influence crude
oil demand patterns. For example, China became
the world’s largest user of energy-efficient vehicles
in 2015, reflecting in part policies to reduce air
pollution (Ma, Fan, and Feng 2017). Electricvehicles continue to account for a low share of
global transportation, but could become an
important force affecting oil demand prospects
over time (Cherif, Hasanov, and Pande 2017).
From a long-term perspective, technologicalimprovements on the consumption side, alongwith policies to limit fossil fuel usage and increaseenergy efficiency, are likely to constrain demand
growth, thus preventing oil prices from reverting
to levels seen during the boom years (IEA 2017).

55

FIGURE
SF1.4 Oil supply and demand shock
decomposition

1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2017

prospects
for EMDEs led to a continued declinein oil consumption expectations for these
economies. Concerns about global growthprospects intensified during 2015 and early 2016,
amid signs of a simultaneous slowdown in China,
major commodity-exporting EMDEs, and theUnited States. In January 2016, oil prices reacheda 15-year low of $31/bbl.

SPECIAL FOCUS 1

Source: World Bank.
A. B. Based on the decomposition of oil price changes from a structural vector autoregressive (SVAR)
model including global industrial production, global oil production, oil and metals prices. The
identification scheme is comparable to that suggested in Caldara, Cavallo, and Iacoviello (2016),
putting restrictions on short-term oil supply and demand elasticities based on a survey of theliterature.
A. Last observation is October 2017.

To help disentangle the contribution of supply
and demand shocks around the 2014–16 collapse,
a Bayesian structural vector autoregressive model
was estimated (see Annex SF1.1 for a description).
The model explores interactions between
international oil prices; global oil output; andcommon demand indicators such as global
industrial production and metals prices, the latterof which co-move with oil prices in the presenceof demand-driven shocks.7
Results confirm that changing supply conditions
played a dominant role in triggering the initial oil
price decline from mid-2014 to early 2015,
explaining about 60 percent of the drop (Figure
SF1.4). These results are consistent with previous
analyses (Baffes et al. 2015; Arezki and Blanchard2015). The role of oil demand shocks, however,strengthened in the second half of 2015 and early
2016, when global activity showed signs ofdeceleration and metals prices continued to slide.
Around that period, changes in supply conditions
are estimated to have accounted for about 40
percent of the price drop. Various other indicators
7 The selected identification method uses a combination of sign
restrictions and bound estimates of short-term elasticities of oil
supply and oil demand (Baumeister and Hamilton 2015; Caldara,
Cavallo, and Iacoviello 2016).

SPECIAL FOCUS 1

56

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE SF1.5
 Global activity
In contrast with initial expectations, the oil price plunge was followed by aslowdown in global growth in 2015 and 2016. The disappointing pace of
global growth during those years was mostly accounted for by a failed
recovery in oil-importing EMDEs and advanced economies.
A. Growth by country groups

B. Contribution to global growthforecast errors

Percent
6

Percentage point
0.6
EMDE oil exporters
EMDE oil importers
0.4
Advanced economies
World
0.2

Start of year estimates

4

2

0.0
-0.2
2013
2014
2015
2016
2017

2013
2014
2015
2016
2017

World

2013
2014
2015
2016
2017

2013
2014
2015
2016
2017

0

-0.4

Advanced EMDE oil
economies importers

EMDE oilexporters

-0.6
2014

2015

2016

2017

Source: World Bank.
A. B. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights. Country
classification is presented in Annex Table SF1.1.
A. Purple diamonds correspond to growth forecasts at beginning of each calendar year from Global
Economic Prospects. Bars represent actual data up to 2016 and estimates for 2017.
B. Forecast errors computed as the difference between actual global growth and forecasts at the
beginning of each calendar year. Sample includes the 153 countries with forecast data available in2014.

used to proxy demand shifts in commodity
markets also point to downward demand pressureson oil prices (Kilian and Zhou 2017).

How did the recent oil pricecollapse impact the global
economy?
The plunge in oil prices that began in mid-2014
led to expectations of global growth windfalls(Baffes et al. 2015). Estimates produced at thetime suggested that a 50 percent supply-driven
decline in oil prices could lift global GDP byaround 0.8 percent over the medium term. Such aboost to global aggregate demand was expected toresult from a transfer of income and wealth fromoil-exporting economies, which tend to have ahigh aggregate savings rate, to oil-importing
economies, where the propensity to spend ishigher. And while lower oil prices were anticipatedto negatively impact investment in the oil
industry, this was expected to have been morethan offset by lower energy costs for consumers
and for energy-intensive sectors, includingtransportation, manufacturing, and agricultural
sectors.
Rather than lifting activity, however, the oil priceplunge was accompanied by a global slowdown(FigureSF1.5). Global growth moderated from
2.8 percent in 2014 and 2015, to a post-crisis lowof 2.4 percent in 2016, amid weakening global
trade, subdued capital flows to EMDEs, and broad-based weakness in commodity prices. A sudden
contraction in government spending, domestic
demand, and imports in oil-exporting economies
had some dampening effects, but the mostimportant factor behind disappointing global
growth during and after the oil price plunge was afailed recovery in oil-importing EMDEs andadvanced economies, particularly the UnitedStates. Growth disappointments among oil importers were partially reversed in 2017, as a broadbased cyclical recovery got underway (Chapter 1).
However, forecast downgrades continued among a
number of oil-exporting EMDEs. Overall, global
growth was overestimated by an average of 0.2
percentage point per year over the period 201417, with 40 percent explained by oil-exporting
EMDEs, 34 percent by oil-importing EMDEs,
and the remainder by advanced economies.
While the impact of low oil prices on growth inoil-importing EMDEs was less than expected,
lower oil prices have helped reduce vulnerabilities
in some of these countries, as reflected in
improved current account positions and lower
inflation. In turn, reduced vulnerabilities supported investor confidence and allowed monetary
policy authorities to regain some space for policy
easing (World Bank 2016b).
Impact on oil exporters
The oil price plunge from mid-2014 to early 2016
had broad-based and long-lasting effects on
economic activity in oil exporters. More than 70
percent of oil-exporting EMDEs registeredslowing growth in 2015 and 2016, with manyfacing a collapse in consumption (e.g., Nigeria,
Russia, the United Arab Emirates, República
Bolivariana de Venezuela) and investment (e.g.,
Angola, Russia, Venezuela; Figure SF1.6). Termsof-trade shocks can impact both actual andpotential output growth, particularly for oilexporting countries, which are generally lessdiversified than other commodity exporters(Aslam et al. 2016). Investment growth tends to
respond particularly strongly to a deterioration interms of trade, which can in turn negatively affectGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

In general, activity in oil exporters with floatingexchange rate regimes (e.g., Albania, Russia) and a
relatively high degree of economic diversification(e.g., Bahrain, Ghana, Malaysia, Qatar) recovered
more quickly from the fall in oil prices than thosewith fixed exchange rates and low diversification.8
Oil exporters with relatively large foreign reserves
and low historical inflation volatility also showed
greater resilience (Grigoli, Herman, and Swiston
2017; World Bank 2016b). High income
inequality and political instability also weakened

8 Although Qatar is primarily a liquefied natural gas (LNG)
exporter, it is classified here as an oil exporter because the natural gas
market is tightly connected to the crude oil market. From 2013 to2015, the years before and after the oil price collapse, oil prices(World Bank average) declined 51 percent, while LNG dropped 36
percent.

A. Share of oil-exporting EMDEs withincreasing/decreasing growth

B. Contribution to oil exporter growth

Share of oil-exporting EMDEs
Increasing
Unchanged
100

Percentage point
0.4

Decreasing

0.0

75

-0.4
50

Investment Consumption

2016

C. GDP levels for oil-exporting
EMDEs, by exchange rateclassification

D. GDP levels for oil-exporting
EMDEs, by export concentration

Index, 100=2014Q2
108
Hard and soft pegs

Index, 100=2014Q2
106 Above average concentration
Below average concentration
104

Floating

106

CanadaSaudi Arabia

Russia2015

Exports

NorwayNigeria

Saudi Arabia

Nigeria

2013
2014
2015
2016
2017

2013
2014
2015
2016
2017

CanadaRussia
GDP

2013
2014
2015
2016
2017

0

Norway

-0.8
25

104
102
102
100

100

98

98

2014Q2
2014Q3
2014Q4
2015Q1
2015Q2
2015Q3
2015Q4
2016Q1
2016Q2
2016Q3
2016Q4
2017Q1
2017Q2The effects of the price shock were also
exacerbated by idiosyncratic factors, including
sanctions on Russia, and conflict and geopoliticaltensions in the Middle East and North Africa
region. Headwinds in Russia and the Gulf
Cooperation Council (GCC) economies also had
adverse spillovers through reduced within-region
flows of trade, remittances, foreign direct
investment, and grants (World Bank 2015b,
2016d). Oil-exporting low-income countries (e.g.,Chad, South Sudan) were hit particularly hard, as
the effect of the oil price shock was exacerbated byconflict and deteriorating security conditions.
Delayed adjustments contributed to a depletion ofreserves and a sharp increase in public debt.

More than 70 percent of oil-exporting EMDEs registered slowing growth in2015 and 2016. The impact of the slowdown or recession in a few large
economies was particularly significant. Activity was generally more resilientin countries with more flexible exchange rate regimes and more diversified
economies.

2013
2014
2015
2016
2017

The oil price plunge quickly depleted oil revenues,
forcing abrupt cuts in government spending that
accentuated the slowdown in private sector activity
in many regions (World Bank 2016b, 2016c,
2017a; Danforth, Medas, and Salins 2016). Thiseffect was amplified in countries that entered themost recent oil price decline with weaker fiscal
positions and higher private sector debt than inprevious episodes. This contributed to a more
pronounced slowdown in aggregate demand,
particularly in investment, in the Middle East,
Sub-Saharan Africa, and Eastern Europe (BIS
2016; Chapter 2).

57

FIGURE
SF1.6 Activity in oil-exporting EMDEs


2014Q2
2014Q3
2014Q4
2015Q1
2015Q2
2015Q3
2015Q4
2016Q1
2016Q2
2016Q3
2016Q4
2017Q1
2017Q2

capitaldeepening and total factor productivity

growth (World Bank 2017a).

SPECIAL FOCUS 1

Sources: International Monetary Fund, United Nations Conference on Trade and Development(UNCTAD), World Bank.
A. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights. Increasing/decreasing growth are changes of at least 0.1 percentage point from the previous year. Countries witha slower pace of contraction from one year to the next are included in the increasing growth category.
B. Blue bars indicate EMDEs, red bars indicate advanced economies.
C. D. Sample includes 11 oil-exporting EMDEs (Albania, Bahrain, Bolivia, Colombia, Ecuador,
Kazakhstan, Malaysia, Nigeria, Qatar, Russia, and Saudi Arabia) for which quarterly GDP data isavailable, and excludes the Islamic Republic of Iran due to the large effect of sanctions. Figures show
median for the separate categories.
C. Exchange rate classification is based on the IMF’s Annual Report on Exchange Arrangements andExchange Restrictions database, in which countries are ranked 0 (no separate legal tender) to 10(free float). “Hard and soft pegs” refers to countries with a ranking of 1 to 6, while “floating” denotes
those with rankings of 7 to 10 and includes countries with horizontal bands and other managed
arrangements.
D. “Above average concentration” and “below average concentration” groups are defined by countries
above or below the sample average for export concentration in 2014. Concentration index measuresthe degree of product concentration, where values closer to 1 indicate a country’s exports are highly
concentrated on a few products. The average for the sample is 0.6, where 1 is the most concentrated.

the ability of oil-exporting economies to weather
low oil prices (Ianchovichina and Onder 2017).
Impact on oil importers
Contrary to expectations in 2014–15, the collapse
in world oil prices did not provide a boost to
activity among oil-importing economies, most ofwhich experienced slowing growth in 2015–16(Figure SF1.7). Growth disappointments wereconcentrated in EMDE oil importers, but anSPECIAL FOCUS 1

58

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE SF1.7
 Activity in oil-importing economies
A majority of advanced economies and oil-importing EMDEs experienced
slowing growth in 2015-16, driven by weakening investment and export
growth. In China, the positive effect was muted by a low share of oil in theenergy consumption mix. A sharp contraction in U.S. mining investment
dragged U.S. GDP growth down.
B. Share of oil-importing EMDEs withincreasing/decreasing growth

Share of advanced economies
Increasing
Unchanged
100

Share of oil-importing EMDEs
Increasing
Unchanged
100

0

0

GDP

Investment Consumption

Exports

GDP

2013
2014
2015
2016
2017

25

2013
2014
2015
2016
2017

25

2013
2014
2015
2016
2017

50

2013
2014
2015
2016
2017

50

2013
2014
2015
2016
2017

75

2013
2014
2015
2016
2017

75

Decreasing

2013
2014
2015
2016
2017

Decreasing

2013
2014
2015
2016
2017

A. Share of advanced economies withincreasing/decreasing growth

Investment Consumption

Exports

C. Consumption by fuel type, 2016

D. Contribution of mining investment
to U.S. GDP growth and U.S. industrial
production growth

Percent of
total energy
consumption
100

Percentage point contribution
0.3
Mining investment
Industrial production (RHS)
0.2

Oil
Coal
Nuclear energy

Natural gas
Hydroelectric
Renewables

80

Percent
12
8

2016
2017

China

India

South
AfricaTurkeyIndonesia

Advanced
economies

MexicoBrazil

2014

-12
2012

-8

-0.3
2010

-0.2
2008

-4

0

2006

20

2004

0

-0.1

40

2002

4

0.0

60

2000

0.1

Sources: BP Statistical Review, Federal Reserve Bank of St. Louis, World Bank.
A. B. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights. Increasing/decreasing growth are changes of at least 0.1 percentage point from the previous year. Countries witha slower pace of contraction from one year to the next are included in the increasing growth category.
C. Oil consumption is measured in million tonnes; other fuels in million tonnes of oil equivalent.
Renewables are based on gross generation from renewable sources including wind, geothermal,
solar, biomass, and waste, but not accounting for cross-border electricity supply.
D. Mining investment is real private fixed investment of nonresidential structures for mining
exploration, shafts, and wells. Data for 2017 are estimated.

unexpected slowdown in the United States in2016 also had an outsized effect. Adjustments
costs and uncertainty associated with large oil
price changes could have disrupted activity andinvestment in the short term (Hamilton 2011; Jo
2014). The most important factors behind thelack of a positive growth response to lower oil
prices are assessed to be the following:
China’s energy mix and rebalancing needs. Chinais the second-largest oil importer in the world, but
the share of oil in its overall energy consumption
is the lowest among G20 economies. Instead,
China relies heavily on coal, which accounted for
65 percent of energy consumption in 2016.
Regulated fuel costs and a low energy andtransportation
weight in consumer baskets alsomean that lower oil prices lead to limited real
income gains for consumers (World Bank 2015c).
Thus, the direct impact of the oil price plunge on
China was relatively modest. Meanwhile, a nearhalving of investment growth since 2012 has
weighed significantly on activity, and is estimatedto have accounted for 40 to 50 percent of theimport deceleration in 2014–15, with significant
knock-on effects for trading partners (Kang andLiao 2016). Since much of investment is resourceintensive, the impact of slower investment growth
was particularly significant for industrial
commodity prices and activity in commodityexporting EMDEs (World Bank 2016b;
Huidrom, Kose, and Ohnsorge 2017).
Lower sensitivity of other oil-importing EMDEs
to oil shocks. A number of recent empiricalstudies suggest that activity in oil-importing
EMDEs is less responsive to oil supply shocks thanthat in major advanced economies (Aastveit,
Bjørnland, and Thorsrud 2014; Caldara, Cavallo,and Iacoviello 2016). These studies explore several
factors, including different energy mixes,
consumption patterns, and energy price controlsthat limit the pass-through of world prices todomestic retail prices. Since many oil-importing
EMDEs took advantage of lower world prices toreduce energy subsidies, real income gains fromdeclining oil prices for consumers were more
limited, even if it created potential fiscal savings.
For non-oil commodity exporters, which represent
approximately half of oil-importing EMDEs,
adjustments to past terms-of-trade shocks
continued to weigh heavily on activity in 2014–16.9 Because investment has responded strongly todeteriorating terms of trade since 2011, bothactual and potential output growth may have been
negatively affected (World Bank 2017b). Someoil-importing EMDEs had also made significant
investments in new oil production capacity andbiofuels during the period of high oil prices,

9 A country is classified as “non-oil commodity exporter” when, on
average in 2012–14, either (i) total commodities exports accounted
for 30 percent or more of total exports; or (ii) exports of any single
commodity other than energy accounted for 20 percent or more of
total exports. The classification of EMDEs into energy exporters,
non-energy commodity exporters, and commodity importers ispresented in Annex Table SF1.1.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

includingin a number of low-income countries(World Bank 2015d). The reduced profitability ofthese projects as prices collapsed led to a sharp
contraction in capital expenditures in those
sectors. The fact that oil-importing EMDEs havebecome a major source of global growth andinternational spillovers could help explain the lackof a global stimulus effect from falling oil prices(Huidrom, Kose, and Ohnsorge 2017).
The impact of low oil prices on investment in the
United States. In the United States, the boost to
private consumption from lower oil prices waspartly offset by a sharper-than-expected
contraction in capital spending in the energy
sector (Baumeister and Kilian 2016). Mining
investment was cut in half in the two years that
followed the mid-2014 oil price plunge. Thisdragged private investment down, curtailing GDP
growth by 0.2 percentage point in both 2015 and2016. The collapse of energy investment reflectedboth the magnitude of oil price changes and thespecific nature of shale oil production, where
capital expenditures are more price elastic thanconventional production (Bjørnland, Nordvik,
and Rohrer 2017; Newell and Prest 2017). U.S.
business activity was also dampened by the sharp
appreciation of the U.S. dollar, which adversely
affected manufacturing exports and profits.
Monetary policy constraints in the Euro Area andJapan. Declining oil prices coincided with a drop
in long-term inflation expectations in a number ofadvanced economies, raising particular concerns
about persistent deflationary pressures in the EuroArea and Japan (Arteta et al. 2016). With these
economies experiencing interest rates close to theirlower bounds before the oil price collapse, reduced
inflation expectations could have resulted in
upward pressures on real interest rates. Central
banks in both the Euro Area and Japan responded
to these deflationary risks by pursuing moreaggressive monetary policy accommodation,
including negative interest rate policies andexpanded asset purchase programs. Coupled withmore supportive fiscal policies, these steps helped
to support an acceleration of activity. Hence, there
is little evidence that monetary policy constraints
were a key factor explaining the muted response of
global demand to lower oil prices since 2014.

SPECIAL FOCUS 1What
was the policy
response in oil exporters
and oil importers?

The sharp oil price decline elicited widely different
monetary, fiscal, and structural policy responses inoil-exporting and oil-importing economies.
Monetary policy and fiscal policy was nearly
universally tightened among oil-exporting
EMDEs, while the policy response in oil importers
was varied. Among oil-exporting EMDEs, thosewith flexible exchange rates or lower-than-averagereliance on oil for government revenue
experienced less abrupt deterioration in fiscal
balances than those with fixed exchange rates orhigher-than-average reliance on oil revenues. For
some major oil-exporting EMDEs, the oil priceplunge triggered structural reforms, including
subsidy reforms, which may in turn support thelongstanding need for economic diversification,
but more sustained efforts are required. Althoughsome oil-importing EMDEs took advantage of theperiod of depressed oil prices to reform energy
subsidies, there has been no noticeable
improvement in fiscal sustainability since 2014.
Policy response in oil exporters
Monetary policy
Many oil-exporting EMDEs experienced sharp
currency depreciation or rapid declines in foreignexchange reserves in 2014–16. Countries withfloating exchange rates were better able to stabilize
reserves, but generally suffered sharper initialdepreciations (Figure SF1.8). Monetary authorities in several countries intervened in foreignexchange markets to support their currencies (e.g.,
Angola, Azerbaijan, Bolivia, Kazakhstan, Malaysia,
Nigeria, Russia, Sudan, Turkmenistan), and many
hiked policy interest rates in response to rising
inflation (e.g., Angola, Azerbaijan, Colombia,
Ghana, Kazakhstan, Nigeria, Russia, Trinidad andTobago) or to support currency pegs (e.g.,Bahrain, Kuwait, the United Arab Emirates).
The erosion of foreign reserves contributed to thewelcome adoption of more flexible exchange rate
regimes in Azerbaijan, Nigeria, and Russia as part59

SPECIAL FOCUS 1

60

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE SF1.8
 Policy response in oil-exporting EMDEs
Many oil-exporting EMDEs experienced a rapid decline in foreignexchange reserves or sharp currency depreciation during 2015 and 2016;
countries with floating and pegged exchange rates were impacted
differently. Fiscal sustainability deteriorated more significantly during therecent oil price plunge than in past episodes, particularly in countries withhigh reliance on oil-related revenue and pegged exchange rates.

C. Fiscal sustainability gaps aroundoil price plunges
Past oil price plunges
Interquartile range
Latest plunge (t = 2014)

Percent of GDP
12
9

Mar-17

Sep-17

Sep-14Mar-14

Sep-17Mar-17

Sep-15

Sep-1670

Mar-1680

60

Mar-159070

Sep-14100

80Mar-1490

Sep-16

Index, 100=Jan. 2014, 3-month moving average
120
Hard and soft pegs
Floating
110Mar-16

Index, 100=Jan. 2014, 3-month moving average
110
Hard and soft pegs
Floating
100Mar-15

B. Nominal effective exchange rate,by exchange rate classification

Sep-15

A. Foreign exchange reserves,
by exchange rate classification

D. Change in overall fiscal balancein oil-exporting EMDE sub-groups
Percentage points
4

Interquartile range
Fiscal balance change

0
-4

6

-8

3

-12

0

-16

-3

-20

-6
t-3

t-2

t-1

t
Year

t+1

t+2

t+3

Above
averageBelowaverageOil revenue

PeggedFloating

Exchange rate regime

Sources: Bank for International Settlements, Haver Analytics, International Monetary Fund, WorldBank.
A. B. D. Exchange rate classification is based on the IMF’s Annual Report on Exchange
Arrangements and Exchange Restrictions database, in which countries are ranked 0 (no separate
legal tender) to 10 (free float). “Pegged” denotes countries ranked 1 to 6. “Floating” denotes countries
ranked 7 to 10.
A. Sample includes 9 oil-exporting EMDEs for which data is available (Albania, Angola, Bolivia,
Colombia, Kazakhstan, Malaysia, Nigeria, Qatar, and Russia). Last observation is October 2017.
B. Sample includes 7 oil-exporting EMDEs for which data is available (Algeria, Colombia, Malaysia,
Nigeria, Russia, Saudi Arabia, and the United Arab Emirates). Last observation is October 2017.
C. Sustainability gap is measured as the difference between the primary balance and the debtstabilizing primary balance, assuming historical median (1990–2016) interest rates and growth rates.
A negative gap indicates that government debt is on a rising trajectory; a positive gap indicatesgovernment debt is on a falling trajectory. Year t refers to the year of oil price plunges. Past oil priceplunges include collapses in global oil prices in 1991, 1998, 2001, and 2008 (World Bank 2015b). The
blue line represents the simple averages of 35 EMDE oil exporters in all episodes. The red line
indicates the latest plunge starting in 2014. Blue dashed lines are the interquartile range for the past
episodes.
D. Sample includes 27 oil-exporting EMDEs (excludes Albania, Bolivia, Brunei Darussalam, Ghana,
Libya, Myanmar, South Sudan, and Turkmenistan). Change in overall fiscal balance is measured from2014-16. Above average and below average oil revenue groups are defined by countries above or
below the sample average of oil revenues as a share of GDP based on 2014 data.

of the adjustment to low oil prices. In contrast,
GCC countries, with larger reserves before the oil
price decline, were able to use their reserves tomaintain their currency pegs, despite intermittent
periods of pressure on exchange rates (World Bank
2016c).
Central banks in oil-exporting EMDEs also took
steps to mitigate tightening banking sector

liquidity
as oil prices declined. In a small numberof countries where liquidity pressure was severe,the monetary authorities responded with unconventional measures, such as placing deposits
from sovereign wealth funds (SWFs; e.g.,
Azerbaijan) and pension funds (e.g., Kazakhstan)in commercial banks (Sommer et al. 2016).
In oil-exporting advanced economies, Canada and
Norway, inflation remained better anchored thanin EMDEs. In light of weakened growthprospects, monetary authorities in these countries
were able to pursue accommodative monetary
policy—each lowered policy rates two times
during 2015—as a complement to an easing fiscal
stance.
Fiscal policy
Many EMDE oil exporters, which rely heavily onhydrocarbon revenues, undertook severe fiscal
consolidation to realign spending with revenues
despite rising economic slack and diminishinglong-term growth prospects (e.g., Algeria, Angola,
Azerbaijan, Iraq, the Islamic Republic of Iran,
Kuwait, Nigeria, Russia, Saudi Arabia, the United
Arab Emirates; Danforth, Medas, and Salins2016). Compared with previous episodes ofdeclining oil prices, the impact on public financesin EMDE oil exporters was compounded byweaker initial fiscal positions. Fiscal sustainability
gaps continued to widen in 2015 and 2016, andgovernment debt ratios rose on average by 11.4
percentage points, compared with an average of
only 0.9 percentage point in past episodes (IMF
2017a; World Bank 2017a).
The need for fiscal adjustment was greater in oilexporting EMDEs that lacked the necessary
buffers (Husain et al. 2015; World Bank 2015d).
Oil-exporting EMDEs with higher reliance on oilrelated revenues faced a more pronounced
deterioration in fiscal balances than in thoseeconomies that managed to diversify government
revenue away from oil before 2014. Fiscal balances
also fared better in oil-exporting EMDEs withmore flexible exchange rate regimes, in part
because real exchange rate depreciation mitigatedrevenue declines and spurred needed adjustment
within the private sector.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018A number of oil exporters that had previously
built up buffers in SWFs—approximately 60
percent of oil-exporting EMDEs have at least one
SWF—appropriately used these resources toalleviate fiscal and exchange rate pressures (e.g.,
Algeria, Azerbaijan, Kazakhstan, Kuwait, Saudi
Arabia, the United Arab Emirates; World Bank
2015c). However, policymakers continue to facetradeoffs in their choices between drawing down
assets—in particular, from SWFs—and issuing
sovereign debt to finance budget deficits. Givenbenign global financing conditions, many havechosen to issue debt (Lopez-Martin, Leal, andMartinez 2016; Alberola-Ila et al. forthcoming).
Expenditure cuts have helped lower the fiscal
break-even oil price in most oil-exporting EMDEs
since 2015, although they remain higher than thecurrent oil price in some countries (e.g., Bahrain,
Saudi Arabia, Oman, Libya, the United ArabEmirates; Baffes et al. 2015; World Bank 2017b;
World Bank 2017c). Absent a stronger-thanexpected rebound in oil prices, further fiscal
reforms in many oil-exporting EMDEs will benecessary. Contingent liabilities associated withpotential bailouts of stated-owned oil companies
and banks also remain a source of fiscal
vulnerability, highlighting the importance ofstrengthening fiscal frameworks to mitigate suchrisks (Bova et al. 2016).
For some oil-exporting EMDEs, the fall in oil
prices has helped spur longer-term fiscal reforms,
including the introduction or planned
introduction of additional indirect taxes (Malaysia,
GCC countries). However, only one-fourth of oilexporting EMDEs have fiscal rules to act as buffers
to smooth the impact of oil price cycles on activity
and public finances. Moreover, some countries
failed to satisfy their existing fiscal rules (e.g.,
Nigeria), or subsequently modified them (e.g.,
Russia). This suggests the need for stronger fiscal
frameworks to help reduce the procyclicality offiscal policy and to establish a firmer foundation
for long-term fiscal sustainability (Mendes andPennings 2017). Oil price hedging and indexationof government bonds to oil prices could also help
reduce exposure to short-term fluctuations in oil
prices (Frankel 2017).

SPECIAL FOCUS 1In oil-exporting advanced economies (e.g., Canada
and Norway), the availability of fiscal buffers
provided space to loosen fiscal stances, asmeasured by changes in the structural budgetbalance (i.e., the budget balance adjusted for the
gap between actual and potential output levels).
For example, Norway’s fiscal rule of allowing up
to 4 percent of its SWF to be drawn down to fundfiscal deficits provided a countercyclical policy tool
to support growth.
Structural policy
Many oil-exporting EMDEs entered the 2014 oilprice bust still heavily reliant on oil (Figure
SF1.9). Hydrocarbon sector activity represented
more than one-third of GDP in a number ofcountries in Central Asia, Sub-Saharan Africa,
and, in particular, the Middle East. Oil
production represented the majority of
government revenue and exports in most oilexporting EMDEs in 2013. Cross-country studies
underscore that greater diversification of exports
and government revenues can bolster long-term
growth prospects and resilience to external shocks
and increase per-capita income growth (Lederman
and Maloney 2007; Hesse 2008; IMF 2016). In
oil-exporting EMDEs that have previously
successfully diversified, a combination of measures
to stimulate non-energy exports and broad reforms
to improve the business environment, education,and skills acquisition have been vital (e.g.,
Malaysia, Mexico; Callen et al. 2014). Efforts to
attract capital flows to non-resource sectors may
also encourage diversification.
Following the recent oil price collapse, several
large oil-exporting EMDEs have laid out mediumto long-term plans to reshape their economies byreducing reliance on the energy sector. For
instance, Saudi Arabia’s 2016 National
Transformation Program targets an increase in
non-oil commodity exports of 62 percent and non-oil government revenues of almost 225 percent by
2020 (Kingdom of Saudi Arabia 2016; WorldBank 2016d). A GCC-wide implementation of a 5
percent value-added tax, expected to become
effective in 2018, is intended to boost non-oil
revenues in these countries. Nigeria has identified
several sectors to promote greater diversification of

61

62

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FIGURE SF1.9
 Oil dependency in oil-exporting EMDEs
Oil exporters still have among the lowest levels of export diversification in
EMDEs, and oil tax revenues still account for a large share of government
revenues, particularly in the Middle East and North Africa. Despite subsidy
reforms, gasoline prices are still significantly lower in oil-exporting EMDEs
than in oil-importing ones.

B. Export concentration, 2016

A. Hydrocarbon sector activity in
oil-exporting EMDEs
Percent of GDP
45

2010

2014

2016

Index, 1=most concentrated
0.6

0.4

30

0.2

15

0
0
ECA

LAC

MNA

C. Hydrocarbon fiscal revenue
in oil-exporting countries
Percent of GDP
30

2014

EMDE oilexporters

SSA

EMDE oilimporters

Advanced
economies

D. Gasoline prices in EMDEs

2017

Index, 100=median advanced economies
160
140

25

120
20

100

15

80

10

60

ECA

LAC

MNA

SSA

EMDE oil importers

2017

2014

2014

0

2017

40

5

EMDE oil exporters

Sources: GlobalPetrolPrices, Haver Analytics, International Monetary Fund, United Nations
Conference on Trade and Development (UNCTAD), World Bank.
A. C. ECA = Europe and Central Asia, LAC = Latin America and the Caribbean, MNA = Middle Eastand North Africa, and SSA = Sub-Saharan Africa.
A. Regional aggregates are medians. Sample includes 19 oil-exporting EMDEs (Algeria, Angola,
Azerbaijan, Bahrain, Bolivia, Cameroon, Colombia, Ecuador, Ghana, the Islamic Republic of Iran,Kazakhstan, Kuwait, Nigeria, Oman, Qatar, Russia, Saudi Arabia, the United Arab Emirates, andVenezuela). For Angola and Venezuela, 2016 reflects 2015 data.
B. Orange diamonds denote the median and blue bars represent the interquartile range of individual
country groups. Sample includes 34 oil-exporting EMDEs (excludes South Sudan), 116 oil-importing
EMDEs, and 36 advanced economies. Concentration index measures the degree of productconcentration, where values closer to 1 indicate a country’s exports are highly concentrated on a few
products.
C. Regional aggregates are medians. Sample includes 24 oil-exporting EMDEs (Algeria, Angola,
Azerbaijan, Bahrain, Bolivia, Cameroon, Chad, Colombia, Republic of Congo, Ecuador, Equatorial
Guinea, Gabon, the Islamic Republic of Iran, Iraq, Kazakhstan, Kuwait, Nigeria, Oman, Qatar,
Russia, Saudi Arabia, Sudan, Trinidad and Tobago, and the United Arab Emirates).
D. Retail gasoline prices benchmarked against the median for advanced economies. Local prices
converted using 2014 exchange rates against the U.S. dollar. Sample includes 6 oil-exporting EMDEs(Bolivia, Colombia, Ghana, Kuwait, Malaysia, and Russia) and 45 oil-importing EMDEs. Lastobservation is November 2017.

export earnings and government revenues.10
Kazakhstan’s “100 Concrete Steps” program,
adopted in 2015, aims to diversify the economy
and improve competitiveness and transparency.

Nigeria aims to raise manufacturing sector growth to an averageof 8.5 percent in 2018–20 and agricultural sector growth to 6.9
percent in 2017–20 (Nigeria Ministry of Budget and National
Planning 2017).
10

Other
recent examples of efforts to encouragediversification include: reducing labor market
rigidities (e.g., Saudi Arabia, Oman), supporting
foreign investment (e.g., Saudi Arabia), expanding
infrastructure investment (e.g., Malaysia), andbroadly improving the business environment (e.g.,
Algeria, Bahrain, Brunei Darussalam, Kazakhstan,
Nigeria, the United Arab Emirates; Figure
SF1.10). Reforms have also been encouraged bymultilateral initiatives, including the WorldBank’s assistance to diversification efforts in somecountries (e.g., the Republic of Congo, Nigeria,
Qatar, and members of the Central African
Economic and Monetary Community). However,in some cases, the structural reform agenda has
faced legislative or implementation delays (e.g.,
Algeria, Kazakhstan) or has been scaled back as
fiscal pressures recede (e.g., privatization efforts in
Russia).
The sharp reduction in government revenues
among oil-exporting EMDEs has also led to anincreased emphasis on energy subsidy reforms.
These have been aimed at restoring fiscal space,discouraging wasteful energy consumption, andgenerating capacity for programs that better target
the poor (IMF 2017b). Between mid-2014 andend-2016, more than half of oil-exporting
EMDEs reformed energy subsidies, including ageographically diverse set of countries in the
Middle East and North Africa, Sub-SaharanAfrica, East Asia, Latin America, and Central
Asia.11 A number of oil exporters have reduced
utility subsidies as well. In some cases—for instance, in GCC countries—
subsidy reform was a significant break from pastpolicy (Krane and Hung 2016; World Bank
2017c). Yet the need for reforms in this area isunderscored by the fact that energy subsidies
represented an average of nearly 6 percent of
GDP as of 2014 among those oil-exporting
EMDEs where subsidy reform occurred between
2014 and 2016. Encouragingly, the design andimplementation of recently-implemented energy
11 Energy subsidies were reformed between mid-2014 and late2017 in Algeria, Bahrain, Cameroon, Ecuador, Gabon, Ghana, theIslamic Republic of Iran, Iraq, Kazakhstan, Kuwait, Malaysia,
Nigeria, Oman, Qatar, Saudi Arabia, Sudan, Trinidad and Tobago,
Turkmenistan, the United Arab Emirates, and Yemen.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Monetary policy
The plunge in oil prices, coupled with a weak
global growth environment, exacerbated theexisting disinflation trend in many oil-importing
EMDEs. In this context, several central banks cut
interest rates, or otherwise pursued accommodative monetary policy during 2015–16 (e.g.,
China, Croatia, Dominican Republic, Hungary,
India, Pakistan, Poland, Romania, Thailand). Yet,a number of non-oil commodity exporters raised
rates during part of the 2015–16 period because
they experienced significant currency depreciation,in part due to increasing concerns about external
vulnerability (e.g., Brazil, Kenya, Mongolia, Peru,
South Africa, Uganda, Ukraine, Zambia) andabove-target inflation (e.g., Brazil, Mexico, Peru,
Sri Lanka, Ukraine).
For major advanced economies, the fall in oil
prices put significant downward pressure on
inflation in 2015 and 2016. Several central banks
responded by further cutting policy rates or
expanding unconventional measures after reaching
the zero lower bound of policy rates. In particular,
the European Central Bank and Bank of Japan
introduced negative interest rate policies andexpanded their asset purchase programs.
Fiscal policy
Depressed oil prices were expected to provide oil
importers an opportunity to rebuild fiscal space,but fiscal positions instead worsened in a numberof these countries over the period 2014-16 (e.g.,
Argentina, Brazil, Turkey). In fact, cyclicallyadjusted fiscal balances of oil-importing EMDEs

Oil-exporting EMDEs have accelerated reforms to improve the businessenvironment since the oil price plunge, but more reforms will be needed to
improve the environment in many areas.
A. Number of reforms implemented
in oil-exporting EMDEs

B. Doing Business scoresin oil-exporting EMDEs

Number of reforms
70
60
50
40
30
20
10
0

Distance to frontier score (100=best)80
As of June 2014
As of June 2017
60
40
20
Insolvency

Trading

Contracts

Paying taxes

Getting credit

Investor protec.

Property registr.

Permits

Electricity

Starting business2016-17

2015-16

2014-152013-140

2012-132011-12

Policy response in oil importers

63

FIGURE
SF1.10 Reforms and Doing Business scores 2010-11subsidy
reforms has been superior to past efforts,
which were poorly phased and hampered byinsufficient communication to the public about
the rationale for reform (Clements et al. 2013;
Asamoah, Hanedar, and Shang 2017). In manycases, recent reforms have also helpfully included
measures to mitigate the impact on the poor andto strengthen social safety nets (e.g., Algeria,
Angola, Saudi Arabia). Available data suggests that
fuel price reforms since mid-2014 have succeededin raising gasoline and diesel prices in oilexporting EMDEs closer to international prices.

SPECIAL FOCUS 1

Source: World Bank Doing Business.
A. B. Sample includes 35 oil-exporting EMDEs.
B. The full names of the reform areas given on the x-axis are: making it easier to start a business,making it easier to deal with construction permits, making it easier to get electricity, making it easier toregister property, making it easier to get credit, making it easier to protect minority investors, making iteasier to pay taxes, making it easier to trade across borders, making it easier to enforce contracts,and making it easier to resolve insolvency.

deteriorated significantly, and government debt
ratios increased (Figure SF1.11). In some cases,
this reflected the effects of the broader decline incommodity prices, which reduced government
revenues and necessitated spending cuts (e.g.,
Mongolia, Mozambique, Namibia, Rwanda,
Ukraine). But even in countries where growth
remained relatively robust and output gaps
positive, governments missed the opportunity oflower energy prices to rebuild necessary fiscal
space (Kose et al. 2017).
For advanced economies, fiscal stances continued
to tighten in 2014-15, on average, but thenbecame slightly expansionary in 2016, amid
concerns about persistently weak growth andincreasingly constrained monetary policies (IMF
2017a). Lower oil prices implied smaller directfiscal windfalls in advanced economies comparedto EMDEs given the smaller prevalence ofsubsidies (Coady et al. 2017; IEA 2016).
Structural policy
Like oil-exporting EMDEs, oil-importing EMDEs
have taken advantage of declining oil prices tobegin dismantling energy subsidies, which tend tobenefit high-income earners, can crowd out public
investment, and encourage more intensive use offossil fuels (Arze del Granado, Coady, andGillingham 2012). Since mid-2014, a number of

64

SPECIAL FOCUS 1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE SF1.11
Policy response in oil-importing
economies
In oil-importing EMDEs, fiscal balances worsened as expenditure growth
outpaced revenues, despite the reduction or removal of energy subsidies
in some countries, while little progress was made in closing sustainability
gaps.
A. Change in structural fiscal balanceand growth

B. Sustainability gaps and fiscal
balances in oil-importing EMDEs

Percentage-point change
1.5Real GDP growth (RHS)
1.0

Percent of GDP
0.0

Sustainability gap

2017

2016

2015

-3.5

2014

Oil-importing
EMDEs

-3.0

2013

2013
2014
2015
2016
2017

Advanced
economies

-2.5

2017

2013
2014
2015
2016
2017

-1.5

-2.0

2016

-1.0

-1.5

2015

-0.5

-1.0

2014

0.0

-0.5

2013

0.5

Percent
8
6
4
2
0
-2
-4
-6
-8

What
were the main drivers of the price plungefrom mid-2014 to early 2016? Supply factors
appear to have played a predominant role,
particularly during the initial drop from mid-2014
to early 2015. Rising production and efficiency
gains in U.S. shale oil, diminishing supply
disruptions in the Middle East, and OPEC’s
decision in November 2014 to abandon pricecontrols amplified market perception of asignificant supply glut. However, disappointing
global growth, particularly from mid-2015 to early
2016, played a significant role as well,underpinning expectations of weakening demand.

Fiscal balance

Sources: International Monetary Fund, World Bank.
A. Structural balance is the fiscal balance adjusted for the economic cycle and for one-off effects.
Positive values indicate fiscal expansion, while negative values indicate contraction. Figure shows
GDP-weighted average in each country group. Sample includes 34 advanced-economy oil importersand 30 EMDE oil importers. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP
weights.
B. Sustainability gap is measured as the difference between the primary balance and the debtstabilizing primary balance, assuming historical average (1990 to 2016) interest rates and growth
rates. A negative gap indicates that government debt is on a rising trajectory; a positive gap indicatesgovernment debt is on a falling trajectory. Figure shows median for EMDE oil importers. Sample
includes 54 oil-importing EMDEs.

countries have implemented such reform (e.g.,
China, the Arab Republic of Egypt, Mexico,
Morocco, Tunisia), while others have raisedenergy taxes (e.g., China, Rwanda, South Africa,
Vietnam; IEA 2015; IMF 2016; Kojima 2016).
These steps have also included measures to avoid
energy subsidies re-emerging if oil prices
rebound—automatic pricing mechanisms or fullenergy price liberalization have been common(e.g., China, Côte d’Ivoire, India, Jordan,
Madagascar,
Mexico,Thailand,Ukraine;Asamoah, Hanedar, and Shang 2017; Beylis andCunha 2017).

Concluding remarks andimplications for the future
The plunge in oil prices from June 2014 toJanuary 2016, one of the three largest declines
since World War II, was accompanied by an
unexpected slowdown in global growth and a hostof policy responses in oil-exporting and oilimporting economies. The key takeaways are as
follows:

How did the recent oil price shock impact the
global economy? In contrast to earlier
expectations, the oil price plunge did not provide
a noticeable boost to global activity, and wasinstead accompanied by slowing growth from2014 to 2016. Despite a significant upturn in
2017, global growth was overestimated by anaverage of 0.2 percentage point per year over theperiod 2014-17, with 40 percent explained by oilexporting EMDEs, another 34 percent by oilimporting EMDEs, and the remainder byadvanced economies. In oil importers, the shortfall
reflected the low responsiveness of activity tofalling oil prices, ongoing economic rebalancing in
China, and the dampening impact of a sharp
contraction in U.S. energy investment and a rapid
appreciation of the U.S. dollar on growth in the
United States. Growth slowdowns in oil exporters
were sharper and longer-lasting than expected,
contributing to global growth shortfalls despite thelimited size of these economies.
What was the policy response in oil exporters andimporters? The collapse in oil prices provided a
new impetus to implement policy reforms in oilexporting EMDEs. Some have adopted more
flexible currency regimes, which appear to havebuffered the negative fiscal impact of falling oil
prices in countries where they were already inplace in 2014, while a large number of thesecountries have reduced or eliminated fiscally costly
energy subsidies. Some oil exporters have started
reducing or are planning to reduce their relianceon the energy sector. A number of oil-importing
EMDEs have also lowered energy subsidies.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Despite a rebound in oil prices in the second halfof 2017, which was supported by prospects ofstrengthening demand and production cuts by
OPEC and non-OPEC producers, numerous
factors limit upside risks to the outlook. First,
greater price responsiveness of shale comparedwith conventional oil should ensure a rapid
recovery in supply if upward price pressuresmaterialize. Second, on the demand front, an
accelerated uptake of more fuel-efficienttechnologies (e.g., electric vehicles and natural gaspowered commercial trucks), or new technologicalbreakthroughs (e.g., self-driving cars or fuel cell
technology) could considerably reduce oil
consumption prospects (Cherif, Hasanov, andPande 2017; International Energy Agency 2017).
Third, environmental concerns (driven bypollution or climate-change considerations) could
accelerate the use of policy tools that favorrenewable energy. However, oil supply shocks(notably geopolitically-driven disruptions) or
demand shocks (especially from large EMDEs,
such as India and China, where most demand
growth is expected to originate) could still trigger
sharp fluctuations in oil prices and overshooting inboth directions (Arezki et al. 2017).
The episode of falling oil prices in 2014-16
illustrates that large price changes can havedisruptive effects on global activity, including bydiscouraging investment in both energy and some65

FIGURE
SF1.12 Long-term outlook Long-term oil price forecasts have been considerably downgraded overthe last few years. The growth potential of oil-exporting EMDEs will likely
suffer from past contractions in activity and investment, making reforms
ever more urgent.
A. Oil price forecasts

B. EMDE potential growth response
to contraction events

US$/bbl120

Percentage points
0.0

100

80

-0.5

60
40

-1.0

2030

2025

2020

2015

2005

0

2010

Oil price
July 2014 forecast
July 2015 forecast
October 2017 forecast

20

2000

What
are long-term prospects for oil prices andfor oil-exporting EMDEs? Looking forward, oilprices are likely to remain markedly below levels
prevailing before 2014. In particular, shale oil has
altered long-term price expectations, increasing
global recoverable oil reserves, and turning anenergy scarcity challenge in the late 2000s into a“supply glut.” Forecasts in 2014, which envisioned
the Canadian oil sands as the world’s marginal oil
supplier, projected a nominal oil price of $100/bbl
in 2025 (Figure SF1.12). Yet technologicaladvancements and rising productivity in the U.S.
shale oil industry, coupled with efficiency
improvements on the consumption side andsubstitution away from oil, have brought the 2025
nominal oil forecast down to $65/bbl.

SPECIAL FOCUS 1-1.5
Year 1

Year 3

Year 5

Source: World Bank.
A. Forecasts from various editions of World Bank’s “Commodity Markets Outlook” report.
B. Contractions are defined as the years of negative output growth from the year after the output peakto output trough. Sample includes up to 45 EMDEs from 1989-2016. Dependent variable defined as
cumulative slowdown in potential growth after a contraction event. Bars show coefficient estimates,
while vertical lines show shock +/- 1.64 standard deviations (10 percent confidence bands). The
methodology is described in Chapter 3.

non-energy sectors. While persistently low oil
prices could help sustain aggregate demand in oilimporting economies, positive effects would likely
be limited in view of the recent experience. Low
oil prices could also deter oil conservation efforts
and incentives to develop renewable energies,
which carry significant economic opportunities,
including in low-income countries (World Bankand International Energy Agency 2015).
For oil exporters, the 2014–16 oil price plunge has
cast a long shadow, as significant declines ininvestment and output tend to lead to weakerpotential output growth in subsequent years. The
expectation that oil prices will remain markedly
lower than previously expected increases theurgency of reforms to restore growth and fiscal
sustainability, whereas efforts so far have been
mixed. The successful diversification experience ofsome energy producers (e.g., Malaysia, Mexico)
suggests the need for both vertical diversificationin oil, gas, and petrochemical sectors, as well as
horizontal diversification beyond these sectors,
with an emphasis on technological upgrades andcompetitiveness. Policy should help support
investment in human capital, entrepreneurship,and employment in the non-oil private sector.

66

SPECIAL FOCUS 1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

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 3RODQG
 5RPDQLD
 6HUELD 6H\FKHOOHV 6RORPRQ,VODQGV
 6RPDOLD 6UL/DQND
 6W.LWWVDQG1HYLV 6W/XFLD 6W9LQFHQWDQGWKH*UHQDGLQHV
 6ZD]LODQG
 6\ULDQ$UDE5HSXEOLF
 7KDLODQG 7XQLVLD 7XUNH\ 7XYDOX 9DQXDWX 9LHWQDP* Primarily natural gas exporter.
A country is classified as oil exporter when, on average in 2012–14, exports of crude oil and natural gas accounted for 20 percent or more of total exports. Countries for which this thresholdis met as a result of re-exports are excluded. Countries that are primarily exporters of natural gas are included in this category, as the price of natural gas is tightly connected to crude oil.
When data are not available, judgment is used.
2 A country is classified as non-oil commodity exporter when, on average in 2012–14, either (i) total commodities exports accounted for 30 percent or more of total exports; or (ii) exports ofany single commodity other than oil and gas accounted for 20 percent or more of total exports. Countries for which these thresholds are met as a result of re-exports are excluded. When data
are not available, judgment is used. This taxonomy results in the classification of some well-diversified economies as importers, even if they are exporters of certain commodities.
3 Commodity importers are EMDE economies that are not classified as commodity exporters.

1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018



SPECIAL FOCUS 1

 of supply and demand
ANNEX SF1.1 Decomposition
shocks to oil prices: Bayesian structural vector
autoregressive model approach

Oil supply and demand shocks are not observableand must be inferred from complex interactions
between oil price fluctuations and changes inselected demand and supply indicators. Suchstatistical inference relies on a set of structural
identification restrictions. This annex elaborates on
the Bayesian structural vector autoregressive(SVAR) approach used to distinguish supply anddemand shocks and assess their respective roles in
the 2014–16 oil price plunge.
The use of structural VAR models to identify shifts
in oil supply and demand curves was first
introduced by Kilian (2009) and then extended by
Kilian and Murphy (2012) and Baumeister andPeersman (2013). Their identification strategy was
based on the notion that a favorable supply shockshould lead to a combination of rising oil
production, higher economic activity, and lower
oil prices. In contrast, a favorable demand shockshould lead to an increase in economic activity
and oil production, and higher oil prices. In thiscontext, shocks are identified based on sign
restrictions, occasionally complemented by anassumption that the oil supply response to shortterm price movements is close to zero (Kilian andMurphy 2012). Further research undertaken by
Baumeister and Hamilton (2015) demonstrated
that some of these identification strategies can leadto implausible estimates of oil demand and supply
elasticities. Following Caldara, Cavallo, andIacoviello (2016), a more flexible approach wasselected, which complements sign restrictions on
the short-term supply and demand elasticities withprior ranges based on a survey of the literature.
The specification of the model is as follows:ൌሺሻǦͳ൅Hሺͳሻ ൌ ሾǡǡǡሿǯ denotes the vector of four
endogenous variables and includes global oil
production (q t), international oil prices (p to), global
industrial production (y t), and metals prices (p tm);
A and B (L) are coefficients matrices capturing
instantaneous and dynamic relationships of thesystem; and Ht is a vector of error terms. The firstand second equations of the system capture oil
supply and demand conditions, while the thirdand fourth equations capture global demandconditions proxied by global industrial production
and metals prices. The identification strategy
consists of imposing prior distributions that map
the parameters space of the matrix A to theirrespective empirical ranges, as follows:

The parameters Įs > 0 and Ⱦd < 0 capture shortterm supply and demand elasticities of oil,respectively. The elasticity of oil price with respect
to economic activity is captured by Ⱦy > 0. Onlychanges in oil quantity directly affectmanufacturing production through the parameterȾs > 0 , while changes in oil prices have an indirect
effect via their impact on oil quantity. The metals
price index (p tm) is a leading indicator capturing
global economic activity not accounted for byindustrial production (Kilian and Zhou 2017;
Baumeister and Kilian 2016; Alquist and Coibion
2014; Delle Chiaie, Ferrara, and Giannone 2016).
It is assumed that both oil prices and quantities
affect metals prices through the parameters Gs and
Gd. Industrial production is positively correlatedwith metals prices (Gy > 0). In the estimation, theprior distributions of Įs and Ⱦd are restricted to becentered at median values of 0.1 and -0.1. These
values were taken from a literature survey of 32
studies (including Baumeister and Peersman 2013;
Kilian 2009; Kilian and Murphy 2012, Asali
2011; Lin and Prince 2013). The model was
estimated based on monthly data over the period
1991–2017.
While the identification strategy is more flexible
and offers more plausible estimates of short term
oil supply and demand elasticities, results tend to
confirm the conclusions of earlier studies—
namely, that an oil price decline driven by afavorable supply shock should be expected to

67

68

SPECIAL FOCUS 1

supportglobal industrial production over time,
while a price decline resulting from a drop in
demand is associated with a subsequent slowdown
in global activity. The model also suggests thatdemand shocks played a major role in driving oil
price fluctuations during the 2000s, in line withfindings of Baumeister and Peersman (2013) andKilian and Hicks (2013). However, the relative
importance of supply factors was substantiallyhigher during the 2014-16 oil price plunge.

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71

CHAPTER 2REGIONALOUTLOOKS

Growth in the East Asia and Pacific (EAP) region strengthened marginally to 6.4 percent in 2017, 0.2
percentage point higher than expected, largely reflecting a significant improvement in the external environment.
Regional growth is projected to gradually slow to 6.2 percent in 2018, and to 6.1 percent on average in 201920, broadly in line with previous forecasts, with the structural slowdown in China outweighing a modest
further cyclical pickup in the rest of the region. Risks to the forecast have become more balanced, especiallybecause of the potential for further upside surprises to growth in advanced economies, but are still tilted on thedownside. Downside risks include rising geopolitical tensions, an abrupt tightening of global financing
conditions, increased global protectionism, and steeper-than-expected slowdowns in major economies, including
China. Highly leveraged economies and countries with high or rapidly rising fiscal deficits are particularly
vulnerable to financial and real disruptions.

Recent developments
Growth in the region is estimated to have pickedup slightly to 6.4 percent in 2017, 0.2 percentage
point above our June forecast, amid astrengthening expansion of global activity andtrade, and a recovery in commodity prices, against
the backdrop of benign financing conditions(Chapter 1; Table 2.1.1; Figure 2.1.1). The region
continued to be a major driver of global growth,
accounting for more than a third of it in 2017,
mostly because of China’s significant contribution. Growth in China inched up in 2017—a
deviation from the economy’s structural slowdown, related to softening in its fundamental
drivers (Box 2.1). Growth in the region excluding
China accelerated slightly to around its potential
rate, reflecting a cyclical recovery in large commodity exporters (e.g., Indonesia and Malaysia)
and Thailand (Box 2.1).
In China, economic activity continued to be
driven mainly by consumption. The strongerthan-expected growth in 2017 was mainly due toan acceleration in exports on the back of firming
global demand. This outweighed a rebound inimports stemming from solid domestic demand
Note: This section was prepared by Ekaterine Vashakmadze. Anh
Mai Bui and Jinxin Wu provided research assistance.

and production cuts in overcapacity sectors,
resulting in a positive contribution from net
exports to GDP growth (World Bank 2017a).
Domestic rebalancing continued, with consumption growing faster than investment and services
faster than industry (Figure 2.1.2). Despite someacceleration, consumer price inflation continued
to be below target. Despite regulatory tightening,credit growth continued to support economic
activity. Meanwhile, housing prices eased in
response to tighter policies targeting real estate
sector. Tighter capital controls contributed toreduced capital outflows, a reversal of the earlier
foreign reserve drawdown, and an appreciation of
the renminbi.
The modest acceleration of growth in the rest of
the region was broad-based. Strong domestic
demand was supported by improved confidence,accommodative policies, and a reversal of capitaloutflows. A recovery of commodity prices
supported activity in commodity exporters (Special Focus 1). The recovery in regional exports
stemmed from the upturn in global trade andmanufacturing, which in turn was encouraged bystronger capital spending in advanced economies
and a rebound of imports in China and several
other large EMDEs (Chapter 1). Regional headline inflation moved up, reflecting higher energy
prices, but core inflation rates remained moderate.
Among the highlights:

CHAPTER 2.1

76

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 2.1.1
 EAP: Recent developments
Growth remained robust in 2017 on solid domestic demand and firming
exports. Financial markets remained broadly stable and capital outflows
from the region (excluding China) reversed. Inflation across the region
picked up, but remained below central banks’ targets in China, Thailand,
and Vietnam. Real credit growth generally moderated on tighter regulations
and higher inflation, but remained high in China, the Philippines, andVietnam.

B. Goods exports volume growthCommodity
importers
ex. China

China

C. Sovereign bond spreads
Basis points
450

China
Malaysia
Vietnam

2017

2013
2014
2015-16
2017

Commodity
exporters

Exports

2016

2013
2014
2015-16
2017

China

2016

2013
2014
2015-162017

2003-08 average

Imports

Commodity
exporters

2017

Percentage points
12
10
8
6
4
2
0
-2

1990-2008 average

2017

Percent
12
10
8
6
4
2
0

2016

A. Output growthCommodity
importers ex.
China

D. EAP excluding China: Balance of
payments
Current accountNet capital flows
Change in reserves

Percent of GDP
4

Indonesia
Philippines

350

2
250
0

E. Inflation

2017

2016

2015

2014

2013

2012

Commodity
exporters

ThailandChina

2008-14 average

Philippines

VietnamThailand

China

Vietnam

Malaysia

Philippines

Commodity importers

Malaysia

0-3

Percent, year-on-year25
2015 2016 2017
20
15
10
5
0
Indonesia

Inflation target

3

Indonesia-2

F. Credit growth

Percent, year-on-year
92015
2016 2017
6

Commodity
exporters

Dec-17May-17Oct-16

Mar-16

Jan-15Aug-15Jun-14Apr-13

Nov-13

50

2011

150

Commodity importers

Sources: Central Bank News, Haver Analytics, International Monetary Fund, J.P. Morgan, WorldBank.
Notes: EAP = East Asia and Pacific. Commodity exporters include Indonesia, Lao PDR, Malaysia,
and Mongolia. Commodity importers ex. China include Cambodia, Philippines, Solomon Islands,
Thailand, Vanuatu, and Vietnam. GDP-weighted averages.
B. Data for 2017 are year to date. Horizontal lines indicate long-term averages. Long-term average is
2006-17 for China, and 2012-17 for others.
C. Measures the average spread of a country’s sovereign debt (as measured by J.P. Morgan’s
Emerging Markets Bond Index) over their equivalent maturity U.S. Treasury bond. Last observation is
December 18, 2017.
D. Data for 2017 reflect 2017Q3.
E. Average year-on-year growth. Inflation targets for 2017 are 3 percent in China and 5 percent in
Vietnam. The figure shows the mid-points of targeted ranges in Indonesia (3-5 percent), Philippines(2-4 percent), and Thailand (1-4 percent). For Malaysia, the mid-point of Bank Negara’s 2017 forecastof 3-4 percent is used. Data for 2017 are year to date.
F. Real private sector credit growth. Average year-on-year growth. Data for 2017 are year to date.

x Growth in commodity exporters was higher
than expected and within reach of its longterm rate. GDP accelerated sharply in
Malaysia, supported by increased private
sector spending and rising exports, and inched
up in Indonesia, due to stronger growth ininvestment and exports. Among smaller
commodity exporters, growth in Mongolia
began to recover from its 2016 low, helped bya rebound in private investment in the wakeof a new stabilization program backed byinternational financial institutions (IMF
2017a). Growth in Myanmar also rebounded,though by less than expected, amid policy
uncertainty. Exceptions to the broad acceleration included the Lao People’s Democratic
Republic, where growth slowed on weakertourism activity, stronger controls on government spending, moderating credit growth,and decelerating investment. More marked
slowdowns were noted in Papua New Guinea
and Timor-Leste, as these economies adjusted
to lower commodity prices, and policy uncertainty (World Bank 2017b; Table 2.1.2).
x More generally, stronger initial conditions andfundamentals helped some regional commodity exporters to recover from the commodity
price shock more quickly than others(Chapter 1, Special Focus 1). Key determinants of the speed of recovery in Indonesia
and Malaysia included ample macroeconomic
policy space, adequate reserve buffers, effective
policy frameworks such as flexible exchange
rate regimes, and diversified export bases (e.g.,Indonesia and Malaysia). In contrast,
adjustment to low commodity prices has
proven more protracted than initially expectedin some energy exporters (Special Focus 1).
Regional commodity exporters with sluggish
performance in 2017 include countries thatbegan to undertake belated policy adjustment(e.g., Timor-Leste).
x Aggregate growth in commodity importers, ataround 5 percent and near its potential rate,
was broadly in line with expectations, but
performance was mixed within the group.
Following several years of weakness, growth
picked up in Thailand on stronger domestic

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Trade flows recovered markedly across the region.
A significant pickup in import growth reflected
firming domestic demand, especially investment.
Export growth also rebounded amid firming
commodity prices, improved foreign demand, andstrengthening manufacturing activity encouragedby higher capital spending. The pickup in global
investment
andmanufacturing
growthcontributed to a recovery of regional exports inmachinery, electronics, and semiconductors.
Services trade also recovered in 2017, albeit at a
slower pace than goods trade, as the former isgenerally less affected by short-term inventory andproduction cycles (Chapter 1).

GDP growth in China inched up in 2017, with drivers of activity continuing
to shift away from largely state-led investment. Growth continued to becredit-intensive. Tighter regulations led to a significant slowdown of house
price growth in Tier 1 and 2 cities.
A. Output growth: Expenditurecomponents

B. Credit growth

Percentage points
14
12
10
8
6
4
2
0
-2

Percent
25

Consumption
Investment
Net exports

15
10
5
2017Q3

2017H1

2014-16

2011-13

2010

2017

2016

2014-150

2011-132010

Non-financial enterprises
Households
Nominal GDP

20

C. Housing prices

D. Balance of payments

Percent, year-on-year40

1st tier
2nd tier
3rd tier

Percent of GDP
830

Current accountNet capital flows
Change in reserves

4

20

0
10
-4

0

2017Q3

2017H1

2016H2

2016H1

2015H2

2015H1

Nov-17May-17

Nov-16May-16

Nov-15May-15

Nov-14May-14

2010-14-8-10

Nov-13

Investment in the region excluding China showedsigns of a cyclical upturn, driven mainly by theprivate sector. Although investment performance
was mixed across countries, it generally accelerated
in commodity exporters and in commodity
importers with improving cyclical positions (e.g.,
Fiji and Thailand). Among commodity exporters,
stronger investment growth reflected risingcommodity prices and reduced financing costs(e.g., Indonesia, Malaysia, Mongolia) and
improved business confidence (e.g., Malaysia andMongolia). Investment growth remained generally
solid among commodity importers—acceleratingin Thailand, reflecting improved business
confidence and increased public infrastructure
spending, and in Fiji, boosted by post-cyclone
reconstruction spending. In contrast, investment
growth declined from earlier record-high rates in
the Philippines, as front-loaded investment
spending eased.

77

FIGURE
2.1.2. China


Nov-12

demand, supported by improved consumer
and business confidence and accommodative
policies. A sharp recovery in exports after two
years of weakness also helped spur growth.
Growth in Vietnam accelerated, on the backof solid export growth. In Cambodia, stronger
growth in emerging manufacturing exports(e.g., auto parts, electrical appliances) androbust tourist revenues partly offset a slower
growth in garment exports. In the Philippines,
growth decelerated slightly, to a still-solid 6.7
percent, as the impact of election-related
spending in 2016 dissipated (World Bank
2017c).

May-13



EAST ASIA AND PACIFIC

Sources: Haver Analytics, World Bank.
A. Data for 2017 reflect 2017Q3.
C. The National Bureau of Statistics of China surveys house prices in 70 cities and divides them into
three tiers. The first tier includes Beijing, Guangzhou, Shanghai, and Shenzhen. The second tierincludes 31 provincial capital and sub-provincial cities. The second tier in this chart includes
Chengdu, Chongqing, Tianjin, Wuhan, and Xiamen. The third tier includes 35 other cities. The last
observation is November 2017. Horizontal lines indicate February 2011 to November 2017averages.

Regional financial markets remained stablethroughout the year. Bond spreads have generally
declined, particularly for commodity exporters
and investment grade borrowers, and net capitaloutflows from the region (excluding China) havereversed (Figure 2.1.1). The region has
experienced a substantial rise in portfolio andinternational bond issuance. Aggregate foreign
direct investment (FDI) inflows were stable, but
trends were mixed across countries. FDI flows toIndonesia, Malaysia, and Mongolia accelerated,
supported by a robust or improved outlook in
the wake of a modest rise in commodity prices
and lower financing costs. Most regional
currencies have generally appreciated in realeffective terms, except for the Philippine peso and
Lao kip, and regional stock markets have generally
strengthened.

CHAPTER 2.1

78

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 2.1.3
 EAP: Outlook and risks
Regional growth is projected to moderate slightly during the forecasthorizon. This reflects a gradual slowdown in China, which offsets a pickupof activity in the rest of the region led by a cyclical rebound in several
commodity exporters. Risks have become more balanced, but remain tilted
to the downside. Elevated domestic debt (e.g., China, Malaysia, Thailand)and sizable external financing needs (e.g., Indonesia, Mongolia) would
amplify the impact of external shocks. Regional potential growth is set to
decline over the next decade, as demographic tailwinds turn into
headwinds and capital accumulation slows.



A. Regional output growth
Percent
12

June 2017 forecast
1990-2008
08 averagaverage
2003-08 average

10

B. Output growth by groups
Percent
6.0

June 2017 forecast
1990-2008008 average
avera
2003-08
8 average

5.5

8

EAP ex. China

C. Total debt

Malaysia Thailand Indonesia

EMDEs

2019

2018

2017

2018-272013-17

2003-07

1998-20172018-27

CapitalPotential growthwth

2013-17

TFP
Labor

2003-07

Percent
10
8
6
4
2
0

1998-2017

2007
2015
2016
2017

2007
2015
2016
2017

Public debt
Household debt
Corporation debt
Peak

2007
2015
2016
2017

2007
2015
2016
2017

Commodity exporters Commodity importers
ex. China

D. Potential growth

Percent of GDP
280
240
200
160
120
80
40
0

China

2016

2019

2017

2018

2016

2019

2018

2017

2016

EAP

2019

4.0

0

2018

4.5

2

2016

4

2017

5.0

6

EAP

Sources: Bank for International Settlements; Haver Analytics; International Monetary Fund; Quarterly
External Debt Statistics, World Bank.
Note: EAP = East Asia and Pacific.
A. B. Commodity exporters include Indonesia, Lao PDR, Malaysia, and Mongolia. Commodity
importers ex. China include Cambodia, Philippines, Solomon Islands, Thailand, Vanuatu, andVietnam. Yellow diamonds correspond with the June 2017 edition of Global Economic Prospects.
Shaded areas indicate forecasts.
C. The highest debt-to-GDP ratio since 1995Q1. The peak is identified to have occurred in 1997Q4
in Thailand, 1998Q4 in Malaysia, 2001Q4 in Indonesia, and 2017Q2 in China. 2017 data reflect
2017Q2. Total debt comprises of credit to household and non-financial corporations and general
government debt (broad definition). For China, the sum of credit to household and non-financial
corporations is consistent with the People’s Bank of China Aggregate Financing to the Real Economy(stock) level. General government debt includes central and local government debt and social
security funds, but excludes public enterprises. Data presented in the chart is broadly consistent with
the IMF estimates of total debt (World Bank 2017a).
D. Potential growth estimates based on production function approach (Chapter 3).

Two decades after the Asian financial crisis, which
triggered a series of structural reforms, the region
has become more resilient with healthier financial
systems. This resilience was tested a decade later,by the global financial crisis and led to additional
reforms, especially in commodity-exporting economies (e.g., Indonesia, Malaysia; Special Focus 1;
World Bank 2016a, 2017a, 2017d). As a result,stronger fundamentals—including narrowing
domestic and external imbalances, and stronger
policy buffers amid solid growth—further im-

provedthe region’s ability to withstand externalheadwinds.
These improvements notwithstanding, somecountries in the region continue to facevulnerabilities in their financial sectors, with highlevels of debt (e.g., China, Lao PDR, Malaysia,
Mongolia, Thailand) and fast credit growth (e.g.,
China, the Philippines, and Vietnam). For
example, the stock of non-financial sector debt in
China reached 260 percent of GDP in 2017—
above levels observed at the peak of previous credit
cycles in other major EMDEs (BIS 2017; IMF
2017b; World Bank 2017e). Malaysia andMongolia have large external financing needs.
Limited policy buffers—including high or raisingfiscal deficits in some smaller economies (e.g., Lao
PDR and Vietnam) and among commodity
exporters following the plunge of commodity
prices (e.g., Mongolia and Papua New Guinea)—
is a concern, especially if they are compound withhigh stock of debt (e.g., Mongolia and Papua New
Guinea) (Kose et al. 2017, World Bank 2017a).

Outlook
Regional growth is projected to gradually slow to
6.2 percent in 2018 and 6.1 percent on average in
2019-20, broadly unchanged from June forecasts(Figure 2.1.3), with the continuing gradualstructural slowdown in China offsetting a cyclical
pickup in the rest of the region.
The region is expected to continue to be a major
driver of global growth and account for more thana third of it in 2017-20, mostly because of China’s
significant (30 percent) contribution. The outlook
is predicated on a modest continuing recovery ofcommodity prices, improved external demand,and moderately tighter but still-supportive global
financing conditions (Chapter 1).
x Growth in China is projected to slow from
6.8 percent in 2017 to 6.4 percent in 2018,
and 6.2 percent on average in 2019-20, as
rebalancing proceeds and credit growth
decelerates. Policy support is expected todiminish, as monetary policy remains tightand fiscal policy becomes less accommodative.
This outlook is predicated on continued

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

reforms, reaffirmed by China’s 19th Party
Congress, which are expected to lead tofurther reduction in excess capacity, gradual
unwinding of financial sector vulnerabilities,
and shift of growth drivers from capital
accumulation to total factor productivity(TFP). Growth in the rest of the region is
projected to accelerate marginally to 5.3
percent in 2018, led by a continued cyclicalrebound in commodity-exporters, and stayaround this level for the most part of theforecast horizon.

x Growth in majority of commodity exporters is
projected to accelerate, and negative output
gaps—the legacy of the weakness ofcommodity prices in the wake of the global
financial crisis—are expected to graduallyclose. Among the large commodity exporters,
growth is expected to accelerate in Indonesia,
as private consumption strengthens in linewith gains in real wages. Growth is projected
to remain strong at around 5 percent on
average in 2018-20 in Malaysia, despite somemoderation in investment and export growth.
Among smaller economies, a cyclical recovery
is expected to continue in Mongolia, and get
underway in Papua New Guinea and TimorLeste, as domestic headwinds graduallydissipate. Lao PDR is expected to maintain arapid pace of growth, led by the electricity
sector.
x Growth in commodity importers is projected
to remain slightly above 5 percent in on
average in 2018-20. In Thailand, growth isprojected to remain around 3.5 percent on
average in 2018-20 reflecting recovery inmerchandise exports and tourism (WorldBank 2017f). In Vietnam, growth will slightly
moderate to a still-strong 6.5 percent on
average in 2018-20, supported by robust
agricultural production and strong exportoriented manufacturing. The Philippines willcontinue to be the fastest-growing economy in
the Association of Southeast Asian Nations(ASEAN), despite some stabilization of
investment growth. Cambodia is expected tomaintain rapid expansion, supported by tradeand FDI inflows.

EAST ASIA AND PACIFIC

Beyondthe forecast horizon, regional potential
growth is anticipated to decelerate to under 6
percent in 2018-27, as demographic pressures in
China and other large economies (e.g., Thailand)
dampen labor supply and slow productivity
growth, and capital accumulation slows (Chapter
3; Box 2.1).

Risks
Risks to the regional forecasts have become morebalanced, but they continue to be tilted to thedownside. On the upside, stronger-than-expected
growth observed in 2017 in the largest advanced
economies and EMDEs could continue in thenear term. Amid diminishing crisis legacies inadvanced economies and the fading effect ofearlier terms-of-trade shocks in commodityexporting EMDEs, rising business confidence andfinancial market optimism could underpin astronger investment-led recovery in the short term.
More generally, a further strengthening ofinvestment in the largest advanced economies and
EMDEs could stimulate trade and have positive
spillover effects on activity across the region(Chapter 1, World Bank 2016b).
On the downside, there are three major risks to
the forecasts, which could be amplified by thevulnerabilities of some economies, such as elevateddomestic debt, large external financing needs, andlimited policy buffers.
Geopolitical tensions in the Korean peninsula
increased substantially in 2017. A rise in this andother geopolitical risks, especially those involving
large economies, could negatively affectconfidence and lead to bouts of risk aversion andfinancial stress across the region. The materialization of such risks could have very serious
effects on regional activity.
A faster-than-expected tightening of global
financing conditions, or a steeper-than-expected
slowdown in major economies, including China,
could exacerbate existing financial vulnerabilities
and set back regional growth. The shock could
propagate across the region through reduced
capital flows, heightened financial market
volatility, pressures on exchange rates and asset

79

80

CHAPTER 2.1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

prices,and increased risk premiums. A significant

disruption to China’s growth could have large
regional spillovers (Huidrom, Kose, and Ohnsorge
2017; World Bank 2016a).
Increased protectionist sentiment in some advanced economies, particularly the United States,and possible policy changes related to the United
Kingdom’s anticipated exit from the European
Union, continue to exacerbate uncertainty about
the future of established trading and investment
relationships. Trade restrictions in advanced
economies could disproportionately affect themore open economies in the region. Significant
disruption to China’s exports would undermine its
growth, with possible large adverse effects on theregion. Trade and investment-restricting measuresin the United States could trigger retaliatory

measures,possibly worsening the effect of protec
tionism on regional activity.
Domestic vulnerabilities, including high leverage
rates and high or rapidly rising fiscal deficits, could
amplify the impact of external shocks (World Bank
2015a, 2016b, 2016c, 2017a). Over the longer
term, a more pronounced slowdown in potential
output growth in both advanced economies and
EMDEs would make the global economy more
vulnerable to shocks and worsen prospects for
improved living standards (Chapters 1 and 3).
Slowing long-term growth in large economies—
particularly in advanced economies, and China,
which both have substantial trade, commodity,
and financial linkages with the EAP region—
would have important negative spillovers on theregion (World Bank 2015a, 2016b, 2016c).

TABLE 2.1.1 East Asia and Pacific forecast summary
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Notes: e = estimate; f = forecast. EMDE = emerging market and developing economy. World Bank forecasts are frequently updated based on new information and changing (global)
circumstances. Consequently, projections presented here may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any
given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars. Excludes American Samoa and Democratic People’s Republic of Korea.
2. Sub-region aggregate excludes American Samoa, Democratic People's Republic of Korea, Fiji, Kiribati, the Marshall Islands, the Federated States of Micronesia, Myanmar, Palau, Papua
New Guinea, Samoa, Timor-Leste, Tonga, and Tuvalu, for which data limitations prevent the forecasting of GDP components.
3. Exports and imports of goods and non-factor services (GNFS).
For additional information, please see www.worldbank.org/gep.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

EAST ASIA AND PACIFIC

1
TABLE
2.1.2 East Asia and Pacific country forecasts(Real GDP growth at market prices in percent, unless indicated otherwise)

81

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Notes: e = estimate; f = forecast. World Bank forecasts are frequently updated based on new information and changing (global) circumstances. Consequently, projections presented here
may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars. Excludes American Samoa and Democratic People’s Republic of Korea.
2. Non-oil GDP. Timor-Leste’s total GDP, including the oil economy, is roughly four times the non-oil economy. It is highly volatile, sensitive to changes in global oil prices and local
production levels.
For additional information, please see www.worldbank.org/gep.

CHAPTER 2.1

82

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.1.1 Potential growth in East Asia and Pacific

The East Asia and Pacific region’s potential growth rate has fallen in recent years to well below the high rates prior to the global
financial crisis and its longer-term average. Notwithstanding this decline, the 7 percent pace remains twice as high as the
emerging market and developing economy (EMDE) average. Growth rates in China and in the rest of the region are graduallyconverging.
The slowdown of reginal potential growth reflects a moderationof potential growth in China. In the rest of the
region, potential growth has been strengthening compared to its longer-term average, mainly reflecting a robust capital
accumulation. Policies to boost total factor productivity across the region could partly offset the diminishing returns from capitaland the effects of demographic trends in several major economies that dampen labor supply and slow productivity growth.

Introduction
Since the Asian financial crisis 20 years ago, growth in the
East Asia and Pacific (EAP) region has been twice as highas the EMDE median (Figure 2.1.1.1). However, theregion’s growth rate has slowed sharply, especially since theglobal financial crisis, reflecting both cyclical downturns
and a weakening of the region’s underlying rate ofpotential growth (Chapter 3).
Notably, China’s potential growth rate fell sharply fromaround 10 percent during 2003-07 to around 7-8 percent
during 2013-17, about 1.3 percentage points below its
longer-term (1998-2017) average. Following initial effort
to sustain actual growth above potential growth,
government-initiated policies that gradually brought actual
growth in line with the lower potential growth rate andshifted the impetus of growth from investment to
consumption. This prevented the opening of large output
gaps. However, and sizable financial vulnerabilities,
accumulated during the earlier period of rapid, creditfueled expansion, have yet to be addressed (World Bank
2016a, 2016d).
Elsewhere in the EAP region, potential growthstrengthened somewhat in 2013-17, although with wide
divergences among countries. The region excluding China
is now experiencing a cyclical upturn of growth toward its
trend level, led by the commodity exporters (e.g.,Indonesia, Malaysia, Mongolia) that were hit by sharply
lower world prices, and Thailand, which faced domestic
challenges.
Against this backdrop, this box examines deeper thefollowing questions:xHow has potential growth evolved in the region andwhat were its main drivers?

xWhat are the prospects for potential growth?

xWhat are the policy options to lift potential growth?

Note: This box was prepared by Ekaterine Vashakmadze. Anh Mai
Bui and Jinxin Wu provided research assistance.

This box suggests that China’s potential growth is expected
to be limited by the effects of demographic trends thatdampen labor supply and by diminishing returns from
capital, while the rest of the region continues to face thechallenge of boosting its relatively subdued total factor
productivity growth. The EAP region is expected toexperience a broad-based slowdown in potential growth toa (still-robust) rate of around 6 percent during the next
decade (2018-27). This box concludes that policy efforts
could help moderate the slowdown, support poverty
reduction, and even help several middle-income regional
economies to attain high-income status. As factor
accumulation is expected to slow, accelerating productivity
growth is the main path for many regional economies toachieve convergence with upper income economies.

Evolution of potential growth1
At around 7.2 percent in 2013-17, potential growth in the
EAP region was about twice as high as the average forother EMDEs, but still well below the rates achieved overthe past two decades (Figure 2.1.1.2). This weakeningreflected a slowdown of potential growth for China fromaround 10 percent prior to the global financial crisis toaround 7-8 percent.
In contrast, potential growth elsewhere in the EAP region
reached about 5 percent in 2013-17, about 0.7 percentage
point above the longer-term (1998-2017) average rate,
although rates varied considerably from country tocountry.
1 The remainder of this box refers to potential growth measuresderived using the production function approach, as described in Chapter
3. Although estimates of potential growth can vary depending on theunderlying methodology, other studies find results similar to thosedescribed here. For instance, Anand et al. (2014) report that China’s
trend growth appears to have peaked around 2006–07 at 11 percent andthen slowly declined to below 8 percent by 2013. By contrast, trend
growth for the ASEAN countries (e.g., Indonesia, Malaysia, thePhilippines, Thailand, and Vietnam) has been stable or marginallystronger. The ADB (2016) estimates potential growth at around 9
percent for China, and 3-5 percent for the ASEAN economies (e.g.,
Philippines, Indonesia, Malaysia, and Thailand). Bai and Zhang (2017),
Nabar and N’Diaye (2013), Maliszewski and Zhang (2015), OECD(2012a), and Perkins and Rawski (2008) have also confirmed theslowdown of potential growth in China.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

EAST ASIA AND PACIFIC

83


BOX
2.1.1 Potential growth in East Asia and Pacific (continued)


FIGURE 2.1.1.1 Regional actual and potential growth rates
Since the Asian financial crisis 20 years ago, growth in the EAP region has been twice as high as the EMDE median. Slowing
structural factors. Growth rates in China and in the regional GDP growth in recent years reflects both cyclical and longer-run
rest of the region are gradually converging.
A. Actual output growth

B. Potential output growth

C. Contribution to post-crisis actual
growth slowdown

Percent
12

Percent
10

Percent
12
10
8
6
4
2
0

EAP ex. China

8

8

6

6

2003-07

4

4

2

2
0

0
1998-2017 2003-07

2013-172018-20Growth

1998-2017 2003-07

2013-172018-27

Potential

China

Cycle

2013-1710

EAP

2003-07

Median2013-17

EAP

EAP ex. China

D. Estimates of potential output growth

E. Regional potential output growth bydifferent estimates

F. China potential output growth bydifferent estimates

Percent
12

Percent
12

Percent
12

10

10

10

8

8

6

6

2

4

4

0

2

2

8

2003-072013-1764Precrisis

Postcrisis
China

Precrisis

Postcrisis

EAP ex. China

02003-072013-170
Production
function

MVF

UVF

Expectations

Production
function

MVF

UVF

Expectations

Sources: World Bank, World Development Indicators, Penn World Tables, International Monetary Fund.
Note: EAP = East Asia and Pacific. EAP ex. China includes Indonesia, Mongolia, Philippines, and Thailand.
A. Blue bars show period averages of annual GDP-weighted averages of EAP countries. Red markers show median GDP-weighted averages of the six EMDE regions.
Vertical lines denote range of regional GDP-weighted averages.
B. C. D. Potential growth estimates based on production function approach.
C. Blue bars denote average actual growth over five-year period. Red bars denote contribution of potential growth to change in actual growth between the two five-year
periods; orange bars denote contribution of cyclical growth.
D. Pre-crisis denotes 2003-07 for World Bank (2018), 2000-07 for ADB (2016), 2003-07 for Anand et al. (2014), and 2006-07 for Barnett et al. (2015). Post-crisis denotes
2013-17 for World Bank (2018), 2008-14 for ADB (2016), 2011-13 for Anand et al. (2014), and 2013 for Barnett et al. (2015). Vertical lines denote range of potential
growth estimates in the four above sources. EAP ex. China in the World Bank sample includes Indonesia, Mongolia, Philippines, and Thailand. EAP ex. China in Anand etal. (2014) and the ADB (2016) papers include Indonesia, Malaysia, Philippines, and Thailand.
E. F. MVF stands for multivariate filter-based potential growth estimates; UVF stands for univariate filter-based potential growth estimates (specifically, theHodrick-Prescott filter); Expectations stands for potential growth proxied by five-year-ahead World Economic Outlook growth forecasts.

x

x

Potential growth accelerated in Malaysia to around 5
percent in 2013-17 (just above its longer-term
average), thanks to a series of comprehensive
structural reforms that offset the impact of a declining
workforce on labor supply (ADB 2016; BNM 2012
and 2015; IMF 2016a; Lian and Shahrier 2014;
Munoz et al. 2016).
In contrast, potential growth in Thailand weakened toaround 3.5 percent on average in 2013-17, close to
the long-term average, following a short-lived
acceleration to around 4 percent in 2003-07. Potential
growth in Thailand, which is the lowest in South East
Asia, was held back by unfavorable demographics anddomestic policy uncertainty that discouraged
investment, all of which weighed on TFP growth(ADB 2016; IMF 2016b).
x

Potential growth in Indonesia, the country most
severely affected by the Asian financial crisis,
strengthened to above 5 percent in 2013-17, thanks
to favorable demographics, robust investment growth
and reforms (Tabor 2015; IMF 2017c; OECD
2016a; World Bank 2015b).

x

Potential growth also accelerated in the Philippines toaround 5-6 percent in 2013-17—more than 1
percentage point above the longer-term average rate.

CHAPTER 2.1

84

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.1.1 Potential growth in East Asia and Pacific (continued)


FIGURE 2.1.1.2 Drivers of potential growth
Slowing regional potential growth, increasingly determined by China’s performance, was broad based and reflected accumulation offset weakening productivity growth in the weakness in all of its main drivers. Excluding China, rising capitalregion.

A. Potential output growth
Percent
10

EAPEAP ex. ChinaMedianB. Potential output growth decomposition

C. Investment growth

Percent
10

Percent
20

TFP
CapitalLabor
Potential growthh88EAP ex. ChinaMedian

15

6

4

6

EAP

10

2

1998-2017

2003-07

E. Education attainment

Percent
6

Percent
100

EAP ex. ChinaMedianEAP

2018-272013-1750-5EAP ex. China

D. Trend TFP growthEAP2003-072018-27

EAP

2013-17

1998-20170

2013-17

1998-20172

2003-070

4

1998-2017

2003-072013-17

F. Working age population growth

EAP ex. ChinaMedianPercent
4

EAP

EAP ex. ChinaMedian

80

4

2

60

2
40

0

0

20

-2

0

1998-2017

2003-072013-17-2
1998-2017

2003-072013-17

1998-2017

2003-072013-17

Sources: Haver Analytics, World Bank staff estimates, Penn World Tables, World Development Indicators, United Nations Educational, Scientific, and Cultural
Organization (UNESCO) Institute of Statistics.
Note: EAP = East Asia and Pacific.
A. C. -F. Yellow markers show median of the six EMDE regions.
B. Potential growth estimates based on production function approach (Chapter 3).
C. -F. Vertical bars denote range of averages for all EMDE regions.
E. The percentage of population ages 25 and over that attained or completed lower secondary education. EAP ex. China includes Indonesia, Malaysia, Mongolia,
Philippines, and Thailand.

More than a decade of policies aimed at shifting
growth from consumption to investment resulted in astrong capital accumulation, supported by favorable
demographics.
x

x


Potential growth in Cambodia, Lao PDR, andVietnam, three economies closely linked to China,
remained high in 2013-17 (around 6 percent in
Vietnam and around 7 percent in Cambodia and Lao
PDR). But these rates are below longer-term averages
and reflect the limitations of growth driven by foreign
inflows (Cambodia), natural resources (Lao PDR),
and public spending (Vietnam) (Breu et al. 2012;
World Bank and Ministry of Planning andInvestment of Vietnam 2016).
Potential growth slowed in Myanmar, Papua New
Guinea, Timor-Leste, and Mongolia, owing to theirdependence on commodity exports, the collapse inglobal commodity prices, and weakness in majorcommodity-importing economies such as China.
x

Potential growth in Pacific Islands was weak andvolatile throughout the entire period reflecting
country-specific factors, but may have improved
recently amid a global growth recovery (World Bank
2017g).

Drivers of potential growth
The recent slowdown in regional potential growth, which
has been mostly attributable to China, reflected weakness
in all its fundamental drivers (Figure 2.1.1.2).
xContribution from regional working-age population
growth to regional potential growth fell from about

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

EAST ASIA AND PACIFIC


BOX
2.1.1 Potential growth in East Asia and Pacific (continued)





x

x

0.6 percentage points in 2003-2007 to around 0.3
percentage point in 2013-17. This reflects a sharp
slowdown of growth of China’s working-age
population since the late 2000s. Notwithstanding these regional demographic trends, many countries,
including Malaysia, the Philippines, and Cambodia,
continue to enjoy rising working-age populations.
Regional potential growth that had resulted fromrapid capital accumulation also moderated as theeffects of the recent investment surge, especially in
China faded. Although investment growth has eased
from stimulus-driven peaks in 2010-12 that produced
overcapacity in some economies, high investment
ratios across the region (e.g., about 43 percent of
GDP in China in 2013-17 on average) continued tosupport potential growth.
Regional TFP growth also slowed, as the productivity
boost following China’s World Trade Organization(WTO) accession in 2001 dissipated, the allocation ofcapital become less efficient during a prolonged
investment boom, and as economies increasingly
shifted their production from the manufacturingsection with stronger TFP growth to the services
sector with lower TFP growth (Nabar and N’Diaye
2013; Maliszewski and Zhang 2015).

There have been important cross-country differences in the
recent trends in potential growth within the EAP region.
x

x



China’s slowdown was broad-based. As its population
ages, the contribution from working-age population
growth has fallen from about 0.6 percentage points in
2003-07 to –0.1 in 2013-17. Despite a policy-guided
decline in investment, capital accumulation slowed,
but remained strong, accounting for about 40 percent
of potential growth. TFP growth declined, in partreflecting declining productivity of investment,
misallocation of resources, and narrowing room forcatchup productivity growth. But its contribution topotential growth remained higher than the EMDE
average (Chapter 3; Nabar and N’Diaye 2013; Anandet al. 2014).
In the rest of the region, potential growth continued
to rely heavily on factor accumulation, while TFP
growth remained subdued. Notably, diminishinglabor supply growth was more than offset by a higher
contribution from capital accumulation (Anand et al.
2014). Although productivity growth remained
subdued, it inched up in 2013-17, led by Indonesia,
the Philippines, and Vietnam. In contrast to the rest

of the group, Thailand experienced a broad-based
decline in potential growth. This follows several years
of weak confidence, investment, and FDI inflows, against the backdrop of sharp decline in labor supply
growth.

Labor supply
During the past five decades and until the late 2000s,
regional growth has been supported by a rapidly growing
working-age population (IMF 2017d; World Bank 2013a,
2015c). Many regional economies reaped a “demographic
dividend” as the number of workers grew faster than thenumber of dependents. However, overall, thesedemographic trends have since turned less favorable andare expected to deteriorate over the next decade.
The contribution from labor supply growth declined tojust 0.3 percentage point in 2013-17 from around 0.6
percentage point during the 2003-07 period. This was
especially stark in China, where the contribution declined
from 0.6 percentage point pre-crisis to –0.1 post-crisis,
and in Thailand where labor supply growth has also stalled
due to rapid aging.
Despite this overall regional trend, many regional
economies are still enjoying the demographic dividend
from rapid labor supply growth (e.g., Cambodia,
Indonesia, Malaysia, Myanmar, Lao PDR, and Papua New
Guinea, and the Philippines; World Bank 2015c). While
this supports potential growth, rapidly growing
populations in lower-income countries pose otherchallenges, including providing adequate public service
delivery.
Several factors besides demographic trends have affectedlabor supply within the EAP region. For example, labor
force participation rates (and productivity) have been
boosted by increases in secondary school completion ratesof 10 percentage points between 2013-17 and 2003-07,
tertiary enrollment rates by 14 percent, and life expectancy
by 2 years. The effect was particularly pronounced in
China and Malaysia, which have made large strides in
improving life expectancy and education over the past two
decades. In contrast, the region has not seen a major
improvement in its female labor force participation rate
between 2013-17 and 2003-07, with some exceptions(e.g., Malaysia).

Capital accumulation
Although rates of capital accumulation eased in most EAP
economies during 2013-17 compared with pre-crisis rates,
their contribution to potential growth remained robust.

85

CHAPTER 2.1

86

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.1.1 Potential growth in East Asia and Pacific (continued)


FIGURE 2.1.1.3 Income convergence
Over five decades and until the late 2000s, regional growth was supported by a rapidly growing working-age population.


expected
to deteriorate over the next decade. Malaysia and However, demographic trends are now less favorable and areChina could reach high-income status within a decade, even at expected slower potential growth rates. A combination ofpolicies to improve investment, education and health outcomes and labor market reforms could stem the expected decline inglobal potential growth over 2018-27.

Percent of U.S. per capita income level
2009

Years
80

100

1992

60
1986

60
40

60

40
20

2019

20

2010 2010

0

2013

Cambodia
Philippines

Years
100
80
60
40
20
0

Lao PDR
VietnamVietnam

China

Thailand

Malaysia

Germany

2060

2050

2040

2030

2020

2010

2000

1990

1980

1970

High-income

Korea, Rep.

U.S.

E. Baseline potential output growth

F. Potential output growth under reform
scenarios

Percent
9Percent
9

Baseline
Demographic trends
Other factors
acto

7

Labor market reforms
Education and health improvements
Fill investment
inv
needs
Baseline
Basel

7

5

EMDEs

EAP

EMDEs

Reformimpact2018-272013-17

Reformimpact2018-27

3
2013-172018-272013-172018-272013-17

U.S.

Contribution

Korea,
Rep.

2003-072013-17

2003-072013-17

Highincome

Contribution

Uppermiddleincome

2003-072013-17

2003-075
3

2013-17

1960

D. Years for per capita income toconverge to upper-middle-income levels

Japan

UnitedStates050

Thailand2013-17

70

Malaysia
Mongolia

2003-07

80

China
Indonesia

2013-1780

Late dividend
United States

2003-07

Early dividend
Post-dividend

C. Years for per capita income toconverge to higher income levels

2013-17

Percent of total population

B. Relative per capita income at peakworking-age population share

2003-07

A. Share of working-age population

EAP

Sources: United Nations World Population Prospects: 2017 Revision (medium-fertility scenario); World Bank staff estimates; International Monetary Fund, World Economic
Outlook.
A. Early dividend countries include Cambodia, Lao PDR, Indonesia, and Philippines. Late dividend countries include Malaysia and Vietnam. Post dividend countries
include China and Thailand. Post dividend is defined as a total fertility rate 30 years earlier below 2.1, and a shrinking working-age population share over the subsequent
15 years, or a shrinking absolute working-age population. Late dividend is defined as a total fertility rate 30 years earlier above 2.1, and a shrinking working-age
population share over the subsequent 15 years. Early dividend is defined as an increasing working-age population share over the subsequent 15 years.
B. Figure shows per capita income in percent of U.S. per capita income in the year when the working age population share peaked (years shown above the bars).
Only countries where working-age population shares reach peak before 2020. Red bars are East Asia Pacific countries.
C. D. Number of years to converge to per capita GDP of the specified country or income group in 2017. The years to converge for each country are calculated as theyears to close the difference between GDP per capita in 2017, assuming average potential growth in the period specified. Potential growth of China, Indonesia, Mongolia,
Philippines, and Thailand is from the production function approach. Potential growth of other countries is from the five-year expectation approach.
E. “Other factors” reflects declining population growth, trend improvements in human capital, and a slowdown in investment growth to output growth.
F. Policy scenarios are described in Annex 3.1.

x

In some ASEAN economies, such as Indonesia andthe Philippines, supportive monetary policy had
spurred investment and, hence, capital accumulationin the wake of the global financial crisis.

x

x

Rapid capital accumulation has also reflected
infrastructure upgrades. In the Philippines, improved
macroeconomic policy management and thegovernment’s public-private partnership initiative,
have boosted capital accumulation.

Investment in developing EAP was largely supported byhigh domestic saving rates and foreign investment. EAP
attracted half of global FDI during 2013-17, and FDI
stocks exceeded 50 percent of GDP in all economies.
Foreign capital played an important role in transfer of new

In Malaysia, capital accumulation has gathered
momentum with investments made under the
Economic Transformation Program (Munoz et al.
2016).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

EAST ASIA AND PACIFIC


BOX
2.1.1 Potential growth in East Asia and Pacific (continued)

technologies and knowhow, the development of humancapital, the integration into global markets, improved
competitiveness, and firms’ development and reorganization(Moura and Forte 2010; World Bank 2017h).
However, in smaller, heavily commodity-dependent
economies, including Mongolia and Papua New Guinea,
investment has contracted sharply during 2013-17 as FDI
for mining-sector projects declined.

TFP growth
In most EAP countries, potential TFP growth has eased orremained subdued post-crisis. This has been attributed totemporary and persistent factors (Asian Productivity
Organization (APO) 2016; Box 3.2; World Bank 2017h).2
Temporary factors include heightened policy uncertainty(e.g., Myanmar, Thailand) and investment weakness inseveral commodity-exporting economies severely affectedby the plunge in commodity prices (e.g., Mongolia, Papua
New Guinea). Persistent factors, which contributed to amoderation of TFP growth, include maturing global value
chains (e.g., China, Malaysia), a switch in information andcommunications technologies to consumer applications
from productivity-enhancing hardware and software (e.g.,
China), and slowing human capital accumulation andweak human capital investment in lower income
economies with limited fiscal space (e.g., Cambodia, Lao
PDR). Slowing productivity growth has also been
attributed to slowing factor reallocation (e.g., China,
Malaysia, Thailand). In contrast, TFP growth in several
economies (e.g., Indonesia and the Philippines) benefited
from sustained high investment rates amid politicalstability, and the potential for productivity increases fromfactor reallocation that is at quite early stages.
Maturing gains from factor reallocation. The reallocationof labor toward sectors enjoying higher or fasterproductivity growth—particularly from agriculture to
manufacturing, construction, and non-traditional
services—has been an important channel underpinning
productivity gains in the region and has slowed in somecountries (World Bank 2017h). This transformation has
stalled in Thailand, weakened significantly in China, andproceeded slowly in Malaysia since the Asian financial
crisis. In contrast, TFP has grown in Indonesia, Vietnam,
and the Philippines, where labor reallocation continues at
a rapid pace. In Vietnam, intersectoral reallocation
continues to account for approximately half of labor

For more detailed discussion please see the “World Bank East Asia
Regional Economic Update,” April 2017.
2



productivity growth, with no signs of a slowdown (WorldBank 2017h).
global supply chains. Productivity in the region, Maturingand especially in China, was boosted by rapid integration
into global and regional supply chains in the wake of
China’s accession to the World Trade Organization. The
maturing of these supply chains has meant that this surge
in productivity growth has waned (Constantinescu,
Mattoo, and Ruta 2017; Kummritz et al. 2017).
Other factors. Among the factors contributing to theregion’s subdued TFP are weak research and development(particularly in Indonesia, the Philippines, Thailand,
Vietnam), inadequate infrastructure (particularly inIndonesia and Thailand), low levels of economic
complexity (particularly in Indonesia, the Philippines, andVietnam), and difficulty in doing business and stringent
regulations in product markets (particularly in Malaysia
and Thailand) (Munoz et al. 2016; World Bank 2017h).
Finally, distortions in economic incentives leading tofactor misallocation (reflected in sectoral overcapacity, forexample) appear to be holding back productivity in China
and Vietnam (IMF 2017d).

Prospects for potential growth: What could
happen?
Potential growth within the EAP region is expected to easefurther by about 1 percentage point to around 6 percent
during 2018-27, reflecting a slowdown in China.3
This potential growth slowdown reflects ongoing
demographic trends that are dampening labor supply,
slowing productivity growth and putting the region at risksof becoming old before becoming rich (Figure 2.1.1.3;
IMF 2017d). The largest declines in the share of theworking-age population are expected in China. In
contrast, many countries, including Cambodia, Indonesia,
Lao PDR, Malaysia, Myanmar, and Papua New Guinea,
and the Philippines, will see a rise in working-age
populations and could enjoy a demographic dividend ifthey generate sufficient jobs (Bloom, Canning, and Fink
2010; IMF 2017d; World Bank 2015c).
A slowing pace of capital accumulation is projected toreduce EAP potential growth by about 0.4 percentage
point. The steepest slowdowns in capital accumulation are
3 The baseline scenario assumes broadly constant policies, long-term
investment-to-GDP ratios, and population dynamics as projected in the
UN Population Projections (Chapter 3).

87

88

CHAPTER 2.1

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.1.1 Potential growth in East Asia and Pacific (continued)


expected in China, where policy efforts to rein in credit
growth continue, and the Philippines, where a surge inpublic investment is expected to fade. In contrast, inThailand, investment is expected to recover from depressedlevels.
Stabilizing global value chains (GVC) and maturing
electronics technologies may also dampen productivity
growth. In manufacturing, greater vertical specialization
has been associated with higher labor productivity(Kummritz et al. 2017). The slower pace of GVC
expansion could slow productivity growth by removing
incentives to take advantage of a more efficientinternational division of labor and diffusion of technology.

Policy options to lift potential growth
Against this backdrop, the region faces the challenge ofcompleting China’s transition to a slower but moresustainable and balanced growth path, and of
implementing growth-enhancing reforms to achieve
convergence with higher income status. Meeting thesepriorities will require attending to the following policy
priorities:enterprises could ease pressure on fiscal resources (e.g.,
Thailand, Vietnam; World Bank 2016a).
Trade integration. Rising international trade has been animportant source of EAP growth. The region opened its
economies to trade and foreign direct investment,
exploiting competitive advantages in the manufacturingsector. Increased trade openness has brought strong
productivity gains, especially after the Asian financial crisis,
against the backdrop of solid economic institutions andimproved macroeconomic fundamentals (Havrylyshyn
1990; Trejos and Barboza 2015; Eris and Ulasan 2013).
However, protracted weakness in advanced economies,signs of weakened commitment to trade liberalization, andan increased risk of protectionism are threatening
prospects for a further expansion of trade. Steps that could
help counter this risk include:x

Improved resource allocation in China. Corporate sector
reform, more sustainable credit growth, and a stronger
intergovernmental fiscal system could help eliminate excess
industrial capacity and improve the allocation of resources(IMF 2017d; Jin and Rial 2016; World Bank 2017i).
Institutional reforms—such as better corporate
governance, enhanced auditing and accounting standards,
and a stronger regulatory framework—could promotecompetition and productivity growth.

Lowering non-tariff barriers would further expand
global and regional trade and improve theinternational allocation of investment, thereby
boosting productivity and competitiveness. Barriers toservices trade remain elevated for many countries of
the region (e.g., Indonesia, Malaysia, the Philippines,
Thailand). Restrictions on foreign control andownership, discretionary licensing, and limits on theoperations of foreign companies have significant
negative impacts on the delivery of services acrossborders. In addition, foreign entry restrictions in some
EAP countries are prohibitive for many professional
services such as legal, accounting, or engineering(World Bank 2016a).

x

Investment into technological and physical capital.
Several countries in the region continue to have sizableinfrastructure investment needs (Vashakmadze et al.
2017). Such investment can be financed by raising
additional revenue (e.g., Cambodia, Indonesia, Lao PDR,
the Philippines), reducing reliance on resource revenues(e.g., Indonesia, Malaysia, Mongolia, Papua New Guinea),
increasing the efficiency of public investment (Indonesia,
Lao PDR, Vietnam), rebalancing public expenditures
towards public investment and promoting public-private
cooperation (World Bank 2011, 2015b). Developing andimplementing rigorous and transparent processes for
project selection, appraisal, and procurement, could makepublic investment more efficient and could improve
operation and maintenance of assets (IMF 2017d).
Enhancing transparency and governance of state-owned

Regional partnerships and trade agreements, including
the ASEAN economic community and the proposed
Regional Comprehensive Economic Partnerships, will
help stimulate structural reforms and promote stable
income growth. These partnerships can also help toboost the region’s resilience, as they did during the
global financial crisis in 2008-09, facilitate reforms
and help to overcome constraints in services,
investment, competition, and small and medium
enterprise (SME) development (World Bank 2016a,
2016f).

Investment into human capital. High-quality education
would raise labor-force skills, and promote productivity
growth (World Bank 2014a, 2017j). Reforms that reducebarriers to female labor force participation could increase
participation rates and productivity (ADB 2015; Kinoshita
and Guo 2015).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

EAST ASIA AND PACIFIC


BOX
2.1.1 Potential growth in East Asia and Pacific (concluded)

Investment in technological capital and spurringinnovation. Productivity growth can also be boosted byspurring innovation and technology adaptation (Cirera
and Maloney 2017). This could be achieved throughhigher spending on research and development andattracting foreign direct investment, which can be an
important source of technology transfer.
xIn China and upper-middle-income economies, theeffectiveness of R&D spending could be improved,
and measures could be taken to raise productivity inthe services sectors, in particular by reducing barriers
to competition (World Bank and Development
Research Center of the State Council of the People’s
Republic of China 2012; Munoz et al. 2016; WorldBank 2016g).

x

Lower-income EAP countries may be able to capitalize
on rising FDI inflows by strengthening their capacity
to adopt new technology (World Bank 2014b,
2017h) The ASEAN-4 countries (e.g., Indonesia,
Malaysia, Thailand, and the Philippines) have begun
by strengthening the quality and flexibility ofdomestic education systems. In some economies,
better public infrastructure could foster connectivity
and spur innovation.

Urbanization. The region has the potential for continued,
rapid urban development (World Bank 2015d). Althoughmore than 450 million people moved to cities between
2000 and 2016, the share of people living in urban centersin the EAP region remains at 54 percent in 2016 (around50 percent excluding China), well below the advanced-

economy average (80.5 percent) in the majority of theregion’s economies.4 China’s current urbanization rate is
55.6 percent, with only 23.7 percent of China’s
population in urban agglomerations compared to 45.3 percent in the United States. With still a large share of the
EAP workforce engaged in agriculture, there is scope for
substantial productivity gains from moving workers tourban centers and employment in manufacturing andservices, particularly in Cambodia, Indonesia, thePhilippines, Timor-Leste, Thailand, and Vietnam (WorldBank 2016a). Measures to foster urbanization include
investment in infrastructure and social services, making
land more accessible on a fair and transparent basis,
encouraging facilities that support recent migrants, andcoordinating urban services across municipal boundaries.5
Business climate reforms. Improvements in the businessclimate and reductions in the cost of doing business would
also help (e.g., Cambodia, Fiji, Lao PDR, Myanmar,
Papua New Guinea, Timor-Leste, and the small PacificIslands; World Bank 2017k, 2017l). Cambodia, Lao
PDR, Myanmar, and Papua New Guinea rank low on the2016 Corruption Perception Index reported byTransparency International and on other governanceindicators.
Enhancedtransparency,
strengthened
accountability, and greater responsiveness of state
institutions to the needs of the private sector would bolster
investor confidence and invite productivity-enhancing
investment (Kummritz et al. 2017).

4 Urbanization rates are particularly low at only 13 percent in Papua
New Guinea, 21 percent in Cambodia, and around 35 percent in
Myanmar and Vietnam.
5 Felipe, Sotocinal, and Bayudan-Dacuycuy (2015), ADB (2016),
Creehan (2015), Bryson and Nelson (2016), World Bank and Development Research Center of the State Council, China (2014).



89

Growth in the Europe and Central Asia (ECA) region is estimated to have accelerated from 1.7 percent in2016 to 3.8 percent in 2017, up from 2.5 percent expected in June 2017. The recovery was broad-based andsupported by revitalized domestic demand and robust external demand. Growth is expected to moderate to 2.9
percent in 2018 and stabilize at 3 percent in 2019-20. Risks appear more balanced than in June 2017 but
continue to be tilted to the downside. Domestic fiscal, external, and financial sector vulnerabilities, as well as
policy uncertainty, amplify risks.

Recent developments
In 2017, the ECA region emerged from three
years of subpar growth, following the 2014-16 oilprice plunge (Special Focus 1). Growth isestimated to have strengthened to 3.8 percent, 1.3
percentage point higher than projected in June,
supported by a broad-based recovery across theregion. Growth strengthened in the commodityexporting eastern part of the region as well as thecommodity-importing western part (Figure 2.2.1).
The acceleration of activity was largely driven by
private consumption and investment, though inthe western part net exports also contributed.
The stabilization and partial rebound of oil prices
since early 2016 and supportive macroeconomic
policies buttressed the recovery of large energy
exporters in the eastern part of the region. Their
recovery was facilitated by easing inflation, rising
real incomes, improving financing conditions, andimproved
investor
confidence.
Growthmomentum in the western part of the region was
supported by tightening labor markets, as
manifested in declining unemployment rates androbust real wage growth, as well as improving
consumer confidence and investment bolstered byincreased absorption of EU structural funds (IMF
2017e). In addition, the pickup in growth in the

Note: The author of this section was Yoki Okawa. Research
assistance was provided by Shituo Sun.

advanced economies of Europe from late 2016provided tailwinds to the region’s economies
through increased export demand.
The two largest economies, the RussianFederation and Turkey, accounted for most of the
improvement in the region’s expansion in 2017.
However, growth picked up in most ECA
countries as well, with particularly notableadvances in Armenia, Belarus, Kazakhstan and
Poland. In contrast, growth weakened in the
Kyrgyz Republic, the former Yugoslav Republic ofMacedonia, Moldova, Serbia, Ukraine, andUzbekistan. Azerbaijan continued contracting,albeit at a slower pace.
In Russia, after a two-year recession, output
expanded by 1.7 percent in 2017, bolstered byhigher oil prices and supportive monetary policies
amid lower inflation (World Bank 2017n).
Floatation of the currency in 2014 helped cushion
the impact of the oil price plunge andinternational sanctions, as did financial sector
support. The decline in inflation from a 17
percent peak in early 2015 to below the 4 percent
target in late 2017 buttressed disposable income
and consumption growth. Stabilizing oil prices
supported private investment, primarily in energy
and transportation.
The significant rebound in Turkey’s growth lastyear—to 6.7 percent, from 3.2 percent in 2016—
was supported by fiscal stimulus aimed at expe-

CHAPTER 2.2

92

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 2.2.1
 ECA: Recent developments
Growth continued to rise in 2017 in a broad-based recovery. The
acceleration has been largely driven by private investment andconsumption, though exports have also contributed to commodity
importers. Labor markets have remained robust. Inflation in commodity
exporters is slowing as depreciation pressures ease, while inflation incommodity importers is gathering speed.

A. Growth

B. Growth decomposition

RussiaTurkeyOther commodity exporters
Other commodity importers
ECA

Percent
54Percent
8

Private cons.
Investment
Imports

Government cons.
Exports
GDP

4

3

2

0

1

-4

0

2014

2015

2016

2017

2017

2016

2015

2017

-2

2016

2015

-8

-1

Commodity exporters Commodity importers

C. Industrial production

D. Inflation

Percent, year-on-year
Commodity exporters
20
Commodity importers
16

Percent
8

Nov. 2014
Nov. 2016
Nov. 2017
Inflation target

7

6

12

5

8

4

2017Q3

2017Q2

E. Labor market (commodity
exporters)

14

0

12

-6

10

-12

8

2017

16

6

2015

2017

2015

2013

2011

0

Percent, year-on-year
Unemployment rate
8
Real wage growth (RHS)
7
6
5
4
3
2
1
0
-1

2013

12

4
2

Percent
18

2011

Percent, year-on-year
Unemployment rate
18
Real wage growth (RHS)2009

Commodity
importers

F. Labor market (commodity importers)

6

2007

Commodity
exporters

2009

Percent80

2007

2017Q1

2016Q4

2016Q3

2016Q2

2016Q1

2015Q4

1
2015Q3

2-4

2015Q230

2015Q1

4

Sources: Haver Analytics, national central banks, World Bank.
A. GDP-weighted averages. Other commodity exporters include Albania, Armenia, Azerbaijan,
Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. Other
commodity importers include Belarus, Bulgaria, Bosnia and Herzegovina, Croatia, Georgia, Hungary,
Kosovo, FYR Macedonia, Montenegro, Moldova, Poland, Romania, and Serbia.
B. GDP-weighted averages. Commodity exporters include Albania, Armenia, Azerbaijan, Kazakhstan,
the Kyrgyz Republic, Russia, Ukraine, and Uzbekistan. Commodity importers include Belarus,
Bulgaria, Croatia, Georgia, Hungary, FYR Macedonia, Moldova, Poland, Romania, and Turkey.
C. GDP-weighted averages. Commodity exporters include Albania, Armenia, Azerbaijan, Kazakhstan,
the Kyrgyz Republic, Russia, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. Commodity
importers include Belarus, Bulgaria, Bosnia and Herzegovina, Croatia, Georgia, Hungary, Kosovo,
Moldova, FYR Macedonia, Montenegro, Poland, Romania, Serbia, and Turkey.
D. Inflation and target are median in each sub-grouping. Commodity exporters include Albania,
Azerbaijan, Kazakhstan, the Kyrgyz Republic, Russia, Ukraine, and Armenia. Commodity importers
include Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Georgia, Hungary, Kosovo, FYR
Macedonia, Moldova, Poland, Romania, Serbia, and Turkey.
E. F. Averages among the country group. Real wage growth is year-on-year growth. Commodity
exporters include Kazakhstan, Russia, and Ukraine. Commodity importers include Bulgaria, Croatia,
Hungary, FYR Macedonia, Poland, Romania, Serbia, and Turkey.

ditingrecovery from the economic repercussions

of the 2016 failed coup attempt. Export growth
also rose on the back of strengthening demand
from the European Union and competitivenessgains from the 2016 currency depreciation.
In Kazakhstan, growth is estimated to haverebounded to 3.7 percent in 2017 from 1.1
percent in 2016. The recovery was boosted byincreased production at the Kashagan oil field(exempt from production cuts agreed by OPEC
and some non-OPEC producers) and supportive
macroeconomic policies. The latter included fiscal
stimulus (the authorities’ flagship “Nurly Zhol”
initiative,
which
providedfundingtoinfrastructure, SMEs, and housing), greater
exchange rate flexibility, and easing monetary
policy. Declining inflation helped support private
consumption (World Bank 2017m). Recovery in
Russia and Kazakhstan generated positive
spillovers for commodity-importing countries in
the region through remittances and exports (e.g.,
Armenia, Belarus, Georgia, Moldova).
The economy of Azerbaijan continued
contracting albeit at a slower pace of 1.4 percent
in 2017 compared to 3.1 percent in 2016. The
economy is weighed down by the legacies of the
2014-16 oil price plunge, including a damagedbanking sector, subdued credit growth, and lower
government revenue. Weak monetary policy
transmission, impaired by shallow financial
markets, limited the effectiveness of monetary
policy in fighting inflation, damaging real income
growth. There were, however, signs of recovery in
the non-oil sector and an increase in investment.
The economic contraction in Belarus abated, as
inflation declined and the economy benefited
from the resumption of growth in Russia.
In Ukraine, growth weakened in 2017 in thewake of the trade blockade with eastern Ukraine,
which disrupted mining and electricity
production. Growth in the Kyrgyz Republic wasadversely affected by a slowdown at the Kumtor
gold mine. Despite recent improvements, a stillweak business environment continued weighingon growth in Uzbekistan.
Continued expansion in the advanced economies
of Europe supported growth in the western part

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018of
 the region. Export and strong consumption
helped raise growth in Central Europe, from 3.2
percent in 2016 to 4.7 percent in 2017.1 Consumption rose supported by robust labor markets
and, in some cases, fiscal stimulus (e.g., childsubsidies in Poland, VAT cuts in Romania).
Investment growth also strengthened, partly
reflecting increased absorption of EU structural
funds.
The impact of the recent recovery on labormarkets varied across countries. The unemployment rate for commodity exporters declined
by only 0.2 percentage points from the peak in
15Q2 to 17Q3, while real wage growth recoveredfrom -8 percent to 4 percent over the same
period. In contrast, the unemployment rate forcommodity importers declined more significantly
on the back of strengthening growth and labormarket reforms (World Bank 2018o).
Amid tightening labor markets, inflation rosesomewhat in the western part of the region in2017 but continued falling in the eastern part of
the region as exchange rate depreciation pressures
eased. Inflation rates were generally below central
bank target ranges in both parts of the region.

Outlook
Regional growth is expected to moderate to 2.9
percent in 2018 and stabilize at 3 percent in
2019-20 (Figure 2.2.2). The relatively stable
overall growth forecast, however, masks considerable cross-country differences. The forecast ispredicated on a modest recovery in commodity
prices, a gradual moderation of growth in theEuro Area following a strong cyclical pickup in
2017-18, an orderly tightening of global
financing conditions, and the absence of new
geopolitical tensions.
In the eastern part of the region, growth isexpected to continue strengthening during 201820, in line with firming commodity prices andstrengthening domestic demand supported by

1 Central Europe includes Poland, Hungary, Bulgaria, andRomania.

EUROPE AND CENTRAL ASIA

remittances(Armenia, Azerbaijan, Belarus, the
Kyrgyz Republic, Tajikistan). Commodity exporters that have already adjusted to current oil
price levels are expected to follow a somewhat
different path. Growth in Russia is expected tostabilize at around 1.8 percent in 2018-20.
Growth in Kazakhstan is projected to moderate to
2.6 percent in 2018 as the one-off effects ofincreased production at the Kashagan oil field andthe fiscal stimulus wane. It is set to rise to 3
percent by 2020 as the country reaps the benefitsof structural reforms. Ukraine’s economy isexpected to continue mending as geopoliticaltensions subside, with growth strengthening to 4
percent in the medium term. In Uzbekistan,exchange rate liberalization in September 2017,
which resulted in a significant currency
depreciation, will help improve competitiveness,enhance market efficiency, and economic growth.
Growth in the western part of the region is
projected to slow in line with the maturing
recovery in the Euro Area. The gradual slowdown
in EU growth (Chapter 1) will weigh on theregion’s export growth, particularly in Central
Europe, where growth is projected to deceleratefrom 4.7 percent in 2017 to 3.2 percent in 2020,
with growth weakening in Hungary, Poland, andRomania. Growth in Turkey is projected tomoderate to around 3.5 percent in 2018, as theimpact of the 2017 fiscal measures fades.

Risks
The risks to growth in the region have become
more balanced but continue to be tilted to thedownside. On the upside, a more favorable
external environment than assumed, including
faster-than-expected growth in the EU—thelargest trading partner and financing source for
ECA countries—as well as other major
economies, could benefit growth in the region.
Acceleration in structural reforms could also
boost growth by more than is projected.
However, downside risks remain significant. A
disorderly tightening of global financing
conditions could raise financing costs andsuppress capital inflows and growth. Lower-thanprojected oil prices could adversely affect oil

93CHAPTER 2.2

94

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 2.2.2
 ECA: Outlook and risks
Regional growth is expected to remain stable in 2018-20. Fiscal
vulnerabilities remain elevated throughout the region, though lower
external debt repayments over the next few years will provide somebreathing space. For commodity exporters, external debt in relation toexports has increased above the level of EMDE peers in the wake of the
2014-16 oil price plunge and financial vulnerabilities persist. In contrast, forcommodity importers, external debt has remained on par with other
EMDEs and financial indicators have continued improving.
A. Growth forecast

B. Growth decomposition

Percent

Percent

RussiaTurkeyOther commodity exporters
Other commodity importers
ECA

4

Private cons.
Investment
Imports

8

Government cons.
Exports
GDP

4

These risks may be amplified by various countryspecific vulnerabilities, which include:302exporters,
undermining
theirstill-fragile
recoveries and spilling over into smallerneighboring countries through trade and financial
channels. An escalation of geopolitical tensions in
Ukraine, a tightening of international sanctions
on Russia, or an intensification of disagreementsof some countries with the EU could deterinternational investors. The latter could lead to
expectations of an end to EU accession protocol
for Turkey and of disruptions in EU funding tosome countries during the next budget cycle.

2017

2018

2019

Percent of GDP
2007
0

2020

2019

2018

x

External vulnerabilities: large external deficits(e.g., Belarus, Bosnia and Herzegovina,
Georgia, Kosovo, the Kyrgyz Republic,
Moldova, Montenegro, Serbia, Turkey) andhigh external debt (Tajikistan), which
increased in the wake of the 2014-16 oil priceplunge in the eastern part of the ECA region.

x

Fiscal vulnerabilities: limited room for fiscal
maneuvering, partly stemming from the fiscal
stimulus implemented in the wake of the
2014-16 oil price plunge by both oil
exporters (Kazakhstan, Russia) and some oil
importers (Romania, Turkey). Lower external
debt repayments coming due over the next
few years, however, will reduce financing
requirements and mitigate rollover risks.

xFinancial sector vulnerabilities: weak asset
quality of banks and other financial
institutions in some countries (e.g., Belarus,
Bosnia and Herzegovina, Croatia, Moldova)
and deteriorating asset quality in others (e.g.,
Kazakhstan, Russia, Ukraine). Public funds
injected into the troubled banks of
Azerbaijan, Kazakhstan, Russia, Ukraine, andUzbekistan in 2017 attest to continued
challenges faced by the financial systems ofthese countries.

Commodity exporters Commodity importers

2020

C. Fiscal balance

2019

2018

0

2020

-4

1

D. External repayment
2013

2016

2017

Percent of GDP
Number
14
4
Average No.
o. of countries (RHS)
12
3

10
8

2

-2

6
4

1

2
-4

0

E. External debt

F. Non-performing loans

Percent
300

Percent
14

Range Median EMDE median

250

2026

2024

2022

2020

2018

2016

2014

2010

Commodity
importers

2012

0

Commodity
exporters

Commodity exporters
Commodity importers

12

200
10

150

100

8

50

6

2017

Commodity
importers

4

2016

2017

2015

2013

2014

Commodity
exporters

2007

2013

2017

2012

2013

2011

2007

2010

0

Sources: Bloomberg, Haver Analytics, International Monetary Fund, World Bank.
A. GDP-weighted averages. Other commodity exporters include Albania, Armenia, Azerbaijan,
Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. Other
commodity importers include Belarus, Bulgaria, Bosnia and Herzegovina, Croatia, Georgia, Hungary,
Kosovo, FYR Macedonia, Montenegro, Moldova, Poland, Romania, and Serbia.
A. D. Shaded areas indicate forecasts.
B. GDP-weighted averages. Commodity exporters include Albania, Armenia, Azerbaijan, Kazakhstan,
the Kyrgyz Republic, Russia, Ukraine, and Uzbekistan. Commodity importers include Belarus,
Bulgaria, Croatia, Georgia, Hungary, FYR Macedonia, Moldova, Poland, Romania, and Turkey.
C. Median of general government net lending/borrowing over GDP in each sub group. Commodity
exporters include Albania, Armenia, Azerbaijan, Kazakhstan, the Kyrgyz Republic, Russia, Tajikistan,
Turkmenistan, Ukraine, and Uzbekistan. Commodity importers include Belarus, Bosnia andHerzegovina, Bulgaria, Croatia, Georgia, Hungary, Kosovo, FYR Macedonia, Moldova, Montenegro,
Poland, Romania, Serbia, and Turkey.
D. The average of total sovereign/local authority international bond repayments over GDP among
countries who are scheduled to repay that year. Because countries who are not scheduled to repay in
a given year are excluded from the average, the number of countries for each year is reported aswell. Country sample includes 18 countries.
E. Total external debt over exports of goods and services plus primary income. Commodity exporters
include Armenia, Russia, and Ukraine. Commodity importers include Belarus, Croatia, Georgia,
Hungary, FYR Macedonia, Moldova, Poland, Romania, Serbia, and Turkey.
F. Average share of non-performing loans in percent of total loans. Commodity exporters include
Armenia, Kazakhstan, the Kyrgyz Republic, Russia, Tajikistan, Ukraine, and Uzbekistan. Commodity
importers include Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Georgia, Hungary, Kosovo,
FYR Macedonia, Moldova, Poland, Romania, and Turkey.

In the medium and long term, slower-thanexpected productivity growth, partly as a result of
low investment and delays in structural reforms,
could reduce potential growth and slow down
income convergence (Box 2.2.1, Chapter 3).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Major
energy exporters, in particular, may sufferfrom lower growth if they fail to diversify theireconomies away from oil—for example, if the

EUROPE AND CENTRAL ASIA

95

medium-term
strategies recently adopted to that
aim in Azerbaijan, Kazakhstan, Russia, andUzbekistan fail to materialize. 

TABLE 2.2.1 Europe and Central Asia forecast summary
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Source: World Bank.
Notes: e = estimate; f = forecast. EMDE = emerging market and developing economy. World Bank forecasts are frequently updated based on new information and changing (global)
circumstances. Consequently, projections presented here may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any
given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars.
2. Sub-region aggregate excludes Bosnia and Herzegovina, Kosovo, Montenegro, Serbia, Tajikistan, and Turkmenistan, for which data limitations prevent the forecasting of GDP
components.
3. Exports and imports of goods and non-factor services (GNFS).
4. Includes Albania, Armenia, Azerbaijan, Kazakhstan, the Kyrgyz Republic, Kosovo, Russia, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan.
5. Includes Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Georgia, Hungary, FYR Macedonia, Moldova, Montenegro, Poland, Romania, Serbia, and Turkey.
6. Includes Bulgaria, Croatia, Hungary, Poland, and Romania.
7. Includes Albania, Bosnia and Herzegovina, Kosovo, FYR Macedonia, Montenegro, and Serbia.
8. Includes Belarus, Moldova, and Ukraine.
9. Includes Armenia, Azerbaijan, and Georgia.
10. Includes Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan.
For additional information, please see www.worldbank.org/gep.

CHAPTER 2.2

96

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

TABLE 2.2.2 Europe and Central Asia country forecasts1

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Source: World Bank.
Notes: e = estimate; f = forecast. World Bank forecasts are frequently updated based on new information and changing (global) circumstances. Consequently, projections presented here
may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars, unless indicated otherwise.
2. GDP growth rate is based on production approach.
For additional information, please see www.worldbank.org/gep.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018



EUROPE AND CENTRAL ASIA


BOX 2.2.1 Potential growth in Europe and Central Asia
Potential growth in Europe and Central Asia has declined by around 1.4 percentage point in 2013-17 from pre-crisis period, to
2.3 percent. The decline is mostly attributable to weaker productivity growth, but shrinking labor supply have played a role.
Although population aging and slowing productivity growth are expected to continue weighing on potential growth over the next
decade, there are policy options available to offset the decline.

Introduction
Growth in Europe and Central Asia (ECA) has slowed
considerably since the global financial crisis, reversing the
rapid convergence to advanced EU per capita incomes seenin prior years. To a large extent, this slowdown reflected
cyclical factors—including the global financial crisis in
2007-08, the European debt crisis in 2010-11, and the oil
price collapse in 2014-16—which triggered deep output
contractions in some ECA countries.
Concurrent with the cyclical slowdown, potential growthappears to have slowed as well. Historical evidence suggeststhat steep output contractions can leave a lasting dent in
potential growth through legacies such as human capital
loss in extended unemployment spells, weakened investor
confidence about growth prospects, and slower
productivity gains resulting from weak investment(Chapter 3).1

from severe output contractions from falling commodity
prices and geopolitical tensions in large commodity
exporters such as Russia and Ukraine weighed oninvestment and potential growth for commodity exporters.
Potential growth in Russia and Poland showed a decline
after 2008-09, reflecting weak investment anddemographic trends (Narodowy Bank Polski 2017). The
exception was Turkey, where potential growth was largely
unchanged during 2013-17 due to large numbers of youth
entering the labor force.

Total factor productivity growth
Total factor productivity (TFP) growth in the region
declined to 0.8 percent in 2013-17, about 0.4 percentage
points below the long-term average. The deceleration of
TFP growth reflected three factors (Figure 2.2.1.2):x

Slowing foreign direct investment (FDI) inflows.
Growth in FDI flows to the region slowed to 1
percent per year in 2013-16 from 37 percent in 200507 (EBRD 2015). This likely adversely affected TFP
growth in light of evidence that FDI has fostered
technological transfers and productivity gains in the
ECA region as a whole and particularly in Central
Europe (Goldberg, Goddard, and Kuriakose 2011;
Bijsterbosch and Kolasa 2010; IMF 2016c).

x

Slowing sectoral reallocation. The reallocation of laborfrom the agriculture sector to services and industry
has been an important source of economy-wide
productivity gains over the past two decades (IMF
2016c). However, in the Western part of the region,
the shift from agricultural to non-agricultural
employment slowed after the global financial crisis.

x

Slowing reform momentum. Over the past decade,countries in the ECA region have made large strides
in improving their business environments, and therelevant indexes in Central and Eastern Europe, theWestern, Balkans, and the South Caucasus areapproaching the levels in advanced EU countries.
However, reform momentum appears to have slowed
after EU accession in the mid-2000s for Central
Europe. Business climates in Central Asia continue tolag well behind those elsewhere in the region (EBRD
2014).

Against this backdrop, this box discusses the following
questions.
xHow has potential growth evolved in the region andwhat were its main drivers?

xWhat are prospects for potential growth?

xWhat are the policy options to lift potential growth?

Evolution of potential growth and its drivers
Potential output growth in ECA has declined significantly
since the global financial crisis, from 3.7 percent in 200307 to 2.3 percent in 2013-17 (Figure 2.2.1.1). About
three-quarters of the decline reflected slowing total factor
productivity (TFP) growth, and the remainder due toslowing labor supply growth. The decline in potential
growth over the previous decade was steeper among
commodity exporters (-1.7 percentage points) than among
commodity importers (-0.9 percentage points). Spillovers
Note: This box was prepared by Yoki Okawa, Sinem Kilic Celik, andModeste Some. Shituo Sun provided research assistance.
1 The recent slowdown of potential growth and its implications forlong-term growth prospects have been highlighted by EBRD (2014) for
the region as a whole, IMF (2016c) for Central and South-Eastern
Europe, and by ADB (2016) for Central Asia and the Caucasus.

97

CHAPTER 2.2

98

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

BOX
2.2.1 Potential growth in Europe and Central Asia (continued)

FIGURE 2.2.1.1 Regional growth and drivers of potential growth
The growth slowdown in the region reflects both cyclical and longer-term structural factors. Unfavorable demographic trends,
easing productivity growth, and weak investment have weighed on potential growth.

Percent
8

6

6

4

4

2

2

1998-2017

2003-072013-172013-17

2003-07

EMDEs

Contribution0

2013-17

5

Contribution

2003-07

0

TFP
Labor

CapitalPotential growth

0

ECA

EMDEs

2018-27

Cycle

2013-17

Potential

2003-07

Growth

1998-201710

Percent
8

2018-27

Median2013-17ECA

C. Potential growth

2003-07

Percent
15

B. Contributions to post-crisis slowdown
in actual growth

1998-2017

A. Growth

ECA

Source: World Bank.
Notes: GDP-weighted averages.
A. Blue bars indicate GDP-weighted average of 24 ECA countries. Vertical lines indicate range of averages for all EMDE regions.
B. C. Based on potential growth estimates using the production function approach (Chapter 3).
C. Shaded areas indicate forecasts.

countries since 1990, these flows have slowed since
the global financial crisis amid weak Euro Area
activity. While emigration has helped reduce
unemployment and poverty in origin countries (partly
by generating large remittance inflows), it has weighedon growth in these countries, especially where highskilled workers have left (Docquier, Ozden, and Peri
2014; IMF 2016c; Mansoor and Quillin 2006;
Hausmann and Nedelkoska 2017). In addition, large
remittance inflows have generated currency
appreciation pressures and further dampened
competitiveness of origin countries (World Bank
2017b; Meyer and Shera 2017).

Capital accumulation
Post-crisis, investment growth in the ECA region slowedfrom double-digit rates in 2011 to near-zero in 2015-16.
In most Western ECA countries, investment growth has
remained well below the EU average, reflecting weak
activity in Euro Area trading partners, external borrowing
constraints especially during the Euro Area debt crisis, andstructural and institutional impediments that slowed
productivity growth (World Bank 2017b). Elsewhere in
the region, low commodity prices, slowing growth inChina, and weak activity in major advanced economies
have softened growth prospects and weighed oninvestment (EBRD 2015). The oil price plunge of 201416 also had negative spillovers for investment in themining sector.

Labor Supply
Working-age population growth, which has long been well
below the EMDE average, has turned negative in the ECA
region (Figure 2.2.1.3). This demographic shift began in
the late 2000s and is attributed to collapsing fertility rates
in the 1990s in the aftermath of the collapse of the Soviet
Union. Slowing emigration and rising female labor force
participation have only partially mitigated the effects of
population aging.
x

Immigration to EU. Although proximity to the EU has
encouraged large-scale emigration from ECA

xImmigration to Russia. Linguistic, family, cultural, andeconomic ties with Russia and neighboring countries
created strong migration flows to Russia, especiallyfrom Central Asia (World Bank 2017s). This hashelped slow the decline in working-age population
growth in Russia, but accelerated the slowdown inCentral Asia. However, immigration to Russia slowed
sharply in the steep recession of 2015-16.

Potential growth prospects
Regional potential growth is expected to remain subdued
in 2018-27 at 2.2 percent, slightly down from 2.3 percent
in 2013-17 (Figure 2.2.1.4). This reflects a combinationof weak productivity growth and unfavorable demographic
trends in many countries. Population aging, which leads toGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

EUROPE AND CENTRAL ASIA

99


BOX
2.2.1 Potential growth in Europe and Central Asia (continued)


FIGURE 2.2.1.2 Factors contributing to the slowdown in productivity
Total factor productivity growth has slowed below its long-term average. In the western part of the region, the reallocation oflabor from agriculture to the more productive industry and service sectors slowed, as did FDI inflows. In Central Europe,
reform momentum slowed after 2007 as well. Investment growth
decelerated
sharply following the crisis. Among commodity
exporters, a slowdown in the mining sector played a significant role.
A. TFP growth

B. Labor share in agriculture

Percent
6

Percent

ECA
MedianC. Foreign direct investment
Percent

East

30

40

West
EU15

4

30

20

2

20
10

0

10

D. Ease of Doing BusinessE. Investment growth

Score

Percent
20

80

Central Asia
Eastern Europe
Western Balkans

Central Europe
South Caucasus

2016

2013-172011

2003-072006

1998-2017

2001

-2

1996

1991

0

0
2005-072013-16

F. Mining investment
ECA
MedianPercent
15

15

70
10

10
60
5

5

50
0

2017

2015

2013

2011

2009

2007

2005

40
0

-5
1998-2017

2003-072013-17

2005-072013-16

Sources: European Bank for Reconstruction and Development, Haver Analytics, International Labor Organization (ILO), Ministry of the National Economy of the Republicof Kazakhstan, Organization for Economic Co-operation and Development, Penn World Tables, Russian Federation Federal State Statistics Service, World Bank.
A. GDP-weighted average of TFP growth from Chapter 3. Blue bars indicate average for 10 ECA countries; vertical lines indicate range of averages for all EMDE regions.
B. Percent of agricultural employment in total employment in each region. “East” includes Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, the Kyrgyz Republic,
Moldova, Russia, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. “West” include Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Hungary, FYR Macedonia,
Poland, Montenegro, Romania, Serbia, and Turkey. “EU15” includes Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg,
Netherlands, Portugal, Spain, Sweden, and the United Kingdom.
C. Average annual growth in FDI inflows to Belarus, Croatia, Georgia, Hungary, Kazakhstan, FYR Macedonia, Moldova, Poland, Russia, Romania, and Ukraine.
D. Distance to frontier in Doing Business Indicators, with a higher index denoting easier business environments. Central Asia includes Kazakhstan, the Kyrgyz Republic,
Tajikistan, and Uzbekistan. Central Europe includes Bulgaria, Croatia, Hungary, and Romania. Eastern Europe includes Belarus, Moldova, Russia, and Ukraine. South
Caucasus includes Armenia, Azerbaijan, and Georgia. Western Balkan includes Albania, Bosnia and Herzegovina, Kosovo, FYR Macedonia, Montenegro, Serbia,
and Turkey.
E. GDP-weighted average annual growth rates.
F. Average annual growth rates of mining sector investment in Kazakhstan and Russia.

both a shrinking labor force and a growing share of older
workers, will weigh particularly heavily on potential
growth in the Eastern part of the ECA region. Increasing
share of older workers tends to reduce aggregate labormarket participation rate and productivity growth. A
notable exception is Turkey, where continued strong
growth in the working-age population supports a positive
outlook for potential growth.
Among commodity-exporting economies, limited
prospects of the substantial recovery in commodity prices
could continue to adversely affect investment. In turn,lower investment growth would cap potential growththrough slower capital deepening and embodied
technological improvements.

Policy options to lift potential growth
A wide range of policy options is available to help stem thedecline in potential growth in the ECA region. A
simulation suggests that increasing investment and labormarket reforms can reverse the expected slowdown (Figure
2.2.1.5).

CHAPTER 2.2

100

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.2.1 Potential growth in Europe and Central Asia (continued)


FIGURE 2.2.1.3 Labor supplyWorking-age population growth, which has long been well below the EMDE average, declined across the region in the late
2000s. Rising female labor force participation has only partially mitigated the effects of unfavorable demographic trends and
outward migration (except Russia). People who live outside theirnative country are better educated than those who remain.
Russia saw net immigration from neighboring countries.
A. Working-age population growth

B. Working-age population growth insubregions

Percent

Percent
3

ECA

4MedianECACentral Asia

C. Labor market participation
Percent
100

West ECA
Russia

ECA

EMDEs

80
2

60

1

40

0

20

0
-1

0
1998-2002 2013-17 1998-2002 2013-17

Belarus

UkraineTurkmenistan

Uzbekistan

Georgia

TajikistanAzerbaijan

2025

2020

2015

2010

2005

2030

Workers who left home workforce
Workers in Russian foreign work force

Kyrgyzstan

RussiaTurkeyEasternEuropeCentralEuropeCentralAsia

Western
Balkans

South
Caucasus-1

Home resident

Armenia0

Percent
35
30
25
20
15
10
5
0

Emigrant

Turkey1

Percent
70
60
50
40
30
20
10
0

Russia1995-20052010-15

FemaleF. Immigrants in Russia

Western
Balkans

Per 1000 population
2

Male

E. Tertiary education for immigrants

CentralEuropeD. Net outward migration

CentralAsia

2013-17

2000

2003-07

South
Caucasus

1998-2017

EasternEurope

-2

1995

-2

Kazakhstan

2

Sources: International Labor Organization, Organization for Economic Co-operation and Development, Russian Federation Federal State Statistics Service, United
Nations, World Bank.
A. GDP-weighted average shares of population aged 15-64 years as a percent of total population.
B. Annual growth rate of total population aged 15-64 aggregated by subregions. ECA includes Albania, Armenia, Azerbaijan, Belarus, Bulgaria, Bosnia and Herzegovina,
Georgia, Croatia, Hungary, Kazakhstan, the Kyrgyz Republic, Moldova, FYR Macedonia, Montenegro, Poland, Romania, Russia, Serbia, Tajikistan, Turkmenistan, Turkey,
Ukraine, and Uzbekistan. West ECA includes Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Hungary, FYR Macedonia, Montenegro, Poland, Romania, Serbia, andTurkey. Central Asia include Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan. Shaded areas indicate forecasts. 
C. Simple average of 24 ECA countries. EMDE average includes 151 countries.
D. -E. Central Asia includes Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan. Central Europe includes Bulgaria, Croatia, Hungary, Poland, andRomania. Eastern Europe includes Belarus, Moldova, and Ukraine. South Caucasus includes Armenia, Azerbaijan, and Georgia. Western Balkans includes Albania,
Bosnia and Herzegovina, FYR Macedonia, Montenegro, and Serbia.
D. Number of total emigrants per 1,000 population during the sample period. Number is simple average across countries in each sub-region.
E. Percentage of the population above age 24 who completed some tertiary education in 2010 or closet year available. Emigrant is defined as a person who lives outsideof their birth country. Numbers are simple averages across birth countries in the sub-region.
F. Number of total immigrant workers who arrived in Russia during 1997-2016 divided by the total labor force of the origin country in 2016. Number of total immigrant
workers who arrived in Russia from each country during 1997-2016 divided by total immigrant workers who arrived in Russia during 1997-2016. For Tajikistan, datasuggested by the domestic survey may differ from the data used here. For details, see Strokova and Ajwad 2017.

Raise capital accumulation
Increase public investment efficiency. Infrastructure needs
are sizable in the ECA region. Investment gaps are
estimated to be the equivalent to 1.3 percent of GDP(EBRD 2015). Although there is limited fiscal space
available for governments to fill these gaps, there is scope
to improve the efficiency of public investment (WorldBank 2017p). This could be achieved with more strategic,
rigorous, and transparent project selection mechanisms,
and by strengthening the institutional capacity to fund,manage, execute, and monitor project implementation.
For example, by introducing a rate-of-return criterion for
public investment, Azerbaijan has reduced the completiontime of key projects by 26 percent (World Bank 2016h).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

EUROPE AND CENTRAL ASIA

101

BOX
2.2.1 Potential growth in Europe and Central Asia (continued)

FIGURE 2.2.1.4 Regional potential growth outlook
Regional potential growth is expected to slow marginally to 2.2 percent in 2018-27 from 2.3 percent in 2013-17. The raising
share of older workers will result in lower labor participation and could contribute to slower productivity growth. The lower
energy price outlook could further weigh on investment and capital accumulation in energy exporters.
A. Potential growth outlook

B. Composition and labor force
participation rate of working-age population

C. Energy price outlook

Percent
4

Percent
100
80
60
40
20
0

Index, 100 = 2010
150

2025

2020

Participation

Population
share

50-65

2015

25-49

0

2010

15-24

2014
14 forecast
2017
17 forecast

2005

West

Participation

2018-272013-172018-27
East

50

2000

ECA

2013-172018-272013-17

0

Population
share

1

2018-27

100

Participation

2

Population
share

3

1998-2007

Sources: International Labor Organization, World Bank.
A. GDP-weighted averages. East includes 12 countries in Central Asia and Western Balkan. West includes 11 countries in Eastern Europe, South Caucasus, and Central Asia.
A. C. Shaded areas indicate forecasts.
B. Population share refers to the average share of the population of certain age ranges over the total population aged 15-65, weighted by the population of each country.
Participation is a simple average of the labor market participation rate.
C. Index of energy prices and outlook published in “Commodity Markets Outlook” (World Bank 2014, 2017q).

Increase savings. The financing available for private
investment could be expanded by raising householdsavings. In the western part of the region, for example,
household savings rates are low by EU standards. Pension
reforms, development of the mutual fund industry, andefficiency improvements in pension administration would
yield benefits (IMF 2016c; World Bank 2011b).

Expand labor supply
Raise labor force participation. Male labor force
participation in ECA lags behind that in other EMDE
regions; female labor force participation, while higher thanthe EMDE average, lags behind that in advanced
economies. Female labor force participation is responsive
to steps to improve the educational attainment of womenand to better access to child care services (Chapter 3). In
Western Balkan countries, where multiple barriers anddisincentives discourage female labor force participation,
increased parental leave, decreased labor taxes, and lower
childcare costs could significantly increase female labor
force participation rates (World Bank 2016i, 2016j,
2017r; Atoyan and Rahman 2017).
Attract and retain skilled labor. Brain drain is a significant
problem in the ECA region, especially in the Western
Balkans where rates of emigration among the highly
educated are high. Steps to mitigate the loss of skilledworkers could pay considerable dividends (IMF 2016c;

World Bank 2017s). Several countries have launchedinitiatives to retain skilled workers or to encourage theirreturn after years of absence. In 2006, Albania
implemented a “brain gain” program to promote return
migration by offering employment in public administration and improving the work environment inuniversities and research institutions (Agolli and Gugu
2010). Youth workforce development projects, such as
entrepreneurship training programs and provision of
micro credits, have created opportunities for skilled young
people in the Western Balkans, the South Caucasus, andCentral Asia (International Labor Organization 2017;
World Bank 2013b).

Increase productivity
Reform state-owned enterprises. Public firms tend to beless efficient than private firms in ECA (Böwer 2017).
While Central European has attained a private sector shareof the economy similar to that in advanced economies,
the private sectors for the rest of the region account forconsiderably smaller shares of the economy. Further
privatization in these regions presents an opportunity toraise economy-wide productivity, especially if it isaccompanied by improved management and corporate
governance, open access to world markets, and wellfunctioning legal and institutional frameworks (Estrin etal. 2009). Short of privatization, there are important

102

CHAPTER 2.2

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.2.1 Potential growth in Europe and Central Asia (continued)


FIGURE 2.2.1.5 Policies to stem declining
potential growth A range of policy options is available to help stem thedecline in potential growth in the ECA region, including
measures to raise capital and increase labor force participation. Privatization in the ECA region continues to lag
behind advanced economies, particularly countries in
Eastern Europe.
A. Potential growth under reform scenarios
Percent
6

Baseline
Fill investment needs
Labor market reforms

5

opportunities to strengthen the governance and therefore
the productivity of state-owned enterprises, as illustrated
by the efforts being made by Romania and FYR
2Macedonia.

Make more business-friendly environments. Efforts toimprove the business environments in commodityimporting Central European economies to EU15
standards stalled after the global financial crisis (WorldBank 2017l; IMF 2016c). International integration or
external standards such as the Doing Business Index cananchor reforms. Improvement in local-level transparency
and accountability standards can be politically easier thannational-level reform and can lead to national-level reform(EBRD 2014).

4
3
2
1

0
2013-17 2018-27

Reformimpact2013-17 2018-27

EMDEs

ReformimpactECA

B. Privatization
Index
5

Advanced-economy average

43

EasternEuropeCentralAsia

Western
BalkanSouth
Caucasus

CentralEurope

ECA
Graduate

2

Sources: European Bank for Reconstruction and Development, World Bank.
A. GDP-weighted averages. Derived using the methodology described in
Chapter 3.
B. Privatization index from EBRD. “ECA graduate” refers to regional economies no longer categorized as “emerging and development economies.”
These include Estonia, Latvia, Lithuania, Slovak Republic, and Slovenia.

Integrate into global value chains. Cross-country evidenceshows that exporting firms tend to benefit from fasterproductivity growth, especially through their participationin global value chains (Ruta, Constantinescu, and Mattoo2017).3 Over the past two decades, Central European
countries have developed a comparative advantage inknowledge-intensive manufacturing, including as part of
the German supply chain (Figure 2.2.1.6; IMF 2013).
Policies to foster the integration of domestic industry into
global supply chains go beyond tariffs and quotas. They
include coordination of intellectual property rights
protection, competition laws, FDI frameworks, andtransportation infrastructure (Baldwin and LopezGonzalez 2015). Moreover, manufacturing productivity
can also be improved by lowering barriers to services trade(Beverelli, Fiorini, and Hoekman 2017). For countries in
the South Caucasus and Central Asia, the Eurasian
Economic Union and China’s Belt and Road Initiative
present opportunities to adopt a regional approach tobuilding productivity-enhancing value chains (Ustyuzhanina 2016).

2 In Romania, a number of state-owned enterprises depoliticized andprofessionalized their boards in 2013-16. Romania also passed a law onstate-owned enterprise governance (Law 111/2016), which improved thecriteria for the selection and evaluation of state-owned enterprise managers and introduced performance monitoring for others (Capannelli2017). However the implementation of the law is lagging behind andresistance to change is significant. In FYR Macedonia, institutional andorganizational reform combined with capital investment improved theoperational effectiveness of the state-owned railway company (WorldBank 2012).
3 In the ECA region, a positive relationship between exports andproductivity has been documented for Poland, Romania, and Russia.
Cross-country studies in the region also find a positive relationship.
(Goldberg, Goddard, and Kuriakose 2011; Gabrielczak and Serwach
2014; Stefanescu and Dumitriu 2014; Krasnopeeva et al. 2016).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

EUROPE AND CENTRAL ASIA

103


BOX
2.2.1 Potential growth in Europe and Central Asia (concluded)







Commodity dependence for ECA countries increased
most among EMDE regions, reflecting the increased
participation and specialization in global trade. Global
value chain integration substantially increased in mostof the countries.

1995

2011

Romania

Index
60

PolandA. Global value chain integration

50
40
30
20
10

EMDEs

TurkeyRussiaHungary0

Croatia

1995

2015

EMDE 2015

MNA

SAR

Index

LAC

B. Commodity dependence

0.7

0.6
0.5
0.4
0.3
0.2
0.1

SSA

0

ECA



Bulgaria

Diversify resource-intensive economies. Increasing
specialization in global trade raised the share ofcommodities in exports for commodity-exporting ECA
countries (van Eeghen et al. 2014). Reliance on natural
resources poses several policy challenges. By concentrating
on a few commodities, economies remain vulnerable tonegative prices shocks. Even positive price shocks can be
disruptive by weakening the competitiveness of othersectors in resource-intensive economies (“Dutch disease”).
Strong policy frameworks to manage commodity revenues
can promote long-term investment and job creation by
reducing cyclical fluctuations and mitigating the adverse
effects of Dutch disease. For example, in Russia, newpublic spending rules based on oil prices should help
reduce pressures for procyclical fiscal policy responses tocommodity price shocks from 2019 onwards. Moreover,
governments in commodity-dependent economies areoften slow to promote competition and entrepreneurship,
favoring a known revenue stream over that which may
develop from non-commodity sectors (van Eeghen et al.
2014). Creating a level playing field by improving the ruleof law, reducing corruption, and broadening access tofinance can help creating more resilient and balanced
growth.

FIGURE 2.2.1.6 Policies for moreconnected economy

EAP

Promote FDI. Inward FDI stands to boost productivity in
ECA by accelerating technology absorption. In Serbia, forexample, firms with foreign capital have more efficient
production
technology, better foreign marketing, andmore research and development activity than firms that do
not have foreign capital. Foreign-owned firms initiatedgreater plant modernization and automation thandomestically-owned firms, raising labor productivity(Goldberg, Goddard, and Kuriakose 2011). Suchproductivity-enhancing foreign investment can be
encouraged by liberalizing FDI and merger and acquisition
rules. Moreover, spillovers to domestically-owned firms
can be encouraged by building public research anddevelopment infrastructure that bridges the gap between
foreign entrants and domestic research capacity. In
addition, improving domestic human capital by training
and high-quality education encourages technologicaltransfer to domestic firms that received FDI (Fu 2008;
Teixeira and Fortuna 2010).

Sources: Organization for Economic Co-operation and Development, United
Nations Conference on Trade and Development (UNCTAD).
A. Backward participation index in global value chains from OECD. It ismeasured by share of foreign value added content in gross exports.
B. Average trade concentration index for commodity exporters in eachregion. The trade concentration index is a measure of the degree of productconcentration from UNCTAD. An index value closer to 1 indicates higher
concentration. EAP = East Asia and Pacific, ECA = Europe and Central
Asia, LAC = Latin America and the Caribbean, MNA = Middle East and North
Africa, SSA = Sub Saharan Africa, and EMDE = Emerging Market andDeveloping Economies.

The region has begun to recover from a two-year contraction, growing by an estimated 0.9 percent in 2017,supported predominantly by private consumption. Growth is expected to accelerate in coming years, reaching
2.7 percent in 2020, as conditions in commodity exporters continue to improve. Several downside risks could
derail the recovery, however, including economic spillovers from domestic policy uncertainty, additional
disruptions from natural disasters, and negative spillovers from international financial market disruptions or arise in U.S. trade protectionism.

Recent developments
Growth in Latin America and the Caribbean(LAC) is estimated to have reached 0.9 percent in2017, the first positive rate since 2014. The
recovery was broadly in line with expectations inJune 2017, as stronger-than-expected growth inBrazil was offset by a much deeper-than-expected
contraction in República Bolivariana de Venezuela
and more modest shortfalls in the Caribbean
subregion and Peru.
Private consumption was the main contributor toactivity in the region in 2017. Investment has
been slower to recover in LAC than in othercommodity-reliant
emerging
marketanddeveloping economy (EMDE) regions, where
investment growth picked up in 2017 after years
of weakness. Notably, fixed investment isestimated to have contracted for four consecutive
years through 2017 in Brazil and Peru (Figure
2.3.1). Investment also fell in Mexico in 2017,
likely reflecting uncertainty with respect to the
U.S. commitment to the North American Free
Trade Agreement (NAFTA) and possible domestic
policy shifts following the 2018 presidential
elections. Political and policy uncertainty isviewed to have weighed on investment in several
countries (e.g., Brazil, Venezuela; World Bank
2017p). The extended slump in commodity prices

Note: This section was prepared by Dana Vorisek. Shituo Sun
provided research assistance.

has also required cuts in public investment incommodity-exporting economies in response to
weaker government revenues.
In South America, a cyclical recovery is underway
in Brazil following a deep, two-year-longrecession. Brazil’s economy is estimated to have
expanded by 1.0 percent in 2017. Retail trade andindustrial production growth have picked up,
despite a continued contraction in theconstruction sector, while consumer confidence
was stable in 2017 and labor market conditions
began to improve. Growth in Argentina recoveredin 2017 from a recession in 2016, driven by astrong rebound in investment, particularly public
investment, and rising private consumption,
supported by higher real wages. However, in a
number of commodity-reliant economies, weak orcontracting production in the extractive industries
held back growth, reflecting subdued oil prices
and oil field maturation (e.g., Colombia), labor
strikes (e.g., Chile), policy uncertainty (e.g., Chile,Peru), and major floods early in the year (e.g.,Peru).
Growth in Mexico in 2017 is estimated to havebeen 1.9 percent, slightly stronger than expected
in June, despite the effects of two powerfulearthquakes in September. Activity was supported
primarily by private consumption, which wasresilient in light of a healthy labor market andrising remittances, offsetting weak investment. Net
exports are estimated to also have contributed
positively to growth. The rise in remittances

CHAPTER 2.3

106

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 2.3.1 LAC: Recent developments
Legacies of a two-year recession in LAC are fading. Investment started torecover. Consumer confidence improved in the largest economies in 2017,
despite policy uncertainty in Brazil and Mexico. Remittance inflows to
Mexico and several Central American countries continued to rise in 2017,
perhaps reflecting fears of changes in U.S. immigration policy. Inflation
eased in most countries in the region and has been accompanied bybroadly accommodative monetary policy. Output gaps are nearly closed inmost countries.

Percent, year-on-year
9
Industrial production
6
3
0
-3
-6
-9
-12
-15

C. Consumer confidence

20

Jan-16

Jul-17Jan-17

4
0

E. Consumer price inflation

Mexico

60

2017

8

Guatemala

30

2016

12

Jul-1740

70Jan-1780

Jul-1650

Jul-1560

90Jan-15

100

Jul-1470

Annual percent growth
2010-15 average
16

El Salvador+50=growth
80

Argentina (RHS)110

Jan-14Jul-16

D. Remittance inflows

DomincanRepublic

Index, 100=Jan. 2014
120
Brazil Mexico

Retail tradeJan-16

Jan-14

2017Q3

2016Q3

2014Q3

2015Q3-10

2013Q3-5-10

2012Q30-52011Q350

2010Q3

5

Jul-15Percentage points Percent change, year-on-year
BrazilMexicoArgentina
Colombia
15
15
Chile
Peru
Inv. growth (RHS)
1010

Jul-14

B. Industrial production and retailtrade, Brazil

Jan-15

A. Regional investment growth

F. Output gaps

Percent, year-on-year7

Jan-17
Nov-17
Target6

5Percent of potential GDP
Commodity exporters
1
Commodity exporters excl. Brazil
Commodity importers
0

4
-1

3

2
-2

LAC

Peru

MexicoColombia

Chile

Brazil

1

-3
2016

2017

during 2017 to Mexico and several Central
American countries has been at least partly
ascribed to precautionary flows in anticipation of
possible changes in U.S. immigration policy, andso may not be sustained (World Bank 2017t).
Natural disasters had a massive impact on the
Caribbean in the second half of 2017, destroying
infrastructure and lowering growth prospects.
Hurricanes Irma and Maria devastated Dominica,
and Antigua and Barbuda (in particular, Barbuda),
and caused severe damage in the British Virgin
Islands, the Dominican Republic, Guadeloupe, St.
Kitts and Nevis, Turks and Caicos, the U.S.
territories of Puerto Rico and the Virgin Islands.
Inflation in the region was low in 2017 andtrended downward in most major economies,
underpinned by prior exchange rate appreciations
and, in Brazil, food price deflation. Inflation is
now below or at the lower bound of target ranges
in a number of countries (e.g., Brazil, Chile,
Paraguay). The central bank of Brazil announced
in June that its target band would be lowered in
2019, while historically low levels of inflation in
Honduras caused the central bank to lower its
target band in the same month. A key exception
was Mexico, where inflation rose for on a
reduction of fuel subsidies early in the year andincreasing agricultural prices later in the year.
With aggregate output gaps in most of the region
nearly closed (an exception is Brazil, where thenegative gap is still large), the monetary policy
stance may become more neutral, following easing
across the region in 2017. The major exception is
Venezuela, which continues to experienceextremely high inflation and severe policy
imbalances.

2018

Sources: Haver Analytics, World Bank.
A. Line shows GDP-weighted average of gross fixed capital formation growth in Argentina, Brazil,
Chile, Colombia, Mexico, and Peru using non-seasonally-adjusted data. Bars show contribution ofeach of the six economies to regional investment growth. The six economies represent 85 percent ofregional GDP.
B. Lines show 3-month moving averages using non-seasonally-adjusted data. Last observation is
October 2017.
C. Data for Brazil and Mexico are seasonally adjusted. Last observation is November 2017.
D. Last observation is November 2017 for Guatemala, October 2017 for El Salvador and Mexico,and September 2017 for the Dominican Republic. Annual growth rates for 2017 are estimates basedon available data.
E. Blue boxes show central inflation targets; vertical lines show target bands. LAC shows median
inflation in Argentina, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic,
Ecuador, Guatemala, Honduras, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Trinidad
and Tobago, and Uruguay.
F. Output gaps estimated using multivariate filter. Bars show GDP-weighted averages of individual
country output gap estimates using, as weights, real GDP at 2010 prices and market exchange rates.
Economies include Argentina, Bolivia, Brazil, Chile, Colombia, Mexico, and Peru.

With benign external financing conditions
extending through the second half of 2017, capital
inflows to LAC are estimated to have risen in2017. After easing in the second half of the year in
most large economies in the region, especially inArgentina, sovereign bond spreads were at or
below the average since 2010.
Fiscal conditions in the region reflect the impact
of previous policy decisions and trends incommodity prices in recent years. In commodity
exporters, especially oil exporters, fiscal

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Growth in Latin American and the Caribbean is expected to accelerate,
driven by private consumption and, to a lesser degree, investment. Despite
the steady recovery, growth in the region is expected to continue to be
weaker than both historical averages for the region and growth in all other
EMDE regions. Fiscal sustainability has deteriorated in commodity
exporters in the region, particularly oil-exporting countries, and government
debt, already at high levels in the Caribbean, may expand in the aftermathof the natural disasters. Together with fiscal vulnerabilities, domestic policy
uncertainty and natural disasters could undermine regional growth.
A. Regional growth

LAC 1990-2008 average
LAC 2003-08 average

6
4
2

2017

EAP

SAR

SSA

MNA

LAC

ECA

EAP

SAR

SSA

ECA

0

2019

2018

2017

2016

2015

2014

2013

Percent
8

LAC

Government consump.
Exports
GDP growth
g
(RHS)
(
) 4

3
2
1
0
-1
-2
-3

2020

C. Economic and trade policy
uncertainty

D. Fiscal sustainability gap in LAC

Index, 100=1985-2010
Index, 100=1996-2016
U.S. trade policy uncertainty
Economic policy uncertainty, Mexico 200
350

Percent of GDP
Percentage points
2017
44
2013-17 change (RHS)
0

100

-4

-4

-8

-8

Energyexporters

50

Nov-17

Sep-17

Jul-17May-17Jan-17Mar-17

Nov-16

Sep-16

Jul-16May-16

Jan-16

Mar-160Commodity
importers0Agricultural
exporters

150

Metalsexporters

300
250
200
150
100
50
0

0.4

30

0.2

20

0.0

2017

0.6

40

2015

0.8

50

2013

60

2011

Percent of GDP, annual average

2009

F. Damage from natural disasters

Percent of GDP
EMDEs excluding LAC
South America, Mexico, & Central America
80
The Caribbean
70

2007

E. Gross government debt

2005

Regional growth is projected to gather
momentum, rising to 2.0 percent in 2018 and 2.6
percent in 2019 (Figure 2.3.2, Tables 2.3.1 and2.3.2). With the external drivers of growth for theregion expected to be decreasingly supportive—
the large gains in some commodity prices in 2016
are not envisaged to continue, while growth in
the United States and China is projected todecelerate in 2019 and 2020—the region willneed to rely on domestic sources of growth morethan in the past (Végh et al. 2017). Indeed, thebaseline outlook of accelerating regional growth is
supported by strengthening private consumption
and investment, particularly in commodityexporting countries in the region. Domestic
demand is expected to respond to strengthening

4
3
2
1
0
-1
-2
-3

Private consump.
Investment
Imports

2003

Outlook

B. Growth compared to other regions
and historical levels

Percentage points Percent change, year-on-year

2001

Although the median government debt burden asa share of GDP in the South America and Mexico
and Central America subregions is similar to thatin other EMDEs, government debt levels haverisen since the financial crisis. Government debt
has increased markedly in several large economies(e.g., Argentina, Brazil, Colombia, Mexico),
although in all of these cases except Brazil thedebt-to-GDP ratio is estimated to have fallen in2017. Government debt is particularly high in the
Caribbean region: above 60 percent as of 2017 in
11 of 15 countries, and 90 percent or above inthree countries. The buildup reflects years of fiscal
slippage following post-natural-disaster reconstruction, assumption of new debt to service
existing debt, and the assumption of previously
unrecognized contingent liabilities, notwithstanding restructuring and fiscal consolidation thathave reduced debt loads in several countries (e.g.,
Grenada, Jamaica, and St. Kitts and Nevis;
Rustomjee 2017).

107

FIGURE 2.3.2 LAC: Outlook and risks

MNA

sustainability has deteriorated sharply due tofalling commodity prices and, in many cases,
inadequate policy responses, leaving considerable
scope for growth-enhancing fiscal reforms (asdiscussed in the EMDE fiscal policy section ofChapter 1 and Special Focus 1). Fiscal deficits also
reflect procyclical public spending in the leadup
to the commodity price downturn several years
ago (Végh, Lederman, and Bennett 2017).

LATIN AMERICA AND THE CARIBBEAN

1.4
1.2

1990-99 average
2000-17 average

1.0

The EAP ECA LAC MNA SAR SSA
Caribbean

Sources: Baker, Bloom, and Davis (2015); Centre for Research on the Epidemiology of Disasters;
Haver Analytics; International Monetary Fund; national statistical agencies, World Bank.
A. Bars show contribution of each of the selected components of GDP to regional growth.
A. B. GDP-weighted averages.
B. F. EAP = East Asia and Pacific, ECA = Europe and Central Asia, MNA = Middle East and North
Africa, SAR = South Asia, and SSA = Sub-Saharan Africa.
C. Policy uncertainty indexes are constructed using the methodology in Baker, Bloom, andDavis (2015) and are based on the frequency of relevant articles in domestic newspapers.
D. GDP-weighted averages. Sustainability gap is measured as the difference between the primarybalance and the debt-stabilizing primary balance, assuming historical median (1990–2016) interest
rates and growth rates. A negative gap indicates that government debt is on a rising trajectory; apositive gap indicates government debt is on a falling trajectory. Energy exporters include Bolivia,
Colombia, Ecuador, Trinidad and Tobago, and Venezuela; metals exporters include Chile and Peru;
agricultural exporters include Argentina, Belize, Brazil, Costa Rica, Guatemala, Honduras, Paraguay,and Uruguay; and commodity importers include the Dominican Republic, El Salvador, Jamaica,
Mexico, and Panama.
E. Lines show medians of respective country groups. Country groups are as given in notes below
Table 2.3.1.
F. Simple average during year spans of aggregate regional damages per year.

108

CHAPTER 2.3

confidence, relatively low inflation and still
supportive, if somewhat tighter, global financing
conditions.
In Brazil, the recovery is expected to solidify in2018, with growth reaching 2 percent, as
improving labor market conditions and low
inflation support private consumption, theresidual effects of the deep recession fade, andpolicy conditions become more supportive ofinvestment.
Investment is also envisaged to be a key driver ofaccelerating growth in several other SouthAmerican economies during the forecast period,
supported by a push to upgrade infrastructure in
Argentina, recovery efforts in Peru following
major floods in early 2017, and constructionof a third paper pulp mill and transportation
upgrades in Uruguay. Growth in Colombia is
expected to pick up through the forecast period as
moderating inflation supports private consumption, export growth recovers on rising oil prices,the 4G road infrastructure program is executed,
and structural reforms to enhance competitivenessand foster diversification are implemented. In
Chile, rising disposable incomes and mining
exports, together with supportive financial
conditions, are expected to support faster private
consumption and investment growth in 2018,
underpinned by a sharp rise in copper prices in thesecond half of 2017.
Growth in Mexico is forecast to be moderately
higher in 2019 and 2020, at 2.6 percent, as
investment picks up following the fading of
uncertainty related to the renegotiation of NAFTA
and the outcome of July presidential elections.
Growth in Central America is projected to remain
stable, at 3.8–3.9 percent.
In the Caribbean, post-hurricane reconstruction is
expected to support a recovery in growth to 3.5
percent in 2018 and 2019, from an estimated 2.3
percent in 2017. The vital importance of tourism
to Caribbean economies underscores the need totarget infrastructure and services that support thisindustry as part of reconstruction.
Despite the projected growth acceleration in LAC,
regional growth is expected to continue to be

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

lower than the historical (1990–2008) average forthe region. Furthermore, a slowdown in potential
growth in commodity exporters in the region
raises questions about the sustainability of an
expected regional recovery driven by accelerating
activity in these economies. Weak productivity
growth in the region has long held back potential
growth (Box 2.3.1).

Risks
The regional growth outlook continues to be
subject to considerable downside risks. A further
rise in policy uncertainty, additional disruptions
from natural disasters, negative spillovers frominternational financial market disruptions or a risein U.S. trade protectionism, and further
deterioration in fiscal conditions could all knock
the regional growth trajectory off course.
Persistent domestic policy uncertainty (e.g., Brazil,
Guatemala, Peru) and poor economic policy
management (e.g., Venezuela) may negatively
impact confidence and growth in some countries.
Policy uncertainty stemming from forthcoming
legislative and presidential elections in a numberof economies in 2018 is a short-term downsiderisk for growth in a number of large (e.g., Brazil,
Colombia, Mexico) and small (e.g., Costa Rica, El
Salvador, Paraguay) economies.
Natural disasters—including drought, earthquakes, floods, hurricanes, and wildfires—have
had a significant impact on activity in the LAC
region, especially in the Caribbean, suggesting therisk that these shocks could become morecommonplace in the medium term if climate
conditions remain adverse (Acevedo 2016).
Further risks stem from international trade andfinance channels. Notably, a contentious or
prolonged completion of NAFTA renegotiations—or, in an extreme case, the collapse of theagreement—could derail growth in Mexico in themedium term through decreased trade. A
disorderly adjustment of long-term interest rates
in major advanced economies or a downturn inglobal foreign direct investment flows would
weigh on fixed investment and growth in theregion. A sharp tightening of financing conditions,GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

LATIN AMERICA AND THE CARIBBEAN

109

in several countries, the need to accommodate
post-hurricane reconstruction costs even as
government revenues fall due to the disruption of
economic activity. For Brazil, an improvement infiscal sustainability depends on pension reform.

stemming from faster-than-expected interest rate
hikes in advanced economies or significant
appreciation of the U.S. dollar, in which much of
LAC’s debt is still denominated, would increasedebt service costs in the region and potentiallyrequire tightening of fiscal policies in the context
of already-constrained fiscal space.

For Mexico and Central America, an envisaged
slowing of potential growth in advanced economies represents a downside risk for growth in themedium and long term (Chapter 3).

The Caribbean faces not only the challenge ofreducing government debt from high levels, but,

TABLE 2.3.1 Latin America and the Caribbean forecast summary
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Source: World Bank.
Notes: e = estimate; f = forecast. EMDE = emerging market and developing economy. World Bank forecasts are frequently updated based on new information and changing (global)
circumstances. Consequently, projections presented here may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any
given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars. Excludes Cuba.
2. Aggregate includes all countries in notes 4, 5, and 6 except Grenada, St. Kitts and Nevis, and Suriname, for which data limitations prevent the forecasting of GDP components.
3. Exports and imports of goods and non-factor services (GNFS).
4. Includes Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Uruguay, and Venezuela.
5. Includes Costa Rica, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, and Panama.
6. Includes Antigua and Barbuda, The Bahamas, Barbados, Belize, Dominica, Dominican Republic, Grenada, Guyana, Haiti, Jamaica, St. Kitts and Nevis, St. Lucia, St. Vincent and the
Grenadines, Suriname, and Trinidad and Tobago.
7. Recent statistical changes in the measurement of Mexico’s GDP, including a change rebasing from 2008 to 2013, has resulted in significant changes to historical growth rates comparedto June 2017.
For additional information, please see www.worldbank.org/gep.

CHAPTER 2.3

110

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

TABLE 2.3.2 Latin America and the Caribbean country forecasts1

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Source: World Bank.
Notes: e = estimate; f = forecast. World Bank forecasts are frequently updated based on new information and changing (global) circumstances. Consequently, projections presented here
may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars.
2. GDP is based on fiscal year, which runs from October to September of next year.
3. Recent statistical changes in the measurement of Mexico’s GDP, including a change rebasing from 2008 to 2013, has resulted in significant changes to historical growth rates
compared to June 2017.
For additional information, please see www.worldbank.org/gep.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

LATIN AMERICA AND THE CARIBBEAN

BOX 2.3.1 Potential growth in Latin America and the Caribbean
A sharp growth slowdown in Latin America and the Caribbean during the past five years has been accompanied by weak andslightly decelerating potential growth, in turn reflecting slowing productivity and less supportive demographic conditions. Trends
in the underlying drivers of potential growth suggest that the modest slowdown in potential growth in LAC will persist during thenext decade. This outlook underscores the necessity of policy actions that lift physical and human capital and improve
productivity.

Introduction

Evolution of potential growth and its drivers

Growth slowed sharply in Latin America and the
Caribbean (LAC) in recent years, falling from a mostrecent high of 6 percent in 2010 to -1.5 percent in 2016,
in response to the precipitous drop in global commodity
prices and domestic challenges in some of the region’slargest economies. Although the slowdown, which began
to fade in 2017, appears to have been almost entirely due
to cyclical factors, there are worrisome signs that
underlying potential growth has also fallen in recent years
compared to the long-term (1998–2017) and pre-crisis(2003–07) averages.

During 2013–17, potential growth in LAC is estimated tohave averaged only around 2.7 percent, slightly less thanthe long-term (1998–2017) average of 2.9 percent andfurther below the pre-crisis (2003–07) average of 3.1
percent (Figure 2.3.1.1; Chapter 3).1 The recent deceleration, which is robust to the choice of measure, reflects ashrinking contribution of both TFP and labor supply topotential growth, rather than a shortfall in capital
accumulation.

This slowdown in LAC’s potential growth rate raises
questions about the sustainability of the expected regional
growth recovery, and doubts about the region’s ability todeliver sustained progress on economic well-being and per
capita income convergence with advanced economies. In
light of the important policy implications of the slowdown
in potential growth, this box addresses the following
questions:xHow has potential growth evolved in the region andwhat were its main drivers?

xWhat are prospects for potential growth?

xWhat are the policy options to lift potential growth?

The box finds that the recent slowdown in potential
growth in LAC was due to weakening productivity growthand less favorable demographic conditions, which hit
South America the hardest. More worryingly, it concludes
that adverse trends are likely to cause a further slowdown
in the coming decade. Reforms to boost investment andfemale labor force participation and to improve educationand health outcomes could help offset the expected
deceleration in potential growth, but productivityenhancing reforms may be the most effective policy
approach given the longstanding weakness of total factor
productivity (TFP) in the region.

Note: This box was prepared by Dana Vorisek. Shituo Sun provided
research assistance.

Total factor productivity growth. Potential TFP growthin LAC, which has long been below that in other emerging
market and developing economy (EMDE) regions, has
steadily slowed since last peaking in 2007 due to a
combination of temporary and long-term factors. Weakinvestment during the past five years, as commodityexporting economies struggled to adapt to fallingcommodity prices, held back the absorption of
productivity-enhancing new technologies (OECD 2016b).
Worsening terms of trade, a consequence of the downturnin commodity prices during most of 2013–17, may havealso dampened TFP growth in commodity exporters in theregion, by slowing the pace of technology adoption andreducing spending on research and development (Aslam etal. 2016). This hypothesis is supported by evidence thatthe positive terms-of-trade shock during 2001–07
explained more than one-quarter of the average growthrate of TFP in Mexico, Chile, and Peru (Castillo and Rojas
2014).
Education- and skills shortcomings have had a long-term
dampening effect on productivity growth in LAC.
Although school enrollment and completion rates havesteadily risen in recent decades, completion rates,
particularly at the tertiary level, remain poor (OECD/
ECLAC/CAF 2016). Moreover, the low quality of primaryand secondary education in the region relative tointernational standards and to countries with similar levelsof per-capita income hinders productivity gains fromincreased access to education (OECD 2015; OECD/

1 Details on the production function approach to estimating potential
growth are provided in Annex 3.1.

111

112

CHAPTER 2.3

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

BOX 2.3.1 Potential growth in Latin America and the Caribbean (continued)
FIGURE 2.3.1.1 Regional growth and drivers of potential growth
Growth in LAC during 2013–17 was sharply lower than in the pre-crisis (2003–07) period or the long term (1998–2017). The
growth slowdown was accompanied by weak and slightly decelerating potential growth, reflecting decreasingly favorable
trends in its fundamental drivers.
B. Potential growth

A. Actual growth
Percent
12

LAC

Median10

Percent
10

C. Potential growth by different measures

LAC

Percent
4

Median8

8

1998-2017 average
2013-17 average

3

6

2

6

4
4
1

2

2

0

0
1998-2017

2003-07

D. Potential TFP growth
Percent
6

LAC

Median0
1998-20172013-17

2003-07PF

2013-17MVF

UVF

E. Working-age population growth

F. Investment growth

Percent
4

Percent
20

LAC

MedianLAC

Exp.

Median

15

4

2

10

2
5

0

0

0

-2

-2
1998-2017

2003-072013-17-5
1998-2017

2003-072013-17

1998-2017

2003-072013-17

Sources: Haver Analytics, national statistical agencies, Penn World Tables, UN Population Prospects, World Bank.
A. B. D. -F. Blue bars show simple averages during year spans of annual GDP-weighted averages of LAC countries. Red markers show median GDP-weighted averagesof the six EMDE regions and vertical lines denote range of regional GDP-weighted averages.
B. Potential growth is measured using the production function approach. GDP-weighted averages for a sample of 15 LAC economies and 49 EMDE economies.
C. Bars reflect estimates based on different potential growth measures. “PF” stands for potential growth estimates using the production function approach, “MVF” stands
for those derived using the multivariate filter, “UVF” for those derived using the Hodrick-Prescott filter, and “Exp.” for those based on 5-year-ahead IMF World Economic
Outlook forecasts. Details on the production function approach to estimating potential growth are provided in Annex 3.1; details on statistical filter approaches areprovided in Annex 3.2. Sample includes a consistent set of five economies: Argentina, Brazil, Chile, Mexico, and Peru.

ECLAC/CAF 2016). Weak productivity growth in LAC
also reflects still-stringent labor and product market
regulations and a high level of informality (IDB 2013).
Numerous studies have documented that weak TFP
growth has been the principal factor explaining low
potential growth in the region (Loayza, Fajnzylber, andCalderón 2005; IMF 2017f) and in individual countries.2
During the nearly half-century leading up to the financial
crisis, low TFP growth, rather than weak capital or labor
accumulation, has been the main reason for a widening
income gap between most LAC countries and the UnitedStates (Daude and Fernández-Arias 2010).
2 See, for instance, Faal (2005) on Mexico, and Ollivaud, Guillemette,and Turner (2016) on Chile.

Labor supply. Although the working-age share of the
population in LAC continues to expand marginally, therate of working-age population growth was slower during
the past five years than during the pre-crisis years or thelong term. On the other hand, female labor force
participation in LAC has risen rapidly relative to other
EMDE regions, from an average of 47 percent in 1998–
2002 to 53 percent in 2013–17. Over the long term
(1998–2017), the rise in female labor force participation
contributed 0.3 percentage point to potential growthin LAC.
Physical capital accumulation. Fixed capital investment
contracted each year between 2014 and 2017 in LAC and,in particular, South America. The deterioration in terms oftrade was a key factor underlying the investment decline,GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

LATIN AMERICA AND THE CARIBBEAN

BOX 2.3.1 Potential growth in Latin America and the Caribbean (continued)
but policy uncertainty and bouts of tightening of financial
conditions have also been important (IMF 2015, 2016d;
World Bank 2016b, 2017p). These factors werecompounded in some commodity-exporting countries by
the impact of low global commodity prices on fiscal
revenues, which led to cuts in public capital expenditures.
Comparison to other EMDE regions. Decreasingly
favorable trends in the main drivers have resulted in
potential growth in LAC lagging that of most other
EMDE regions in the past five years (Figure 2.3.1.2).
Similar to other commodity-reliant regions, such as theMiddle East and North Africa and Sub-Saharan Africa(SSA), productivity in LAC contributes very little topotential growth, and in the most recent five years has
contributed almost nothing. At the same time, labor has
begun contributing less to potential growth in LAC asworking-age population growth has decelerated, albeit
much less strongly than in East Asia and Pacific (EAP) andin Europe and Central Asia (ECA). Like in other EMDE
regions where large post-crisis investment stimulus was
implemented, such as in SSA and ECA, capital
accumulation still contributed more to potential growth in
LAC in 2013–17 than during previous periods.
Subregional patterns. The recent slowdown of potential
growth in LAC was predominantly due to the SouthAmerica subregion—by far the largest of the threesubregions in economic size, and where half of thecountries experienced a slowdown. Potential growth in
Mexico and Central America has been comparatively stable
over the past two decades. Although the contribution of
TFP to potential growth in Mexico and Central America
remains low relative to that in other EMDE regions, andwas slightly negative in 2013–17, this LAC subregion
avoided the slowdown in potential TFP growth thatlowered potential growth in South America, commodityexporting EMDEs, and EMDEs as a whole. TFP made anotably higher contribution to potential growth in the
Caribbean than in other LAC subregions.

Potential growth prospects
In the years ahead, potential growth in LAC appears set tocontinue to decelerate modestly. Demographic trends willcontinue to become less favorable. Investment growth isexpected to recover but not rapidly and not to thestimulus-fueled rates of the early 2010s. Thus, without
significant policy changes or a major productivity
breakthrough, potential growth in LAC is expected tocontinue to weaken, to an average of 2.4 percent in the

coming decade, approximately 0.4 percentage point below
the rate achieved in the past five years (Figure 2.3.1.3).
The deceleration of potential growth in 2018–27 would
result from weaker capital accumulation and labor force
growth, which would shave off slightly less than 0.3 and0.2 percentage point, respectively, of the 2.7 percent
potential growth in 2013–17, while TFP contributes
slightly more positively. The contribution of labor topotential growth will be constrained not only by aworking-age population share that is expected to peakaround 2020, but also by limited capacity for an additional
increase in region-wide female labor force participation
given already relatively high rates compared to other
EMDE regions (Sosa, Tsounta, and Kim 2013). While
investment growth is projected to recover from the recent
period of weakness, it is not expected to return to the rates
observed prior to the oil price plunge in mid-2014, partly
due to a recent rise in policy uncertainty.
Despite the continued weakness in potential growth in
LAC, a more supportive demographic profile relative tomost other regions will help LAC avoid a large slowdownof the sort in store for EAP. The prospect of decelerating
potential growth in South America raises concerns about
the sustainability of an expected recovery in actual growthin LAC driven by accelerating activity in the SouthAmerica subregion, and suggests that per capita income
convergence with advanced economies will be further
delayed.

Policy options to lift potential growth
The analysis in Chapter 3 can be used to illustrate theimpact of policies to improve physical capital and humancapital and increase labor supply (Annex 3.1). In a scenario
in which the largest 10-year improvements on record ineducation and health outcomes, investment, and female
labor force participation are repeated, potential growth in
LAC could be lifted by about 0.6 percentage point in the
coming decade, more than enough to offset the projected
deceleration in potential growth (Figure 2.3.1.4). The bulkof the impact would result from filling investment needs,
which remain large in LAC and are constrained by limited
public funds to expand investment spending(Vashakmadze et al. 2017). In such an environment,
increasing the efficiency of public investment, perhaps
through additional use of public-private partnerships or by
implementing reforms that improve the businessenvironment, is key.

113

CHAPTER 2.3

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

BOX 2.3.1 Potential growth in Latin America and the Caribbean (continued)
FIGURE 2.3.1.2 Regional potential growth
The growth slowdown in LAC in recent years, although almost entirely due to cyclical factors, was also accompanied by amodest slowdown in already-weak potential growth. The slowdown in potential growth in LAC in 2013–17, which is robust to
the choice of measure, reflected a falling contribution of labor supply and TFP. The potential growth slowdown was stronger
in South America than in other subregions.
A. Contribution of potential growth andbusiness cycle to actual growth

B. Contributions to regional potential
growthC. Contributions to subregional potential
growthPercent

Percent
10

Percent
4

Growth

6
5
4
3
2
1
0

Potential

Cycle

TFP
Labor

CapitalPotential growth

8

TFP
Labor

CapitalPotential growth

3

6
2

4

1

SA

MCA

CAR

EAP

ECA

LAC

MNA

SAR

SSA

SA

MCA

2013-17

2003-072013-17

2003-07

1998-20172013-170-1

2003-07-2

1998-20170

1998-2017
2003-072013-17
1998-2017
2003-072013-17
1998-2017
2003-072013-17
1998-2017
2003-072013-17
1998-2017
2003-072013-17
1998-2017
2003-072013-172013-17

2003-07

Contribution

2013-17

Contribution

2003-072013-17

2003-07

2
Contribution

114

CAR

Sources: Haver Analytics, Penn World Tables, UN Population Prospects, World Bank.
A. -C. Simple averages during year spans of annual GDP-weighted averages. Potential growth is measured using the production function approach.
A. C. SA = South America, MCA = Mexico and Central America, and CAR = the Caribbean. SA includes eight economies (Argentina, Brazil, Chile, Colombia, Ecuador,
Paraguay, Peru, and Uruguay), MCA includes five economies (Costa Rica, Guatemala, Honduras, Mexico, and Panama), and CAR includes three economies (Antigua
and Barbuda, Dominican Republic, and Jamaica).
B. EAP = East Asia and Pacific, ECA = Europe and Central Asia, MNA = Middle East and North Africa, SAR = South Asia, and SSA = Sub-Saharan Africa. GDP-weighted
averages for a sample of four EAP economies, 10 ECA economies, 15 LAC economies, five MNA economies, two SAR economies, and 13 SSA economies.
C. The 1998-2017 bar for the Caribbean is missing due to data availability for the Dominican Republic, the largest economy in the subregion.

In some cases, the gains from reforms in the areas
considered by the scenario analysis could be considerablylarger given relatively unsupportive current conditions. In
Mexico and a number of Central American economies, forinstance, female labor force participation is well below thatof male participation. Measures to improve access tochildcare and parental leave have been found to raise
female labor force participation in Latin America (Novta
and Wong 2017). Moreover, since Central American
economies have some of the highest child dependency
ratios and worst education attainment within LAC, thissubregion would likely benefit significantly frominvestments in education and health care. In many
countries in the region, students from the poorest
households are substantially less competent than thosefrom the richest households in reading and mathematics(World Bank 2017j). Targeting improved skills absorption
by poor students may improve productivity.
Reforms in several areas beyond the scope of the scenario
analysis also stand to boost potential growth by raisingproductivity growth:
Improve labor market functioning. Labor markets in the
LAC region have long been less flexible than in other
EMDEs. Reforms to deregulate labor markets, includingin the areas of wage determination, hiring and firingconstraints, reduction of mismatches between skills andjobs, and improved alignment of compensation withproductivity, would likely pay important productivity
dividends. Moreover, improving the quality of education
could also raise labor productivity (Ferreyra et al. 2017).
Lower informality. A key priority for the LAC region
should be to encourage a shift of resources from theinformal economy, where productivity is lower than in theformal economy (La Porta and Shleifer 2014). Indeed, a 1percentage-point drop in the share of the informal
economy has been associated with a 0.5-percentage-point
narrowing of the gap between TFP in LAC and the UnitedStates (IDB 2013). Together with better-functioning labormarkets, policy interventions that simplify businesslicensing and tax procedures, increase access to social
security systems, and lower tax rates for small and microenterprises would also help reduce informality (GarciaSaltos, Teodoru, and Zhang 2016; OECD 2017).3 The

3 For a number of countries in LAC, not only tax system reform but
also comprehensive pension system reform would strengthen potential
growth, by freeing fiscal resources for other uses and encouraging
investment through improved investor confidence.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

LATIN AMERICA AND THE CARIBBEAN

BOX 2.3.1 Potential growth in Latin America and the Caribbean (continued)
FIGURE 2.3.1.3 Regional potential growth prospects
Trends in the underlying drivers suggest that the modest slowdown in potential growth in LAC will continue during the next
decade, particularly in South America, owing to slowing labor supply growth and capital accumulation. The weakness is
expected to be broad based, with potential growth in about four out of five economies in the region expected to be below thelong-term average. Although potential growth in LAC is expected to continue to be well below the EMDE average, it is likely to
be on par with that in commodity-exporting EMDEs.

LAC

SA

MCA

CAR

SA

MCA

CAR

LAC

EMDE
commodity
exporters

2018-272018-272013-172018-272013-172018-27-1
0

2013-170

1

2013-171

2003-072

2018-27

2

CapitalPotential growth

1998-2017

3
3

TFP
Labor

Percent
6
5
4
3
2
1
0

2013-17

CapitalPotential growth

2003-07

TFP
Labor

2018-27

Percent
4

1998-20172013-17
1998-20172013-17

2003-072018-27

2003-07

Percent
4

C. Contributions to regional potential
growth

1998-2017

B. Contributions to subregional potential
growthA. Potential growth

EMDEs

Sources: Haver Analytics, Penn World Tables, UN Population Prospects, World Bank.
A. B. Simple averages during year spans of annual GDP-weighted averages. Potential growth is measured using the production function approach. SA = South America,
MCA = Mexico and Central America, and CAR = the Caribbean. GDP-weighted averages for a sample of eight economies in South America, five economies in Mexico
and Central America, and three economies in the Caribbean (as given in note below Figure 2.3.1.2).
A. The 1998-2017 average for the Caribbean is missing due to data availability for the Dominican Republic, the largest economy in the subregion.
C. Simple averages during year spans of annual GDP-weighted averages of 15 LAC economies, 29 commodity-exporting economies, and 49 EMDE economies.

experience of several LAC countries in recent years
suggests that creating conditions conducive to economic
growth is also key to lowering informality (OECD 2017).
Foster innovation. There are important opportunities tospur innovation in LAC, which underperforms other
EMDE regions in its capacity to innovate (World
Economic Forum 2017). For example, ensuring that theeducation system prepares students to identify
opportunities for innovation, supporting collaboration
between institutions where innovation occurs (firms,
universities, research institutes), and ensuring that
financing for innovation is accessible could be beneficial(Vostroknutova et al. 2015). Creating incentives for firms
to invest in knowledge may also boost productivity. Latin
American firms that invest in knowledge are found to bebetter able to innovate than those that do not, and firmsthat innovate are in turn found to have significantly higher
labor productivity than firms that do not (Crespi andZuñiga 2012; Crespi, Tacsir, and Vargas 2016).
Deepen trade integration. Despite the existence of several
extra- and intra-regional trade agreements, LAC is lessopen to trade than most of the six EMDE regions (WorldBank 2016b). Trade (exports plus imports) represented

one-third of regional GDP in LAC in 2016, compared to a
median of more than two-fifths in all EMDE regions. Nor
is the region deeply integrated into global supply chains(Estevadeordal 2012; de la Torre et al. 2015). LAC also
has one of the lowest intra-regional trade intensities, partly
because of a sparse regional road and rail network andmediocre-quality logistical services relative to otherregions. Increasing trade integration, whether throughformal trade agreements or otherwise, could lift
productivity by increasing competition and providing
opportunities for firms to specialize and to benefit from
economies of scale. In the medium to long terms,
increased trade linkages can facilitate knowledge andtechnology transfer through traded goods (Bown et al.
2017). This transfer of embedded knowledge andtechnology is key especially for the large number of small
and medium enterprises in the region (OECD 2016).
Policy interventions that enhance upstream participationin global value chains could also improve firm productivity(Montalbano, Nenci, and Pietrobelli 2016).

Conclusion
At an average of 2.7 percent in 2013–17, potential growthin LAC was weak and slightly lower than during the long-115

CHAPTER 2.3

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

BOX 2.3.1 Potential growth in Latin America and the Caribbean (concluded)
FIGURE 2.3.1.4 Policies to raise potential growth
The prospect for a further slowdown in potential growth in LAC underscores the necessity of reforms, especially reforms that
increase productivity. A combination of additional investment, education and health improvements, and labor force
participation could raise potential growth by about 0.6 percentage point. Productivity could be accelerated by reducing
informality, improving labor market flexibility, fostering innovation, and deepening trade integration.
A. Potential growth under reform
scenarios
Percent
6
5
4
3
2
1
0

Labor market reforms
Education and health improvements
Fill investment needs
Baseline

B. Firms identifying inadequately
educated workforce as biggest obstacle

C. Labor market flexibility

Percent
8

Index, 1-7 (7=best)
5

LAC

EMDEs

LAC

EMDEs

7
4

6
5

3

4

EMDEs

Reformimpact2018-272013-17

Reformimpact2018-27

3

2013-17116

Percent of formal economy
LAC
35

1
1

0
2006-12LAC

D. Informal economy

22

Index, 1-7 (7=best)4

2013-18

F. Trade

E. Innovation

EMDEs

2007-122013-17

LAC

EMDEs

30

Percent of GDP
50

LAC

Median

40

25

3

30

2

10

20

20

15

10
5

0
2011-141

0
2003-072013-142007-122013-18

2015-16

Exports

2011-142015-16

Imports

Sources: IMF Direction of Trade Statistics, World Economic Forum Global Competitiveness Index, World Bank Enterprise Surveys, World Bank.
A. Simple averages during year spans of GDP-weighted averages for 15 LAC economies and 49 EMDE economies in each year. Derived using the methodology
described in Annex 3.1.
B. Simple averages during year spans of simple averages of rates in each year. Sample includes seven LAC economies and 65 EMDE economies.
C. E. Simple averages during year spans of simple averages of scores in each year. Sample includes 26 LAC economies and 115 EMDE economies.
D. Simple averages during year spans of GDP-weighted averages in each year. Sample includes 25 LAC economies and 125 EMDE economies.
F. Blue bars show simple averages during year spans of GDP-weighted average of LAC countries in each year. Red markers show median GDP-weighted averagesof the six EMDE regions and vertical lines denote range of regional GDP-weighted averages. Sample includes 32 LAC economies and 155 EMDE economies.

term (1998–2017) and pre-crisis (2003–07) periods,
reflecting slowing productivity and less supportive
demographic conditions. Trends in the underlying driversof potential growth suggest that the modest slowdown will
persist during the next decade, particularly in SouthAmerica, owing to falling labor supply growth and capital
accumulation. Policy actions, including those targeting
longstanding weakness in TFP growth, may counter the
projected slowdown in potential growth.

Growth in the Middle East and North Africa region is estimated to slow sharply from 5.0 percent in 2016 to
1.8 percent in 2017, 0.3 percentage point lower than June projections. The impact of oil production cuts andheightened geopolitical tensions on oil exporters has more than offset a pickup among oil importers. Regional
activity is forecast to strengthen gradually over the medium term, in response to policy reforms and easing fiscal
adjustments. Key downside risks to the outlook include continued conflicts in the region, weakness in oil prices,and obstacles to reform progress, which are only partly offset by the effects of possible stronger-than-expected EuroArea activity.

Recent developments
Growth in the Middle East and North Africa(MENA) region is estimated to have declined
markedly to 1.8 percent in 2017 from 5.0 percent
in the previous year, contributed by hydrocardonsector-led growth decelerations among regional oil
exporters.1 In contrast, growth in oil importers in2017 has strengthened to 3.7 percent from theprevious year, supported by reforms and improved
competitiveness. Growth in both groups of
economies continue to face headwinds from fiscal
consolidation plans and geopolitical tensions.
Growth among the oil exporters was affected by
OPEC oil production cuts and fiscal consolidation(Figure 2.4.1). Besides the effect of a slowdown in
its oil sector following an exceptionally high 2016
surge, activity in the Islamic Republic of Iran wasdampened by weak foreign investor confidence
associated with geopolitical tensions (including

Note: This annex was prepared by Lei Sandy Ye. Research
assistance was provided by Ishita Dugar and Shituo Sun.
1 The World Bank’s Middle East and North Africa aggregate
includes 16 economies, and is grouped into three subregions.
Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United ArabEmirates comprise the Gulf Cooperation Council (GCC); all are oil
exporters. Other oil exporters in the region are Algeria, the Islamic
Republic of Iran, and Iraq. Oil importers in the region are Djibouti,
the Arab Republic of Egypt, Jordan, Lebanon, Morocco, Tunisia, andWest Bank and Gaza. The Syrian Arab Republic, the Republic of
Yemen, and Libya are excluded from regional growth aggregates due
to data limitations.

new sanctions and hardened nuclear-deal stance by
the United States). Algeria and Iraq’s growth arealso estimated to have decelerated in response to
fiscal consolidation, moderating hydrocarbon
sector growth, and weak non-oil activity. Lower
growth among the Gulf Cooperation Council(GCC) members mainly reflects lower oil output
from production cuts. Data for first half of 2017and purchasing managers’ indexes point to amodest recovery of the non-oil sector in the GCC.
In June 2017, Bahrain, Saudi Arabia, the United
Arab Emirates, and the Arab Republic of Egypt
cut diplomatic and economic ties with Qatar. Allseaborne and air travel links from the involved
countries to Qatar were shut and bank lending to
Qatar was restricted. This led to financial market
disruptions in Qatar, where non-resident deposits
have fallen by 27 percent, although thegovernment has intervened heavily by injecting
public sector deposits to the banking system. The
diplomatic rift is estimated to have weighedsomewhat on activity in Qatar in 2017, but its
impact on other neighboring economies has been
limited.
Among the region’s oil importers, growth
improved in 2017, including as a result of reforms
and improved competitiveness. Egypt experienced
strong industrial production, investment, andexports, supported by the effects of the exchange
rate devaluation on competitiveness. In Morocco,
a strong rebound in agricultural production in theCHAPTER 2.4

118

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 2.4.1
 MENA: Recent developments
Growth in MENA is expected to decelerate in 2017, driven by weakness inoil exporters. The latest oil production data show significant reductions
associated with OPEC agreement among major oil exporters. The onset of
the Qatar diplomatic rift led to Qatari nonresident deposit outflows andinterventions through public sector deposits injections. Large recent
sovereign bond financing has contributed to a rapid expansion ininternational debt securities raised by MENA economies.

A. Growth

B. Oil production: Oil exporters

Percent
8

Millions of barrels per day
25

MENA
Oil importers
Oil exporters

6

24

4
2

2017

2016

2015

2014

2013

2012

2011

2010

2016
2016 Q3
2016 Q4
Nov-16
Dec-16
Jan-17
Feb-17Mar-17
Apr-17May-17
Jun-17
Jul-17Aug-17
Sep-17Oct-17
Nov-1723
0

Riyals, billions
250
Public sector deposits in for. currency

US$, billions
350
300
250
200
150
100
50
0

2017Q2

2016Q2

2015Q2

Nov-17

Apr-17

Sep-16

Feb-16

Jul-15

Dec-14Oct-13May-14Mar-13Jan-12

Aug-12

Jun-11

Nov-100

2014Q250

2013Q2

150
100

Non-financial sector
Financial sector
General government

2012Q2

Nonresident deposits

2011Q2

D. International debt securities: MENA

2010Q2

C. Qatar: Banking deposits

200

most
other countries. An important exception is
Egypt, where inflation has risen rapidly from 2016
and remains elevated (above 25 percent, y-on-y,by November 2017). This has reflected the effectsof the currency float in November 2016, higher
food prices, and administered price hikes,
prompting the central bank to hike interest rates
twice in 2017, taking its overnight rate to 18.75
percent. These inflationary pressures have eased
somewhat, however, towards the end of 2017.

Sources: Bank for International Settlements, Haver Analytics, International Energy Agency,
World Bank.
Notes: MENA = Middle East and North Africa.
A. Weighted average growth of real GDP.
B. Sum of daily crude oil productions of the Islamic Republic of Iran, Iraq, Kuwait, Saudi Arabia,
and the United Arab Emirates. Red columns denote months since November OPEC agreement.
Blue columns denote 2016 annual, Q3, and Q4 average daily productions. Last observation isNovember 2017.
C. Data for commercial banks. Last observation is November 2017.
D. Sum of international debt securities outstanding for 14 MENA countries. Last observationis 2017Q2.

first three quarters of 2017 from severe droughts
in the previous year further supported theeconomy’s recovery. Tunisia has experienced
gradualrecoveriesinagriculturalandmanufacturing sectors. Policy reforms in theregion have helped boost domestic business
confidence and foreign investment. Coupled with
an improvement in net exports, foreign reserves
have risen and current account deficits appear tohave remained stable in 2017 for some oil
importers.
Inflation is generally well-contained across the
MENA region, averaging less than 3 percent(monthly y-on-y) in the GCC, as well as easing in

Financial sector developments within the MENA
region have been generally favorable. Equity
market indexes in the GCC remained stable in2017, notwithstanding the effects of the disputewith Qatar. And despite the shadow ofgeopoliticaltensions,
long-term
investor
confidence has been bolstered by reforms toforeign investment accessibility and capital market
development (e.g., leading to the potential
inclusion of Saudi Arabia in the MSCI EM index
in 2018 and supporting the economy’s planned
IPO of Aramco), as well as large sovereignissuances, contributing to a rapid expansion ininternational debt securities (Lorente, Ismail, andSchmukler 2016). Banking sector liquidity in oil
exporters has generally eased in 2017 relative tothe previous year, as higher oil prices havesupported higher government deposits.
Fiscal and structural weaknesses remain key
challenges in many MENA countries. However,supported by IMF and World Bank programs,
many economies (e.g., Egypt, Morocco) have
improved their fiscal positions. These efforts wereaccompanied by broader reforms, such as steps toimprove the functioning of labor markets, which
promise to boost overall and female labor force
participation in the region and spur stronger longterm growth (Chapter 3). Business climate
reforms, such as measures to ease businessregistration and to strengthen investor protection,
have also been introduced across both oil exporters
and importers.

Outlook
Regional growth is projected to increase steadily
after 2017, to 3.0 percent in 2018 and 3.2 percent
by 2020, reflecting accelerations among both oil

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Forward-looking indicators suggest stable momentum in the corporate
sector of the GCC. Elevated debt burdens of oil importers serve as aheadwind to medium-term growth for the region. Potential growth in theregion is expected to be supported by reforms, but is limited by a range of
obstacles to private sector activity. The region faces downside risks fromheightened geopolitical tensions, which may deter tourism, and upsiderisks from stronger-than-expected activity in the Euro Area.
A. Equity market indexes: GCC

B. Government debt positions

Index, 100=Jan. 2013
300

Percent of GDP
100

250

80

60

150
100

40

50

20

Fiscal balances are expected to improve further
over 2018-2020, reflecting plans for reducing
subsidies and tax increases in many economies(e.g., a GCC-wide VAT tax of 5 percent isscheduled to launch in 2018), as well as the effects
of somewhat higher oil prices on revenues among
the oil exporters. Current account balances in the
MENA region are also expected to strengthen as a

C. Tourism growth

D. Private sector constraints:
Enterprise surveys

Percent, year-on-year, 6-month moving average
Egypt
UAE
MoroccoJordan60

Percent of firms
30

2019

2018

2017

2016

2015

2014

2013

2012

2011

0

2010

Jul-17

Nov-17Mar-17

Jul-16

Nov-16

Mar-16

Jul-15

Nov-15Mar-15

Jul-14

Nov-14

0

25

30

20

0

15
10

-30

5
0
Political Electricity
instability

Accesstofinance

Tax
rates

Corruption

Percent
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0

Advanced economies

50
40
30
20
10
GCC

Non-GCC oil
exporters

Oil importers

2017

Jan-17

EMDEs

2018

2019

2020

Jul-17

Percent60

Apr-17

F. Euro Area consensus growthforecasts

Oct-16

E. Women labor force participation
rate

Oct-17Oct-17Oct-16

Apr-17Oct-15

Apr-16

Apr-15Oct-14Apr-14Oct-13Oct-12-60

Apr-13Growth among oil importers is expected to further
improve over 2018-20, as business and consumer
confidence are boosted by reforms and as external
demand improves. A key challenge to growthamong these countries stems from their elevatedlevels of public debt, which will require cuts inpublic spending and infrastructure investment.
The collapse in world oil prices has helped spurneeded reforms of energy subsidies and other fiscal
adjustments (see Special Focus 1). Moreover, in
Egypt, the move to a floating exchange rate has
improved competitiveness and provided a needed
boost to industrial activity and exports, which are
expected to strengthen further as the businessclimate improves. Lastly, there is scope for afurther recovery of tourism, an important revenue
source in oil importers (e.g., Egypt and Morocco),
if geopolitical tensions remain contained.

GCC
Non-GCC oil exportersers
Oil importers

200

Mar-14The pickup in growth among oil exporters would
be led by the GCC economies. Growth in the
GCC is expected to reach 2.7 percent by 2020,
supported by easing fiscal adjustments,
infrastructure investment (e.g., Dubai Expo 2020;
Qatar World Cup 2022), and reforms to promote
non-oil sector activity. Equity market indexes in
the GCC suggest stable business prospects in thecorporate sector (Figure 2.4.2). Growth in theIslamic Republic of Iran, the second largest
economy in the region, is expected to reach 4.3
percent by 2020, with higher investment growth
offset by lower oil production and limited accessto finance. In Algeria, new government investment
spending associated with the 2018 budget and amore expansionary fiscal stance than previously
planned is expected to raise growth in the shortterm. Iraq’s activity is expected to improve amid
more favorable security conditions.

119

FIGURE
2.4.2 MENA: Outlook and risks

Nov-13exporters
and importers. This forecast reflects
assumption of a moderation of geopoliticaltensions as well as a modest rise in oil prices.

MIDDLE EAST AND NORTH AFRICA

Forecast date

Sources: Consensus Economics, Haver Analytics, International Monetary Fund, World Bank.
A. Sample includes Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates.
Last observation is November 2017. Unweighted average. Shading denotes range.
B. General government gross debt. GCC, non-GCC oil exporters, and oil importers include 6, 3, and6 economies, respectively. Unweighted averages. Shaded area denotes forecasts.
C. Growth of tourist arrivals for Egypt, Jordan, and Morocco. Data for the United Arab Emirates
denote hotel guest arrivals in Abu Dhabi.
D. Percent of firms citing each noted indicator as biggest obstacle. Unweighted averages. Based on
the World Bank’s enterprise surveys for 9 MENA economies and latest available data since 2011 foreach country.
E. Workforce as a percent of female population ages 15+. Unweighted average of 5 GCC economies,
2 Non-GCC oil exporters, and 5 oil importers. Based on latest available data since 2010 for eachcountry.
F. Annual consensus growth forecasts for each year denoted in the legend. 2017 denotes estimates.
X-axis denotes the date for which the forecast is conducted.

120

CHAPTER 2.4

resultof stronger external demand, higher oilprices (for oil exporters), and the effects of fiscal
consolidation. Remittance inflows are expected tobe supported by strength in Euro Area activity andconfidence in exchange rate stability in Egypt(World Bank 2017t).

Risks
The risks to the outlook, while varying between oil
exporters and importers, are generally to thedownside. The regional outlook faces four mainrisks: amplification of geopolitical tensions, weak
momentum in oil prices, obstacles to reform
progress, and stronger-than-expected Euro Area
activity. Geopolitical risks remain elevated, and arecomplicated by a variety of intra-regional
diplomatic tensions. These risks may weigh on
growth prospects and may harm investor
confidence in the MENA region, reducing
investment, driving up sovereign bond spreads,
and complicating the prospects for achieving
needed fiscal adjustments.
While economic conditions appear to be
improving among the oil importers, theirprospects are vulnerable to spillovers from armed
conflicts in fragile economies (e.g., Libya, Syrian
Arab Republic, Republic of Yemen), such as via
disruptions of trade routes or reduction of crossborder investment. These conflicts have also
challenged residents’ basic access to food services,education, and health (e.g., cholera outbreak in
the Republic of Yemen). Furthermore, theprotracted displacement of people in the fragile
economies has generated a refugee crisis that not
only raised the macroeconomic challenges (e.g.,
structural changes to labor markets) for hostcountries like Djibouti, Jordan, and Lebanon, but
also
amplifiedfundamental
development
challenges in education, health, jobs, water, andlivelihood for refugees, such as through expansionof health service delivery (World Bank 2017u).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Weaker-than-expected
global oil prices mayfurther cloud growth prospects for the MENA
region’s oil exporters. It remains to be seen
whether OPEC and non-OPEC production cuts
will affect prices in light of the fact that U.S. oilinventories remain at high levels, despite
stabilizing recently. This suggests the risk that if
compliance with the agreement waivers, world oil
prices could fall, complicating the ability toachieve planned fiscal adjustments and weakening
growth.
Although reforms are expected to support
potential growth and enhance the business climate
environment, the pace of improvement may beconstrained by obstacles to private sector activity,
such as political instability and electricity
deficiencies (World Bank 2016k). This is further
complicated by high youth unemployment andlow labor force participation rates, especiallyamong women (Box 2.4.1 and Chapter 3;
Schiffbauer et al. 2015). Multi-year public-private
financing initiatives in the region, such as theInternational
Finance
Corporation’s
newinvestment and technical assistance in Egypt’s
solar capacity, are expected to alleviate these
constraints by facilitating private sector
participation.
On the upside, stronger-than-expected economic
activity in the Euro Area would provide animportant support to growth in the MENA
region. A number of economies in North Africa(e.g., Tunisia) are heavily dependent on theEuropean Union (EU) for trade, remittances, or
financial flows, and stronger-than-expected
activity in the Euro Area is already expected tosupport the recovery of these economies (WorldBank 2017p; chapter 1). It is also capable ofoffsetting the potential negative spillovers of weakgrowth in the GCC, from which some (e.g.,
Jordan, Lebanon) are also dependent on
remittances and foreign direct investment.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

MIDDLE EAST AND NORTH AFRICA

TABLE
2.4.1 Middle East and North Africa forecast summary
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Source: World Bank.
Notes: e = estimate; f = forecast. EMDE = emerging market and developing economy. World Bank forecasts are frequently updated based on new information. Consequently, projections
presented here may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars. Excludes Libya, the Syrian Arab Republic, and the Republic of Yemen due to data
limitations.
2. Aggregate includes all countries in notes 4 and 6 except Djibouti, Iraq, Qatar, and West Bank and Gaza, for which data limitations prevent the forecasting of GDP components.
3. Exports and imports of goods and non-factor services (GNFS).
4. Oil exporters include Algeria, Bahrain, Iraq, the Islamic Republic of Iran, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates.
5. The Gulf Cooperation Council (GCC) includes Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates.
6. Oil importers include Djibouti, Egypt, Jordan, Lebanon, Morocco, Tunisia, and West Bank and Gaza.
7. The fiscal year runs from July 1 to June 30 in Egypt; the column labeled 2017 reflects the fiscal year ended June 30, 2017.
For additional information, please see www.worldbank.org/gep.

122

CHAPTER 2.4

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

TABLE 2.4.2 Middle East and North Africa economy forecasts1
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Notes: e = estimate; f = forecast. World Bank forecasts are frequently updated based on new information. Consequently, projections presented here may differ from those contained in other
Bank documents, even if basic assessments of countries’ prospects do not differ at any given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars. Excludes Libya, the Syrian Arab Republic, and the Republic of Yemen due to data
limitations.
2. The fiscal year runs from July 1 to June 30 in Egypt; the column labeled 2017 reflects the fiscal year ended June 30, 2017.
For additional information, please see www.worldbank.org/gep.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

MIDDLE EAST AND NORTH AFRICA

123


BOX
2.4.1 Potential growth in the Middle East and North AfricaThe Middle East and North Africa’s (MENA) potential growth has been held back by structural challenges over the past decade.
These include low labor force participation (especially of women), low economic diversification outside of oil production, andweak private sector dynamism. Potential growth in the region is expected to strengthen somewhat in the coming years, supported
bycommitment
to reforms, such as those aimed at encouraging
 recovery in investment and productivity growth. Continued
diversification, improving governance and business climates, and strengthening fiscal management, has the potential to further
improve potential growth.

Introduction
Growth has been uneven over the past decade in the
Middle East and North Africa (MENA) region. Like otheremerging market and developing economies (EMDEs), theregion experienced high growth during 2003-07, which in
MENA’s case was supported by rising oil prices. However,growth slowed during 2010-14, mainly in response to theeffects of political turmoil and military conflict, including
Arab Spring revolutions in Egypt, Tunisia, Libya, andYemen and associated conflict spillovers to neighboring
countries, civil wars in Iraq and Syria, and the war on ISIS
that halted economic activity and trade. Growth
performance decelerated further after the oil price collapseof 2014 (Figure 2.4.1.1).
A key policy question for the region is whether thisslowdown has been a temporary phenomenon or reflects
deeper-seated structural impediments that will need to be
tackled, especially in the context of subdued oil prices.
Against this backdrop, this box will discuss the following
questions:xHow has potential growth evolved in the MENA
region and what were its main drivers?

xWhat are the prospects for potential growth?

xWhat are the policy options to lift potential growth?

The literature covering these issues is sparse, but has
documented a broad-based decline in potential growthwithin the MENA region, including both oil exporters andoil importers. Moreover, relative to the EMDE average,
this deterioration has been more severe, reflecting low totalfactor productivity growth and labor supply growth(Mitra et al. 2015; Alkhareif and Alsadoun 2016; IMF
2016e; IMF 2017g). These studies have underscored thatreversing these trends requires policies to boost
investment, especially in oil importers, as well as steps toimprove the business environment, strengthen worker
Note: This box was prepared by Lei Sandy Ye, Sinem Kilic Celik, andModeste Some. Ishita Dugar and Shituo Sun provided research
assistance.

skills, and deepen financial markets (Mitra et al. 2016;
World Bank 2017v).
The analysis here also highlights that the MENA region’spoor growth performance in recent years has been largely
driven by a slowdown in its potential growth, in turndriven by broad-based decelerations in capital stock
growth, weak total factor productivity (TFP) growth
relative to other regions, and slowing working-age
population growth. It highlights, however, that a commitment to structural reforms would help improve potential
growth and provide greater scope for improvements inliving standards within the region.

Evolution of potential growth and its drivers
Growth in the MENA region declined sharply from 6
percent prior to the global financial crisis (2003-2007) toabout 3 percent in 2013-17, and empirical analysis
suggests that this was in large part the result of adeceleration of the region’s potential growth, a slowdown
that was more severe than those experienced by other
EMDEs. A production function approach and analternative estimate based on long-term (5-year-ahead)
growth expectations suggest that potential growth during
2013-17 has fallen below its long-term average (19982017) rate of about 4 percent (Figure 2.4.1.2).
The recent decline in potential growth occurred against
the backdrop of high geopolitical tensions, volatile oil
prices, high structural imbalances, and conflict within theregion, factors that have contributed to the region’s
relatively lackluster potential growth performance for atleast two decades. However, an important factor behindthe more recent slowdown has been investment growth,which more than halved in recent years. In fragile areas of
the region, this was compounded by the outrightdestruction of capital (World Bank 2017w).1 Also

1 In the fragile areas, prolonged crises impose large negative impact on
potential output in the short run, followed by a prolonged period of slow
growth as economies adjust to their post-crisis growth paths. These
countries face a “permanent level loss” in the potential output meaningthat the economy eventually would return to its pre-crisis potential
growth rate but would fail to recoup all of the lost output.

CHAPTER 2.4

124

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.4.1 Potential growth in the Middle East and North Africa (continued)


FIGURE 2.4.1.1 MENA potential growthThe slowdown of MENA’s regional output growth in recent years has partly resulted from a decline in its potential growth rate.
A wide range of factors have underpinned this slowdown, including weak investment, persistently low productivity growth,and slowing working-age population growth.
A. Output growth
Percent

MENA

Median15

B. Potential growth decomposition

C. Working-age population growth

Percent
8

Percent
4

6

TFP

CapitalLabor

Potential growth
wth

MENA

Median

4
2

2

10

0

1998-2017

2003-072013-172018-272013-17

2003-072018-272013-17

EMDE

1998-20170

2003-07

1998-2017

-2
5

0

-2
MENA

1998-2017

2003-072013-17

Sources: International Monetary Fund, Penn World Tables, United Nations, World Bank estimates.
Notes: GDP-weighted averages.
A. C. Red markers show median GDP-weighted averages of the six EMDE regions and whiskers denote range of regional GDP-weighted averages.
B. Estimates based on the production function approach for 50 EMDEs and 7 MENA economies. See Annex 3.1 for more details.
C. Working-age population refers to population of ages 15-64.

contributing were a continued slowdown in labor supply
growth and stagnant TFP, the latter related to the region’shigh reliance on oil production and corresponding lack of
economic dynamism.
While the slowdown in potential growth is broad-based
across oil exporters and importers, the relative importanceof contributing factors varies. In oil exporters, TFP growthhas been negative (partly reflecting low labor market
efficiency and subsidized energy), capital growth is weak,and employment growth is declining. In oil importers,
while TFP, labor supply, and capital growth are all
slowing, low investment growth is especially a concern.
However, common to the entire region are female labor
force participation rates that are among the lowest in theworld. For example, women make up half the populationin the GCC and yet represent only about one-fourth of thelabor force (Constant 2016). Overall labor force
participation rates are also very low outside of the GCC.
Moreover, while educational attainment has risen during
the post-crisis period, the quality of education, such asmeasured by primary school proficiency tests, remains low
compared to most other regions (World Bank 2017j).

Potential growth: prospects and policy options
Over the coming years, potential growth in the region is
expected to strengthen somewhat from its 2013-17 averagerate of 2.9 percent. This is predicated upon trend
improvements in educational and health outcomes,
median fertility projections in population dynamics (as in
the UN Population Projections), and continued
investment growth at its long-term average rate (Annex
3.1). While projected change in demographic structure is
expected to weigh on potential growth, the long-term
trajectory of potential growth is marked by considerable
uncertainty. For example, unlike many other EMDEs, theyouth share of population is currently high (more than athird of the region’s population is under the age of 25).
This generates a large potential pool of new entrants into
the labor force as well as a large consumer base forinnovative activity, despite an aging population structure.
But such capacity can only be realized to boost potential
growth if the private sector is sufficiently vibrant, such as
having a flexible labor market and more educatedworkforce, to create new jobs.
Raising private-sector participation. Looking ahead, thechallenge for the region is to tackle the deep-seatedstructural impediments to sustained and private sector-led
growth, the type of growth that allows job creation to
support higher per-capita living standards. This will requirepolicies to promote economic diversification; measures toimprove the business climate (e.g., the recent introductionof the investment law and industrial licensing act in Egypt
and a bankruptcy protection law in the United ArabGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

MIDDLE EAST AND NORTH AFRICA

125


BOX
2.4.1 Potential growth in the Middle East and North Africa (continued)Emirates); financial sector deepening; and policies topromote education and skills development.

FIGURE 2.4.1.2 MENA potential growthThe slowdown in MENA’s potential growth coincidedwith that of other EMDEs. Both production function and
expectations-based measures suggest that post-crisis
potential growth was substantially weaker than longterm average potential growth.
A. Potential growth
Percent

2003-072013-172018-27

1998-20177

Reconstruction investment. In fragile economies of the region,reconstruction investment that maintains adequate
provision of health, education, electricity, water andsanitation services, remains a high priority (World Bank
2017w). In host countries of refugees, these efforts require
adapting to the structural changes that the refugee crisishas brought to their economies, such as adopting moreinnovative financing mechanisms to fund higher demands
for health service delivery (World Bank 2017u).

6
5
4
3
2

1
0
EMDEs

MENA

B. MENA potential growth: Alternative estimates
Percent

1998-20172013-17

5

4

3

2

1

0
PF

Exp.

Sources: International Monetary Fund, World Bank estimates.
Notes: GDP-weighted averages.
A. Production function approach based on 50 EMDEs and 7 MENA
economies. See Annex 3.1 for more details.
B. “PF” refers to production function approach (7 economies). “Exp.” refers
to potential growth based on long-term IMF WEO (5-year-ahead) growth
expectations (16 economies).

Improving public sector efficiency. Improving the quality
and effectiveness of government will have to be an
important part of the reform effort, especially in anenvironment where fiscal space is limited, public sector
employment is excessive, revenue systems are over reliant
on oil revenues, and energy subsidies are high. This will
require measures to improve the efficiency of public
investment, ensuring that broader spending programs
deliver “value for money,” and a careful review of revenue
systems to enhance tax administrations, improve
compliance, and cut wasteful and ineffective tax incentives.
Improving governance. Strengthening potential growth
also relies on improving the governance environment, as
weak governance in the MENA region has been found to
crowd-out private investment and discourage privatesector growth (Nabli 2007; Benhassine et al. 2009).
Improved governance, such as more structured
measurement of results in training and educational
programs, enhances the match of skills across workers andemployers and may provide more quality jobs in theprivate sector (Gatti et al. 2013). Weak governance may
also be reflected in perceived corruption, which is among ahighly-cited constraint to business activity in MENA basedon the World Bank’s Enterprise Surveys. Higher levels ofcorruption are associated with lower employment andproductivity and may discourage interactions between
private firms and public authorities, subsequently deterring
allocative efficiency (World Bank 2016k). Strengthening
the legal framework, including in areas such as corporate
governance and bankruptcy resolution, can alleviate these
constraints and facilitate market transactions.
Cross-country experience suggests that education, health,and labor market reforms can yield significant benefits interms of higher potential growth (Chapter 3). A scenario
analysis applied to the MENA region suggests that labormarket policies to raise the female labor force participation
rates by its largest 10-year improvement historically couldCHAPTER 2.4

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018



BOX 2.4.1 Potential growth in the Middle East and North Africa (concluded)Potential growth in MENA is expected to strengthen
somewhat over the coming years, partly reflecting
improvements in investment and productivity. However,reforms that boost investment, labor market
participation, or educational and health outcomes havethe capability to further improve potential growth.
A. MENA potential growth
Percent
6

Baseline

Demographic trends
Demog

Other factors
ctors

5
4
3
2
1

EMDEs

2018-27

Contribution

2013-170

2018-27

The MENA region has made substantial progress in
structural reforms in recent years, including theformulation of national development plans to encourage
inclusion of women in the workforce (Constant 2016).2
Multi-pronged
approaches
throughdiagnostics,
investment climate assessment, value-chain analysis, andlabor skills review in areas like North Lebanon may also
help lay the foundation for job creation (World Bank
2017x). Early childhood education programs in Morocco
are expected to help boost educational attainment. The
continued commitment to implementing these reforms
will be critical for realizing higher potential growth
dividends in the coming years.

FIGURE 2.4.1.3 Policies to stem weakness
in potential growth

Contribution

lift potential growth by 0.1 percentage point, while similar
steps to address gaps in investment could yield a further
0.5 percentage point (Figure 2.4.1.3). If policy reforms
were stronger than historical improvements, the gains
realized from these policies could be substantially greater.

2013-17126

MENA

B. MENA potential growth under reform scenarios
Percent
6

5

Labor market reforms
Education and health improvements
Educa
ments
Fill inv
investment needs
Baseline
Baseli4
32
102013-17 2018-27
2 The World Bank and other international financial institutions havealso participated in these efforts, such as by adopting the Women
Entrepreneurs Finance (We-Fi) initiative, a multilateral financing facility;
the Tunisia Youth Economic Inclusion Project to boost young workers’
prospects; the Jordan Innovative Startups Fund Project to boost
entrepreneurship; or the Concessional Financing Facility (WB-UNIslamic Development Bank) to facilitate refugee host country
development.

EMDEs

Reformimpact2013-17 2018-27

Reformimpact

MENA

Source: World Bank estimates.
Notes: GDP-weighted averages. Derived using the production function-based
estimates of potential growth (see Annex 3.1).
A. “Other factors” reflects changes unrelated to population structure. See
Annex 3.1. for methodology.
B. Policy scenarios are described in methodological Annex 3.1.

In South Asia, growth slowed to a still strong 6.5 percent in 2017, below the June forecast, in part reflecting
adjustment in India to the new Goods and Services Tax and the adverse impact of natural disasters across theregion. Growth is expected to stabilize around 7 percent a year over 2018-2020, with private consumption
remaining strong and investment recovered by infrastructure projects and reforms. Main risks to the outlook
include setbacks in reviving investment, fiscal slippages, and disruptions to activity resulting from natural
disasters.

Recent developments
In South Asia, growth slowed to an estimated 6.5
percent in 2017, marginally below the June 2017
forecast owing to temporary disruptions fromadverse weather conditions across the region and,in India, businesses’ adjustment to the newly
introduced Goods and Services Tax (GST).
Domestic demand continued to drive growth,with strong private consumption and a public
infrastructure spending push in India while net
exports subtracted slightly from GDP growth.
Elevated credit growth continued to support
investment in some countries (e.g., Bangladesh,Pakistan).
In India, growth slowed for the fifth consecutive
quarter to 5.7 percent (year-on-year) in the firstquarter of FY2017/18 (April-June 2017), partly
reflecting adjustments by businesses to theprospective introduction of the GST in July 2017.
In addition, protracted balance sheet weaknesses—
in particular, a corporate debt overhang andelevated non-performing loans in the banking
sector—continued to weigh on already weak
private investment (World Bank 2017y). Weakprivate investment was only partly mitigated by apublic infrastructure investment push and a surge
in current expenditures after recent public pay
hikes. In the second quarter of FY2017/18 (July-

Note: This section was prepared by Temel Taskin. Research
assistance was provided by Anh Mai Bui, Ishita Dugar, and Jinxin
Wu.

September 2017), the slowdown in economic
activity bottomed out by a still weak 6.3 percent(year-on-year) growth. The manufacturing
Purchasing Managers’ Index (PMI) and industrial
production growth remained broadly expansionary
after they temporarily weakened as producers
reduced inventories amid uncertainty relating to
the implementation of the GST (Figure 2.5.1).
Despite a recent uptick, inflation remained within
the Reserve Bank of India’s (RBI) target band of
2-6 percent, following a steady decline over the
past year to 1.3 percent in July amid weak foodprices. Fiscal consolidation has continued in thecentral government, but subnational fiscal deficits
have risen, partly reflecting debt payments takenover through Ujwal Discom Assurance Yojana(UDAY) and a broader shift in public expenditures from central to state governments, andrecent public pay hikes.1
In Pakistan, growth continued to accelerate in
FY2016/17 (July-June) to 5.3 percent, somewhat
below the government’s target of 5.7 percent as
industrial sector growth was slower than expected.
Activity was strong in construction and services,and there was a recovery in agricultural production
with a return of normal monsoon rains. In thefirst half of FY2017/18, activity has continued to
expand, driven by robust domestic demand
supported by strong credit growth and investment

1 UDAY is a financial turnaround and operational improvement
program for power sector in India. It was approved by theGovernment of India on November 5, 2015.

CHAPTER 2.5

128

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 2.5.1
 SAR: Recent developments
Credit growth has remained broadly robust and has supported investmentin the region. Exports have picked up amid stronger global demand.
Purchasing Manager Surveys suggest strengthening activity, especially in
manufacturing. Inflation rates are below historical averages. Progress infiscal consolidation has been mixed.
A. Credit to private sector

B. Exports

Percent, year-on-year
25

Percent, year-on-year
20

20

10
15

manufacturing
and services sectors. Robust private
consumption was complemented by strong public
investment growth.
In Sri Lanka, activity expanded at an estimated 4.1
percent in 2017, below the June forecast as a resultof disruptions from droughts and floods. Despite
monetary policy tightening to ease inflationarypressures in the first half of 2017, credit growth
remained strong, supporting private consumption
and investment.

0

10
5
2017

2016
2017Q1
2017Q2
2017Q3

2016
2017Q1
2017Q2
2017Q3

2016
2017Q1
2017Q2
2017Q3

2016
2017Q1
2017Q2
2017Q3-10

Sri Lanka

Bangladesh

India

Pakistan

Sri Lanka

Bangladesh

India

2016

2017

2016

2017

2016

2017

2016

0

Pakistan

C. Purchasing Managers’ Index ofIndia

D. Industrial production

Index, 50+ = expansion
60
Manufacturing

Percent, year-on-year

Percent, year-on-year

20

Sri Lanka (RHS)

Services

India

Pakistan

25

15

10
50

5

0

-5

Apr-17

2014
2015
2016
2017

India

Pakistan

Sri Lanka

Nepal

Oct-17Oct-16

2014
2015
2016
2017

Apr-16

2014
2015
2016
2017

Bangladesh

Oct-15
2014
2015
2016
2017

Apr-15

Nov-17May-17

Nov-16May-16

Nov-15May-15

E. Inflation

-15

2014
2015
2016
2017

-10

40

F. Fiscal balances

Percent, year-on-year10

2008-17 average

Percent of GDP
2

8

0

6

-2

4

-4

2

-6

2015
2016
2017

2015
2016
2017

2015
2016
2017

2015
2016
2017

0

Bangladesh

India

Pakistan

Sri Lanka-8

Elsewhere in the region, activity in 2017 wasunderpinned by strong construction in Bhutan
and the Maldives as large-scale infrastructure
projects were implemented. In Nepal, floods inmore than one-third of the country disrupted thestrong post-earthquake recovery in the second halfof 2017. Security concerns continued to weigh on
activity in Afghanistan, with the number ofcivilian casualties and displaced people reachingrecord levels in 2017.

Sources: Haver Analytics, World Bank.
A. 2017 data represent average year-on-year growth. Last observation is October 2017 for
Bangladesh, India and Pakistan, and November 2017 for Sri Lanka.
B. Last observation is Q3 2017.
C. Index values higher than 50 indicate expansion. Last observation is November 2017.
D. Last observation is October 2017 for India and Sri Lanka, and September 2017 for Pakistan.
E. Last observation is November 2017 for India and Pakistan, and October 2017 for Bangladesh
and Sri Lanka. Due to lack of data, average for Bangladesh is 2009-17 and average for Sri Lanka
is 2015-17.
F. 2017 data are estimated values.

projects related to the China-Pakistan Economic
Corridor. Meanwhile, the current account deficit
widened to 4.1 percent of GDP compared to 1.7
percent last year, amid weak exports and buoyant
imports.
Bangladesh’s growth in FY2016/17 (July-June)was 7.2 percent, exceeding the June forecast owing
to higher-than-expected outturns in the

Inflation has been well below its historical averagein the region, except for a drought-related
temporary rise in 2017 in Sri Lanka. Outside
India, fiscal consolidation slowed in 2017 as aresult of revenue shortfalls and increased
government spending (e.g., Maldives, Pakistan).
Current account deficits gradually widened acrossthe region (e.g., India, Bangladesh, Pakistan).
Balance sheet weakness for corporates (e.g., India)
and financial sectors (e.g., Bangladesh, India)
continued to weigh on private investment. In
particular, non-performing loan ratios remained
high, at around 10 percent, despite progress insome countries (e.g., Maldives, Pakistan,
Afghanistan).

Outlook
The region’s growth prospects appear robust, withhousehold consumption expected to remainstrong, exports expected to recover, andinvestment projected to revive with the support ofpolicy reforms and infrastructure improvements(Figure 2.5.2). Growth in the region is expected topick up to 6.9 percent in 2018, and stabilize
around 7.2 percent over the medium term, but
remain slightly below June projections due to theweaker-than-expected recovery in domestic

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Growth in the region excluding India is expected
to remain stable at an average 5.9 percent a year
over the medium term, broadly consistent with
the June projections, as domestic demand remains
robust and exports recover. In Pakistan, growth isforecast to pick up to 5.5 percent in FY2017/18,
and reach at an average 5.9 percent a year over the
medium term on the back of continued robust
domestic consumption, rising investment, and arecovery in exports. Activity in Bangladesh will
2 A more detailed discussion on the policies to lift growth over the
medium-to-long-term growth is provided in Box 2.5.1 and Chapter 3.
3 The Government of India announced a large recapitalization
program ($ 32 billon) for public sector banks in October. The
program is expected to be implemented within two years and planned
to be financed by recapitalization bonds and budget support.

Growth in the region is forecast to pick up to 6.9 percent in 2018, andstabilize around 7 percent a year over the medium term. Domestic demand
will continue to be the main driver of the growth in the region. Nonperforming loans remain high in South Asia.

B. Growth in remittance inflows

A. Growth

Percent
25

2003-08 averageg2003-08 average
2016

2009-15 average

15

5
-5

Pakistan Bangladesh Sri Lanka

SAR

C. Contributions to growth in SAR

10Sri Lanka

Nepal

Pakistan

D. Non-performing loans

Imports
Exports
Gross fixed investment
tment
Government consumption
sumption
Private consumption
tion
GDP

Percent
15

India

2016
2017
2018
2019
2020

2016
2017
2018
2019
2020

2016
2017
2018
2019
2020

-15

Bangladesh

India

1990-2008 averagegJuneJe 2017 forecast
cast

2016
2017
2018
2019
2020

Percent
9
8
7
6
5
4
3
2
1
0
2016
2017
2018
2019
2020

Percent of total loans
20
Last

2008-16 average

15
10

5

5

Sources: Haver Analytics, International Monetary Fund, World Bank.
A. Shaded area indicates forecasts.
B. Last observation is 2016.
C. SAR = South Asia Region. Shaded area indicates forecasts.
D. Last observation is 2015 for Bhutan and Bangladesh, and 2016 for the others.

grow at an average of 6.7 percent a year over
FY2018-2020, benefiting from strong domestic
demand and strengthening exports. Low interest
rates and improved infrastructure are expected tolift investment. Remittances are expected torebound as the growth firms in Gulf Cooperation
Council (GCC) countries and support private
consumption.
Growth in Sri Lanka is forecast to average 5.1
percent a year over 2018-2020, mainly reflecting
strong private consumption and investment
growth. Exports will be supported by thereinstatement of the Generalised Scheme ofPreferences (GSP+) with the European Union.
Elsewhere in the region, Bhutan’s GDP is
expected to expand 6.7 percent in FY2017/18 andreach an average 7.6 percent a year toward 2020,
supported by hydropower-related construction
and policies supporting the private sector, such as

Sri Lanka

Maldives

PakistanIndia

BhutanBangladesh

2020

2019

2018

2017

2016

2015

-5

Afghanistan

0

0

2014

India’s GDP is forecast to grow 6.7 percent in
FY2017/18, below June projections due to shortterm disruptions from the newly introduced GST.
Growth will pick up to 7.3 percent in 2018/19,
and to 7.5 percent a year in the medium term.
Strong private consumption and services are
expected to continue to support economic activity.
Private investment is expected to revive as thecorporate sector adjusts to the GST; infrastructure
spending increases, partly to improve public
services and internet connectivity; and private
sector balance sheet weaknesses are mitigated withthe help of the efforts of the government and theReserve Bank of India (RBI 2017). Over the
medium term, the GST is expected to benefit
economic activity and fiscal sustainability by
reducing the cost of complying with multiple state
tax systems, drawing informal activity into theformal sector, and expanding the tax base.2 The
recent recapitalization package for public sectorbanks announced by the Government of India is
expected to help resolve banking sector balance
sheets, support credit to the private sector, and lift
investment.3 The global trade recovery is expected
to lift exports.

129

FIGURE
2.5.2 SAR: Outlook and risks
2013

demand(World Bank 2017e). The forecastassumes strengthening external demand as therecovery firms in advanced economies, andsupportive global financing conditions. Monetary
policy is assumed to remain accommodative as
modest fiscal consolidation proceeds in somecountries (e.g., India).

SOUTH ASIA

130

CHAPTER 2.5

improving
the ease of doing business, supporting
research and development, promoting publicprivate partnerships in infrastructure projects, andimproving access to skilled labor (RGOB 2016).
Activity in Maldives is forecast to expand by 4.9
percent a year, on average, over the medium term,
mainly driven by strong construction, tourism,and FDI inflows. In Nepal, growth is expected tosettle at 4.5 percent a year, on average, in themedium term as post-earthquake reconstruction
winds down. Growth in Afghanistan is forecast at
3.4 percent in 2018 to and average around 3.1
percent a year over the medium term, assuming nofurther deterioration in the security situation.

Risks
The main risks to the outlook are domestic,
including fiscal slippages (e.g., Bangladesh,
Maldives, Pakistan), setbacks to reforms to resolve
corporate and financial sector balance sheet
deterioration (e.g. Bangladesh, India), disruptions
due to natural disasters, and persistent security
challenges weakening domestic demand (e.g.,
Afghanistan). As an external risk, an abrupt
tightening of global financing conditions or asudden rise in financial market volatility could set
back regional growth. On the other hand, stronger-than-expected global growth could benefit themore open economies in the region in the nearterm (Chapter 1).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Increasing
contingent liabilities related toinfrastructure projects (e.g., Pakistan), debt writeoffs for farmers (e.g., India), and slippages relating
to upcoming elections and weak tax revenues (e.g.,
Bangladesh, Nepal, Pakistan) could derail fiscal
consolidation efforts. Weaker debt sustainability
could weigh on confidence, financial markets andalready-weak investment (World Bank 2017z).
Corporate debt overhangs and high levels of nonperforming loans have been long-standing
concerns in some countries (e.g. Bangladesh,
India). Setbacks in efforts to resolve thesedomestic bottlenecks would continue to weigh on
investment, and more broadly on medium-term
growth prospects in the region.
Recent adverse weather conditions have reduced
agricultural output in some cases (e.g. Nepal, Sri
Lanka). Such developments continue to pose risks
to regional growth (World Bank 2017e, 2017ac).
Recently, remittance inflows have been subdued
due to fiscal consolidation and growth slowdowns
in the Middle East, which constitutes roughly halfof remittances to South Asia. A protracted
slowdown in remittance inflows would weigh on
domestic consumption (e.g., Bangladesh, Sri
Lanka; World Bank 2017ac).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

SOUTH ASIA

TABLE 2.5.1 South Asia forecast summary


131

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Source: World Bank.
Notes: e = estimate; f = forecast. EMDE = emerging market and developing economy. World Bank forecasts are frequently updated based on new information and changing (global)
circumstances. Consequently, projections presented here may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any
given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars.
2. National income and product account data refer to fiscal years (FY) for the South Asian countries, while aggregates are presented in calendar year (CY) terms. The fiscal year runs from
July 1 through June 30 in Bangladesh, Bhutan, and Pakistan, from July 16 through July 15 in Nepal, and April 1 through March 31 in India.
3. Sub-region aggregate excludes Afghanistan, Bhutan, and Maldives, for which data limitations prevent the forecasting of GDP components.
4. Exports and imports of goods and non-factor services (GNFS).
For additional information, please see www.worldbank.org/gep.

TABLE 2.5.2 South Asia country forecasts
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Source: World Bank.
Notes: e = estimate; f = forecast. World Bank forecasts are frequently updated based on new information and changing (global) circumstances. Consequently, projections presented here
may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any given moment in time.
1. Historical data is reported on a market price basis. National income and product account data refer to fiscal years (FY) for the South Asian countries with the exception of Afghanistan,
Maldives, and Sri Lanka, which report in calendar year (CY). The fiscal year runs from July 1 through June 30 in Bangladesh, Bhutan, and Pakistan, from July 16 through July 15 in Nepal,
and April 1 through March 31 in India.
For additional information, please see www.worldbank.org/gep.

132

CHAPTER 2.5

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.5.1 Potential growth in South Asia

Potential growth in South Asia has slowed from around 7.2 percent just prior to the global financial crisis to an average of 6.8
percent in recent years, reflecting the effects of a sharp investment slowdown. Over the medium-term, South Asia’s potential
growth is expected to stabilize around 6.7 percent. Achieving faster sustained growth will require structural reforms such as
improving
human capital, enhancing female labor force participation,
 strengthening corporate and banking sector balance sheets,and promoting greater integration of the region into global and regional value chains.

Introduction

percent pre-crisis to around 6.8 percent. Other studies
have estimated potential growth in the region. In the caseof India, potential growth is estimated within the range of
6-8 percent in the post-crisis period (Bhoi and Behera
2016; Mishra 2013; Blagrave et al. 2015). Similarly, Ding
et al. (2014) estimate Sri Lanka’s potential growth between
6 and 8 percent after the global financial crisis.1 Looking
forward, achieving faster sustained growth in the region,
with a corresponding improvement in living standards,

Although South Asia was the fastest growing emerging
market and developing economy (EMDE) region in recent
years, it still slowed compared with the rapid pace set prior
to the global financial crisis (Figure 2.5.1.1). This
slowdown was mainly driven by stalled investment inIndia, and it appears also to reflect a more broad-based
easing of potential growth within the region, from 7.2

FIGURE 2.5.1.1 Regional growth
The slowdown of regional GDP growth in recent years has coincided with a decline in potential growth, which has mainlyreflected weak investment.

Percent
20

Potential growth
wth

2
0
-2
2010-142015-17

Percent
6

SAR

Median4Median10
5

2018-19

D. Potential TFP growth

SAR

15

1998-2017

4

Capital

Labor

EMDEs

2018-27

6

TFP

2013-178

Percent
10
8
6
4
2
0

2003-072003-08 average

1998-2017Median2018-27

SAR

C. Investment growth

2013-17

Percent
10

B. Potential growth decomposition

2003-07

A. Actual GDP growth0-5
1998-2017

SAR

2003-072013-17

E. Education attainment, secondary
completion

F. Working age population growth

Percent
50

Percent
4

SAR

Median

40

3

30

2

20

1

10

0

SAR

Median20-201998-2017

2003-072013-17-1
1998-2017

2003-072013-17

1998-2017

2003-072013-17

Sources: Haver Analytics, Penn World Tables, World Bank Estimates, and World Development Indicators.
A. C.-F. Blue bars show GDP-weighted average of SAR countries. Markers show median GDP-weighted averages of the six EMDE regions and vertical lines denote
range of regional GDP-weighted averages.
B. Potential growth estimates based on production function approach for India and Sri Lanka. See Annex 3.1 for more details.

Note: This box was prepared by Temel Taskin, Sinem Kilic Celik,
and Yirbehogre Modeste Some. Anh Mai Bui, Jinxin Wu, and Ishita
Dugar provided research assistance.



1 This estimate does not reflect the GDP revision of 2015, and might
be biased upward.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

SOUTH ASIA

133


BOX
2.5.1 Potential growth in South Asia (continued)
will require identifying and addressing the structural
factors that are constraining the region’s potential.
Against this backdrop, this Box will discuss the followingquestions:xHow has potential growth evolved in South Asia andwhat were its main drivers?

xWhat are prospects for potential growth?

xWhat are the policy options to lift potential growth?

FIGURE 2.5.1.2 Regional potential growthestimates South Asia’s potential growth has slowed from around
7.2 percent just prior to the global financial crisis to an
average of 6.8 percent in recent years, according to thebaseline measure (production function).
A. Potential growth
Percent
8This Box concludes that, in the absence of policy action,
South Asia’s potential growth is likely to remain broadly
steady at its current rate. However, there is scope to boost
the region’s potential growth significantly through productand labor market reforms as well as through investment in
human capital.

Potential growth prospects
Over the medium-term, potential growth in South Asia is
expected to average around 6.7 percent in the next decade.
Although this would be well below the high rates achieved
just before the global financial crisis, it compares favorablywith other EMDEs, where potential growth is expected toslow even further (Figure 2.5.1.2).
Potential growth in South Asia will be underpinned
mainly by a recovery in Total Factor Productivity (TFP)—
in part owing to the effects of improvements in
educational attainment, which will help offset a
moderation in the growth of the working age population,
similar to other EMDEs where aging already weighsheavily on potential growth.



2013-172018-27

1998-20176

4

2

Evolution of potential growth and its drivers
Estimates based on the analysis in Chapter 3 suggest thatthe decline in potential growth in South Asia reflectedslowing capital accumulation which outweighed theacceleration in TFP growth and improved educational
attainment. A number of factors appear to have been atwork, including heightened regulatory and policy
uncertainties,
delayedproject
approvals
and
implementation, continued bottlenecks in the energy
sector, as well as reform setbacks (Anand et al. 2014).
Large corporate debt overhang and non-performing assets
in the banking sector further weighed on credit growthand investment within the region.

2003-07

0
EMDEs

SAR

B. Regional potential growth by different estimates
Percent
2003-078

2013-17

1998-2017

6

4

2

0
Production
function

MVF

UVF

Expectations

Source: World Bank estimates.
Notes: Lines and bars denote averages of different periods.
A. Based on the production function approach for India and Sri Lanka,
as defined in Annex 3.1.
B. MVF stands for multivariate filter-based potential growth estimates; UVF
stands for univariate filter-based potential growth estimates (specifically,
the Hodrick-Prescott filter); Expectations stands for potential growth proxied
by five-year-ahead World Economic Outlook growth forecasts. Sample
includes India and Sri Lanka in the PF estimates, India in the MVF and UVF
estimates and India, Pakistan, Bangladesh, Sri Lanka, Nepal, Maldives,
Bhutan, and Afghanistan in the Expectations.

CHAPTER 2.5

134

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.5.1 Potential growth in South Asia (continued)


FIGURE 2.5.1.3 Policies to stem declining
potential growth Potential growth in South Asia is expected to averagearound 6.7 percent between 2018-27, slightly below its
recent average rate. Labor market, education, andhealth reforms, along with investment, could boost theregion’s potential growth by 0.4 percentage points.
A. Baseline potential growth
Percent
Baseline

8

Demographic trends

Other factors

6

4

2

EMDEs

2018-27

Contribution

2013-172018-27

Contribution

2013-170

SAR

B. Potential growth under reform scenarios
Percent

Labor market reformsIndia’s recent reforms, such as the “Make in India”
initiative and demonetization, are expected to encourageformal sector activity, broaden the tax base, and improve
long-term
growth prospects despite short term disruptions
in the case of demonetization. For instance, the “Make inIndia” initiative, which began in late-2014, aims to
improve investment and innovation as well as develop
skills to meet the demand for skilled labor. To achievethese goals, the government has taken various steps toimprove the business climate, such as shortening approvaltimes for trademarks and patents to enhance property rightprotection, lowering restrictions on foreign direct
investment (including foreign ownership restrictions) invarious sectors, and accelerating investment in energy andtransport infrastructure, which helped improve the ease of
doing business (World Bank 2017l).
The July 2017 introduction of the Goods and Services Tax(GST) in India has caused temporary disruptions in
manufacturing, and is linked to the recent weakness in thePurchasing Managers’ Index and industrial production
growth. However, eventually, it is expected to simplify tax
compliance, deepen economic linkages between Indianstates, broaden the tax base and improve revenue
collections. In turn, this is expected to enhance the broader
business environment and help foster investment andemployment (IMF 2017).

Education and health improvements

8Fill investment needs

Baseline

6

4

2

EMDEs

Reform impact

2018-272013-17

Reform impact

2018-272013-17

0

SAR

Source: World Bank estimates.
Notes: GDP weighted averages. Derived using the production function
approach for India and Sri Lanka. Details are described in Annex 3.1.
A. “Other factors” reflects declining population growth, trend improvements
in human capital, and a slowdown in investment growth to output growth.
B. Policy scenarios are described in Annex 3.1.

Significant vulnerabilities have been recognized in the
Indian banking and corporate sectors that may weigh on
medium-to-long-term growth prospects unless they are
addressed. Encouragingly, several steps have been taken on
this front. For example, the Asset Quality Review initiatedby the RBI in 2015 has led to an increase in therecognition of non-performing assets on financial sector
balance sheets. More recently, the government announced
a large recapitalization package ($ 32 billion) for public
sector banks to be implemented over two years. Over the
medium to long term, these measures are expected to help
resolve private sector balance sheet weaknesses and unlock
lending for private investment. Infrastructure spending inrecent years partly addressed supply side bottlenecks.
However, weaknesses on corporate balance sheets remain
as firms are highly indebted. As corporate lending stillaccounts for a significant part of banks’ assets, their ability
to finance future business investments will require therestructuring of this debt, as well as a broader deleveraging
in the corporate sector.
Sri Lanka’s economic reform agenda, supported by WorldBank and IMF programs, is expected to sustainGLOBAL ECONOMIC PROSPECTS | JANUARY 2018



SOUTH ASIA


BOX 2.5.1 Potential growth in South Asia (concluded)
macroeconomic stability and support potential growthover the medium term (World Bank 2017ab). Public debt
is expected to decline amid ongoing fiscal consolidation,
which will open fiscal space and enable the country toallocate public spending toward human capital
investments that support potential growth. The
government recently adopted the new Inland Revenue
Act, which aims to simplify tax compliance, but which
could also mobilize additional revenue that could support
growth-enhancing spending, including infrastructure
investment.

Policy options to lift potential growth
As illustrated in Chapter 3, structural reforms can provide
a significant boost to productivity, employment, andpotential growth. Indeed, this analysis illustrates that steps
to reform labor markets, as well as education and healthsystems, and policies to encourage private sector
investment could boost potential growth. (Figure
2.5.1.3).
One area that could encourage higher private investment
in South Asia would be steps to enhance its integration in
global value chains. Studies show that this has been

associated with higher growth, but South Asia region lags
behind other EMDE regions in terms of the integration of
its trade and investment flows, both globally and within
the region (Farole and Pathikonda 2016). Closer tradeand investment ties could be supported by closing
infrastructure gaps, removing regulatory and other
impediments to businesses, as well as by promoting a shift
towards higher-value added manufacturing industries(Lopez Acevedo and Robertson 2016).
Addressing corporate and banking sector balance sheet
issues could lift investment and potential growth prospects
in the region. Recent steps taken by the government suchas the recapitalization package for public sector banks are
expected to support credit growth and investment.
Investment in human capital may also help lift
productivity, labor incomes, and potential output,
including by fostering a shift toward higher-value added
and innovative industries (Aturupane et al. 2014). Policies
that can help facilitate this shift include steps to improve
the share the participation of women in the workforce,increase access to higher and better education, andinvesting in vocational training programs (World Bank
2017p).

135A modest recovery is underway in Sub-Saharan Africa, supported by an improvement in commodity prices.
Although growth rebounded in Angola, Nigeria, and South Africa—the region’s largest economies—it
remained low. Metals exporters in the region experienced a moderate rebound, partly reflecting an uptick inmining output amid rising metals prices. Growth was stable in non-resource-intensive countries, supported byinfrastructure investment. The region is projected to see a pickup in activity over the forecast horizon, on theback of firming commodity prices and gradually strengthening domestic demand. However, given demographic
and investment trends, structural reforms would be needed to boost potential growth over the next decade.
Downside risks continue to predominate, including the possibilities that commodity prices will remain weak,
global financing conditions will tighten disorderly, and regional political uncertainty and security tensions will
intensify. On the upside, a stronger-than-expected pickup in global activity could further boost exports,
investment, and growth in the region.

Recent developments
Growth in Sub-Saharan Africa (SSA) is estimatedto have rebounded to 2.4 percent in 2017, afterslowing sharply to 1.3 percent in 2016, as
commodity prices recovered, global financing
conditions remained favorable, and slowing
inflation lifted household demand (Figure 2.6.1).
However, the recovery was slightly weaker thanforecast in June, and was marked by still-negative
per capita income growth, low investment, and a
decline in productivity growth (Box 2.6.1).
In particular, the rebound in the region’s largest
economies—Angola, Nigeria, and South Africa—
was modest. A recovery in the oil sector, partly
due to a decline in militants’ attacks on oil
pipelines, helped bring Nigeria back to positive
GDP growth. The performance of the agricultural
sector was relatively solid. However, activity
remained weak in the non-oil industrial sector, as
inadequate
power
generation
hurt
themanufacturing and construction industries. Strong
Note: The author of this section is Gerard Kambou. Research
assistance was provided by Xinghao Gong.

growth in the agricultural sector, due to improved
rainfalls, helped South Africa exit recession. The
mining sector expanded at a solid pace andmanufacturing activity rebounded. However,growth in the rest of the economy was subdued
amid elevated policy uncertainty, which continued
to weigh on business confidence. In Angola, achallenging operational environment limited
investment in the oil sector. Prolonged low growthand high unemployment has weighed on social
progress in all three countries, with per capita
GDP falling and the poverty headcount rising in
Nigeria and South Africa. In South Africa, theproportion of poor individuals in the total
population rose across all poverty lines between
2011 and 2015. Using the upper bound poverty
line (R1,138 per person per month), theproportion of poor individuals increased from
53.1 percent of the population in 2011 to 55.5
percent in 2015 (Statistics South Africa 2017).
Elsewhere in the region, activity was weak among
oil producers in the Central African Economic andMonetary Community (CEMAC), as they
continued to deal with the effects of the earlier oil
price collapse (Special Focus 1). By contrast,
growth rebounded in the metals-exportingCHAPTER 2.6

138

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 2.6.1
 SSA: Recent developments
Regional growth rebounded in 2017, reflecting a modest recovery in Angola, Nigeria, and South Africa—the region’s largest economies. Regional
activity was also supported by an increase in commodity prices, a reboundin oil production in Nigeria, and strong agricultural growth in South Africa.
The current account deficits narrowed in oil and metals exporters, but remained elevated in the non-resource-intensive countries due to strong
import growth. Fiscal deficits narrowed slightly in 2017, reflecting large
expenditure cuts in some oil exporters. Government debt continued to rise
across the region.
A. Growth

B. Oil production
2003-08 average

mb/d
2.4

AngolaNigeria

Current account deficits and financing

2.2
2.0

1.6

C. South Africa: Agriculture growth

D. Current account balance

Percent,
Percent,
quarter-on-quarter
quarter-on-quarter
4
10
Retail sales
Agriculture (RHS)
52

Percent of GDP
0

2016

2017

Jul-17Oct-17

Apr-17Jan-17

Jul-16Oct-16

Apr-16

Jan-16

Jul-15Oct-15

1.4

Apr-15

2017

2016

2015

2016

2017

SSA excl.
Angola,Nigeria, andSouth Africa

Angola,Nigeria, andSouth Africa

Jan-15

SSA

2015

2017

1.8

2016

2015

Percent
8
6
4
2
0
-2

2018

-10
-5

E. Fiscal balance
Percent of GDP
0-15

2017Q3

2017Q1

2016Q3

2016Q1

2015Q3

2015Q1-10

2014Q3-2

Sub-SaharanAfrica

SSA oilexporters

SSA metals
exporters

SSA nonresourceintensive
countries

F. Public debt
2016

2017

2018

Percent of GDP
70

2016

2017

2018

SSA metals
exporters

SSA nonresourceintensive
countries

60
50

-2

40
30

-4

20
10
0

-6
Sub-SaharanAfrica

SSA oilexporters

SSA metals
exporters

SSA nonresourceintensive
countries

Current account deficits narrowed, but remained
elevated, with the median current account deficit
estimated at 7 percent of GDP. Oil exporters saw
a significant decline in their deficits, as imports
remained subdued due to sluggish growth andtheir terms of trade improved. Deficits narrowed
moderately among metal exporters but were stillhigh in the non-resource-intensive countries, due
to strong import growth.

-5

0

0

2014Q1countries—which
consist mostly of agricultural
exporters—was broadly stable, supported byinfrastructure investment and crop production.
Economies in the West African Economic andMonetary Union (WAEMU) and in East Africa
expanded at a robust pace. However, activity
slowed in some countries, due to lower cocoa
prices (e.g., Côte d’Ivoire), drought (e.g., Kenya,
Uganda), and weak execution of the capital
expenditure budget (e.g., Tanzania).

Sub-SaharanAfrica

SSA oilexporters

Sources: Haver Analytics, International Energy Agency, Statistics South Africa, World Bank, World
Economic Outlook.
A. GDP-weighted averages.
B. Last observation is November 2017. “mb/d” stands for million barrels per day.
C. Last observation is 2017Q3.
D. -F. Median of country groups. Data for 2017 are estimates, data for 2018 are forecasts.
Non-resource-intensive countries include agricultural exporters and commodity importers.

economies, as mining output and investment
responded to a rise in metals prices andagricultural sectors recovered. Nonetheless, theirrebound was weaker than expected, owing to theeffects of a poor business environment in the nonmetals sector. Growth in non-resource-intensive

Generally accommodative international capital
market conditions helped finance these deficits.
Sovereign bond issuance rebounded in 2017, andimproved global sentiment toward emerging andfrontier markets helped narrow sovereign bondspreads. Nigeria experienced a pickup in equity
and portfolio flows after the central bank
implemented measures to improve access toforeign exchange. However, although firmer
commodity prices encouraged foreign investmentsin the hydrocarbon and mining sectors, foreign
direct investment inflows to the region are
expected to increase only moderately in 2017
(UNCTAD 2017). As a consequence, the level offoreign exchange reserves in the region continued
to be low. The median level of reserves was
equivalent to 3 months of imports in 2017, thesame as in 2016, but below its peak of 3.9 monthsof imports in 2014, pointing to the need forcountries across the region to rebuild externalbuffers.
Exchange rates and inflation
Currencies in the region stabilized in real effective
terms. For oil exporters, exchange rate pressures
eased due to higher oil prices, increased oil

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

production,
and a weaker dollar. The spread
between the parallel and official rates narrowed in
Nigeria, but import restrictions and multiple
exchange rates remained. In May 2017, theCentral Bank of Nigeria introduced a new investor
and exporter window in an attempt to improveaccess to foreign exchange.
Headline inflation declined across the region,
reflecting the confluence of stable exchange rates
and slowing food price inflation. Notably, inSouth Africa, headline and core inflation moved
closer to the middle of the central bank’s target
range. Easing price pressures created space forseveral central banks in the region to cut interest
rates. However, inflation remained elevated insome countries (e.g., Angola, Nigeria). In the caseof Nigeria, this reflected the effects of poor
harvests in some parts of the country on foodprices. A continued moderation of food priceinflation and exchange rate stability are expected
to push headline inflation down further, which
could provide room for further easing of monetary
policy in the region.
Fiscal balance and government debt
Fiscal deficits narrowed slightly. Large spending
cuts reduced the overall deficit in CEMAC
countries. However, in some oil exporters (e.g.,
Angola, Nigeria), fiscal policy was loosened in
response to higher oil revenues. Fiscal deficits
declined in non-resource-intensive countries, but
remained at high levels, partly reflecting
infrastructure investment. Deficits also narrowed
moderately in metals exporters as they continued
to struggle to mobilize domestic revenue. In
South Africa, national government revenue
increased at a slower-than-expected pace, as real
economic activity remained weak, making it
difficult to attain the budget’s deficit target.
Government debt indicators continued todeteriorate in the region in 2017, with the mediandebt-to-GDP ratio rising to 53 percent from 48
percent in 2016. Government debt rose further inSouth Africa, owing to fiscal slippages. Concerns
about the debt outlook prompted Standard &Poor’s to downgrade South Africa’s local currency
debt to sub-investment grade, bringing it in line

SUB-SAHARAN AFRICA

with
its foreign currency rating. Elsewhere,Mozambique defaulted on portions of its debt.
The government debt ratio edged up in nonresource-intensive countries as they continued toborrow (e.g., Burundi, Ethiopia), including on
international capital markets (e.g., Côte d’Ivoire,
Senegal), to finance public investment. Measures
to curtail public spending helped slow the increasein the debt-to-GDP ratio in oil exporters in
CEMAC, but government debt in Equatorial
Guinea is expected to rise sharply in 2017, due toa build-up in domestic arrears. In the Republic ofCongo, the discovery of previously undisclosed
debt could push total government debt to 117
percent of GDP, from 115 percent in 2016.
Fiscal sustainability gaps in the region remain
sizable, which are contributing to growing debtto-GDP ratios (World Bank 2017e). On average,
fiscal sustainability gaps widened between 2007
and 2016 by 4 percentage points, reflecting bothrising debt levels and widening fiscal deficits. The
erosion of fiscal sustainability was widespread. The
share of countries with sizable deterioration insustainability gaps (i.e., worsened by 1 percentage
of GDP or more) over 2007-16 was 80 percent.
Weakening government debt dynamics in theregion was also accompanied by a rapid increase in
private sector debt. In 2016, private credit bydomestic banks averaged 29 percent of GDP. The
rapid increase in private sector debt across theregion suggests the possibility of growing
contingent liabilities for the public sector.

Outlook
Regional growth is projected to rise to 3.2 percent
in 2018, and to an average of 3.6 percent in 201920 (Figure 2.6.2). These forecasts are broadly
unchanged from June, and assume that
commodity prices will firm and domestic demand
will gradually strengthen, helped by slowing
inflation. However, despite the pickup, growth
will remain below the rates seen prior to the global
financial crisis, partly reflecting the struggle facedby the region’s larger economies to boost private
investment. Moreover, while per capita growth isexpected to turn positive after falling in 2016 and2017, this would be at a rate that would remain
insufficient to reduce poverty.

139

140

CHAPTER 2.6

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 2.6.2
 SSA: Outlook and risks
The region is projected to see a pickup in growth as commodity prices
firm, but growth—including in per capita terms—would remain well below
its long-term average. Angola, Nigeria, and South Africa will continue tostruggle to boost growth, while the performance of the rest of the region
will be more favorable. Downside risks to the outlook include the possibility
that borrowing costs will begin to rise on the back of a deterioration in
global sentiment amid weak commodity prices, and adverse weather
conditions.
B. Per capita GDP growth

A. Growth
2003-08 average

Percent
6
4
2
0
-2
-4

5
3
1

2015
2016
2017
2018
2019
2015
2016
2017
2018
2019
2015
2016
2017
2018
2019

-1

SSA

SSA excl.
Angola,Nigeria, andSouth Africa

Angola,Nigeria, andSouth Africa

2003-08 average

2015
2016
2017
2018
2019
2015
2016
2017
2018
2019
2015
2016
2017
2018
2019

Percent
7

SSA

Angola,Nigeria, andSouth Africa

SSA excl.
Angola,Nigeria, andSouth Africa

C. Fiscal balance and government
debt

D. Number of SSA countries affectedby drought

Government debt, percent of GDP
80

Number of countries affected12
1970-2007 annual averageas a successful political transition signals thepossibility of reforms that can ameliorate theinvestment climate.
Outside the three largest economies, among oil
exporters, growth is forecast to strengthen in
Ghana, as increased oil and gas production lifts
exports. Growth in CEMAC is expected to remain
subdued but improve gradually, as countries
continue to adjust to low oil prices. The ongoingrecovery in metals exporters is projected tocontinue. Steadily rising metals prices are expected
to encourage further investment in the mining
sector. In some metals exporters, a combination ofslowing inflation and monetary policy easing is
expected to support a pickup in household
demand. In others, improved weather conditions
will also enhance power generation, supporting
greater private sector activity.

Sources: Emergency Events Database (www.emdat.be, Brussels, Belgium), Université catholique deLouvain, IMF Regional Economic Outlook for Sub-Saharan Africa, World Bank.
A. B. Shaded areas represent forecasts.
C. Blue data points represent 2015 values; red data points represent 2018 World Bank forecasts.
D. Chart shows number of SSA countries experiencing at least one drought in any given year.

Non-resource-intensive countries are projected to
expand at a solid pace, helped by robust public
investment growth. Economic activity is expected
to remain solid in WAEMU, with Côte d’Ivoire
and Senegal expanding at a rapid pace. Among
East African countries, Ethiopia is likely to remain
the fastest growing economy, but growth isexpected to soften as it takes measures to stabilize
government debt. Growth is expected to recoverin Kenya, as inflation eases, and to firm in
Tanzania on strengthening investment growth.

Growth in Nigeria is projected to pick up from 1
percent in 2017 to 2.5 percent in 2018 and 2.8
percent in 2019-20. The forecasts for 2018 and2019 were revised up, reflecting the expectations
that oil production will continue to recover andreforms in the foreign exchange market, alongwith improved supply of electricity, will help lift
growth in the non-oil sector. In South Africa,
growth in 2017 was upgraded from 0.6 percent to
0.8 percent, as activity strengthened more than
expected in the second half of the year. Growth isprojected to pick up to 1.1 percent in 2018 and1.7 percent in 2019-20. However, policy
uncertainty is likely to remain and could weigh on
investment. Growth in Angola is projected to risefrom 1.2 percent in 2017 to 1.6 percent in 2018,

Potential growth increased in SSA following the
global financial crisis, above its long-term and precrisis average rates. By contrast, potential growthin other emerging market and developing
economies (EMDE) regions slowed sharply(Chapter 3). The increase in SSA’s potential
growth reflected the effects of significantly higher
public investment and rising labor inputs (Choand Tien 2014), which offset the headwinds fromthe commodity price collapse, a slow recovery in
the Euro Area following the euro crisis, and aslowdown in economic activity in China as it
began rebalancing its economy toward domestic
consumption. However, in the absence of reforms,
potential growth could slow in the coming decade,owing to a slowdown in the growth of capitalstock and labor supply.

Ghana

70
Zambia

60

Ghana

10

AngolaZambiaEthiopia
Kenya
Rwanda Angola
Ethiopia

8

Kenya

50

40

Rwanda30

Nigeria20

6

Cameroon

4

Cameroon

2

Nigeria

10
0

2017

2016

2015

2014

2013

2012

0

2011

-8
-6
-4
-2
Fiscal balance, percent of GDP

2010

0
-10

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018


Risks

Risks to the regional outlook are, on balance,
tilted to the downside. On the upside, strongerthan-expected activity in the United States andEuro Area could push regional growth above thebaseline through higher exports, and increased
investment flows in mining and infrastructure. On
the downside, an abrupt slowdown in China could
generate adverse spillovers to the region throughlower-than-projected commodity prices, which
would exacerbate economic imbalances andcomplicate adjustment needs in many commodity
exporters. Oil producers in CEMAC and metals
exporters are particularly vulnerable to this risk.
On the domestic front, excessive externalborrowing, in the absence of sound forwardlooking budget management, could worsen debt
dynamics and cause economic instability. Reforms
to contain fiscal deficits and rebuild buffers are
particularly needed in CEMAC as well as in the
non-resource-intensive
countries
where
government debt is high and rising. A quicker andsharper-than-expected tightening of global
financing conditions—triggered, for example, by areassessment in financial markets of the pace ofmonetary policy normalization in the UnitedStates or other major economies—could lead to areversal in capital flows to the region. South Africa
would be particularly vulnerable to adverse swings
in investor sentiment because of its great

SUB-SAHARAN AFRICA

dependence
on portfolio inflows. Moreover, with

the increase in sovereign bond issuance in recent
years, a sharp increase in global interest rates could
also complicate debt dynamics in the region. In
the long run, a sharper-than-expected slowdown
in potential growth could damage prospects forgains in per capita incomes and poverty reduction.
Other downside risks include a protracted periodof heightened political and policy uncertainty,
which could further hurt confidence and deter
investment. This risk is elevated in South Africa,
where the ruling African National Congress’s
leadership election could lead to deep divisions
within the party, and in Zimbabwe, where apolitical transition is unfolding. Droughts,
conflicts, and worsening security conditions would
weigh heavily on economic activity in the region,
especially in fragile countries. This risk isparticularly elevated in West and Central Africa,
where militant insurgencies remain a threat.
The risks to the regional outlook underscore theneed for policy actions to achieve inclusive growth(Chapter 1). The rising government debt levels
highlight the importance of fiscal adjustment tocontain fiscal deficits and maintain financial
stability.
Structural
policies—suchasimprovements in education and health systems, aswell as labor market, governance, and businessclimate reforms—could help bolster potential
growth across the region.

141

142

CHAPTER 2.6

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

TABLE 2.6.1 Sub-Saharan Africa forecast summary

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Source: World Bank.
Notes: e = estimate; f = forecast. EMDE = emerging market and developing economy. World Bank forecasts are frequently updated based on new information and changing (global)
circumstances. Consequently, projections presented here may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any
given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars. Excludes Central African Republic, São Tomé and Príncipe, Somalia, and South Sudan.
2. Sub-region aggregate excludes Central African Republic, São Tomé and Príncipe, Somalia, and South Sudan, for which data limitations prevent the forecasting of GDP components.
3. Exports and imports of goods and non-factor services (GNFS).
4. Includes Angola; Cameroon; Chad; Congo, Democratic Republic; Congo, Republic; Gabon; Ghana; Nigeria; and South Sudan.
5. Includes Benin; Burkina Faso; Cameroon; Central African Republic; Chad; Congo, Republic; Côte d’Ivoire; Equatorial Guinea; Gabon; Mali; Niger; Senegal; and Togo.
For additional information, please see www.worldbank.org/gep.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

SUB-SAHARAN AFRICA

TABLE
2.6.2 Sub-Saharan Africa country forecasts 1


143

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8JDQGD=DPELD
=LPEDEZH



Source: World Bank.
Notes: e = estimate; f = forecast. World Bank forecasts are frequently updated based on new information and changing (global) circumstances. Consequently, projections presented here
may differ from those contained in other Bank documents, even if basic assessments of countries’ prospects do not differ at any given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars. Excludes Central African Republic, São Tomé and Príncipe, Somalia, and South Sudan.
2. Fiscal-year-based numbers.
For additional information, please see www.worldbank.org/gep.

CHAPTER 2.6

144

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.6.1 Potential growth in Sub-Saharan Africa
Sub-Saharan Africa’s potential growth rose following the global financial crisis, above its long-term and pre-crisis averages, due toincreases in the working-age population and capital stock accumulation. Notwithstanding these recent gains, potential growth
could slow in the next decade, as labor force growth stagnates and capital accumulation moderates, which would weigh on percapitaincomes and diminish the prospects for poverty reduction.
However,structural reforms, including additional investment,stronger health and education improvements, and increased female labor participation, could help ensure that the region’s potential growth remains robust.
Introduction
Sub-Saharan Africa (SSA)’s potential growth rose in the
post-crisis (2013-17) period, above its long-term (19982017) and pre-crisis (2003-07) averages, and also above
the regional population growth rate, signaling the prospectof gains in per capita incomes in the medium-term. The
acceleration in potential growth was mainly due toincreases in labor supply, capital stock, and total factor
productivity (TFP) growth. Excluding South Africa,
potential growth rose at a faster pace, above the emerging
market and developing economies (EMDE) average,
reflecting a stronger increase in capital accumulation.
Sustained per capita potential growth is critical forcontinued income convergence and poverty reduction,
which is particularly relevant to countries in SSA where an
increasing share of the world’s poor reside (World Bank
2015e). SSA’s prospects for continued and solid potential
growth are favorable when South Africa is excluded,suggesting that the positive demographic trends that haverecently boosted labor supply growth are likely to continue
in the rest of the region, along with steady growth incapital accumulation and TFP.
Against this backdrop, this box will discuss the following
questions:xHow has potential growth evolved in the region andwhat were its main drivers?

xWhat are the prospects for potential growth in SSA?

xWhat are the policy options for boosting the region’s
potential growth?

The box’s main conclusions are that—in the absence ofreforms—SSA’s potential growth is likely to slow from the
3.3 percent rate achieved in the past five years to 3.2
percent in the next decade (2018-27), as growth in labor
force stagnates and the rate of capital accumulation

Note: This box was prepared by Gerard Kambou, Sinem Kilic Celik,
and Yirbehogre Modeste Some. Xinghao Gong provided research
assistance.



moderates, mainly reflecting a slowdown in employment
and capital stock growth in South Africa. Such a decline inpotential growth would limit the prospects for further
gains in per capita incomes and poverty reduction.
Excluding South Africa, potential growth in the rest of theregion would remain steady at 5 percent a year. This
underscores the importance of structural reforms to boost
potential growth, including those that spur private
investment, skills development, and female labor force
participation.
How has potential growth evolved in
Sub-Saharan Africa and what were its
main drivers?
Potential growth increased in SSA following the global
financial crisis to 3.3 percent a year during 2013-17, above
its long-term (1998-17) average of 2.9 percent and precrisis (2003-07) average of 3 percent (Figure 2.6.1.1). By
contrast, potential growth in other EMDE regions slowed
sharply. Excluding South Africa, potential growth in theregion rose from 3.6 percent a year in the pre-crisis period
to 5 percent during 2013-17, above the EMDE average of
4.8 percent. This acceleration reflected the effects ofsignificantly higher public investment and rising labor
inputs, which offset the headwinds from a commodity
price collapse (2014-15), and a slowdown in major trading
partners, including in the Euro Area following the euro
crisis (2010-13), and in China as it began rebalancing its
economy toward domestic consumption.
The pickup in potential growth can be decomposed into
its principal components:
Rapid capital stock growth. Excluding South Africa,
capital stock growth rose from 1.8 percent a year in 200307 to 2.6 percent in 2008-12. This increase partly reflected
the stimulus measures countries in the region adopted tocushion the impact of the global financial crisis andsupport long-term growth. The impact of the stimulus on
investment was amplified by efforts to improve thebusiness environment and support investor confidence(Devarajan and Kasekende 2011). The growth of capitalstock picked up to 2.9 percent during 2013-17, reflecting

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

SUB-SAHARAN AFRICA

145

BOX
2.6.1 Potential growth in Sub-Saharan Africa (continued)


FIGURE 2.6.1.1 Regional growth and drivers of potential growth




EMDEs
1998-2017

2003-07

D. Potential TFP growth
Percent
6

SSA

2013-17SSA
Median

SSA excl.
South Africa-5

2013-175

2003-072018-270

2018-27

2

SSAMedian10
2003-07

4

CapitalPotential growth15

1998-2017

6

Percent
20

TFP
Labor

1998-2017

8

Percent
10
8
6
4
2
0

2013-17

Median2003-07

SSA

C. Investment growth

2018-27

Percent
10

B. Potential growth decomposition

1998-2017

A. Actual GDP growth

2013-17Although growth slowed in Sub-Saharan Africa during 2013-17, its underlying potential accelerated owing to increases in theshare of working-age population and capital stock growth. Excluding South Africa, potential growth rose at a faster pace.

0

1998-2017

2003-072013-17

E. Educational attainment, secondary
completion

F. Working-age population growth

Percent
50

Percent
4

SSA

MedianSSAMedian

40

4

2
30
2
20
0

0

10
0

-2
1998-2017

2003-072013-17-2
1998-2017

2003-072013-17

1998-2017

2003-072013-17

Sources: World Bank staff estimates, World Development IndicatorsPenn World Tables.
Note: SSA stands for Sub-Saharan Africa.
A. C. -F. Median represents median of the six EMDE regional aggregates. Vertical lines indicate the range of the regional aggregates.

a strong public infrastructure investment drive in the fastgrowing non-resource-intensive countries as well as anincrease in foreign direct investment flows in metals
exporters (World Bank 2017p). The contribution ofcapital stock growth to potential growth was 1.1
percentage points higher than the rates seen prior to theglobal financial crisis. If South Africa is included, thecapital stock growth is more modest, with a 0.3 percentage
points contribution to potential growth in 2013-17.
Solid labor supply growth. Labor supply growth picked
up to 1.4 percent in the post-crisis period, above its
longer-term average of 1.2 percent. This acceleration
mainly reflected the effects on the labor supply of a bulge
in the working-age population along with an increase inlabor force participation rates. As a result, the contributionof labor inputs to potential growth increased by 0.2
percentage points in the post-crisis period, contrastingwith other EMDE regions, where population aging has
dampened the growth of the workforce. If South Africa is

included, the contribution of labor supply growth topotential growth rises to 0.4 percentage points, reflecting
stronger growth in the working-age population.
Modest TFP growth. Potential TFP growth rose slightly
in 2013-17 from the rates seen prior to the global financial
crisis. During 2003-07, TFP growth rose above its longterm average, supported by improvements in health andeducation outcomes, as well as by a decline in the share of
the labor force engaged in agriculture and the associatedreallocation of workers to higher productivity sectors(McMillan and Harttgen 2014). However, TFP growth
remained subdued in the post-crisis period. TFP growthslows markedly if South Africa is included, reflecting the
sharp decline in TFP growth South Africa experienced
following the global financial crisis. Overall, thecontribution of TFP growth to potential growth during
2013-17 was minimal. The low post-crisis increase in TFP
growth in SSA and other EMDE regions has been
attributed to a slowdown in convergence to the



146

CHAPTER 2.6

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018





BOX
2.6.1 Potential growth in Sub-Saharan Africa (continued)

technological frontier after a rapid catch-up in the decadepreceding the crisis (Kemp and Smit 2015).

very modestly, with unfavorable prospects of reducing theregion’s poverty headcount.

In summary, potential growth in SSA picked up in thepost-crisis
period, due to increases in the working-age share of the population, which boosted labor supply
growth, and to increases in the capital stock from higher
investment. TFP growth increased marginally, reflecting
an apparent slowdown in the rate of absorption of newtechnology.

What are the policy options to bolster medium-termpotential
growth in the region?

What are the prospects for potential growth in theregion?

Filling investment needs. Although public investment
picked up in the mid-2000s and reached a peak of 5.8
percent of GDP in 2014, this rate was well below theaverage for other EMDEs (World Bank 2017af).

To examine this question, a baseline projection isconstructed that assumes: population and its composition
grow in line with a median fertility scenario (as projectedin the UN Population Projections); recent trend
improvements in education and health outcomes continue;
and the investment-to-output ratios remain at their latest
five-year average.
Under this scenario, the key determinants of potential
growth would evolve as follows:
The underlying growth of the capital stock would remain
steady, at around 3 percent a year. If South Africa is
included, the capital stock trend growth moderates to 1.8
percent, consistent with a slowdown in investment.
Compared with other EMDE regions, SSA is experiencing
a slow decline in fertility rates (Canning et al. 2015). As aresult, the youth dependency rate would remain high andthe share of working-age population would rise only
slowly. Labor supply growth would remain broadly stable,
at around 1.4 percent a year. However, if South Africa is
included, labor supply growth could slow to 1.1 percent,reflecting declining employment growth in South Africa.
TFP growth would remain steady at 0.6 percent a year. If
South Africa is included, TFP growth could rise, owing toSouth Africa’s innovation strengths (World Bank 2017ae).
On balance, these factors suggest that, in the absence ofreforms, potential growth would remain steady at 5
percent on average in the next decade, if South Africa is
excluded, as the growth of capital stock and labor supply
remains stable. The inclusion of South Africa changes theresults. Potential growth would remain low at around 3.2
percent by 2027, as a slowdown in the growth of capitalstock and labor supply is only partially offset by a modest
increase in TFP growth. Potential growth at this ratewould mean that GDP per capita in SSA would rise onlyThis section assesses the benefits from the implementationof key structural reforms using scenario analysis. These
include filling the region’s investment needs, boosting
human capital improvements, and increasing labor supply.

SSA’s infrastructure investment needs are particularly
sizable. Increasing public investment would provide ashort-run boost to output, but could also have favorable
supply-side effects, including by spurring private
investment (World Bank 2017af). Although many
countries in the region have little fiscal space to raise
public spending through deficit financing, there is scope toreallocate resources from less productive spending
programs and to mobilize domestic revenues. Tax revenues
as a share of GDP are low for most countries in SSA, andcould be increased through reforms including broad-based
consumption taxes, simplified tax design, and improved
tax administration (Mabugu and Simbanegavi 2015).
Simulations based on the analysis presented in Chapter 3
suggests that if, over the next decade, the investment-toGDP ratio for the region were increased by around 2.7
percentage points by 2027—an increase that is within
historical precedent—the region’s potential growth would
be boosted by around 0.6 percentage points by 2027, andby 0.4 percentage points if South Africa is included.
Increasing human capital accumulation. Further
improvements in education and health outcomes could
bolster potential growth by raising labor force
participation rates and TFP growth. Although the region
has achieved significant improvements in these areas,much more remains to be done.
x

Education: SSA lags in education outcomes. In half ofthe countries in SSA, less than 50 percent of the
youth complete lower secondary education and under
10 percent go on to higher education (World Bank
2017ag). Learning outcomes have been generally poorand gender disparities remain significant at thesecondary and tertiary levels (Oyelere 2015). Priorities
vary depending on country-specific circumstances, but

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

SUB-SAHARAN AFRICA

147


BOX
2.6.1 Potential growth in Sub-Saharan Africa (continued)


they center on investing in effective teaching, ensuring
access to quality education for the poor, and closing
gender gaps (World Bank 2017ag).
x

Health: SSA’s average life expectancy of 59 years in 2015 (World Bank 2017ah) also lags other EMDE
regions, and falls well short of 80 years in advanced
economies. SSA is disproportionally affected by the
impact of infectious diseases. Building strong healthsystems, as well as setting up regional coordination
mechanisms, is critical for providing adequate healthservices to the populations (World Bank 2016l).

To illustrate the benefits of tackling these issues,
simulations were conducted that assumed that secondary
school and tertiary enrollment rates, and life expectancy
will rise over 2018-27 by as much as the largest historicalimprovement in any ten-year period for SSA. This would
imply a rise in secondary school completion rates of 3.7
percentage points, tertiary completion rates of 0.4
percentage points, and life expectancy of 3 years. The
effect of these assumptions would be to raise potential
growth by around 0.1 percentage points by 2027,
compared with 2013-17, the same if South Africa is
included.
Increasing labor supply. The labor force participation rate
for women in SSA was around 65 percent in 2015 (UNDP
2016), well below the 76 percent rate for men, indicating
significant scope for increasing the number of women in
the workforce. Studies have shown that gender equality inlabor force participation rates in the region is severely
affected by the burden of unpaid labor, which is
predominantly born by women, as well as by gaps ineducational attainment and restrictions in access to credit
markets (Seguino and Were 2015). This points to thepolicy and institutional frameworks that are needed toincrease female labor force participation.
To illustrate the possible benefits of such measures,
simulations were performed that assumed that the female
labor force participation rate rises by 1 percentage points,
equivalent to the largest historical ten-year improvement
achieved by the region in the past 20 years. The
simulations suggest that this would raise potential growthby around 0.1 percentage points by 2027, compared to
2013-17, the same if South Africa is included.
Overall impact on potential growth. Raising theinvestment-to-GDP ratio, and increasing secondary school
and tertiary education completion rates as well as life
expectancy closer to advanced-economy levels, as assumed
in the scenarios described above, could boost SSA’s


potential growth by 0.7 percentage points by 2027.
Additional gains (0.1 percentage points) could also be
expected from labor market policies that encourage female
labor force participation. Overall, a combination of 
additional investment, increased education and healthimprovements, and higher female labor force participation
could raise SSA’s potential growth by 0.8 percentage
points to 5.8 percent by 2027, excluding South Africa. If
South Africa is included, similar reforms would boost
potential growth by 0.7 percentage points to 3.8 percent
on average by 2027 (Figure 2.6.1.2).
Other productivity-enhancing reforms. In addition to thetypes of reforms that can be captured in the models
described in Chapter 3, there are other productivityenhancing reforms that could also pay significant
dividends (AfDB et al. 2013). These include
diversification to reduce reliance on the resource sector;
stronger property rights to encourage productivityenhancing investment; and greater transport connectivity
to spur competition. Across the region, there is scope forraising productivity in the formal sector, the agricultural
sector, and nonfarm informal sector, which could further
boost the region’s potential growth (World Bank 2016l).
x

Economic diversification: Economies in the region are
striving to diversify away from natural resource
exports, especially by taking steps to make their
manufacturingsectors
more
competitive.
Competitiveness within SSA suffers as a result of poor
business environments, lack of infrastructure, andhigh unit labor costs (Bhorat and Tarp 2016). Alongwith increased human capital and the removal of tradebarriers, improvements in transport and energy
infrastructure could increase the productivity andcompetitiveness of the region, and facilitate its
integration into global value chains (Allard et al.
2016). While the business environment has improved,
there remains considerable scope for simplifying
regulations and administrative procedures for startinga business, increasing the efficiency of the legal
system, and reducing regulatory uncertainty.

x

Boosting agricultural productivity: Across the region,
the share of employment in low-productivity
agriculture remains high. Many countries havesubstantial scope for raising agricultural productivity,
including by taking steps to improve land titles,
increasing access to credit for investment in new
farming techniques, improving the awareness ofmodern farming techniques, and improving theinfrastructure needed to connect farms to markets. In

148

CHAPTER 2.6

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018






BOX
2.6.1 Potential growth in Sub-Saharan Africa (concluded)
Ethiopia, public investments in irrigation,transportation and power have produced a significant
FIGURE 2.6.1.2 Policies to stem declining
increase in agricultural productivity and incomes,
potential growthwhich resulted in growth-enhancing structural change
(Rodrik 2017).
The expected gradual decline in the region’s highfertility rates could slow the growth of the working-age
population, and a weakening of the investment rate will
moderate capital stock growth. In the absence ofreforms, a slowing expansion of the labor supply andcapital stock could reduce regional potential growthfrom 3.3 percent in 2017 to 3.2 percent by 2027, below
the EMDE average. However, the region’s potential
growth could be boosted to 3.8 percent by 2027
through policies to spur investment, improve educationand health, and boost female participation rates.
Excluding South Africa, potential growth could reach 5.8
percent by 2027.
A. SSA potential growth
Percent
7

2003-072018-272013-17
1998-20176x

Raising productivity in the nonfarm informal sector:
Recent studies found that in many countries thedecline in the share of the labor force engaged inagriculture has been matched by a sizable increase in
the share of the labor force employed in the informal
sector (Diao et al. 2017). Raising the productivity of
the informal sector has become an important policy
objective. Fostering a supportive regulatoryenvironment, and promoting investment in basic
infrastructure such as electricity, road networks, andinformation technology, are important areas ofreforms that could make the informal sector more
dynamic and formal, and increase its contribution to
the region’s long-run economic growth (Bhorat andTarp 2016).

5

Conclusion

4

Potential growth rose to 3.3 percent in Sub-Saharan Africa
in the past five years, above the pre-crisis and longer-term
averages, owing to the growth of the working-age
population and capital stock. However, in the absence ofreforms, SSA’s potential growth would remain low ataround 3.2 percent by 2027, given likely trends in labor
supply and investment, which suggests that per capita
income growth would stagnate. The low potential growthrate is mainly due to a moderation in trend growth inSouth Africa. Excluding South Africa, potential growthrose by 5 percent on average following the global financial
crisis, above the EMDE average, reflecting a stronger
increase in the rate of capital accumulation.

3
2
1

0
EMDEs

SSA

B. SSA potential growth under reform scenarios
Labor market reforms
Education and health improvements
Fill investment
estme needs
BaselinenePercent
6

4

2

EMDEs

SSA

Reformimpact2018-272013-17

Reformimpact2018-272013-17

Reform impact

2018-272013-170

SSA excl. South Africa

Source: World Bank staff estimates.
Notes: GDP-weighted averages. Derived using the methodology describedin Annexes 3.1 and 3.3. Policy scenarios are described in Annex 3.3.



There is considerable scope for boosting potential growthwith structural reforms, including policies to increase
investment, improve health and education outcomes, andraise female labor force participation. Bold steps in theseareas could boost SSA’s potential growth by around 0.8
percentage points to 5.8 percent on average over the next
decade. Other productivity-enhancing reforms, including
diversification to reduce reliance on commodities, stronger
property rights to encourage productivity-enhancing
investment, and greater transport connectivity to spur
competition, could safeguard and bolster these gains. A
robust implementation of such policies would be critical if
the region is to take full advantage of its demographic
dividend.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018
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CHAPTER 3

BUILDING SOLID
FOUNDATIONS:How to Promote Potential GrowthGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 3

Despitea recent acceleration of global economic activity, potential
output growth is flagging. At 2.5 percent in
2013-17, post-crisis potential growth is 0.5 percentage point below its longer-term average and 0.9 percentage
point below its average a decade ago, with an even steeper decline in emerging market and developing
economies. This slowdown mainly reflects weaker capital accumulation, but is also evidence of slowing
productivity growth and demographic trends that dampen labor supply growth. These forces will continue and,
unless countered, will depress global potential growth further by 0.2 percentage point over the next decade. A
menu of policy options could help reverse this trend, including comprehensive policy initiatives to lift physicaland human capital, encourage labor force participation, and improve institutions.

Introduction
Although the global economy has regained somestrength since mid-2016, potential output
growth—the rate at which an economy wouldgrow when labor and capital are fully employed—
has continued to decline (Figure 3.1). Post-crisis(2013-17), global potential growth fell short of its
long-term average and was well below its pre-crisis
average. This weakness was broad-based, affecting
both advanced economies, where it was evident
even before the financial crisis, and emerging
market and developing economies (EMDEs),
where there was a short-lived pre-crisis up-tick.
The decline raises concerns about the durability of
the cyclical recovery described in Chapter 1.
Since the growth rate of per capita potential
output is the overriding long-run force forsustained reductions in poverty, this trend is also
cause for concern about the world community’s
ability to meet broader development goals.1 In
some regions, especially commodity-exportingones such as Eastern Europe and Central Asia, andthe Middle East and North Africa, the post-crisis
slowdown in potential growth could set back per
capita income convergence by more than a decade.
Against this backdrop, this chapter addresses thefollowing questions:
Note: This chapter was prepared by Sinem Kilic Celik, M. Ayhan
Kose, Franziska Ohnsorge, and Yirbehogre Modeste Some. Research
assistance was provided by Xinghao Gong and Jinxin Wu.
1 Research suggests that two-thirds of cross-country differences ingrowth of the poorest households’ income are accounted for bydifferences in average income growth (Dollar, Kraay, and Kleineberg
2013; Barro 2000). Mechanisms by which overall growth helps
reduce inequality are varied, but include its impact in raising thedemand for agricultural output which helps poor land holders, as wellas rising urbanization and higher wages (Yankow 2006; Gould 2007;
Ravallian and Datt 2002).

x How has potential growth evolved since theturn of the century?
x What have been the drivers of potential
growth?
x What are the prospects for potential growth?
x What policy options are available to lift
potential growth?
To help answer these questions, the chapter
examines the evolution of potential growth in alarge sample of countries, with a strong regional
focus. Since potential output is not directly
observable, economists estimate it from long timeseries of actual output, employment, capitalstocks, and productivity. The chapter constructs acomprehensive database of potential output
growth series using a variety of techniques.2
Other studies have documented a potential growth
slowdown in advanced economies and Asian
economies, while the focus in this chapter is on
the broader EMDE universe (IMF 2015; DablaNorris et al. 2015; Asian Development Bank
2016; and OECD 2014). There are many ways toestimate potential output. For clarity, and in
keeping with a longer-term focus, this chapter uses
the production function approach.3 Second, the2 Most of the existing literature on potential growth involves
estimating the role of output gaps in driving inflation or domestic
monetary policy in the context of individual countries (in about halfof 67 publications for individual EMDEs surveyed by the authors).
3 Other measures of potential growth incorporate short-term supply
shocks that dissipate over time (Box 3.1). In this chapter, an
exploration of the transition from short-term supply to long-term
potential output is confined to the impact of steep output
contractions to long-term potential output (Box 3.4).

159

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GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 3.1 Global growth

growthis directly derived from the empirical
exercise.4

A cyclical upswing has been underway in the global economy since mid2016. Global growth is estimated to have strengthened to 3.0 percent in2017 from a post-crisis low of 2.4 percent in 2016, within reach of longterm average global growth. However, underneath the cyclical upturn,potential growth is slowing, which could set back income convergence by
several decades in some regions.
A. Growth

B. Potential growth

Percent
8

Percent
8
Potential growth
Actual growth6
1998-2017 potential growth

1998-2017 average

6

The chapter’s principal conclusions are as follows:xThe global financial crisis has ushered in aperiod of persistently weak potential growth.
During 2013-17, global potential growth (2.5
percent a year) fell 0.5 percentage point below
its longer-term (1998-2017) average, and evenfurther below its average a decade ago (200307). EMDE potential growth slowed to 4.8
percent a year, 0.6 percentage point below its
longer-term average. This weakness in potential growth has been broad-based, affecting
almost half of EMDEs and 87 percent ofadvanced economies in the sample, together
representing 69 percent of global GDP.

xA host of factors have contributed to this postcrisis shortfall in potential growth below
longer-term averages. Half of the decelerationreflects weaker-than-average rates of capital
accumulation. Just over one-quarter of theslowdown is due to weaker total factor
productivity (TFP) growth while just under
one-quarter of the moderation is attributableto demographic trends.

x

The global financial crisis and subsequentrecession weakened productivity-enhancing
capital accumulation, and deprived workers ofopportunities to gain experience and skills,
creating a vicious cycle of subdued growth.
Conversely, in the past, cyclical upswings
often generated momentum that fed into
sustained increases in potential growth.

xThe slowdown in potential growth may
extend into the next decade. Trends in its
fundamental drivers suggest that global
potential growth may slow further by 0.2
percentage point on average over 2018-27,
while EMDE potential growth could ease by

4
4

2

2

1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27

0

2010
2012
2014
2016
2018
2010
2012
2014
2016
2018
2010
2012
2014
2016
2018

0

World

AEs

EMDEs

World

AEs

EMDEs

Number of years
150
125
100
75
50
25
0

Number of years
200

EAP

160

120
80
40

LAC

MNA

SAR

2013-17

2003-072013-17

2003-072013-17

2003-072013-172013-17

ECA

2003-070

2003-072013-17

D. Years to converge to U.S. GDP
per capita

2003-07

C. Years to converge to U.S. GDP
per capita

SSA

Sources: Penn World Tables, World Bank.
A. Full sample of countries as in Chapter 1.
B. Based on production function approach, GDP-weighted averages for a sample of 30 advanced
economies and 50 EMDEs.
C.D. GDP-weighted average of years to converge to U.S. per capita GDP in 2017. The years toconverge to U.S. GDP per capita for each country are calculated as the years to close the difference
between GDP per capita in 2017 from U.S. GDP per capita in 2017 assuming average potential
growth in the period specified. EAP = East Asia and Pacific, ECA = Europe and Central Asia,
LAC = Latin America and the Caribbean, MNA = Middle East and North Africa, SAR = South Asia,
and SSA = Sub-Saharan Africa.

chapter examines trends in the structural driversof potential growth, including total factor
productivity (TFP) growth, labor supply growth,and investment in human and physical capital. It
documents how steep output contractions,although typically brief, cast a long shadow on
potential growth, in part through an erosion ofjob skills and discouraged investment. Third, thechapter explores policy options to lift potential
growth. These include measures to improveeducation, reforms to health care and labormarkets, and steps to improve governance andbusiness climates. In contrast to earlier studies,
the discussion of policy options to lift potential

4 Other studies have investigated the link between actual growth orproductivity growth and structural reforms, focusing on the nearterm benefits (Prati, Onorato, and Papageorgiou 2013), productivity
effects (Dabla-Norris, Ho, and Kyobe 2015; Adler et al. 2017) or asample consisting of mostly advanced economies (Banerji et al. 2017;
IMF 2015 and 2016b).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 3

BOX 3.1 What is potential growth?
Potential growth is the rate of increase of potential output, the level of output an economy would sustain at full capacity
utilization and full employment. Since it is not directly observable, the measurement of potential growth relies on a range ofassumptions about its relationship to observable variables. Historical data on the growth of actual output growth, and of thefactors of production—the labor force, physical capital, and human capital—provide the main indicators. Numerous methods ofassessing potential output are available. The key results pertaining to potential growth in this chapter are robust to the choice of
method.
Potential growth is the rate of increase of potential output,
defined as the level of output an economy would sustain atfull capacity utilization and full employment. Although
the concept is of fundamental importance to short- andlong-run macroeconomic analyses, it is not directly
measurable. Estimates of potential growth may, however,be inferred from the behavior of observable variables. An
approach which links potential output to the underlying
factor inputs of labor, capital and technology—known as
the production function approach—is appropriate for theassessment of long-term growth, the main focus of thischapter.
However, the background analysis is based on a wide rangeof methodologies. The headline results are robust to the
choice of methodology. To set the stage, this box discusses
some major conceptual issues. In particular, it addresses
the following issues:x

What is potential growth?

xHow is potential growth measured?

x

Are the results robust to the choice of measure?

What is potential output growth?
Potential output is the level of output an economy would
produce at full capacity utilization and full employment.
Different estimates of potential output growth capture
different time-horizons: “short-term” versus “longterm” (Basu and Fernald 2009).
Short-term potential output growth is the growth ofpotential output that can be achieved without puttingpressure on production capacity and inflation when factorsof production cannot immediately relocate in response to
shocks (Okun 1962). It can be buffeted by temporary
disruptions and boosts to supply that dissipate over the
longer-term. For example, a shift in the composition ofdemand may render part of the existing capital stock
obsolete, effectively reducing potential output; over time,
Note: This box was prepared by Sinem Kilic Celik, M. Ayhan Kose,
Franziska Ohnsorge, and Yirbehogre Modeste Some.

firms would adjust to the new requirements, returningpotential output toward its previous path. The short-term
measure is particularly useful for monetary policy, since
supply constraints or adverse demand shocks, even if they
are not permanent, reduce the effective slack in theeconomy, and therefore influence the policy interest rate ata given decision point.
Long-term potential output is a function of the available
capital stock, labor input and current technology (Solow
1962). As such, long-term potential output growth
captures movements in the slow-moving fundamental
drivers of output assuming allocation of all factors of
production to their most productive uses, regardless of
temporary supply shocks. Long-term potential output sets
the underlying trend of short-term potential output as wellas actual output.

How is potential growth measured?
Estimates of short-term output may be computed using
filtering techniques, including univariate and multivariate
filters, while estimates of long-term potential output reston structural models or long-term growth expectations.
Filtering techniques. Univariate filters involve estimates oftrend output using only GDP series. Multivariate filterstake into account the relationship between GDP and othervariables (such as inflation or unemployment rates) to help
distinguish short-run deviations of output from trends.
The database underpinning this chapter employs the
Hodrick-Prescott filter, the Baxter-King filter, theChristiano-Fitzgerald filter, the Butterworth filter, anunobserved components model, a multivariate filter thatutilizes financial variables and commodity prices, a Phillips curve relationship, and an Okun law (Annex 3.2).
Production function approach. This approach represents
potential output as a (Cobb-Douglas) production functionof the amount of full-employment capital and labor, as
well as technology and efficiency of factor allocation thatdrive total factor productivity (TFP). Potential TFP
growth is estimated as the predicted value of aparsimonious panel regression of five-year averages oftrend TFP growth on lagged per capita income relative to

161

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GLOBAL ECONOMIC PROSPECTS | JANUARY 2018






BOX
3.1 What is potential growth? (continued)


FIGURE 3.1.1 Potential growth estimates
Estimates vary, according to the method of calculation,
but suggest that, in 2013-17, global potential output
growth fell by about 0.5 percentage point below its
longer-term average. This decline is reflected in allmeasures of potential growth and across countrygroups.
A. Global potential growth estimatesadvanced economies (to proxy for convergence-related
productivity catchup), education, demographics, and trend
investment.1 Potential labor supply is estimated as the
population-weighted aggregate of predicted values of ageand gender-specific labor force participation rates from
regressions on policy outcomes and cohort characteristics,
business cycles, and country effects.2 The potential capitalstock is assumed to match the actual capital stock.

1

Expectations. The approaches above are supplemented
with long-term growth expectations, such as five-yearahead growth forecasts from Consensus Economics or the
IMF’s World Economic Outlook. These growth expectations
reflect both model estimates and forecasters’ judgment.
Judgment can be especially useful during periods of major
structural changes, which model-based estimates may not
be well-equipped to capture.

0

Each approach has advantages and disadvantages.

Percent
4

3

PF

MVF

2013-17

1998-20172013-17

1998-20172013-17

1998-2017

1998-20172013-17

2

UVF

x

Filtering techniques. Even in data-poor environments,
univariate filters are straightforward to implement
while multivariate filters utilize additional
information that can ensure that the measure ofpotential output is better aligned with economic
theory. However, all statistical filters suffer from wellknown “end-point” problems—their measured trends
tend to overemphasize actual data at the beginningand end of the sample—and tend to correlate closelywith actual data.3 Measures of potential growth basedon filtering techniques correlate strongly with actual
output growth and with each other.

xProduction function approach. The production
function approach has the advantage of correlating
less with actual growth and producing estimates that
help explain the movement of potential output interms of its inputs. The distinct nature of potential
growth measured by the production function
approach is also reflected in its weak correlation withpotential growth based on filtering techniques. The
production function approach relies on proxies forpotential productivity and labor supply growth andExp.

B. G7 and EM7 potential growth estimates
Percent

8
6
4
2

PF

MVF

UVF
G7

Exp.

PF

MVF

UVF

2013-17

1998-20172013-17

1998-20172013-17

1998-20172013-17

1998-2017

1998-2017

1998-20172013-17

1998-20172013-17

1998-20172013-17

1998-2017

0

Exp.

EM7

Source: World Bank.
Notes: “PF” stands for potential growth estimates using the production
function approach, “MVF” for those derived using the multivariate filter, UVF
for those derived using the Hodrick-Prescott filter, and “Exp.” for those
based on 5-year-ahead World Economic Outlook forecasts. Bars reflect theestimates based on different potential growth measures.
A. To ensure comparability between the measures, the samples
are held constant to include 13 advanced economies and 15 EMDEs.
B. EM7: Brazil, China, India, Indonesia, Mexico, Russia, and Turkey; G7:
Canada, France, Germany, Italy, Japan, the United Kingdom, and theUnited States.

1 This approach is similar to Abiad, Leigh, and Mody (2007);
Bijsterbosch and Kolasa (2010); and Turner et al. (2016).
2 This approach combines those by Fallick and Pingle (2007) andGoldin (1995).
3 However, real-time estimates of actual and potential output responddifferently to shocks (Coibion, Gorodnichenko, and Ulate 2017).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018



CHAPTER 3


BOX 3.1 What is potential growth? (concluded)
capital structural accumulation that are liable tomeasurement error.
x

Expectations. Long-term growth expectations can inprinciple incorporate judgment and, thus, capture
factors that cannot be modelled. As a result, likethe production function based-estimates, long-term
growth expectations are only weakly correlated withfilter-based estimates of potential growth. However,in practice, expectations tend to be highly sticky and,at times, in ways that are challenging to interpret.

assumes that output can be modelled as a (Cobb-Douglas)
production function of total factor productivity (TFP),
labor supply and capital.5x

Estimated potential TFP growth is the fitted value
from a parsimonious panel regression of trend TFP
growth on relative per capita income as a proxy forconvergence potential, education, demographics, andtrend investment.

x

Estimated potential labor supply is the populationweighted aggregate of fitted values of age- and gender-specific labor force participation rates from
regressions on policy outcomes and cohort
characteristics, business cycles, and country effects.

x

The potential capital stock is assumed to match theactual capital stock.

Are the results robust to the choice ofmeasure?
This chapter draws on a comprehensive database that
estimates potential growth using all approaches. For eachapproach, the largest possible sample is used, up to 181
countries for 1980-2017 (extending to 2027 for the
production function approach). For presentational clarity,
the chapter presents only results using a production
function approach, which is available for 30 advanced
economies and 50 emerging market and developing
economies for 1998-2027 (Annex 3.1, Table 3.1.1).4 It

4 The 50 EMDEs include 4 economies in East Asia and the Pacific, 9
economies in Europe and Central Asia, 15 economies in Latin America
and the Caribbean, 7 economies in the Middle East and North Africa, 2economies in South Asia and 13 economies in Sub-Saharan Africa(Annex 3.1). Data for half of EMDEs (especially in Europe and Central
Asia and Sub-Saharan Africa) is missing before 1997. Hence, to ensure
broad country coverage, the sample period is restricted to 1998-2027.

0.5 percentage point. The projected slowdown
from 2013-17 would affect EMDEs andadvanced economies that account for 73
percent of global GDP.
x Policies could help reverse these trends andboost global growth. Among EMDEs, inparticular, education, health, and labor market
reforms could significantly increase potential
growth. Broader reform packages to improve
institutional quality and business climateswould also pay important dividends.
x Policy improvements are particularly critical at
the current juncture. Over the last halfcentury, the world economy has been
disrupted by a financial crisis of varying

The key results pertaining to potential growth presented
in this chapter are broadly robust to the choice ofpotential growth measures: the broad-based post-crisis
slowdown in potential growth (Figure 3.1.1), the decline
in potential growth through investment slumps (Box 3.3)
and deep recessions (Box 3.4), and the increase inpotential growth following multi-year growth upswings.

5 Human capital is not separately accounted for in the production
function approach but affects TFP growth and labor supply growth.

breadth and severity in every decade. If thispattern were to be repeated and another crisis
occurred in the next ten years, it would
generate lasting damage to potential output
that would require a sustained policy push toreverse.
The current cyclical upswing poses a risk ofcomplacency. To sustain higher potential growth,countries need to reform labor and productmarkets, strengthen human and physical capitaland build conducive environments for businessand households to invest. The onus is particularlyon the largest emerging markets and advanced
economies, whose growth momentum generates
spillovers for other EMDEs.

163

CHAPTER 3

164

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 3.2 Evolution of potential growth 
During 2013-17, global potential growth declined to 2.5 percent, below thelonger-term average and average rates a decade ago. In advanced
economies, potential growth declined below its longer-term average, toabout 1.4 percent. It slowed more sharply, to 4.8 percent, in EMDEs. The
potential growth slowdown affected most EMDE regions and accounted forabout one-third of the actual global growth slowdown.

A. Potential growth

B. Potential growth

Percent
8
Potential growth
Actual growth6
1998-2017 potential growth

Percent
10Potential growth
Actual growth
1998-2017 potential growth

8
6

4

4

2

2

World

AEs

0

1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27

1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27

0

EMDEs

G7

EM7

LICs

C. Contribution of potential growthand business cycle to actual growth

D. Share of economies and GDP withpotential growth below 1998-2017
average

Percent
8

Percent
100

20

Share of countries
Share of GDP

World

EMDE

AEs

E. Per capita potential growth

F. Per capita potential growth

Percent
8
Potential growth
Actual growth6
1998-2017 potential growth4

Percent
8 Potential growth
Actual growth
6 1998-2017 potential growth

2

2

EMDEs

1998-2017
2003-072008-122013-172018-27
1998-2017
2003-072008-122013-172018-27
1998-2017
2003-072008-122013-172018-27-2

1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27

0

-2

AEs

EMDEs

4

0

World

2013-17

2003-070
2003-072013-17World

2013-170

Contribution40

2003-0760

2

Contribution4

2003-07680

2013-17Cycle

2003-07

Potential

2013-17Growth

G7

EM7

LICs

Sources: Penn World Tables, World Bank.
Notes: Based on potential growth derived using production function approach.
A. B. C. E. F. GDP-weighted average.
A. C. E. Sample includes 30 advanced and 50 emerging market and developing economies.
B. F. G7 includes Canada, France, Germany, Italy, Japan, the United Kingdom and the UnitedStates. EM7 includes Brazil, China, India, Indonesia, Mexico, Russia, and Turkey. LICs includes 6
countries.
C. Blue bars denote average actual global growth during 2003-07 and 2013-17. Red bars denote thecontribution of global potential growth to the change in actual growth between the two five-year
periods; orange bars denote contribution of the cyclical component of global growth to change inactual global growth between the two five-year periods.
D. Number of economies and their share of global GDP among 30 advanced economies and 50
EMDEs with potential growth in each period below its longer-term average (1998-2017). Horizontal
line indicates 50 percent.

Thischapter draws on a comprehensive databasethat estimates potential growth using all standard
approaches for up to 181 countries for 1980-2017(extending to 2027 for 80 countries). For clarity,
the remainder of the chapter presents only results
using a production function approach for 30
advanced economies and 50 emerging market anddeveloping economies for 1998-2027 that together account for 91 percent of global GDP(Annex 3.1; Box 3.1).5 The key results pertaining
to potential growth presented here—such as thebroad-based slowdown in potential growth, thelong-term effect of deep recessions or investment
busts on potential growth, and the virtuous circle
triggered by sustained cyclical upswings—are
broadly robust to the choice of potential growthmeasures (Annexes 3.2-3.5; Box 3.1).

Evolution of potential
growth: What happened?
Slowdown in global potential growth. Global
potential growth fell to 2.5 percent a year during
2013-17. This is below its longer-term (19982017) average of 3 percent a year and even further
below its average a decade earlier (2003-07; Figure3.2). The potential growth weakness was broadbased and robust to the specific choice of potential
growth measures. During 2013-17, potential
growth was below its longer-term average in 87
percent of advanced economies and in almost halfof EMDEs. Economies with potential growth
below its longer-term average accounted for 69
percent of global GDP. Per capita estimates also
show a trend deceleration. These estimates suggestthat there was a persistent slowdown in global
potential growth beneath the temporary cyclicalshocks that appear to have been the main reasonsfor the post-crisis slowdown in actual growth fromelevated pre-crisis levels.

5 The 50 EMDEs include 4 economies in East Asia and the Pacific,
9 economies in Europe and Central Asia, 15 economies in Latin
America and the Caribbean, 7 economies in the Middle East andNorth Africa, 2 economies in South Asia and 13 economies in SubSaharan Africa (Annex 3.1). Data for more than one-third of them(and about half of the sample’s EMDEs in Europe and Central Asia
and Sub-Saharan Africa) is missing before 1997 and no data for
EMDEs is available before 1991. Hence, to ensure broad country
coverage, the sample period is restricted to 1998-2027.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

A. Potential growth in EMDE regions

B. Potential growth in EMDE regions

Percent
12
10
8
6
4
2
0

Percent
12
10
8
6
4
2
0

EAP

x MNA. The shortfall of potential growthduring 2013-17 from its longer-term (19982017) average was one of the sharpest in the
Middle East and North Africa (MNA, 1.2
percentage point) where investment growthplunged amid the oil price drop of mid-2014,a period of violent conflict and policy
uncertainty in parts of the region.
6 As in the broader set of advanced economies, potential growthin G7 economies—Canada, France, Germany, Italy, Japan, United
Kingdom, and United States—was, at 1.5 percent on average in2013-17, 0.3 percentage points below its longer-term average.
7 The potential growth slowdown from pre-crisis rates was also
evident in EM7 economies—Brazil, China, India, Indonesia, Mexico,
Russia, and Turkey. On average during 2013-17, EM7 potential
growth slowed to 5.4 percent. Almost three-quarters of this decline in
EM7 potential growth between 2003-07 and 2013-17 reflectedslowing potential growth in China.

LAC

MNA

SAR

SSA

D. Share of economies and GDP withpotential growth below 1998-2017
average in EMDE regions

Percent
100

Percent
100

ECA

LAC

MNA

SAR

2018-272013-17

2003-072018-272013-17

2003-072018-272018-272013-170
2003-0720

0

2018-27

40

20

2013-1760

40

2003-0780

60

2018-27

80

Share of countries
Share of GDP

2013-17

Share of countries
Share of GDP

2003-07

C. Share of economies and GDP withpotential growth below 1998-2017
average in EMDE regions

EAP

Regional patterns. Potential growth has fallen
furthest in EMDE regions that had benefited fromrapid per capita income convergence or that
hosted many commodity-exporting EMDEs(Figure 3.3).

ECA

Potential growth
Actual growth
1998-2017 potential growth

1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27

Potential growth
Actual growth
1998-2017 potential growth

2013-17x EMDEs. In the initial wake of the global
financial crisis, a surge in public investment
underpinned EMDE potential growth,
offsetting softening productivity and labor
supply growth. As EMDE policy stimulus was
unwound, and as investment growthplummeted in commodity-exporting EMDEs
following the oil price slide in mid-2014,
EMDE potential growth slowed sharply to 4.8
percent a year in 2013-17, 0.6 percentage
point below its longer-term average.7

Potential growth has slowed from its longer-term average in all EMDE
regions other than South Asia and Sub-Saharan Africa. Among the causes
are weakening fundamentals and disruptions to growth prospects, such as
sharp and persistent commodity price declines (for commodity exporters),
crises in major trading partners such as the Euro Area (for the ECA region),and spillovers from growth slowdowns in major economies (such as from
China).

1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27
1998-2002
2003-072008-122013-172018-27x Advanced economies. After a sharp decline
during 2008-12—the period of the global
financial crisis, the Euro Area crisis, andpronounced investment weakness—potential
growth stabilized in 2013-17 as investment
growth recovered.6 However, at 1.4 percent a
year over 2013-17, potential growth in advanced economies remains about 0.5 percentage points below its longer-term average.

165

FIGURE
3.3 Regional potential growth

2003-07

Broadening
slowdown. In advanced economies,the potential growth slowdown set in before theglobal financial crisis whereas EMDEs enjoyed ashort-lived pre-crisis surge in potential growth that
subsequently faded.

CHAPTER 3

SSA

Sources: Penn World Tables, World Bank.
Notes: EAP = East Asia and Pacific, ECA = Europe and Central Asia,
LAC = Latin America and the Caribbean, MNA = Middle East and North Africa, SAR = South Asia,
and SSA = Sub-Saharan Africa.
A. B. GDP-weighted averages using potential growth estimate based on production function
approach.
C. D. Number of economies and their share of GDP in the region among 50 EMDEs with potential
growth in each period below its longer-term average (1998-2017). Horizontal line indicates 50
percent.

x ECA, LAC. During 2013-17, potential growth
also fell 0.5 and 0.2 percentage points,
respectively, below its longer-term average inEurope and Central Asia (ECA) and Latin
America and the Caribbean (LAC). The ECA
region’s past two decades of rapid integration
into European production networks has
gradually diminished its potential for further
catchup productivity growth. The region also
hosts several energy exporters which suffereddeep recessions or slowdowns following themid-2014 decline in oil prices. Weakproductivity growth and less favorable

CHAPTER 3

166

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 3.4 Drivers of potential growthThe post-crisis slowdown in global potential growth below its longer-term
average rates has mainly reflected slowing capital accumulation, labor
supply growth, and TFP growth. In ECA and LAC, the decline
predominantly reflected weak TFP growth. In EAP and MNA, slowing TFP
growth was compounded by weak investment. In SAR and SSA, favorable
demographic trends offset investment weakness (SAR) and weak
productivity growth (SSA).
B. Contributions to potential growthin EMDE

EMDEs

EAP

ECA

LAC

MNA

2018-272013-17

2003-07

1998-20172018-27

SAR

2018-272013-17

2003-072003-072018-272013-17

2003-07

1998-20172018-272013-17

2003-07

1998-20172018-272013-17

2003-07

1998-2017

0

CapitalPotential growth

1998-20172

2013-17

4

TFP
Labor

1998-2017

Percent
10
8
6
4
2
0
-2

6

EMDEs excl.China

D. Contributions to regional potential
growth2018-27

TFP
CapitalLabor
Potential growth8

2013-17

EMDEs

C. Contributions to regional potential
growthPercent
10

1998-20172018-272013-17

2003-072018-27

1998-20172013-17AEs

2003-07World

2003-072018-27

1998-20170

2013-172

0

2003-074

2

1998-2017

64

2003-078

6

1998-2017

8

TFP
CapitalLabor
Potential growth

Percent
10

2018-27

TFP
CapitalLabor
Potential growth

Percent
10

2013-17

A. Contributions to potential growth

EAP, potential growth rose 0.7 percentage
point on robust capital accumulation andstrengthening TFP growth.

x SAR, SSA. During 2013-17, favorable
demographics have helped lift potential
growth in South Asia (SAR) and Sub-SaharanAfrica (SSA). In SAR, rates were offset byinvestment weakness such that potential
growth in 2013-17 broadly matched its longer-term average. In SSA, potential output
accelerated by 0.4 percentage point during
2013-17 compared to its longer-term average.
This demographic dividend was complemented by rapid capital accumulation over the
past two decades as resource discoveries weredeveloped into operating mines and oil fields
and governments undertook large-scale public
infrastructure investments. The commodity
price slide after 2011 has raised concerns
about the sustainability of such potential
growth.

Drivers of the slowdown inpotential growth

SSA

Sources: Penn World Tables, World Bank.
Notes: GDP-weighted averages of production function-based potential growth estimates (as definedin Annex 3.1). TFP growth stands for total factor productivity growth.
A.B. Sample includes 30 advanced economies and 50 EMDEs.
C.D. Regional samples include largest available sample for each region to ensure broad-based
coverage. EAP = East Asia and Pacific, ECA = Europe and Central Asia,
LAC = Latin America and the Caribbean, MNA = Middle East and North Africa, SAR = South Asia,
and SSA = Sub-Saharan Africa.

demographics reduced potential growth in
LAC.8
x EAP. In 2013-17, potential growth in China
fell 1.3 percentage points below its longerterm average as policy efforts succeeded inrebalancing growth away from investment
towards more sustainable growth engines,
combined with slowing productivity andworking-age population growth. Elsewhere in
8 In contrast to production function-based potential growthmeasures, potential growth estimates based on filtering techniques
have slowed sharply in LAC and SSA. The predominantly hostcommodity exporters, where actual growth decelerated steeply in thecommodity price slide from 2011.

Contribution of different drivers. Of the 0.5percentage-point shortfall in post-crisis (2013-17)
global potential growth below its longer-term(1998-2017) average, about one-half can be
attributed to weaker capital accumulation (0.2
percentage point) and the remainder to weaker
TFP growth and slower labor supply growth (0.1
percentage point, respectively; Figure 3.4). Weakglobal capital accumulation mainly reflected
investment weakness in advanced economies, inthe wake of financial crises in the United Statesand Europe, and a policy-driven rebalancing awayfrom investment in China. Unfavorable
demographics and slowing TFP growth werefeatures of both advanced economies and EMDEs(Figure 3.4).
Total factor productivity growth
Channels of transmission. By allowing output toexpand with a given amount of factor inputs, TFP
growth has historically been the critical driver ofsustained growth in per capita output andGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Evolution of potential TFP growth. Global
potential TFP growth—the part of TFP growththat is stripped of its wide cyclical swings—slowedfrom about 1.3 percent a year a decade ago toabout 1 percent a year during 2013-17, but withwide heterogeneity (Figure 3.5). In advanced
economies, productivity growth showed signs offlattening well before the global financial crisis.
For some advanced economies, the productivity
growth slowdown during the early 2000s has been
described as a return to productivity growth before
the surge of information and communications
technologies in the mid-1990s (Gordon 2013;
Cette, Fernald, and Mojon 2016).
By contrast, TFP growth in EMDEs surged to 2.5
percent a year a decade ago (2003-07), reflecting
productivity-enhancing investment, partly financed by capital inflows.9 Reforms of policy
frameworks after EMDE financial crises in the late
1990s and early 2000s and greater integration into
global value chains provided a conducive
environment for rapid productivity growth.
However, since 2007, TFP growth in EMDEs has
slowed to 1.9 percent a year in 2013-17.
Sources of the TFP growth slowdown. Somesources of the TFP growth slowdown are likely to

9 The regression results suggest that for many EMDEs, catchup
productivity growth is a key driver of overall TFP growth (Annex
3.1).

167

FIGURE
3.5 Total factor productivity growthPotential TFP growth has declined from average rates a decade ago andare now below longer-term averages in the majority of advanced
economies, EMDEs, and EMDE regions.
A. Average TFP growth

B. Share of economies and GDP with
TFP growth below its longer-term
average

Percent
3

Percent
100

1998-2007 average

Share of countries
Share of GDP

80

2

60
40

1

20

AE

EMDE

World

AEs

2018-272013-17

2003-072018-27

1998-2002

2013-17

2003-072018-27

1998-2002

2013-17

2003-072018-272013-17

2003-072018-272013-17

2003-072018-272013-17World

1998-2002

00

2003-07

prosperity(Romer 1986; Lucas 1988; Grossman
and Helpman 1991). TFP growth can rise withthe adoption of new technologies, adaptation ofexisting technologies, introduction of more
efficient processes, or changes in management
practices (EBRD 2014). Differences in TFP
account for about two-thirds of the variation in
per capita income across the world (Jones 2016).
Higher productivity lifts firms’ marginal productand reduces their marginal cost, which allows
firms to increase their demand for factors of
production. Technological advances reduce theprice of capital equipment, encouraging further
capital accumulation which, in turn, embodies
further improvements in productivity (Greenwood, Hercowitz, and Krusell 1997; Sakeflaris
2004; Box 3.2).

CHAPTER 3

EMDEs

Sources: Penn World Tables, World Bank.
Note: TFP growth stands for total factor productivity growth. This figure refers to potential TFP growth(Annex 3.1).
A. GDP-weighted average of total factor productivity growth. Includes 50 EMDEs and 30 advanced
economies.
B. Number of economies among 30 advanced economies and 50 EMDEs in which potential totalfactor productivity growth is lower than its longer-term average (1998-2017).

be structural and persistent. TFP growth may haveslowed as a wave of information and communications technologies matured (Box 3.2). Crosscountry diffusion of technology may have slowed
as global value chains stopped growing. Aging
workforces may have slowed the adoption of new
ideas. In commodity exporters, a downgrading of
expectations for long-term profitability of resource
projects would have reduced investment and, withit, embodied productivity gains. Finally, the largescale factor reallocation, especially from agriculture
to manufacturing, that has supported robust
EMDE productivity growth over the past two
decades appears to be slowing (Box 3.2).
The role of human capital. Over the past three
decades, TFP growth in EMDEs has been
supported by growing human capital. Among a
better-educated and healthier working-age
population, both TFP growth and labor force
participation rates tend to be higher. EMDEs havemade rapid strides towards improving educationand health outcomes over the past two decades.
x On average in EMDEs, secondary school
completion rates have increased by 7
percentage points between 1998-2002 and2013-17. At 27 percent, this is about twothirds of the advanced-economy average.

168

CHAPTER 3

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018






BOX
3.2 Understanding the recent productivity slowdown:
Facts and explanations


Potential total factor productivity growth slowed, post-crisis, below its longer-term average and pre-crisis levels. The slowdown
started well before the global financial crisis in advanced economies (AEs) and spread to EMDEs after the crisis. Weakerproductivity growth has been attributed to slower investment growth, partly because of heightened uncertainty and crisis legacies,
population aging, increased regulation, and maturing global value
chains and information and communications technology.
Introduction
Global growth of total factor productivity (TFP), definedas the residual part of output growth not explained byfactor accumulation, has slowed sharply over the past
decade. Much of this reflected a steep cyclical slowdown,
but global potential TFP growth—the focus of this box—
also slowed in 2013-17 below its pre-crisis and longerterm average (Figure 3.2.1). Labor productivity growth,
defined as output growth per worker, has shown a similar
decline.
In advanced economies, TFP growth was flattening before
the global financial crisis, as documented in the large
literature reviewed below. By contrast, TFP growth in
EMDEs surged to 2.5 percent a year during 2003-07,
reflecting productivity-enhancing investment, partly
financed by capital inflows, and ample room forconvergence-driven productivity growth (Adler et al.
2017). Reforms of policy frameworks after EMDE
financial crises in the late 1990s and early 2000s andgreater integration into global value chains provided a
conducive environment for rapid productivity growth.
However, TFP growth in EMDEs slowed to 1.9 percent a
year in 2013-17 amid investment weakness in the twothirds of EMDEs that are commodity exporters, rapid per
capita income convergence in commodity importers thatnarrowed the room for catchup productivity growth insome EMDEs, and a policy-driven rebalancing away frominvestment growth in China.
The recent slowdown in TFP growth was broad-based but
steepest in commodity exporters (Figure 3.2.1). In EMDE
regions where commodity exporters have struggled toadjust to low commodity prices (MNA, LAC, SSA) or
which faced heightened political uncertainty that weighedheavily on investment, TFP growth slowed to near-zero
during 2013-17. In contrast, TFP growth continued to berobust above 3 percent during 2013-17 in East Asia andPacific (EAP) and Southeast Asia (SAR)—both regions
hosting predominantly commodity-importing economies.

Note: This box was prepared by Ergys Islamaj, M. Ayhan Kose, andFranziska Ohnsorge.

Considering the synchronous slowdown in productivity
growth, this box addresses two questions:x What are the linkages between productivity growthand potential output growth?

x What are the reasons behind the ongoing productivity
slowdown?

Linkages between productivity and potential
output growthDifferences in productivity growth account for about twothirds of the variation in per capita income across theworld (Jones 2016). Higher productivity lifts firms’
marginal product and reduces their marginal cost, whichallows firms to increase their demand for factors of
production and, in turn, expand output. Technologicaladvances can also reduce the quality-adjusted price ofcapital equipment, encouraging further capital
accumulation which, in turn, embodies further
improvements in productivity (Greenwood, Hercowitz,
and Krusell 1997).
Weaker productivity growth reduces not only actual
output growth, but also potential output growth. For
example, the productivity slowdown in the United States,
which pre-dates the global financial crisis, may reflect a
return to productivity growth rates before the surge of
information and communication technologies (ICT) in
the 1990s and the early 2000s and may, therefore, be
associated with a long-term reduction in potential output
growth (Fernald 2015; CBO 2014).1 Other factors, suchas financial frictions that reduce investment in R&D andpopulation aging, have contributed to the recent
slowdown in TFP growth and may have dampened thepotential of the economy to innovate in the future, i.e.,they may have reduced potential TFP and output growth.

Explanations of productivity growth slowdown
The literature offers a number of explanations for slowing
productivity growth. These include temporary factors—
1 CBO (2014) has revised its estimates of potential GDP growthcompared to 2007, taking into account a lower rate of productivity
growth. 

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 3

BOX 3.2 Understanding the recent productivity slowdown: Facts and explanations (continued)
FIGURE 3.2.1 Evolution of potential productivity growth
Potential productivity growth slowed in advanced economies and EMDEs during 2013-17 to rates below longer-term averages
and average rates a decade ago.

1

EMDEs

EAP

ECA

2003-072013-17

2003-07-1
2013-1700

2003-07

1

MNA

LAC

2013-172

2

2013-17

2003-07AEs

3

1998-2017

SAR

SSA

E. Labor productivity growth

F. EMDEs: Labor productivity growth

Percent
4

Percent
3

Percent
7
6
5
4
3
2
1
0

EM7

EM7 excl.
China

Commodity
exporters

Commodity
importers

World

AEs

EMDEs

EM7

EM7 minus
China

Commodity
exporters

2003-072013-172013-17

2003-072013-17

2003-072013-17

2003-072013-17

2003-072013-17

2003-072013-17

2003-072013-170
2003-070

2003-07

1

1

2013-172

2

1998-2017

2003-073

1998-20172013-17

1998-2017

2003-07

D. EMDEs: TFP growth

2013-17World

2013-17

2003-072013-17

2003-070

3

2013-171

4

2003-07

2

Percent
4

1998-2017

2003-07

Percent
5

1998-20172013-17

Percent3

C. Regional TFP growth

2003-07

B. Regional TFP growth

2013-17

A. TFP growthCommodity
importers

Source: World Bank.
Notes: GDP-weighted averages of potential total factor productivity growth, defined as in Annex 3.1. AEs: advanced economies; EMDEs: emerging market and developing
economies; EAP = East Asia and Pacific; ECA = Europe and Central Asia; LAC = Latin America and the Caribbean; MNA = Middle East and North Africa; SAR = SouthAsia; SSA = Sub-Saharan Africa; EM7: Brazil, China, India, Indonesia, Mexico, Russia, and Turkey; G7: Canada, France, Germany, Italy, Japan, the United Kingdom, andthe United States.
A. D. Sample includes 30 advanced economies and 50 EMDEs.
E. F. GDP-weighted averages of potential labor productivity defined as potential GDP divided by potential employment.

such as heightened policy uncertainty, crisis legacies thathave eroded investment—as well as persistent factors, suchas maturing global value chains, a switch in informationand communications technologies to consumer applications (from productivity-enhancing hardware and software), and slowing human capital accumulation.2 In thecontext of EMDEs, slowing productivity growth has also
been attributed to slowing factor reallocation.

2 Some authors question the very existence of a productivity growth
slowdown, arguing that productivity is increasingly mismeasured(Brynjolfsson and McAfee 2011, 2014). However, thus far there has been
limited evidence of rising mismeasurement during the last decade (Byrne,
Fernald and Reinsdorf 2016; Syverson 2017). In addition, in the UnitedStates, the productivity growth slowdown has spread broadly acrosssectors, and, as a result, cannot be explained by a shift of economic
activity towards poorly measured, low-productivity-growth sectors, suchas services (Fernald et al. 2017).

Uncertainty and investment slowdown. The decade
2008-17 was marked by heightened policy uncertainty,
including following the global financial crisis and the EuroArea crisis. Uncertainty dampens investment, leading tolower productivity growth through less investment in
R&D and through the loss of improved technologies
embodied in new capital equipment (World Bank 2017a;
Box 3.3). Uncertainty may also slow the reallocation of
resources from less to more productive firms and fromlarger and older towards more innovative younger firms, ascredit markets may be less willing to finance risky start-ups(Bloom 2009; Bloom 2014; Fort et al. 2013; Baker et al.
2016). In LAC, weak investment, especially in intangible
assets, has contributed to low productivity growth(OECD 2016a).
Crisis legacies. Deep recessions, especially those following
financial crises, can lower TFP levels (Fatás 2000; Adler et

169

170

CHAPTER 3

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018






BOX
3.2 Understanding the recent productivity slowdown:
Facts and explanations (continued)
al. 2017; Reinhart and Rogoff 2014).3 Financial frictions
following severe recessions and crises may reduceinvestment in research and development, especially infirms with pre-existing balance-sheet vulnerabilities
(Aghion et al. 2012; Duval, Hong and Timmer 2017).
Hence, the global financial crisis and Euro Area crisis may
have deepened a TFP growth slowdown already underway(Cette, Fernald, and Mojon 2016). An event study of 161
contractions in 93 advanced and emerging market anddeveloping economies during 1981-2016 show that actual
TFP growth typically fell sharply during contractions, andthe subsequent rebounds were insufficient to lift TFPlevels back to their pre-crisis paths (Figure 3.2.2).4 In
particular, the severe recessions in EMDE commodity
exporters following the commodity price slide from 2011
may account for some of the recent slowdown in EMDE
productivity growth. Yet, the timing of the productivity
slowdown for advanced economies suggests that the main
drivers are factors other than the global financial crisis orsubsequent coping policies.
Trade slowdown. International trade growth slowed
sharply following the global financial crisis (World Bank
2015a). Weaker trade growth slows incentives for firms toinvest and eases competitive pressures. As a result, the paceof resource re-allocation within firms and within sectors
toward more efficient firms and sector slows (Adler et al.
2017; Ahn and Duval 2017). In addition, the spread ofvertical specialization, which had been a significant force
for both earlier productivity gains and trade growth,slowed as global value chains have matured (Matoo,
Neagu, and Ruta 2017). While the post-crisis slowdown intrade has dampened productivity growth in open
economies, elevated tariff and non-tariff barriers havedepressed trade openness, competition, access to global
technologies, and, hence, productivity growth in MNA(Freund and Jaud 2015).
Slowing population growth and human capital
accumulation. As population growth has slowed, thegrowth of the labor force has also declined. In advanced
economies, the working-age share of the population has
declined since the mid-1980s and, more recently, in

3 In theory, the constraints imposed by credit crunches and recessions
should force the least productivity firms out of business and lift aggregate
productivity growth (Petrosky-Nadeau 2013).
4 Contractions are defined as the years of negative output growth fromthe year after the output peak to the output trough. Sample includes 161
events for 32 advanced economies and 61 emerging market anddeveloping economies for the period 1981-2017. The methodology is
described in detail in Annex 3.4. EMDEs. An older labor force has, historically, been
associated with slower learning of new skills and withslowing innovation and productivity growth (Maestas,
Mullen, and Powell 2016). Population aging may haveaccounted for as much as 0.2–0.5 percentage point lower
average productivity growth in advanced economies in the
2000s than the 1990s (Adler et al. 2017). In LAC,
specifically, poor education and skills have been central to
low productivity growth (OECD/ECLAC/CAF 2016).
Maturing ICT. Information and communication
technologies (ICT) has boosted productivity in the ICTproducing and ICT-related industries since the mid-1990s
and, as it became a general-purpose technology, in otherindustries (Fernald 2015; Fernald et al. 2017; Basu et al.
2004). Businesses throughout the economy became more
efficient by reorganizing to take advantage of ICT. Afteran uptick in productivity in the U.S. and other advanced
economies in the mid-90s and early 2000s, ICT
technologies and their absorption appear to have beenmaturing (Fernald 2015).5 Productivity growth in EMDEs
tends to reflect advanced-country productivity trends witha lag, as technological innovations first introduced incountries at the technology frontier are eventually adopted
by the rest (Comín et al. 2014; Gordon 2016). Costs ofextracting ideas may have also increased over time, making
it more likely that productivity growth will remain low in
the future (Bloom at al. 2017). In addition, hi-techinnovation seems to have shifted this century fromproductivity-enhancing hardware and software, toward
consumer applications (Gordon 2016).
Rising regulation and loss of dynamism. The stringencyof labor and product markets regulations may be
negatively correlated with productivity levels acrosscountries (Fatás 2016; Cette, Fernald, and Mojon 2016;
Nicoletti and Scarpetta 2005). Deregulation may boost
productivity by accelerating the reallocation of resources,
facilitating technology diffusion and adoption, andincreasing incentives to innovate. In the U.S. ICT sector,
deregulation may have also increased labor market
flexibility and allocative efficiencies since the early 2000s(Decker et al. 2016, 2017). In contrast, zoning restrictions
in U.S. cities heightened housing supply constraints andreduced the efficiency of labor allocation across the UnitedStates (Hsieh and Moretti 2015). In the United States,changes in the federal regulatory burden do not appear to5 Adler et al. (2017) find that a shock to the U.S. TFP has had agradual, increasing and significant spillover effect in the TFP of otheradvanced economies over the 1970-2010 period. 

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018



CHAPTER 3


BOX 3.2 Understanding the recent productivity slowdown: Facts and explanations (concluded)
FIGURE 3.2.2 Productivity growth around contractions
Productivity growth has tended to slow by 4 percentage points during typical contraction episodes and to rebound quickly
during subsequent expansions. The contraction episodes in commodity exporters following the commodity price slide after
2011 were associated with sharp declines in productivity growth.
A. Advanced economies

B. Emerging market and developing
economies

C. World, 2007-09

Percent
6

Percent
6

Percent
6

4

4

4

2

2

2
0
-2

2013-17

0

0

-2

-2

-4

-4

-4

-6

-6

-6

-8
t-2

t-1

t

t+1

t+2

-8
t-2

t-1

t

t+1

t+2

t-2

t-1

t

t+1

t+2

Sources: Penn World Tables, World Bank.
Notes: Blue lines show unweighted averages around 161 contraction episodes in 32 advanced economies and 61 EMDEs. The methodology is described in detail in
Annex 3.4. Dashed lines show 25th and 75th percentiles. Horizontal axis shows years.
A. B. t denotes the year of a business cycle peak preceding the contraction.
B. Red line shows unweighted average total factor productivity growth in countries that had recessions during 2013-2017 (Brazil, Burundi, Ecuador, Russia, Sierra
Leone, Swaziland, Trinidad and Tobago, Ukraine, and República Bolivariana de Venezuela).
C. There are 52 countries identified as having a business cycle peak in 2008. t denotes 2008.

explain variations in productivity growth, many smallchanges in the regulatory and institutional framework may
have contributed to a decline in entrepreneurshipdynamism and a decline in job and worker flows into thehigh-tech sector (Fernald et al. 2017; Haltiwanger 2015).

McMillan, Rodrik, and Verguzco-Gallo 2014). As thepotential for reallocation is gradually exhausted, related
productivity gains may be slowing.

Slowing reallocation between firms and sectors.
Reallocation of capital and workers toward more efficientfirms and sectors has been an important driver of
productivity growth over the past two decades both in AE
and EMDEs (Restuccia and Rogerson 2017). In Europe,
structural rigidities in labor and product markets may havehindered a favorable reallocation of resources. In China,
the reallocation of labor from agriculture to manufacturing
has been an important source of productivity growth (Caoand Birchenall 2013; Deininger et al. 2014). A
reallocation of labor from low-productivity to highproductivity activities has been a major driver of
productivity growth in Africa, Latin America and the
Caribbean, and East Asia and the Pacific (Űngőr 2017;

Global productivity growth has slowed over the past two
decades. Some of the underlying drivers of this slowdown
may fade over time, such as policy uncertainty and crisis
legacies. Others, however, are likely to persist: the decline
in labor force growth and population aging; a levelling-off
of productivity-enhancing innovations in information andcommunication technologies; and maturing global supply
chains. Policies to address these persistent factors include
better education for improved learning in aging
populations and initiatives to stimulate investment inphysical capital and research and development. Other
measures, such as regulatory reform and tradeliberalization, could raise productivity by reducing
informality and increasing competition.

Conclusion

171

172

CHAPTER 3x Tertiary completion rates have risen by about
one-half to 10 percent in 2013-17, but still
about half of the advanced-economy average.
x Life expectancy has risen by 4 years to 71
years, about 10 years short of the advancedeconomy average.
These substantial improvements in human capital
mitigated other developments weighing on
EMDE potential growth between 1998-2002 and2013-17, and helped raise potential growth inregions where progress was particularly large. The
largest improvements between 1998-2002 and2013-17 were made in SSA, where secondary
completion rates almost doubled (by 7 percentage
points) to approach the advanced-economy
average, and life expectancy rose by 7 years toalmost 60 years. Life expectancy also rose
considerably (4 years) in South Asia to 72 years.
Physical capital accumulation
Channels of transmission. Investment can lift
potential output growth through direct andindirect channels (Box 3.3). Directly, investment
is the source of capital accumulation, which raises
labor productivity and potential output—
provided investment is not channeled into excess
capacity and wasted (Devarajan, Swaroop, andZhou 1996; Presbitero 2016). Indirectly,
investment can raise total factor productivity
because technological improvements are often
embodied in investment (Solow 1962).
Evolution of investment growth. Global
investment growth halved between 2010 and2016, with the investment weakness shifting fromadvanced economies to EMDEs over this period.
Investment growth in advanced economies
declined during the Euro Area crisis and, after abrief rebound, again after the oil price decline that
disrupted energy sector investment in the UnitedStates. In EMDEs, investment growth slowed
sharply following the global financial crisis, fromdouble-digit rates in the immediate wake of thecrisis to a post-crisis low of 3 percent in 2016.
Despite signs of bottoming out in 2017,
investment growth has been well below its precrisis average as well as its longer-term average in

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

more
than half of EMDEs in the sample (Figure3.6). In EMDEs, both public and private
investment were weak. Public investment
accounted for about 31 percent of total
investment in EMDEs and about 15 percent ofadvanced-economy investment during 2010-15(World Bank 2017). After 2011, public
investment growth remained anemic following thestimulus-related surge of 2008-09 and private
investment growth slowed sharply after 2011.
Sources of investment weakness. Whereas
investment weakness in advanced economies
mainly reflected sluggish demand and output
growth, in EMDEs a broader range of factors has
been at play. In commodity importers, slowing
FDI inflows and spillovers from soft activity inmajor advanced economies accounted for much of
the slowdown in investment growth after 2011. In
commodity exporters, a sharp deterioration in
their terms of trade (particularly for energy
exporters), slowing growth in China, andmounting private debt burdens accounted formuch of the slowdown in investment growth. In
several EMDEs, political and policy uncertainty
was a key factor in investment contractions or
slowdowns (Kose et al. 2017). Investment
weakness may also reflect the declining price ofcapital goods or a growing role of poorly-measured
intangible capital, such as design, research anddevelopments, marketing and training (Corradoand Hulten 2010; Ollivaud, Guillemette, andTurner 2016).
Consequences of investment weakness. Cyclicalfactors, although transitory in themselves, canhave long-lasting effects on potential output
growth. More than half of EMDEs in the sample
suffered at least one year of investment contraction
during 2013-17. In some, investment contractions
were triggered by the prolonged slump ofcommodity prices from their peak in early 2011.
In others, it was accompanied by heightened
domestic political or geopolitical tensions. Suchepisodes typically foreshadow weaker potential
growth in the three years surrounding the troughof the investment contraction (Box 3.3).
Investment contractions are one reason for thelong shadow cast by deep recessions over potential

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 3

BOX 3.3 Moving together? Investment and potential output

The recent slowdown in potential growth coincided with considerable investment weakness in emerging market and developing
economies (EMDEs). After briefly reviewing the main linkages between investment and potential output, this box documents thatinvestment busts (booms) are often associated with weaker (stronger) TFP and potential output growth.

Introduction
Since 2010, investment growth slowed sharply inemerging market and developing economies (EMDEs),
from double-digit rates in the wake of the global financial
crisis to a post-crisis low of 3 percent in 2016 (Figure
3.3.1). This slowdown has resulted from a range ofheadwinds facing EMDEs, including a sharp decline incommodity prices, slower FDI inflows, elevated policy
uncertainty, and weaker growth expectations (Kose et al.
2017; Vashakmadze et al. 2017; World Bank 2017).
Irrespective of its causes, weaker investment growth candampen potential growth by reducing the speed of capital
accumulation and the rate at which new technologies
embedded in investment can increase productivity.
As global growth has firmed in recent quarters, investment
growth in EMDEs has begun to bottom out: investment
growth stabilized at 4.5 percent in 2017 and is expected torise to 4.8 percent in 2018. It remains an open question towhat extent the benefits of the ongoing investment pickup
could offset the adverse effects on potential output growthof past protracted weakness in investment andproductivity, and demographic shifts.
Against this background, this box addresses two questions.
xWhat are the basic linkages between investment andpotential growth?

xHow do TFP growth and potential output growthchange during investment booms and busts?

Linkages: Theory and evidence
Investment growth can lift potential output growththrough direct and indirect channels. Directly, capital
accumulation raises potential output growth and laborproductivity growth. Indirectly, investment can raise totalfactor productivity because of technological improvements
embedded in investment in new equipment or researchand development.1
Note: This box was prepared by M. Ayhan Kose, Franziska Ohnsorge,and Temel Taskin.
1 Evidence for such investment-specific technological change has beenpresented in Greenwood, Hercowitz, and Krusell (1997 and 2000);
Cummins and Violante (2002); Fischer (2006); Boileau (2002); He andLiu (2008); Levine and Warusawitharana (2014); Doraszelski and
Jaumandreu (2013); and Hendricks (2000).

A large literature has provided firm-level evidence insupport of the linkages between investment andproductivity growth (Syverson 2011).2 Higher level ofinvestment in research and development, and informationand communications technology are associated withparticularly large gains in firm productivity.3 Jorgenson,
Ho, and Stiroh (2007), for instance, find that investment
in information technology played a dominant role in the
U.S. productivity surge in the late 1990s and accounted
for about one-third of productivity growth over 20002005. In addition to its direct impact on productivity,
investment growth also tends to amplify the benefits ofother sources of firm productivity, including staff
education and experience, managerial skills, and firm
structure (Bloom, Sadun, and Reenen 2012; Cirera andMaloney 2017).4
Macro-level evidence supports the linkages between
investment growth and productivity growth. Investment inmachinery and equipment has supported laborproductivity growth in advanced economies and EMDEs(Herrerias and Orts 2012; De Long and Summers 1992aand 1992b). Research and development investment has
been associated with higher productivity (IMF 2016).
Growth of non-military public investment, especiallyinfrastructure investment, has lifted total factor
productivity growth (Aschauer 1989; Calderón, MoralBenito, and Servén 2015; Ramirez 1998a, 1998b). Finally,
aggregate investment growth appears to be associated withfaster total factor productivity growth in OECD countries(Mourougane et al. 2016; Fournier 2016) and some
EMDEs (Fedderke et al. 2005; Hendricks 2000). The
slowdown in trend labor productivity growth between

2 For firm-level evidence, see Faggio et al. (2013); Boeing, Mueller,
and Sandner (2015); Commander, Harrison, and Menezes-Filho (2011);
and Aw, Roberts, and Xu (2008).
3 Oliner, Sichel, and Stiroh (2007); Castellani et al. (2016); Raymond
et al. (2015); and d’Artis and Siliverstovs (2016).
4 Van Ark, O’Mahony, and Timmer 2008 document that investment
in information and communication technology accounted for about onethird of the contribution of labor productivity to output growth in theEuropean Union and the United States during 1995-2004. De Long andSummers 1992b estimate a 0.2- and 0.4-percentage-point increase inlabor productivity growth in response to a 1-percentage-point increase in
the investment-to-GDP ratio in a large sample of advanced and emerging
market economies. Fournier 2016 finds that a 1-percentage-point
increase in the share of public investment in primary government
spending is associated with a 5 percent increase in long-term output inOECD countries.

173

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




BOX
3.3 Moving together? Investment and potential output (continued)

FIGURE 3.3.1 Potential output growth and investment growth
Investment growth in EMDEs has halved since 2010. Since capital accumulation makes a major contribution to potential
output growth both directly, and indirectly via TFP, the slowdown
has negative implications for future growth prospects.
A. Investment growth

B. Investment growth expectations

C. Output growth expectations

Percent
16
2003-07 average
1998-2017 average
12Percent
8

Percent
8

World
AEs
EMDEs

6

6

4

4

2

2

0

0

8

World
AEs
EMDEs

4

2017

2016

2015

2014

2013

2012

2011

2010

2017

2016

2015

2014

2013

EMDEs

2012

AEs

2011

World

2010

2010
2012
2014
2016
2018
2010
2012
2014
2016
2018
2010
2012
2014
2016
2018

0

Sources: Consensus Economics, Haver Analytics, Penn World Tables, World Bank.
Note: GDP-weighted averages.
A. Investment-weighted averages. Sample includes 37 advanced economies and 145 EMDEs.
B. Based on data for 24 advanced economies and 21 EMDEs. Five-year-ahead Consensus investment growth forecasts. Latest data is from July 2017.
C. Based on data for 24 advanced economies and 21 EMDEs. Five-year-ahead Consensus output growth forecasts. Latest data is from July 2017.

2007 and 2015 has been entirely attributed to weakness incapital accumulation in OECD countries (Ollivaud,
Guillemette, and Turner 2016). Conversely, investment
busts may be accompanied by firm closures that reduceaverage productivity (Campbell 1998).

TFP and potential output during investment
booms and busts
Data. Annual aggregate investment data is available fromseveral sources, including the IMF, Eurostat, OECD, andWorld Bank. The impact of investment booms on TFP
growth and on potential output growth is illustrated withan event study. Potential growth is estimated using the
production function approach, but the results are robust to
using other measures.
Definitions. An investment boom (bust) is defined as an
episode during which investment growth is at least one
standard deviation higher (lower) than its sample average
for at least two consecutive years. The sample covers 94
episodes of investment booms and 32 episodes ofinvestment busts in 40 EMDEs during 1980-2016. About
one-half of busts but few booms occurred after the global
financial crisis. A typical investment boom and bust
episode lasts about 2.7 and 2.3 years, respectively.
Methodology. The evolution of TFP growth and potential
output growth 3 years before and after the boom and bust
episodes are examined. The results derive from simple


averages of the evolution of both variables and from apanel regression of potential growth on dummy variables
for these events, controlling for country and year fixed
effects. The two approaches serve somewhat different
purposes. Simple averages illustrate the evolution of TFP
and output growth during events while the regression
approach allows a test of differences between event andnon-event years.
Results. The event study suggests that the medianinvestment boom in the sample is associated with a 2.8
percentage point a year increase in TFP growth and a 1.1
percentage point a year increase in potential output growthduring the three years leading up to the peak of theinvestment boom (Figure 3.3.2). As the investment boom
subsides, TFP and output growth rates gradually slow.
Investment busts are associated with slowdowns in TFP
growth of 4.9 percentage points a year and in potential
growth of 1.0 percentage point a year during the three
years leading up to the trough of the investment bust
(Figure 3.3.3). Potential output growth and, especially,
TFP growth usually rebound following a trough ininvestment growth. These events coincide with slower
actual output growth. The panel regression confirms thatthe differences in TFP growth and potential growth during
booms and busts from non-event years are statisticallysignificant (Annex 3.3). While these results represent
correlations, they are consistent with the results in theliterature discussed above.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018



CHAPTER 3


BOX 3.3 Moving together? Investment and potential output (concluded)
FIGURE 3.3.2 Growth around investment booms in EMDEs
Investment booms have typically been associated with increases in potential output growth, followed by gradual slowdowns.
Surges in TFP growth during investment booms have tended to be quickly reversed.
A. Potential output growth

B. Investment growth

C. TFP growth

Percent
7

Percent
45

Percent
6
5
4
3
2
1
0
-1
-2
-3
t-3

MedianUpper and lower quartiles

6

35

5

25

4

MedianUpper
pp and lower quartiles

15

3
5

2

1

-5

0

-15
t-3

t-2

t-1

t

t+1

t+2

t-3

t+3

t-2

t-1

t

t+1

t+2

t+3

MedianUpper
pp and lower quartiles

t-2

t-1

t

t+1

t+2

t+3

Source: World Bank.
Notes: An investment boom is defined as an episode during which investment growth is at least one standard deviation larger than its long-run (over the sample period)
average level. t denotes the average of the investment boom. The event studies in this box are conducted using the boom and bust episodes of at least two consecutive
years. Shaded area is the peak of the investment boom. Solid lines indicate median, dotted lines indicate interquartile range.
A. Potential growth defined by production function approach.
C. Actual TFP growth as defined in Annex 3.1.

FIGURE 3.3.3 Growth around investment busts in EMDEs
Investment busts have tended to be accompanied by lower subsequent or contemporaneous potential output growth,followed by gradual recoveries. TFP growth has tended to slump during investment busts but to rebound quickly as
investment growth recovered.
A. Potential output growth

B. Investment growth

C. TFP growth

Percent
6

Percent

Percent
6

MedianUpper and lower quartiles

MedianUpper and lower quartiles

20

4

5
10

2

0

0

4
3

2

-10

1

-20

0

-30

MedianUpper and lower quartiles

-2
-4

t-3

t-2

t-1

t

t+1

t+2

t+3

-6
-8
t-3

t-2

t-1

t

t+1

t+2

t+3

t-3

t-2

t-1

t

t+1

t+2

t+3

Source: World Bank.
Notes: An investment bust is defined as an episode during which aggregate investment is at least one standard deviation lower than its long-run average level. t denotes
the average of the investment bust. The event studies in this box are conducted using the boom and bust episodes of at least two consecutive years. Shaded area is thetrough of the investment bust. Solid lines indicate median, dotted lines indicate interquartile range.
A. Potential growth defined by production function approach.
C. Actual TFP growth as defined in Annex 3.1.

Conclusion
Ample evidence supports the existence of multiple linkages
between investment growth and potential output growth.
By eroding productivity growth, investment busts haveadverse indirect effects on potential growth, above andbeyond the direct effects of slowing capital accumulation.

The slowdown in investment growth in EMDEs since2010, therefore, raises substantial longer-run concerns.
The association between sharp swings in investment
growth and changes in potential output growth suggeststhat proactive policy measures might usefully support
investment, against the risk of investment busts, to avoid
an erosion of potential growth.

175

CHAPTER 3

176

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 3.6 Investment growth
Investment growth in EMDEs has slowed sharply since the global financial
crisis from double-digit rates after the global financial crisis to a post-crisis
low of—3 percent in 2016. Investment weakness during deep recessions,such as the global financial crisis, is one reason why output contractions
are associated with about 1 percentage point lower potential growth for the
next half-decade. Conversely, a cyclical upturn may generate its own
momentum to lift potential growth. Following four-year growth spurts,
potential growth rose around 1 percentage point above median potential
growth in years outside such spurts.
A. Investment growth

B. Share of economies withinvestment growth below its
long-term average

Percent
16
2003-07 average
1998-2017 average
12Percent
100

Share of countries
Share of GDP

80
60
40

8

growth.
In addition, deep recessions may lowerlabor productivity by extending unemployment
spells that erode human capital. If accompanied byfinancial stress, recessions can reduce profitabilityor access to finance for productivity-enhancing
R&D spending, technology absorption, andoperations of innovative firms. Indeed, short-term
output shocks often precede persistent potential
growth slowdowns (Box 3.4). Output contractions
have tended to leave a legacy of lower potential
growth (by as much as 1 percentage point on
average) four to five years after the onset of thecontraction. The effects have tended to be initiallystronger, but less persistent, for EMDEs.

20
4

AEs

World

EMDEs

EMDEs

C. Potential growth during output
contractions

D. Cumulative impulse responseof potential output growth after
contraction

Percent
5

Percentage points
0.0

During all contractions
During years without contractions

2013-17

2003-072013-17AEs

1998-2002

2003-072013-17

1998-2002

2010
2012
2014
2016
2018
2010
2012
2014
2016
2018
2010
2012
2014
2016
2018
World

2003-07

1998-2002

0

0

4

-0.5

3
2

-1.0
1
0
World

AEs

EMDEs

-1.5

Year 1

Year 3

Year 5

E. Potential growth around four-year
growth spurts

F. Actual growth around four-year
growth spurts

Percent
6

Percent
10

5

8

4

Median2003-08

Interquartile range
2011-176

Consequences of sustained cyclical recoveries.
Conversely, the cyclical upswing currently underway may generate its own momentum that feeds
into higher potential growth.10 With improving
growth, investors may become keener to invest.
The embodied new technologies may, in turn,spark a burst of productivity growth. Rising
employment may build workplace skills and,
therefore, raise labor productivity. Over the past
three decades, strong growth spurts—defined as
years in which growth accelerated in four
consecutive years—have been associated with
about 1-percentage-point higher potential growththan in the median normal year.11 Initially, thisincrease in potential growth was only one-third of
the increase in actual growth, but was sustainedeven as the growth spurt dissipated (Figure 3.6).
However, such growth spurts were rare: in thesample used here, they represent only 12 percent
of all country-year pairs.

3
4
2

Median2003-08

1

Interquartile range
2011-17

0

Labor supply

2
0

t-1

t

t+1

t+2

t+3

t+4

t+5

t-1

t

t+1

t+2

t+3

t+4

t+5

Sources: Penn World Tables, World Bank.
A. Investment-weighted averages. For a sample of 37 advanced economies and 145 EMDEs.
B. Share of 139 countries in which investment growth is below the longer-term average (1998-2017).
C. D. Contractions are defined as the years of negative output growth from the year after the output
peak to the output trough, as in Huidrom, Kose, and Ohnsorge (2016). Sample includes up to 32
advanced economies and 45 EMDEs during 1989-2016. The methodology is described in detail in
Annex 3.4. Unweighted averages of potential growth during contractions compared with all othercountry-year pairs without such events (C). Impulse response for the full sample of up to 77 advancedand EMDE economies from local projections model, as described in Annex 3.4, over horizons of 1, 3,
and 5 years (D). Dependent variable defined as cumulative slowdown in potential growth after acontraction event using baseline specification. Bar shows coefficient estimates, vertical lines
shock +/- 1.64 standard deviations (10 percent confidence bands). Potential growth basedon production function approach.
E. F. Median of potential growth using the production function approach (E) or actual growth (F)during 81 episodes (12 percent of country-year pairs) of growth upswings during 1988-2017 (9 inadvanced economies, 72 in EMDEs). t = 0 is the fourth consecutive year in which growth has been
positive and strengthened from year to year. “Median” indicates the median for t years in the five
years around the upswing event. During non-event years, median actual growth was 3.2 percent andmedian potential growth was 2.9 percent. Sample includes 98 economies for 1988-2017.

Channels of transmission. Growing working-age
populations have been associated with “demographic dividends” to growth. Higher working-age
shares of populations have been accompanied byhigher capital accumulation and employment

10 Past growth accelerations have been associated with better
institutions, increased economic openness, and greater macroeconomic stability (Berg, Ostry, and Zettelmeyer 2013).
11 Over the past three decades, there have been about 81 episodes(9 in advanced economies, 72 in EMDEs) in which actual growth
accelerated every year for four consecutive years.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

A. Impact of 1-percentage-point higher
growth of working-age population
share on per capita GDP growth

B. Working-age population

Percent32

Percent of total population
70
World
AEs
EMDEs
65

1

60

The benefits from a rising working-age population have been
particularly pronounced in Asia (Bloom et al. 2010; Bloom et al.
2007; Aiyar and Mody 2011). Demographic change over the period
1960-1995 for 86 countries has been estimated to have accounted forapproximately 20 percent of per capita output growth, and more in
Asia and Europe (Kelly and Schmidt 2005). Cruz and Ahmed (2016)
estimated that a 1-percentage-point increase in the working-age
population share was associated with a more-than-proportional
increase in GDP per capita growth in 160 countries over 1960-2010.
Other studies of the relationship between demographics and growth
include Higgins and Williamson (1997); Eastwood and Lipton(2011); and Kelley and Schmidt (1995 and 2007).
13 These factors have been explored in Mincer (1962); Goldin(1994); Hill (1983); Killingsworth and Heckman (1986); andConnelly (1992).

D. Global potential growth andcontributions

Percent of total population
75
MNA
EAP
ECA
LAC
SAR
SSA
70

Percent
8

2025

2020

2015

2010

2005

2000

1995

1990

1985

1980

1975

1970

55

C. Working-age population

Baseline
Demographic trends
Other factors

6
4

65

2

World

AEs

EMDEs

F. EMDE potential growth andcontributions

Percent
10
8
6
4
2
0

Percent
10
8
6
4
2
0

LAC

MNA

SAR

2013-17

Contribution

2003-072013-17

Contribution

2003-072013-17

Baseline
Demographic trends
Other factors

Contribution

2013-17

Contribution

2003-072013-17

2003-072013-17

Contribution
ECA

2003-07

E. EMDE potential growth andcontributions
Baseline
Demographic trends
Other factors

2013-17

Contribution

2003-072013-17

Contribution

2025

2020

2015

2010

2005

2000

1995

1990

1985

1980

1975

1970

1965

50

2003-07

Contribution

2003-0755

2013-17

0

60

EAP

12

Ahmed
and Cruz
2016

1965

Aiyar and Bloom and Bloom and Bloom etMody 2011 Williamson Canning al. 2000
2004
1998

1960

0

Contribution

Evolution of demographics. In the past five
decades, growth was supported by rapidly growing
working-age populations—until the mid-1980s in
advanced economies and around 2010 in EMDEs(Figure 3.7). Since 2000, countries with rising
working-age population shares accounted for halfof global output growth and three-quarters ofglobal GDP levels. With the retirement of thebaby boom generation and lower fertility rates,
demographic trends have turned less favorable to
growth and will continue to do so over the next
decade. In advanced economies, the working-age
share of the population is set to decline, from 65.4

Higher working-age population shares are associated with higher per
capita output growth. Global demographic trends turned from tailwinds togrowth into headwinds around 2010. Since 1998-2002, demographic
trends shaved about 0.1 percentage point off global potential growth. In
EMDEs, other factors were also important, and the impact varied byregion.

1960

Another important driver of increased labor
supply can be labor force participation among lessrepresented groups, including women, young, andold workers. Rising female labor force
participation rates have been attributed to better
educational attainment (opening access to higherearning jobs), lower fertility rates, a technologydriven shift toward non-manual skills, and cheaper
home production (lowering the opportunity costof working).13

177

FIGURE
3.7 Demographics

2003-07(Bloomand Canning 2004; IMF 2004; Figure3.7).12 Shifts towards an older age structure of the
population affect potential output in several ways.
Population aging may reduce the working-age
population, which directly reduces potential labor
supply. There are also less direct effects of
population aging. For example, aging increases theshare of the population with below-average labor
force participation rates. Aging populations havebeen associated with slower labor productivity
growth for various industries and occupations(Maestas, Mullen, and Powell 2016).

CHAPTER 3

SSA

Source: United Nations World Population Prospects: The 2017 Revision.
Note: EAP = East Asia and Pacific, ECA = Europe and Central Asia,
LAC = Latin America and the Caribbean, MNA = Middle East and North Africa, SAR = South Asia,
and SSA = Sub-Saharan Africa.
A. The sample of each study differs from each other. Aiyar and Mody (2011): Indian states,
1961-2001; Bloom and Williamson (1998): 78 countries, 1965-90; Bloom and Canning (2004):
Over 70 countries, 1965-95; Bloom et al. (2000): 70 countries, 1965-90; Amer and Cruz (2016):
160 countries, 1960-2010.
B.C. Population weighted averages. The working-age population is defined as people aged 15-64
years.
D. -F. GDP-weighted averages. Other factors include contribution from policy changes, cohort effects,
changes in population growth, convergence-driven productivity growth, and investment. “Contribution”
reflects percentage-point changes between the averages of 2003-07 and 2013-17. Methodology is
described in detail in Annex 3.1.

178

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GLOBAL ECONOMIC PROSPECTS | JANUARY 2018






BOX
3.4 The long shadow of contractions over potential
outputContractions are associated with about 1 percentage point lower potential growth four to five years after their onset. The effect isinitially stronger, but less persistent, for emerging market and developing economies.
The slow recovery from the global financial crisis and the 
sharp slowdown in commodity-exporting EMDEs causedby the recent slump in commodity prices have reignited
the debate about the impact of deep recessions on
potential output levels and growth. Global output
contracted by 1.8 percent in 2009 and, in 2017, remained
4 percent below its pre-crisis trend. Most EMDEs avoided
outright contractions in 2009—partly as a result of large
stimulus. However, one-quarter of commodity-exporting
EMDEs subsequently slid into recessions as commodity
prices declined. In others, growth halved as a result ofdomestic political tensions or spillovers from policy
uncertainty elsewhere. This post-crisis growth weakness
has coincided with a decline in potential growth (Figure
3.4.1).

pre-recession for a protracted period.1 On average in asample of 40 advanced economies and EMDEs, a recession
was associated with 0.5 percentage point lower per capita
potential growth in the two years following the prerecession output peak, but half of this decline was reversed
over the following two years (Haltmeier 2012).

Severe short-term output shocks have been associated withhighly persistent losses in output levels in both advanced
economies and emerging market and developing
economies (EMDEs). In advanced economies, output
growth also tends to remain lower after recessions than

Linkages: Theory and evidence

Against this background, this box focuses on the impact ofcontractions on potential growth in a large sample of AEs
and EMDEs. Specifically, it addresses the following
questions:xHow can contractions affect potential growth?

xWhat has been the impact of contractions on
potential growth?

A number of mechanisms may drive potential output
losses as a result of crises or severe contractions. Theoretical models highlight the role of weak profitability for

FIGURE 3.4.1 Output
Global output remains 4 percent below its pre-crisis trend. While most EMDEs avoided outright contractions in 2009—partly
as a result of large stimulus—several subsequently slid into recessions or sharp slowdowns. Since the global financial crisis,
potential growth has also slowed, by all measures of potential growth.
A. EMDE output growth

B. Share of countries with output
contractions

C. Potential growth

Percent
8

Percent
30

Percent
7
6
5
4
3
2
1
0

2001-072008-092010-17

World

AEs

2018-272013-170

2003-07

2017

2016

2015

2014

2013

2012

2011

2010

2009

0

2018-27

2003-0710

2

2013-17

20
4

2003-07

6

Potential growth
1998-2017 potential growth

2018-27

Advanced economies
EMDEs

2013-17

1998-2017 average

EMDEs

Source: World Bank.
Note: GDP-weighted averages.
B. Includes 38 advanced economies and 150 EMDEs.
C. Potential growth estimates based on the production function approach.

Note: This box was prepared by Sinem Kilic Celik and Franziska
Ohnsorge.



1 For research on the impact of contractions on growth, see Cerra andSaxena (2008); Candelon, Carare and Miao (2016); Queralto (2013);
Blanchard, Cerutti and Summers (2015); Martin, Munyan, and Wilson(2015); Ball (2014); and Haltmeier (2012).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 3

BOX 3.4 The long shadow of contractions over potential output (continued)
productivity-enhancing R&D spending (Fatás 2000), a
liquidity demand shock that tightens availability of funds
for technology absorption (Anzoategui et al. 2016), loss ofaccess to bank lending for creative firms (Queralto 2013),
a legacy of obsolete capacity (Nguyen and Qian 2014),
self-fulfilling expectations of weak growth prospects(Caballero and Simsek 2017), human capital loss andreduced job search activity among the long-term
unemployed (Lockwood 1991; Lindbeck 1995; andBlanchard and Summer 1987), and lower laborproductivity after financial crises (Oulton and SebastiaBarriel 2016). Damage to aggregate output during the
global financial crisis in the United States has been
attributed to a nonlinear effect of demand-side weaknesses(as captured by a threshold unemployment rate,
Reifschneider, Wascher, and Wilcox 2015). Other studies
also find that the adjustment of growth or output levels tothe pre-recession trend is non-linear and depends on thepersistence, depth and source of the recession and its
coincidence with financial crises.2

Potential output during contractions
Data. The literature on the impact of recessions on
potential growth has focused on univariate filter-based
methodologies. Since they correlate strongly with actual
growth, including during contractions, these filters tend toshow a decline in potential growth during the depth of therecession and a subsequent rebound in synch with actual
growth (Box 3.1). In contrast, potential growth based on
the production function approach will only change in
response to contractions if long-term fundamental drivers
change substantially for an extended period of time. To
capture this longer-term impact, this box focuses on thepotential growth measure derived from the production
function approach. That said, the results are robust to theuse of other methodologies.

FIGURE 3.4.2 Potential growth aroundcontractions
Contractions are associated with lower potential output
growth.
A. Potential growth during contractions: Production
function approach
Percent
5
Average2011-17
4

3

2

1

0
t-3

t-2

t-1

t

t+1

t+2

t+3

t+4

t+5

B. Actual growth around contractions
Percent
Average2011-17

8
6
4
2
0
-2
-4
-6
-8

Definitions. Contractions are defined as years of negative
output growth as in Huidrom, Kose, and Ohnsorge(2016). Depending on data availability for potential
growth estimates, this definition yields up to 47
contraction events in 32 advanced economies and up to 77
contraction events in 49 EMDEs during 1990-2016(Annex 3.4). Contractions, on average, lasted 1.4 years andwere associated with growth of -4 percent, on average. In
EMDEs, contractions were, on average, similarly short

2 See Claessens, Kose, and Terrones (2009 and 2012); Furceri andMourougane (2012); Haltmeier (2012); and Ball (2014).

t-3

t-2

t-1

t

t+1

t+2

t+3

t+4

t+5

Sources: Huidrom, Kose, and Ohnsorge (2016); World Bank; World
Economic Outlook, International Monetary Fund.
Note: Contractions are defined as the years of negative output growth fromthe year after the output peak to the output trough, as in Huidrom, Kose,
and Ohnsorge (2016). Sample includes 37 contraction events in advanced
economies and 44 contraction events in EMDEs during 1989-2016. The
methodology is described in detail in Annex 3.4. Dotted lines indicate
interquartile range.
A. B. Unweighted averages of potential growth as estimated by the
production function approach (A) or actual growth (B) during contractions. t
denotes the peak preceding the contraction. 2011-17 is the unweighted
average for countries with contraction episodes after a peak in 2014.

179

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GLOBAL ECONOMIC PROSPECTS | JANUARY 2018






BOX
3.4 The long shadow of contractions over potential
output (concluded)

(1.3 years) but somewhat more severe (-4.4 percent) thanin advanced economies (-3.4 percent).

FIGURE 3.4.3 Potential growth after
contractions
The fall in potential growth following contractions persists
over the following half-decade, but with considerable
uncertainty around the magnitude of the effect.

A. Cumulative impulse response of potential output growth
after contraction

Percentage points
0.0

-0.5

Year 1

Year 3

Year 5

B. Cumulative impulse response of EMDE potential output
growth after contraction

Percentage points
0.0

The long shadow of contractions. The local projections
model helps explore the evolution of potential growthfollowing contractions. Contractions leave a legacy oflower potential growth (about 1 percentage point) four tofive years after the onset of the contraction (Figure 3.4.3).
The effect is initially stronger, but less persistent, for
EMDEs.

Conclusion

-0.5

-1.0

-1.5
Year 1

Year 3

Year 5

Sources: Huidrom, Kose, and Ohnsorge (2016); World Bank; World
Economic Outlook, International Monetary Fund.
Notes: Contractions are defined as the years of negative output growth fromthe year after the output peak to the output trough, as in Huidrom, Kose, andOhnsorge (2016). Sample includes yields 37 contraction events in advanced
economies and 44 contraction events in EMDEs during 1989-2016. The
methodology is described in detail in Annex 3.4.
A. Impulse response for the pooled sample of up to 77 advanced and EMDE
economies from local projections model, as described in Annex 3.4, overhorizons of 1, 3, and 5 years. Dependent variable defined as cumulative
slowdown in potential growth after a contraction event using the baseline
specification. Bars show coefficient estimates, vertical lines show 90 percent
confidence bands.
B. EMDE sample only.

Methodology. Two exercises are conducted to estimate theimpact of short-term output shocks on potential growth:
an event study and a local projections model (Jorda,
Schularick, and Taylor 2013; Mourougane 2017). For the
event study, average potential growth during contractions(all years from the year after the peak to the trough ofoutput) is examined over time and compared with averagepotential growth in all other years. The local projections
model is used to estimate impulse responses of potential
growth to contractions.
Evolution of potential growth during contractions. Twoyears following the average contraction, potential growth isstill more than 1.2 percentage point below potential
growth in the year preceding the contraction (exceeding
the decline in actual growth over the same period; Figure
3.4.2). The effect is somewhat stronger in EMDEs than inadvanced economies.

-1.0

-1.5



For advanced economies, short-term economic disruptions
such as output contractions have been shown to reduce
actual output for several yea rs to come. This box
documents that such contractions tend to be associatedwith weaker potential output growth for the following halfdecade, although with considerable uncertainty around themagnitude of the effects. Depending on the measure ofpotential growth, contractions are associated with up to 1
percentage point lower potential growth four to five years
after the onset of the contraction. The effect is initiallystronger, but less persistent, for EMDEs.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

percent
in 2015 to 62.3 percent by 2025. InEMDEs, the working-age share of the population
peaked at 65.8 percent in 2015 and is expected
to stabilize around this level for the next 10 years.
While the largest declines are expected in EAPand ECA, working-age shares of the population
are expected to rise in Sub-Saharan Africa andSouth Asia.
In addition to the changing age composition of
the population, expanding female labor force
participation has increased labor supply, especiallyin EMDEs. Female labor force participation has
been broadly stable over the two decades from1998-2002 to 2013-17, however with a wide
divergence across EMDE regions. Supported bysurging school enrollment and completion rates,
female labor force participation rates in LAC roseby almost 6 percentage points between 1998-2002
and 2013-17. In contrast, despite some (moremodest) improvements in education, they declinedin SAR by almost as much over the same period.
Among EMDEs, female labor force participation
remains less than three-quarters of male labor
force participation.
The role of demographics in potential growth.
The overall effect of demographics on potential
growth—via TFP growth and labor supply
growth—can be assessed using the production
function approach. The estimates compare
baseline potential growth estimates against counterfactual scenarios in which the composition of
the population for all age groups and genders
remains at their 1998 values (Annex 3.1).14 The
results suggest that, in 2013-17, demographic
trends had lowered global potential growth by 0.2
percentage point from its 2003-07 average.
Advanced economies accounted for all of thisdecline. In EMDEs, with the exception of ECA,
growing and younger working-age populations
lifted potential growth marginally over the same
period. Trends in female labor force participation
benefited some EMDE regions’ potential growth
while weighing on others’. Over the longer-term(1998-2017), higher female labor force parti-

14 Such thought experiments are widely used to assess the impact
of demographics on growth or growth projections (Bloom, Canning,and Fink 2010; European Commission 2015).

CHAPTER 3

cipationcontributed 0.3 percentage point topotential growth in LAC, while it did notcontribute appreciably to longer-term potential
growth in SAR.

Prospects for potential
growth: What could
happen?
Factors weighing on potential growth over the
past five years are likely to persist over the next
decade. Demographic trends are expected to
become less favorable. This will weigh on potential
growth even if trend improvements in humancapital and female labor force participation
continue. Although investment growth is expected
to recover from its recent weakness, it is unlikely
to return to elevated pre-crisis levels. Short ofunexpected surges in productivity growth—
perhaps as a result of dissipating crisis legacies orunanticipated technological breakthroughs—thesetrends imply an outlook for mediocre potential
growth.
Baseline scenario assumptions. The forwardlooking scenario presented here applies the
production function approach to assumed paths
for capital, population statistics, and educationand health outcomes.
x The size of the global population and its
composition are assumed to grow in line witha median fertility scenario (as in the UN
Population Projections).15
x Past trend improvements in EMDE educationand health outcomes are expected to continue.
x In line with the historical experience,
investment growth is assumed to remain
constant at its long-term average.
Evolution of drivers of global potential growth.
Under this baseline scenario, the fundamental
drivers of potential growth all point to continued
softening.

15 This scenario also assumes that migration flows continue on pasttrends.

181

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182

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 3.8 Potential growth prospects
Over the next decade, trends in fundamental drivers of potential growthsuggest that global potential growth may slow by another 0.2 percentage
point and EMDE potential growth by 0.5 percentage point. This slowdown
will likely be broad-based: 69 percent of economies, accounting for morethan 78 percent of global output, are expected to have potential growth
below its longer-term average.
A. Potential growth

B. Share of countries and GDP ofcountries with potential growth in
2018-27 below its longer-term average

Percent
2.6

Percent
100

World

2018-27

3.6

Contribution

4.0

2013-17

2.0
1.8

2018-27

4.4

Contribution

2.2

2013-17

2.4

Percent
Baseline
5.2
Demographic trends
Other factors
4.8

EMDEs (RHS)

Share of countries
Share of GDP

80
60
40
20
0
World

AEs

EMDEs

Source: World Bank estimates.
A. GDP-weighted averages. Derived using the production function-based potential growth as
described in Annex 3.1. “Other factors” reflects declining population growth, convergence-related
productivity growth, policy changes, cohort effects, and a slowdown in investment growth relative to
output growth. “Contribution” reflects the percentage-point changes between the averages of
2013-17 and 2018-27.
B. Share of countries and share of GDP of 80 countries in which potential growth in 2018-27 is below
longer-term average potential growth (1998-2017), in percent of all countries or global GDP among
80 advanced economies and EMDEs. Horizontal line indicates 50 percent.

x A slowing pace of capital accumulation,
especially in China, will be offset by growing
capital accumulation in advanced economies.
In EMDEs other than China, the pace ofcapital accumulation will remain broadly
steady as investment growth keeps pace withrecovering output growth after its pronounced
weakness of 2015-16.
x Subdued investment and less room forcatchup productivity growth as per capita
income differentials narrow for EMDEs will
sap productivity growth. This could reduce
potential growth by about 0.1 percentage
point.
x Even if education and health outcomescontinue to improve in line with their longerterm trends, aging populations combined withwithdrawal from the labor market of older
cohorts of workers could reduce global
potential growth by another 0.2 percentage
point on average.
Global potential growth. Thus, absent significant
policy changes or productivity breakthroughs,

globalpotential growth could decline by 0.2
percentage point, to 2.3 percent a year in 2018-27(Figure 3.8). Two-thirds of the sample’s economies, accounting for 78 percent of global output,
would be left with potential growth below thelonger-term average. Advanced-economy potential
growth could slow by 0.1 percentage point to 1.3
percent a year.
EMDE potential growth could slow by 0.5
percentage point to average 4.3 percent a year
during the next decade, well below its longer-term
average. This slowdown would mostly reflect
demographic trends (across most EMDEs) andweaker capital accumulation in China, as China’s
policy-guided investment slowdown continues(elsewhere capital accumulation is expected torecover partially from its post-crisis weakness).
While China will account for 0.4 percentage pointof the 0.5-percentage-point decline in EMDE
potential growth, the decline will be broad-based,
affecting almost two-thirds of EMDEs in thesample.
The slowdown would also be sizable for the largest
EMDEs, which could generate adverse spillovers
to other EMDEs that the production function
approach does not explicitly account for.16 Largely
owing to weakening demographic trends andChina’s slowing capital accumulation, potential
growth in the seven largest emerging markets(EM7) is expected to slow by 1.1 percentage pointon average, of which China accounts for morethan three-quarters. Aging (and, in some cases,
shrinking) populations are expected to reduce G7
potential growth by 0.2 percentage point on
average.
Regional potential growth. Potential growth isexpected to slow over the next decade in all
regions and fall below the longer-term average inall regions except SSA. In most regions, workingage shares of the population are expected toshrink. In SAR and SSA, working-age shares of the
16 A 1-percentage-point decline in growth in the seven largest
emerging markets (EM7) could slow growth in other EMDEs by 0.9
percentage point over the following three years. A similarly-sized
decline in G7 growth could have a one-half to three times larger
impact than an EM7 slowdown (Huidom, Kose, and Ohnsorge2017).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

population
are expected to rise, but a shift is
expected within the working-age population
towards older cohorts with weaker labor market
attachment.
x EAP, LAC. Potential growth is expected tomoderate in EAP as policy efforts in China
succeed shifting towards more sustainablegrowth engines, and the region’s working-age
population ages. China’s potential growth isexpected to slow to 6.5 percent, on average in2018-27, from 9.1 percent on average during
1998-2017 (Figure 3.4). Elsewhere in EAP,
potential growth is expected to remain solid.
In LAC, demographic trends and the legacy of
weak investment over the past half-decade will
weigh on potential growth.
x ECA, SAR, SSA. Shrinking labor supplies andweak investment will weigh on potential
growth in ECA and SAR as investment fails toreturn to the elevated levels seen before the oil
price plunge and onset of policy uncertainty
in mid-2014. In SSA, an expected slowdown
in potential growth largely reflects population
aging in South Africa, while elsewhere in SSA
potential growth is expected to remainbroadly steady at a robust 5 percent.
x MNA. Potentia l growth is expected tostrengthen somewhat in the Middle East andNorth Africa. Investment and productivity
growth are expected to firm provided conflictand geopolitical risks do not intensify again.

Policy options to lift
potential growth
The production function framework can beapplied to examine stylized policy scenarios. The
impact of better policy outcomes is estimated as
the difference between potential growth under acounterfactual scenario of higher growth ofphysical or human capital or labor supply
compared with the baseline scenario (Annex 3.1).
All counterfactual scenarios model a repeat of acountry’s best ten-year improvement, up toreasonable ceilings. The potential growth dividendof the scenarios therefore depends on each

CHAPTER 3

country’s
track record as well as its room for
improvement. For productivity-raising reforms
not easily measured or explicitly modelled in the
production function, such as improvements togovernance or business climates, an event study
provides some guidance about possible effects.
The estimate provided in these stylized scenarios
may well be lower bounds because they disregard
nonlinearities in reform impacts as well as
synergies between different reform measures.
Raising physical capital
All EMDE regions have sizable investment needs(Vashakmadze et al. 2017). UNCTAD (2014)
estimated that unfilled global investment needsamount to up to 3 percent of global GDP.
Depending on the availability of financing, these
could be filled through either public or private
investment or a combination of both in publicprivate partnerships. Increasing public investment
can be an effective policy tool to support shortterm demand while also helping to raise future
potential growth (World Bank 2017a; Calderón
and Servén 2010a, 2010b, and 2014). Although
the rapid increase in public debt over the past
decade has constrained fiscal space in mostcountries, there remains scope to shift existing
government expenditures toward public investment to make government operations more
growth-friendly (World Bank 2017b). Moreover,in many countries, government revenue ratios
remain low, indicating that in some cases tax
revenues could be raised, including by expanding
tax bases or improving the quality of tax
administration (World Bank 2015).
In addition, policies can support productivityenhancing private investment. Innovation-related
investment tends to be low in EMDE firms, partly
because of limited availability of complementary
inputs such as trained engineers or effective
organization techniques (Cirera and Maloney2017). Policy efforts to expand the supply ofcomplementary inputs and capabilities and to raise
the returns on investment through intellectual
property right protection may foster private
investment.
If, over the next decade, each country raised its
investment growth as much as its largest increase183

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GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE 3.9 Policies to stem declining potential growth 
A combination of additional investment, education, and health improvements and labor market reforms could stem the expected decline in global
potential growth over 2018-27.
A. Global potential growth underreform scenarios

B. EMDE potential growth underreform scenarios

Labor market reforms
Education and health improvements
Fill investment needs
Baseline

Percent
3.0
2.8

Percent
5.2
5.0

Labor market reforms
Education and health improvements
Fill investment needs
Baseline

4.8
4.6

2.6

potential
output would rise even more (5 percentcumulatively by 2027; Figure 3.9).
Implicit in these scenarios is the premise that theadditional investment will be used productively.
In the context of EMDEs, there is some evidence
that absorptive capacity can limit the success oflarge scaling-up of public investment, although
this adverse effect is small in lower-income andcapital-scarce countries (Presbitero 2016).

4.4

2.4

Raising human capital

4.2
4.0

2.2

3.8
2.0

3.6

C. EMDE potential growth underreform scenarios

ECA

LAC

MNA

SAR

Reformimpact2018-272013-172013-17

Reformimpact2018-27

ReformimpactReformimpact2018-272013-170
2018-272

0
2013-174

2
2013-17

6

4

Reformimpact8

6

EAP

Reform impact

Labor market reforms
Education and health improvements
Fill investment needs
Baseline

2018-27

Percent
10

2013-178

2018-27

D. EMDE potential growth underreform scenarios

Labor market reforms
Education and health improvements
Fill investment needs
Baseline

Percent
10

2013-17

Reform impact

Reformimpact2018-272018-272013-17SSA

E. Change in TFP growth 2-4 years
after reform episodes

F. Change in real investment growth
2-4 years after reform episodes

Percentage points
1.0

Percentage points
20
15
10
5
0
-5
-10
-15
2
4
2
yrs yrs yrs

0.5
0.0
-0.5
-1.0
2
yrs

4
yrs

Spurt

2
yrs

4
yrs

Setback

Global

2
yrs

4
yrs

Spurt

2
yrs

4
yrs

Setback

EMDE

Spurt

4
yrs

Setback

Global

2
yrs

4
yrs

Spurt

2
yrs

4
yrs

Setback

EMDE

Source: World Bank estimates.
Note: GDP-weighted averages.
A. B. Derived using the methodology described in Annex 3.1.
E. F. Regression coefficients of potential TFP growth (E) and real investment growth (F) on dummies
for structural reform spurts and setbacks—defined as statistically significant changes in fourWorldwide Governance Indicators—from local projections model for lags of two and four years, for asample of 136 EMDEs and 38 advanced economies during 1996-2015. Vertical bars show 90 percent
confidence interval. A detailed methodology is available in Annex 3.5.

over any historical ten-year interval, global
investment-to-GDP ratios would rise by 2.3
percentage points of GDP. Investment-to-GDP
ratios would rise somewhat more in EMDEs, by
2.9 percentage points of GDP. It is estimated thatsuch an investment boost would raise global
potential output by 2 percent by 2027, reversing
the slowdown under the baseline scenario. EMDE

Measures to raise human capital could lift bothlabor supply and TFP growth: A better educatedworkforce is more securely attached to the labormarket and more productive. In particular, abetter-educated workforce may be better able toadjust to technological disruptions that reduce
employment and wages by replacing jobs
(Acemoglu and Restrepo 2017a).17 In the framework used here, human capital has twodimensions, educational attainment and healthoutcomes (proxied by life expectancy).
Education. While secondary school enrollment
rates are near advanced-economy levels in the
average EMDE, tertiary school enrollment rates(40 percent) and secondary and tertiary school
completion rates (27 and 10 percent, respectively)
were less than two-thirds of the advancedeconomy average in 2013-17 on average. In
addition to expanding access to education, such as
captured by these measures, improving the qualityof education to improve education outcomes iscritical (World Bank 2017c).
There are a number of policies that can improveeducation outcomes. At the national level, theseinclude policies targeted at better training forteachers, greater teacher accountability, andperformance incentives (Evans and Popova 2016).
The development of metrics to assess andaccelerate progress toward learning goals is a
17 The impact of such technological disruptions on output may
not be clear-cut. For example, in aging societies, technologicalchange to replace jobs may relieve pressures resulting from ashrinking labor supply (Acemoglu and Restrepo 2017b and 2017c).
In addition, automation may expand labor demand by creating newtasks for which labor has a comparative advantage (Acemoglu andRestrepo 2016).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

prerequisite
for policy actions to improve
educational outcomes (World Bank 2017c).18 At
the student-level, useful policies include efforts to
tailor teaching to the requirements of students(Kremer, Brannen, and Glennerster 2013). Grants
may encourage school attendance by disadvantaged students (Glewwe and Marulidharan2015). Better early childhood nutrition andcognitive development improve students’ capacity
to learn (Tsimpo Nkengne, Etang Ndip, andWodon 2017).
In a stylized policy scenario, education-related
policy indicators—secondary and tertiary enrollment and completion rates—are assumed to riseover 2018-27 in each EMDE by as much as theirlargest historical improvement in any ten-year
period. This would imply that EMDEs, on
average, would raise secondary school completion
rates by 5 percentage points and secondary andtertiary enrollment rates by 7 percentage points,
on average, during the next decade. In EMDE
regions that have made particularly large strides in
improving education outcomes but still haveample room for further improvements, such as
SAR, secondary school completion rates could riseas much as 16 percentage points over the next
decade.
Health policies. At 71 years on average in 201317, life expectancy in EMDEs is still below that inadvanced economies (82 years). Although regions
such as SAR and SSA have made large
improvements, raising life expectancy by 4-7 years
over the past two decades, it remains about oneeight below advanced-economy levels.
Policy interventions to improve public health, andto ensure productive working lives, range widely.
Better sanitation and access to clean water would
improve public health: 9 percent of the global
disease burden may be attributable to unsafe
water, inadequate sanitation, and insufficienthygiene (WHO 2008). In addition, improvements
in health care provision can be spurred by welldefined and regularly monitored performance
18 Other measures such as reducing student-teacher ratios oradditional years of schooling have effects that differ widely depending
on country circumstances (Evans and Popova 2016; Hanushek andWoessman 2008).

CHAPTER 3

indicators(Bradley et al. 2010). Comprehensivecoverage of health services has been followed bybetter health outcomes in countries with higher
per capita incomes (Maeda et al. 2014). At the
local level, programs targeted at local health service
providers or groups of patients have generated
considerable improvements in health care services
and outcomes. For example, in Rwanda,
performance-based incentive payments helped
significantly improve health indicators for children(Gertler and Vermeesch 2012). In India, enhanced
training of primary health care providers led tobetter identification and treatment of patientailments (Das et al. 2016).
In a stylized scenario of improved health, life
expectancy is assumed to rise over 2018-27 in each
EMDE by as much as its largest improvement
over any historical ten-year period. This would
imply an increase in life expectancy in EMDEs by
2.5 years, on average, but as much as 3.8 years in
MNA over the next decade.
Impact on potential growth. These stylized
scenarios suggest that improvements in educationand health outcomes—via their effect on labor
supply and TFP growth—could lift global and
EMDE potential growth by 0.2 percentage pointon average. In some EMDE regions with a strong
track record of boosting human capital and ample
room for improving education and healthoutcomes, such as in EAP, potential growth could
rise by one-and-a-half times as much.
Impact on inequality. Better education and longer
life expectancy will not only raise potential growth
but also have implications for income inequality.
While economic development may exert pressuresfor higher income inequality (e.g., because of
growing urbanization), better education may
alleviate some of these pressures (Special Focus 2).
Raising labor supply
At 49 percent, on average, in 2013-17, global
female labor force participation remains two-thirds
that of men (75 percent), and it is even lower in
EMDEs. Similarly, in both EMDEs and advanced
economies, the average labor force participation
rate among workers aged 55 years or older is about
one-half that of 30-45-year-old workers, and labor

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GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

force
participation among 19-29 year-olds is only
four-fifths that of their 30-45-year-old peers.

decade,sufficient jobs will be created to absorb
this additional labor supply.

Labor supply can be raised by drawing a greater
share of the working-age population into the labor
force. This can be achieved through policies to“activate” discouraged workers or groups withhistorically low participation rates, such as womenand younger or older workers.

Impact on potential growth. In such a stylizedlabor market reform scenario, global and EMDE
potential growth could rise by 0.2-0.1 percentage
point, respectively, on average, over 2018-27.
Again, such a renewed reform push could yield thelargest dividends for EMDE regions with both astrong track record and sizable remaining gaps
between male and female labor force participation
rates (e.g., LAC).

In advanced economies and EMDEs, active labormarket policies and reforms to social benefits were
followed by higher labor force participation rates(Betcherman, Dar, and Olivas 2004; Card, Kluve,
and Weber 2010). Less rigid employment
protection regulation and lower minimum wages
have had mixed effects on employment and labor
force participation and, at times, unintended side
effects such as lower labor force participation ofdisadvantaged groups (Betcherman 2014).
In EMDEs, policies aimed at other objectives havesometimes brought important collateral benefits
that improve labor force participation. For
example, in Nigeria, improved access to financeand training programs increased female labor force
participation by encouraging firm startups(Brudevold-Newman et al. 2017). In Uruguay,
the extension of the school day was associatedwith higher adult labor force participation (Alfaro,
Evans, and Holland 2015). In Eastern Europe andCentral Asia, shifting health care systems towards
services targeted at the elderly has helped extend
productive life times, and providing support
services to women with families has helped
encourage labor force participation (Bussolo,
Koettl, and Sinnott 2015).
Female labor force participation rates—alongcohort-, age-, and country-specific dimensions—are assumed to rise, over the next decade, by thelargest historical ten-year improvement in each
EMDE (in a stylized labor market reform
scenario), although they will not exceed the rates
of same-aged men. On average, this would imply
raising female labor force participation rates by 10
percentage points by 2027. The premise
underlying this assumption is that, over theRaising productivity
Institutional reforms could help lift productivity
growth. Better institutional quality, such as
control of corruption, application of the rule oflaw, and improved political stability, has
accompanied higher and more stable growth. At
the firm-level, more friendly business climateshave favored firm productivity and a shift frominformal activities to more productive formal
activities (Box 3.5).
Reforms that lift microeconomic distortions andfrictions can unlock productivity growth by
fostering reallocations at the sectoral, firm, andworker level. Reforms that increase productmarket flexibility or competition (e.g., tradeintegration) could raise aggregate productivity
growth by encouraging a reallocation of resourcesaway from unsuccessful firms to more productive
ones (Melitz 2003; Bernard, Jensen, and Schott2006). Labor market reforms that improve theallocation of talent, such as broadening access to
occupations, can generate considerable productivity growth (Hsieh et al. 2013). Reforms to level
the playing field (e.g., state-owned enterprisereforms) could encourage entry of more productive firms and, thus, raise aggregate productivity(Brandt, van Biesebroek, and Zhang 2012).
Reforms to strengthen competition could havesynergies with reforms to improve human capital.
Firms in EMDEs tend to innovate in marginal
process and product improvements rather thanengaging in significant technology adoption or
new product imitation (Cirera and MaloneyGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 3

BOX 3.5 Productivity and investment growth during reforms
Wide-ranging governance and business climate reforms have been associated with higher potential growth through an increase in
TFP growth and investment growth over the subsequent two to four years.
In many emerging market and developing economies(EMDEs), enterprises claim that a wide range ofinstitutional problems constitute significant obstacles todoing business. Recent World Bank enterprise surveys formore than 10 percent of EMDEs rank law and order,
customs and trade regulation, and tax administration
among the top three non-financial obstacles to doing
business.1 Weak governance, often manifested incorruption and large informal sectors, was also a common
complaint.
By removing obstacles to firms’ operations, governanceand business climate reforms can raise potential growththrough their impact on productivity and investment
growth.2 This box addresses the following questions.
xHow do weak governance and business climates affectgrowth?

x

How has TFP and investment growth evolved during
major reform episodes?

Business climate. Poor business climates encourage
anticompetitive practices, curtail innovation and hold backan efficient allocation of factors of production (Bourles etal. 2013; Buccirossi et al. 2013; Aghion and
Schankermann 2004). While they be intended to provide
social protection, stringent labor regulations often encourage informal employment and constrain firm size (Bruhn
2011; La Porta and Shleifer 2014; Loayza, Oviedo, andServén 2005; Loayza and Servén 2010). Weak businessenvironments dampen the crowding-in effects on domestic
investment that would otherwise accrue from public andforeign direct investment (Kose et al. 2017). Burdensome
business regulations amplify the adverse effect of
corruption on firms’ labor productivity (Amin and Ulku
forthcoming). Trade restrictions are associated with lower
firm productivity, especially when accompanied by heavy
domestic industrial regulation (Topalova and Khandelwal2011). Conversely, reforms that implement major improvements in business environments are associated withincreased output growth (Divanbeigi and Ramalho 2015;
Kirkpatrick 2014).

How do weak governance and businessclimates affect growth?

How has TFP and investment growth evolved
during major reform episodes?

Institutional quality. Improved institutional quality
clarifies and protects property rights, facilitates contracts
between non-related parties and, therefore, promotes amore efficient allocation of resources (Acemoglu andJohnson 2005). Institutional quality is associated withhigher and more stable long-term growth. In particular,less corruption typically accompanied higher growth andinvestment, although such dividends have depended on
country circumstances (Hodge et al. 2011; de Vaal andEbben 2011; Shleifer and Vishny 1998). Greater politicalstability encourages stronger growth, investment, andlower levels of government spending (Aisen and Veiga2013). Aspects of the rule of law, such as the provision of
security and the protection of property rights, arecorrelated with higher growth or lower growth volatility(Haggard and Tiede 2011; Acemoglu, Johnson, andRobinson 2001; World Development Report 2017).

To illustrate the linkages between major governance andbusiness climate reform efforts and TFP (or investment)
growth, an event study and a local projections model areemployed.3 Two sets of events are defined, based on two
different datasets of structural indicators. Major reformspurts and setbacks are either defined as those that lift or
reduce at least one of four Worldwide GovernanceIndicators (government effectiveness, control of corruption,
rule of law, and regulatory quality) by at least 2 standard
errors over two years as in Didier et al. (2015).4
Alternatively, major reform spurts and setbacks are definedas those that lift or reduce the “distance to the frontier”5
for at least one of the ten Doing Business indicators by atNote: This box was prepared by Sinem Kilic Celik.
1 This ranking excludes the two financial obstacles, access to financeand tax rates.
2 Reform payoffs may take some time to materialize and their growth
dividend will depend on the country’s stage of development and thetechnology level of the country (Dabla-Norris 2016).

3 This box analyzes potential TFP growth to assess the long-term effectof structural reforms. Hence, TFP growth refers to potential TFP growththroughout the box.
4 This yields 247 events in 136 EMDEs and 38 advanced economies
during 1996-2015.
5 An economy's distance to frontier is indicated on a scale from 0 to100, where 0 represents the lowest performance and 100 the frontier,which is constructed from the best performances across all economies andacross time.

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


BOX
3.5 Productivity and investment growth during reforms(continued)

least two standard deviation over two years.6 Details of the
FIGURE 3.5.1 Reform spurts and setbacks
methodology are described in Annex 3.5.
Progress in reforms has been mixed since 2014, withsome evidence that the pace of governance reforms has
accelerated more than that of business climate reforms.

A. Worldwide Governance Indicators: Number of reformspurts and setbacks
Number of events

25
Spurt

Setback

Net

15

5

-5

-15

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

-25



Progress in reforms has been mixed since 2014, with someevidence that the pace of governance reforms has
accelerated more than that of business climate reforms.
Over 2014-15 (the last available data), governance reformspurts have become more common while reform setbacks
have become less common compared to the immediate
post-crisis period (Figure 3.5.1). In 2015, for the first timesince the global financial crisis, reform spurts
outnumbered reform setbacks. For business climate
reforms, however, a surge in reform spurts in 2015-16 waslargely offset by a surge in reform setbacks. As a result,while reform spurts have continued to outnumber
setbacks, the pace of net improvements has not accelerated
compared to the immediate post-crisis period (Figure
3.5.1). Around reform episodes, potential TFP andinvestment growth has tended to be higher than during“normal” years.
xReform spurts reflected in Worldwide GovernanceIndicators were, on average, associated with about 1
percentage point higher TFP growth globally andsomewhat more in EMDEs during the spurt (Figure
3.5.2).7 Investment growth was 9 percentage points
higher during the average reform spurt and about 2
percentage points lower during the average reform
setback.

x

When reform spurts reflected in Doing Businessindicators exceeded reform setbacks, TFP growth
typically rose by 0.2 percentage point among EMDEs.
During these episodes investment growth in EMDEs
was about 1.6 percentage points above that in“normal” years (Figure 3.5.2).

B. Doing Business indicators: Number of reform spurts
and setbacks
Number of events
80
Spurt

Setback

Net

60
40
20

0
-20

-40

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

-60

Source: World Bank.
Note: A detailed methodology is available in Annex 3.5.
A. For Worldwide Governance Indicators, reform events are defined as twostandard-error changes in one of four Worldwide Governance Indicators for
136 EMDEs and 38 advanced economies during 1996-2015.
B. For Doing Business indicators, reform events are defined as two-standarddeviation changes in distance to frontier in one of ten Doing Businessindicators in 127 EMDEs and 34 advanced economies during the same
period during 2002-17.

The local projections model suggests that the effects ofgovernance reform spurts and setbacks build over time.

6 This yields 44 events in 127 EMDEs and 34 advanced economies
during 2002-17. The sample for potential TFP growth is smaller so there
are no setbacks identified in the case of Doing Business among this smaller
sample.
7 For comparison, using industry-level data, Bourles et al. (2013)
estimate that a removal of all anti-competitive regulations in upstream
industries might have raised TFP growth by 1.7 percentage points per
year in the average OECD country during 1995-2007. Dabla-Norris etal. (2015) estimate that the full elimination of labor and product market
distortions would lift TFP in 13 advanced economies by 3.8-19.5
percent. Studies of aggregate growth find better business climates areassociated with 1 percentage point higher actual growth in EMDEs or 0.8
percentage point higher per capita growth in a broader sample ofcountries (Didier et al. 2015; Divanbeigi and Ramalho 2015).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 3

BOX 3.5 Productivity and investment growth during reforms (concluded)
FIGURE 3.5.2 Potential TFP and investment growth around reform spurts and setbacks
Reform spurts were, on average, associated with a statistically significant 0.1 percentage point per year increase in TFP
growth above its “normal-year” average (0.8 percent) and 2.8-3.5 percentage points per year increase in investment growth
above its “normal-year” average (6.4 percent) two-four years after the reform spurts.
A. Average change in potential TFP
growth around Worldwide GovernanceIndicators reforms

B. Average change in potential TFP
growth around Doing Business reforms

C. Change in potential TFP growth 2-4
years after reform episodes

Percentage points
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
World

Percentage points
0.4

Percentage points
1.0

Reform spurt
Reform setback

Reform spurt

0.3

0.5

0.3

0.0

0.2

-0.5

0.2

-1.0

0.1

2
yrs

0.1

Spurt

0.0
World

EMDEs

4
yrs

2
yrs

4
yrs

Setback

2
yrs

Spurt

World

EMDEs

4
yrs

2
yrs

Setback

EMDEs

D. Average change in investment growtharound Worldwide Governance Indicators
reforms

E. Average change in investment growtharound Doing Business reforms

F. Change in investment growth 2-4
years after reform episodes

Percentage points
10

Percentage points
4

Percentage points
20
15
10
5
0
-5
-10
-15
2
4
2
yrs yrs yrs

Reform spurt
Reform setback

8

Reform spurt
Reform setback

2

6

4

0

2

-2

0
-4

-2
-4

Spurt

-6
World

EMDEs

World

EMDEs

4
yrs

Setback

World

4
yrs

2
yrs

4
yrs

Spurt

2
yrs

4
yrs

Setback

EMDEs

Source: World Bank staff estimates.
Note. TFP growth refers to potential TFP growth, as estimated in Annex 3.1. A detailed methodology is available in Annex 3.5.
A. B. D. E. Simple averages of potential TFP (A and B) and investment (D and E) growth during reform spurts and setbacks (minus simple average potential TFP andinvestment growth outside such episodes) for all countries (“Global”) or for EMDEs only (“EMDE”). For Worldwide Governance Indicators (A and D), based on an event
study of statistically significant 247 reform events—defined as two-standard-error changes in one of four Worldwide Governance Indicators—for 136 EMDEs and 38
advanced economies during 1996-2015. For Doing Business indicators (B and E), based on an event study of 44 reform events—defined as two-standard-deviation
change in one of ten Doing Business Indicators—in 127 EMDEs and 34 advanced economies during the same period during 2002-17. TFP data not available for the 4
reform setback events in Doing Business indicators (A).
C. F. Regression coefficients of potential TFP (C) and investment (F) growth on dummies for structural reform spurts and setbacks—defined as two-standard-error
changes in one of four Worldwide Governance Indicators—from local projections model for lags of two and four years, for a sample of 136 EMDEs and 38 advanced
economies during 1996-2015. Vertical bars show 90 percent confidence interval.

Typically, while it takes four years for growth dividends tomaterialize after governance reform spurts, the adverse
impact of reform setbacks materializes faster (within about
two years) and is less persistent for governance reform
setbacks. Potential TFP growth is, on average, about 0.1
percentage point per year above its “normal-year” average(0.8 percent) four years after reform spurts and about 0.2
percentage point per year below two years after setbacks.
Investment growth is, on average, about 2.8-3.5
percentage points per year above its “normal-year” average(6.4 percent) two-four years after governance reform spurts

and about 2.7 percentage points per year below two years
after reform setbacks.

Conclusion
Governance reforms have accelerated over the past three
years while mixed progress has been made on businessclimate reforms. A renewed boost to both types of reforms
promises sizable dividends for both productivity growthand investment.

189

190

CHAPTER 32017).
This can partly be attributed to weak
managerial
capabilities.
Bettereducation,
especially if combined with greater competition,
can induce an upgrading of managerial skills thatcan foster more ambitious innovations.
An event study suggests that major reform
episodes are followed by higher potential TFP
growth and investment growth over several years,
and conversely for major reform reversals. Major
reform packages are defined as those thatsignificantly improve governance (proxied byWorldwide Governance Indicators) or businessclimates (proxied by Doing Business indicators).
Four years after governance reform spurts inadvanced economies and EMDEs, potential TFP
growth was about 0.1 percentage per year above
the average in years without spurts (0.8 percent)and investment growth was about 2.8-3.5 percentage points per year above its average in years
without spurts (6.4 percent; Figure 3.9, Box 3.5).
Reform setbacks were followed by slower TFP andinvestment growth.
Other reforms, including fiscal structural reforms,
could also yield important productivity dividends.
Several studies have highlighted the long-term
growth dividends of fiscal reforms, especially whencombined with other structural reforms (IMF
2015b). In OECD countries, the growthenhancing effects of a budget-neutral shift ingovernment spending towards health, education,and transport often becomes apparent after five
years (Barbiero and Cournède 2013). More
broadly, low- and lower-middle-income countries
with a greater share of non-wage government
spending tend to have higher long-term growth(Gupta et al. 2005). On the revenue side, also, abudget-neutral increase in the efficiency of the tax
system could raise long-term growth. Sixty percent
of fiscal reform episodes in 112 countries—such as
switching from labor taxation to consumption
taxation and shifting spending towards health,education, and infrastructure—were followed by
growth accelerations of more than 1 percentage
point (IMF 2015b). Over the longer-term, fiscal
reforms such as the establishment of fiscal rules
have also proven growth enhancing in EU
countries (Miyazaki 2014; Castro 2011; Afonsoand Jalles 2012).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018


Reformsfor growth: More
important should history
repeat itself

The stylized scenarios above suggest that a
combination of additional investment, better
educational and health outcomes, labor market or
business climate and governance reforms could
stem or even reverse the expected decline inpotential growth over the next decade (Figure3.9). The human and physical capital and labormarket reform scenarios above are associated with
0.7 percentage point higher EMDE potential
growth. This would more than offset the 0.5percentage-point slowdown in EMDE potential
growth expected under the baseline scenario.
However, good policies could be thwarted by bad
luck. If one or several global and country-specificrisks to growth materialize, some EMDEs could
experience a crisis that is associated with deep
output contractions (Chapter 1). Moreover,historically, the global economy has experienced amajor recession in every decade of the last halfcentury (Kose and Terrones 2015). Althoughthese global recessions were triggered by different
types of shocks, each of them was accompanied bya financial crisis somewhere. In 1975, oil pricesurges coincided with recessions in majoradvanced economies and crises in some EMDEs.
In 1982, monetary policy tightening in majoradvanced economies preceded recessions in thoseeconomies and debt crises in many EMDEs. In
1991, an abrupt tightening of credit in the UnitedStates coincided with banking and currency crises
in many European countries. And in 2008-2009,
there were particularly deep financial crises inmajor advanced economies. The global economy
slowed significantly during the 1997-98 Asian
Crisis and the 2001 dot-com crash, and thesecoincided with recessions in major advanced
economies and some EMDEs.
If this pattern is any guide, it may not be
unreasonable to anticipate that the global
economy could experience another recession or
slowdown over the next ten years. This could
again be accompanied by financial upheaval in one
or more countries. It is impossible to know when

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

and
where the next crisis might occur and what
would trigger it, but past crises have often been
associated with severe short-term output losses.
Short-term contractions, in turn, were followed byhighly persistent losses in output levels in bothadvanced economies and EMDEs.
A recession would also have lasting effects on
potential growth, in addition to the obvious shortterm output disruptions. Box 3.4 estimates theimpact of severe output contractions on potential
growth over the next 1-5 years. Among 49
EMDEs during 1990-2016, there were 77 such
events and, among 32 advanced economies, 47
such events. Contractions in EMDEs, on average,
lasted 1.3 years and were associated with annual
average growth of -4.4 percent. On average, they
were followed by about 1 percentage point lower
potential growth five years after the event.
What would be the implications of a crisis thatinduced a severe recession in the event of anothereconomic shock during the next decade? Threestylized scenarios are considered to illustrate theimpact of a possible crisis on potential output: abaseline scenario consistent with potential growthprospects for 2018-27, a scenario in which a crisis
triggers a severe recession, and a scenario thatinvolves a crisis accompanied with a sustained
policy push as described in the previous section.19
Under the baseline scenario, EMDE potential
output a decade from now would be 52 percent
above current levels (Figure 3.10). However, in thecrisis scenario, these output gains could be 7
percentage points lower. Crises have at times been
associated with growing inequality and setbacks in
19 In the baseline scenario, EMDE potential growth is assumed to
be 4.3 percent on average over 2018-27. In the crisis scenario,
EMDE potential growth is assumed to fall to 3.8 percent on averageduring 2018-27 (3.3 percent during 2021-26 and 4.3 percent
otherwise). In the policy-push-and-crisis scenario, EMDE potential
growth is assumed to average 4.5 percent during 2018-27 (4 percent
on average during 2021-26 and 5 percent otherwise). The stylized
nature of these scenarios implies that the calculation ignores a wide
range of factors that could affect the cost of crises. In particular, theexercise does not take into account the nature of the crisis that would
determine the severity of its impact; the underlying shock that would
trigger the crisis; the initial conditions that determine an economy’svulnerability to shocks; the geographical distribution of costs; or the
likely policy response that could mitigate the impact of the crisis(Claessens and Kose 2014).

CHAPTER 3

191

FIGURE
3.10 Growth and crisis scenarios
If one or several global and country-specific risks to growth materialize,
some EMDEs could face a crisis that generates deep output contractions.
Past experience suggests that such a deep recession could reduce
potential growth by about 1 percentage point over half a decade. A
sustained policy push would be needed to reverse such output losses.

A. EMDE potential growth duringcontractions

B. Cumulative impulse response of
EMDE potential output growth after
contraction

Percent
6

Percentage points
0.0

Average2011-17



5

-0.5

4
3

-1.0

2

1
-1.5

0
t-3

t-2

t-1

t

t+1 t+2 t+3 t+4 t+5Year 1

Year 3

Year 5

C. Global cumulative output change,
2017-27

D. EMDE cumulative output change,
2017-27

Percent
40

Percent
80

Baseline
2013-17

30

60

20

40

10

20

0

Baseline
2013-170
Policy push

Policy pushand crisis

Crisis

Policy push

Policy pushand crisis

Crisis

Sources: Huidrom, Kose, and Ohnsorge (2016); World Bank; World Economic Outlook, International
Monetary Fund.
A. Contractions are defined as the years of negative output growth from the year after the output peakto the output trough, as in Huidrom, Kose, and Ohnsorge (2016). Sample includes 44 contraction
events in EMDEs during 1989-2016 (Annex 3.4). Figure shows unweighted averages of potential
growth as estimated by the production function approach during contractions. t=0 denotes the peakpreceding the contraction. 2011-17 is the unweighted average for countries with contraction episodes
after a peak in 2014. Dotted lines indicate interquartile range.
B. Contractions are defined as the years of negative output growth from the year after the output peakto the output trough, as in Huidrom, Kose, and Ohnsorge (2016). Sample includes yields 44
contraction events in EMDEs during 1989-2016 (Annex 3.4). Figure shows impulse responses fromlocal projections model (Annex 3.4), over horizons of 1, 3, and 5 years. Dependent variable definedas cumulative slowdown in potential growth after a contraction event using the baseline specification.
Bars show coefficient estimates, vertical lines show 90 percent confidence bands.
C. D. GDP weighted averages. Derived using the production function-based potential growth as
described in Annex 3.1. Baseline scenario as described in Annex 3.1. Policy push scenario assumes
0.5 percentage point increase in global potential growth (0.7 percentage point for EMDE potential
growth) during 2018-27 compared with 2013-17 because of investment boost (0.2 percentage point),
improved human capital (0.2 percentage point) and increased labor supply (0.1 percentage point).
Crisis scenario assumes that potential growth is reduced by 1 percentage point for five years andthen reverts to baseline scenario (“Crisis”) or to policy push scenario (“Policy push and crisis”).

development goals (Ötker-Robe and Podpiera
2013; Feyen 2009). It would take a decade’s
worth of sustained policy efforts to reverse
potential output losses. Absent a crisis, a similar
policy push could lift EMDE potential output by
11 percentage points over the baseline over the
next decade.
Any reform package has to take into accountseveral additional considerations.

192

CHAPTER 3x

x

Synergies. Implementing multiple reforms
simultaneously rather than piecemeal cangenerate mutually-reinforcing synergies. For
example, in OECD countries, labor andproduct market reforms, FDI, and trade
regulation potentially yield important synergies (OECD 2017). In another example, land,fiscal, and social benefit reforms yield larger
growth benefits in China when implemented
jointly (Ran et al. 2011). In addition, crosscountry synergies from coordinated reforms
may arise. The potential for growth spillovers
puts a premium on reform efforts in advanced
economies that have large repercussions fortheir EMDE trading partners.
Country-specific reform priorities. In practice,reform priorities differ across countries,
calling for tailored policies (Dabla-Norris2016). For example, school enrollment andcompletion rates in several economies in the
MNA region exceed the EMDE average.
However, education reforms continue to beneeded to address poor scores on international
tests and pervasive skills mismatches in thelabor market (World Bank 2008 and 2013).
Region-specific reform priorities are discussed
in detail in Boxes 2.1-2.6.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018xTiming. Reform payoffs may take more time
to materialize than in the stylized scenarios
discussed here. There is some evidence thatreforms have had the largest growth dividends
when they were well-timed—at least in thecontext of advanced economies. For example,
labor market reforms may lift growth moreduring economic upswings, when job entrants
can more easily find jobs appropriate to theirskills, than downturns (IMF 2016c).

The current cyclical upswing is an auspicious time
to implement reforms that may yield long-term
gains. There can be no quick fix for reversing the
expected slowdown in potential output growth at
the global level, since it reflects underlying
economic factors that are not susceptible to rapidchange. More importantly, if history repeats itself,
a possible crisis over the next decade may have asubstantial adverse impact on potential growthprospects. Mitigating pressures from the shortterm risks and long-term headwinds requires the
adoption of appropriate policies over time. A
package that delivers substantial material benefits
at an early date is more likely to be politically
viable, and stands more chance of success in thelong run.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 3


ANNEX 3.1 Potential output estimatesusing the production
function approachThe production function approach assumes that
potential output can be captured by a CobbDouglas production function:
Yt = At KtȽLt Ƚ (1- )where Yt is potential output, At is potential totalfactor productivity (TFP), K t is the potential
capital stock, and Lt is potential employment. To
extend the sample beyond 2014—the latest
available data from Penn World Tables—TFP wasrecalculated as the Solow residual of output,
employment (extended using data from Haver
Analytics) and capital (extended using investment
data from Haver Analytics and the perpetualinventory method). Labor and capital shares are
the within-country averages of those reported in
Penn World Tables. Two of the three componentsof potential output—potential TFP and potential
employment—are proxied by the fitted values
from panel regression estimates. The third
component, the contribution of capital topotential growth, is assumed to be the same as thecontribution of capital to actual growth. Thisapproach yields an unbalanced panel dataset for
32 advanced economies and 63 EMDEs for 19922027 (Table 3.1.1).
Capital stock data from Penn World Table 9.0 isused until the latest available year in the data set(2014 for most countries in the sample). For
2015-17, investment data are compiled fromnational statistics offices and Haver Analytics,
while the capital stock is estimated from investment data by the perpetual inventory method
using historical average depreciation rates.1
Estimating potential total factor productivity
Potential TFP growth is defined as the fitted valueof a panel fixed effects regression for 37 advanced
economies and 74 EMDEs for 1983-2017 of
Hodrick Prescott-filtered trend of actual TFP
Implicitly, this approach does not account for the possibility thatinefficient investment is written off during downturns but depreciates
only gradually. Hence, it may overstate the capital stock during
downturns.
1

growth (the Solow residual) on determinants ofproductivity. These include GDP per capita
relative to advanced economies, education(secondary school completion rate), the workingage share of the population, and the five-year
moving average real investment growth (as in
Abiad, Leigh, and Mody 2007; Bijsterbosch andKolasa 2010; Turner et al. 2016; Feyrer 2007).2
To allow for nonlinearities in the productivity
dividends from education, schooling is interactedwith a dummy for schooling in the bottom twothirds across the sample. A dummy for commodity
exporters between the period 2003-07 captures theimpact of credit boom in commodity exporters.
dtfpi,t = Ƚ0 + Ƚ1 GDP per capitai,t + Ƚ2 wapi,tbottom two-thirds+ Ƚ3 educationi,t + Ƚ4 educationi,t * dedu i,t
+ Ƚ5 dcebi,t + Ƚ6 dinvi,t + ɂi,t

where dtfp is the logarithmic first difference oftrend TFP, GDP per capita is GDP per capita inpercent of advanced economies per capita GDP,wap is the working-age share of the population,
education is the percent share of the population
who completed secondary school, dinv is the fiveyear moving average real investment growth,bottom two-thirds
dedu
is a dummy variable taking the value of
1 if the secondary completion rate is in the bottom
two-thirds of the distribution, and dceb is adummy variable taking the value 1 if the country
is a commodity exporter for the period 2003-07.
The data were compiled using UN Population
Statistics (for population growth, the working-age
share of the population), Barro and Lee (forsecondary school completion), the World
Development Indicators (for GDP per capita
relative to the advanced economies, and life
expectancy), and Haver Analytics (for investment).

2 The results are robust to using GDP per capita instead of GDP
per capita in percent of advanced-economy GDP per capita. GDP
per capita relative to a frontier (advanced economies) is used here toproxy the catch-up effect highlighted in the literature on stochastic
frontier analysis (Growiec et al. 2015).

193

194

CHAPTER 3

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

The
results are broadly in line with the existing
literature (Annex Table 3.1.2). TFP growth slows
as per capita incomes converge toward advancedeconomy levels (Barro and Sala-i-Martin 1997). A
younger and better-educated population andaccelerated investment lift TFP growth. However,
the effect of education diminishes as educationlevels rise toward advanced-economy levels (Kato
2016; Benhabib and Spiegel 1994 and 2005; Coe,Helpman, and Hoffmaister 1997). As a result, thecoefficient on secondary school completion rates isonly significant for countries with completion
rates below the top third.
Estimating labor force participation rates
Potential employment is defined as the product of
the working-age population and the fitted value ofage- and gender-specific regressions of labor force
participation rates (lfpra,g,t) on their structural
determinants (X a,g,t) and controlling for cohort
effects, fixed effects, and the state of the businesscycle, defined as the deviation of the logarithm ofreal GDP from the Hodrick-Prescott-filteredtrend. The vector X a,g,t includes gender-specificeducation outcomes (secondary and tertiarycompletion and enrollment rates), age-specificfertility rates and life expectancy. The vector C a,g,t
includes all the control variables.
lfpra,g,t = Ƚa,g + Ⱦa,g Xa,g,t + ɀa,g Xa,g,t * demde+ Ɂa,g Ca,g,t +ɂa,g,t
Data on the working-age population comes fromthe UN Population Statistics Database. Data forage- and gender-specific labor force participation
rates are available from Key Indicators of the Labor
Market (KILM) of the ILO Population Statistics
Database for 1990-2016 for up to 35 advanced
economies and 133 EMDEs.3 Completion rates ofsecondary and tertiary education are from Barroand Lee (2013); age-specific fertility rate and life
expectancy are from the UN’s World Population
Projections database; gender-specific secondary andtertiary school enrollment rates are from the WorldThis is an unbalanced sample because some of the exogenous
variables are not available for the full period for all countries.
However, the regression results are robust to restricting the sample tothe balanced panel with fully available data.
3

Development
Indicators.4 The results are broadly inline with findings in the existing literature (Annex
Table 3.1.3).
Fertility rates. Higher fertility rates reduce labor
force participation of women aged 25-49 years.
This could reflect caregiving for young children orchallenges in rejoining the labor market after
temporary exit (Bloom et al. 2007). Among teenage and younger women, fertility rates increase
labor force participation as mothers are more
likely to discontinue their education and participate in the labor force, at least in advanced
economies (Fletcher and Wolfe 2009; Azevedo,
Lopez-Calva, and Perova 2012; Herrera, Sahn,
and Villa 2016). This effect is more muted in
EMDEs, potentially reflecting an earlier averageage of marriage, which tends to reduce female
labor force participation (UN 2012).
Educational enrollment and attainment.
Educational attainment, in the years when the agegroup was at the relevant age, increases
participation rates, except for young men andwomen aged 20-24 in EMDEs. The positive
correlation between completion rates and labor
force participation may partly reflect higher
compensation for more educated workers. For the
young age groups in EMDEs, higher secondary
and tertiary educational attainment reduces labor
force participation. This might reflect the lack ofdemand for employment in sectors where theseeducated workers would expect to be employed,
discouraging them from labor force participation(Klasen and Pieters 2013). For men aged 50-64
and all workers aged 65 years and older, education
becomes an insignificant determinant of labor
force participation (as in Fallick and Pingle 2007).
Secondary and tertiary enrollment rates in all
relevant age groups reduce labor force
participation as students devote time tocompleting their degree (Linacre 2007; Kinoshita
and Guo 2015; and Tansel 2002).
Life expectancy. Life expectancy is one of themain determinants of participation for workers
4 UN data for life expectancy is for five-year periods so life
expectancy for historical years is used from the World Developing
Indicators database and then spliced with UN World Population
Statistics and Prospects data for the projection years or if the data are
not available in the World Development Indicators database.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018aged
50 and above (Fallick and Pingle 2007). Forthe younger ones among them, between the agesof 50-64, higher life expectancy raises labor force
participation, possibly reflecting the need toaccumulate savings for a longer retirement period
or the positive association between better healthamong older workers and higher incomes (Haider
and Loughran 2001). Among those aged 65 years
or older, higher life expectancy increases labor
force participation in advanced economies, butdoes not significantly change participation in
EMDEs. Life expectancy may be a weak proxy fora healthy old age in EMDEs with less-developed
health care systems or where differences in life
expectancy might mostly reflect differences in
infant mortality (Eggleston and Fuchs 2012). The
effect of life expectancy on labor force
participation of workers aged 65 years or older also
depends on the business cycle. The increased
participation of older workers in a weakereconomy might reflect the increased desire forpart-time positions for this age group when they
are healthier (as proxied by higher life expectancy).
It may also reflect rising employer interest because
this age group, if healthy, can act as a highly
flexible source of employment (Buddelmeyer,
Mourre, and Ward 2004; Baer 2015).
Business cycle. Labor force participation isprocyclical—albeit less so in EMDEs than inadvanced economies—in most age groups until
the age of 50 and even for men aged above 65.5 As
the working age population increases, thesensitivity to cyclicality decreases and participation
eventually becomes countercyclical (Duval, Eris,and Furceri 2011; Balakrishnan et al. 2015). This
may reflect greater ability of more experienced
workers to remain employed or return into
employment after spells of unemployment(Shimer 2013; Elsby, Hobijnb, and Sahin 2015).
However, participation becomes pro-cyclical again
for workers aged 65 and above as they become
eligible to retire and may be readier to drop out of
the labor force in a weaker economy.

5 In several instances, there were no statistically significant
differences between advanced economies and EMDEs in thecyclicality of their labor force participation. Hence, the interactions
were omitted from the regressions.

CHAPTER 3

Scenario
analysisContribution of aging to potential growth. The
contribution of aging to potential growth iscalculated as the difference between actual
potential growth and a counterfactual derived
from an “unchanged demographics” scenario. The
counterfactual scenario is one in which population
shares are fixed at 1998 levels (for historicalcontributions) or 2017 levels (for forward-looking
scenarios) in the calculation of labor force
participation rates and TFP growth. All othervariables, including fitted labor force participation
rates for each age group and gender, remain thesame in both scenarios. Hence, aggregated labor
supply differs between the two scenarios only
because different age groups (with different
inclinations to participate in the labor force) havedifferent population shares.
Baseline scenario. The baseline scenario is one of“business as usual” in that it assumes that allpolicy variables follow their long-term averagetrends. The scenario assumes that all populationrelated variables (including age and gender
structure of the population, fertility, and life
expectancy) evolve as in the UN Population
Projections under the assumption of medianfertility and normal mortality.6x Secondary and tertiary enrollment rates bygender are assumed to grow through theforecast horizon at their average growthduring 1998-2017 but are capped at 100
percent.
Economy-wide
averagesarecalculated as the population-weighted (200016) average of these gender-specific rates.
x Secondary and tertiary education completion
rates by gender and age group are assumed to
grow at their average rate during 1998-2017.
Economy-wide averages are calculated as the

6 UN World Population Prospects defines medium fertility in which
total fertility in all countries eventually converges toward a level of
1.85 children per woman. Under normal mortality, mortality is
projected on the basis of models of life expectancy based on recent
trends in life expectancy by gender. Life expectancy projections arecapped at 100 years.

195

196

CHAPTER 3

population-weighted (2000-16) average ofthese gender and group-specific rates.

x Cohort effects are assumed to stay constant attheir latest level throughout the forecasthorizon, starting in 2018.
x The investment growth rate is assumed toremain constant at its longer-term averagethroughout the forecast horizon.7
Based on these assumptions about drivers of TFP,
capital stock, and labor supply, potential growth isestimated using the production function approachdetailed above.
Policy scenarios. The policy scenarios are “beston-record” scenarios. Each policy variable isassumed to rise as much as its biggest ten-year
improvement on record, subject to ceilings.
x Meeting investment needs. The investment
growth rate in each country is assumed to riseby its largest increase in any ten-year period
during 1998-2017.

7 Considering the policy-driven rebalancing away from investment
in China, investment growth rates are assumed to be constant at theirlast five-year average (2013-17).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018x Better human capital. Educational outcome
indicators—secondary and tertiary enrollment
and completion rates—are assumed to rise ineach country by as much as the maximum
improvement over any ten-year period during
1998-2017. Enrollment rates remain capped
at 100 percent. Completion rates are cappedat the maximum across advanced economies
in 2016. Life expectancy is assumed to rise ineach country as much as the largest
improvement over any ten-year period during
1998-2017, but not above the medianadvanced-economy life expectancy in 2016
(capped at 100 years).
x Labor market reform. For each age group ineach country, female labor force participation
rates are assumed to rise by the largest increaseover any ten-year period during 1998-2017,
but not to exceed male labor force
participation rates in the same age group.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 3

ANNEX
TABLE 3.1.1 Country and year coverage &RXQWU\

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ANNEX TABLE 3.1.2 Regression resultsof total factor productivity
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and 0.001, respectively.

198

CHAPTER 3

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

ANNEX TABLE
3.1.3 Regression results of labor force participation
rates
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GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

CHAPTER 3

 ANNEX 3.2 Potential output estimates
using statistical filters

Univariate filters
A univariate statistical filter decomposes a series y t
into trend and cyclical components. Univariate
filters (UVF) have the advantage of being simple
to implement, since the only data required in theestimation is y t (here, real GDP). The trend
component is used as a proxy for potential output.
However, the resulting estimates do not ensure
consistency between cyclical output and othercyclical indicators or between potential output andits fundamental drivers. Moreover, the so-called“end-point problem” inherent in purely statisticaltechniques often implies significant revisions of
output gaps toward the end of the sample, as new
data becomes available.
Five univariate filters are applied to estimate
potential output: filters based on Hodrick andPrescott (1997), three band-pass filters (Christiano
and Fitzgerald 2003; Baxter and King 1999;
Butterworth 1930), and the Unobserved
Components Model. Confidence bands for all
univariate filters are based on the confidence bands
estimated by the Unobserved Components Model.
The Hodrick-Prescott (HP) filter minimizes
deviations of a series y t from its trend ɒ, assuming
a degree of smoothness ɉ of the trend.1 The threeband-pass filters aim to isolate fluctuations in atime series which lie in a specific band of
frequencies. They eliminate slow-moving components (trend) and very high frequency components
and define the intermediate components as
business cycles. Specifically, the three band-passfilters differ in their approximations of the optimallinear filter (also known as the “ideal” band-passfilter) to deal with finite time series.
x

The Baxter and King (BK) filter is a moving
average of the data with symmetric weights onlags and leads. Therefore, it loses observationsin the beginning and towards the end of the

A larger ɉ indicates a smoother trend. For ɉ=0, the trend is equal tothe actual series and for ɉ՜൅λ the trend is a linear time trend with aconstant growth rate. Typically, the value of ɉ is set at 1600 for
quarterly data (Hodrick and Prescott 1997). The trend is estimatedbased on past values as well as projected values of the series y t .
1sample.2 It is particularly well-suited when the
raw series follows a near independent andidentically distributed process (Christiano andFitzgerald 1999).
x

The Christiano and Fitzgerald (CF) filter is a
one-sided moving average of the data withweights that minimize the distance between
the approximated and the “ideal” filter. Since
the filter is one-sided, it does not lose
observations towards the end of the sample. It
is most suitable for random-walk series.3x

The Butterworth (BW) filter—widely used inelectrical engineering for signal extraction—
isolates only low-frequency fluctuations, nothigh-frequency ones. It is particularly suitable
for series with sharp changes in the underlying
trend.

In contrast to other univariate filters, theUnobserved Components Model does not impose
specific parameter assumptions about the degree ofsmoothing, lead and lag windows, or businesscycle frequencies. Instead, it relies on assumptions
about the underlying process followed by output
gaps and potential growth, and is estimated in a
Kalman filter (Harvey 1990):
LYt = Lt + YGAPt(1)

Lt = Lt-1 + Gt + ɂt

(2)Gt = (1 - ɒ)Gss +ɒGt-1 + ɂtG(3)

YGAPt = Ⱦ1YGAPt-1 + Ⱦ2YGAPt-2 + ɂtYGAP(4)

where LY is the log of seasonally adjusted quarterly
real GDP, L the log of potential output, YGAP
the output gap, G t potential output growth,  thesteady state growth, and ɂt and ɂtG are
independently and identically distributed disturbances. Note that the shock ɂt shifts the level ofpotential output whereas ɂtG is a shock to potential
2 This implies a loss of k observations on both ends of the sample,
with a higher k approaching closer to the ideal filter. Baxter and King(1999) suggest using of k = 3 for annual and quarterly data.
3 The Baxter-King and Christiano-Fitzgerald filters require anassumption about business cycle frequencies. The default businesscycle frequencies used here are 1.5 to 8 years.

199

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CHAPTER 3

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

outputgrowth. Equation (3) assumes that
potential growth converges (at a speed ofconvergence ɒ) to its steady level G ss after a shock.
The output gap follows a commonly used secondorder autoregressive process (equation 4).

statevalue Uss according to the parameter ɒͳ and
has a trend component G Ut which has an
autoregression process (9).
UNt - Uss = ɒ1(UNt-1 - Uss) + GtU + ɂtU (8)uU+ ɂtG  (9)GtU = ɒuGt-1

Multivariate filters
The unobserved components model can be
expanded to include additional indicators ofdomestic demand pressures to help identify theoutput gap (Benes et al. 2015). The mostcommonly used indicators are inflation and theunemployment rate. Specifically, the univariate
model of equations (1)-(4) is augmented with a
Phillips Curve relationship between inflation andoutput gaps (equation 5), an Okun’s Law
relationship between unemployment rates andoutput gaps (equations 6-9), and a relationshipbetween capacity utilization and output gaps
(equations 10-13).
Phillips Curve. The Phillips Curve relates inflation
to output gap, controlling for the impact of supply
side shocks such as import prices on domestic
inflation.
m + ɂɎ
Ɏt = ɏɎt-1 + (1 - ɏ)Ɏt+1 + Ƚ1YGAPt + ɉ1Ɏt-1

t

(5)

where Ɏt is quarter-on-quarter inflation at time tand Ɏtm is import price inflation at time t.
Expectations are assumed to be an average ofadaptive and rational expectations, weighted by ɏ.
Okun’s Law. The Okun’s Law relates
unemployment gap UNGAPt (defined as thedifference between the actual unemployment rate
UNt and the equilibrium (or natural)unemployment rate UN t in equation 6) to UN t
the output gap as:
UNGAPt = UNt - UNt (6)Capacity utilization. Since capacity utilization ishighly pro-cyclical, it can help identify the cyclicalcomponent of output even during joblessrecoveries. Equations (10)-(13) describe therelation between capacity utilization and output
gaps and the exogenous process for capacity
utilization, where CAPUss is the steady state ofcapacity utilization rate.
CAPUGAPt =ᖫCAPUGAPt-1 + Ƚ3YGAPt + ɂtCAPUGAP (10)CAPUt = CAPUGAPt + CAPUt (11)CAPUt - CAPUss = ɒ2 (CAPUt-1 - CAPUss)(12)

+ GtC + ɂtCAPU
CC
GtC = ɒcGt-1+ ɂtG (13)Output gap. To close the model, a process for the
output gap needs to be specified. Inflation andunemployment might fail to capture all domestic
demand pressures, such as credit or asset pricegrowth or commodity price cycles. This may leadto an underestimation of the output gap and an
overestimation of potential output, especially at
the peak of the cycle. Instead of assuming that theoutput gap process is exogenous, as in the
traditional multivariate Kalman filter, three
additional indicators are included in the output
gap equation: house price, credit, and commodity
price growth:
YGAPt = Ⱦ1 YGAPt-1 + Ⱦ2 hprt-1+ Ⱦ3comprt-1 + Ⱦ4crt-1 + ɂtYGAP(14)

UNGAPt = ɀUNGAPt-1 - Ƚ2YGAPt + ɂtUNGAP (7)Following Blagrave et al. (2015), the equilibrium
unemployment rate process is specified indeviation from steady state. Equation (8) specifies
the process for UN t . It implies that following a
shock, the NAIRU converges back to its steady

where crt , hprt , and comprt are cyclical components of year-on-year private sector credit
growth deflated by consumer price inflation,quarterly seasonally-adjusted house prices, andexport-weighted real average commodity prices
respectively.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Database
Output gaps and potential growth are estimatedfor 15 advanced economies and 23 EMDEs, for

201

ANNEX
FIGURE A3.2.1 Global output gaps

Output gaps implied by univariate filters tend to be narrower than thoseestimated by the multivariate filter and tend to have wider confidence
bands.
B. Uncertainty in global output gap
Percent of potential GDP
5
4
3
2
1
0
-1
-2
-3
-4
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2018

2009

2006

2003

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2018

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2015

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2012

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UCM
MVF
MVF 95% CI
UCM 95% CI

2009

1
0

2006

BKF
BWF
UCM

2003

2

HPF
CFF
MVF
PF

2000

3

2015

Percent of potential GDP
42012

A. By methodology

2000

Estimation.
The model parameters are estimated
using Bayesian techniques and the state variables
are estimated by a Kalman filter algorithm. A key
parameter determining the shape of potential
output is the variance of the output gap relative topotential growth innovations. The variance of theinnovations ɂtYGAP and ɂtG are set such that theratio of the variances matched the typically usedsmoothness parameter of the Hodrick-Prescottfilter. All priors for persistence parameters follow abeta distribution. The priors for the slope of thePhilipps curve Ƚ1 , the sensitivity of inflation toimport prices ɉ1 , the elasticities of output gap
with respect to house price and credit growth
cycles Ⱦ2 and Ⱦ4,respectively, as well as Ƚ2 and Ƚ3
are set as gamma distributions. The prior for theelasticity of output gap with respect to commodity
price Ⱦ3 follows a normal distribution to allow fora potentially negative impact of commodity priceincreases in commodity importers. The priordistributions for all standard deviations are inverse
gamma distributions. The standard deviations of
ɂtCAPUGAP and ɂtUNGAP are set as the OLS standard
errors of equations (5) and (9) based on HodrickPrescott-filtered data. Steady state values ofgrowth, unemployment, and capacity utilization
are calibrated to the sample mean of theircorresponding HP-filtered series. Confidence
bands are constructed based on the variancematrix of the smoothed (filtered) estimates of thestate variables provided by the Kalman filter
algorithm. The variance of the state variable iscomputed at the posterior mode of the parametersand does not reflect uncertainty related to model
parameters.

CHAPTER 3

Source: World Bank.
A. Figure defines the global output gaps as the real GDP-weighted average of country-specific output
gaps based on different methodologies—the five univariate filters (HPF, BKF, CFF, BWF, UCM), themultivariate filter (MVF), and the production function approach (PF). HPF = Hodrick-Prescott filter,
BKF = Baxter-King filter, CFF = Christiano-Fitzgerald filter, BWF = Butterworth filter,
UCM = unobserved components model.
B. Dashed lines “UCM 95% CI” are 95 percent confidence bands of UCM-based estimates. Dottedlines “MVF 95% CI” are 95 percent confidence bands of MVF-based estimates.

1980Q1-2016Q4 (Annex Table 3.2.1). GDP,
inflation, unemployment rates, and capacity
utilization rates are from Haver Analytics. Private
sector credit is from the Bank for International
Settlements (BIS), when available, or International
Financial Statistics when not available from BIS.
House price growth is from Haver Analytics.
Commodity prices are from the World Bank’s
Pink Sheet, and export weights are from UN
Comtrade. For the purposes of this chapter,country-specific output gaps are aggregated using
real GDP weights at 2010 exchange rates andprices.
Multivariate filter-based estimates of output gaps
have narrower confidence bands than those of
univariate filters (Figure A.3.2.1). This reflects theuse of additional demand pressure indicators in
the MVF that help identify the output gap moreaccurately.

202

CHAPTER 3

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

ANNEX TABLE
3.2.1 Country and year coverage$GYDQFHGHFRQRPLHV(PHUJLQJPDUNHWDQGGHYHORSLQJHFRQRPLHV&RXQWU\

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GLOBAL ECONOMIC PROSPECTS | JANUARY 2018



CHAPTER 3

203

ANNEX 3.3 TFP and potential  output growth during investment
booms and busts

Definitions. An investment boom (bust) is defined
as an episode during which investment growth isat least one standard deviation higher (lower) thanits sample average for at least two years.1 The
sample covers 94 episodes of investment booms
and 32 episodes of investment busts in 40 EMDEs
during 1980-2016.

ANNEX FIGURE A3.3.1 Potential growth aroundinvestment booms and busts in EMDEs: Alternative
measures

Methodology. The evolution of TFP growth andpotential growth 3 years before and after the boom
and bust episodes are examined. The results arederived from both simple averages of theevolutions and a panel regression of potential
growth on dummy variables for these events,
controlling for country- and year-fixed effects.
Simple averages illustrate the evolution of TFP
growth and potential output growth during
events, while the regression approach allows a basic
comparison with non-event country-year pairs.

A. Multivariate filter: Booms

B. Consensus expectations: Booms

Percent
7

Percent
7

Robustness of results. As a robustness check, theevent study is conducted for alternative potential
output measures (Figure A3.3.1, Annex Table
3.3.1). Potential growth estimates based on
the multivariate filter and 5-year-ahead Consensus
growth forecasts return similar results to thebenchmark case of production function-based
potential growth estimates. Both boom and bust
dummies are estimated to be statisticallysignificant in most of the cases as shown in Annex
Table 3.3.1.

The correlations between potential growth and investment booms andbusts are robust to alternative measures of potential output such as
multivariate filter approach and five-year-ahead Consensus growthforecasts.

MedianUpper and lower quartiles

6

MedianUpper and lower quartiles

6

5
5
4
4

3
2

3
t-3

t-2

t-1

t

t+1

t+2

t+3

C. Multivariate filter: Busts

t-2

t-1

t

t+1

t+2

t+3

D. Consensus expectations: BustsMedianUpper and lower quartiles
2014-17

Percent6

t-3

MedianUpper and lower quartiles
2014-17

Percent
6

5

5

4

4

3

3

2

2

1

1

0

0
t-3

t-2

t-1

t

t+1

t+2

t+3

t-3

t-2

t-1

t

t+1

t+2

t+3

Sources: Consensus Economics, World Bank.
Notes: An investment boom is defined as an episode during which investment growth is at least one
standard deviation larger than its long-run (over the sample period) average level. t denotes theaverage of the investment boom in years. The event studies in this box are conducted using theboom and bust episodes of at least two consecutive years.

1 The same exercise was repeated for investment booms or busts ofmore than one year’s duration. Results were qualitatively similar.

ANNEX TABLE 3.3.1 Potential growth, TFP growth, and investment
9DULDEOHV

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Consensus

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Notes: Robust standard errors in brackets. *** p<0.01, ** p<0.05, * p<0.1
The table presents estimated coefficients of investment boom and bust dummy variables in a panel regression in which time and country fixed effects are controlled. The dataset is annualand covers the period between 1980 and 2016. MVF, PF, UCM, WEO, and Consensus stand for potential growth estimates derived using the multivariate filter, the production function
approach, the unobserved component model, 5-year ahead World Economic Outlook and Consensus growth forecasts. Consensus Forecasts are available for a highly restrictive sample that
reduces the precision of coefficient estimates.

204

CHAPTER 3



GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

ANNEX 3.4 Long-term effects of output contractions

ANNEX TABLE 3.4.1 Impulse response of potential
growth to contraction events'HILQLWLRQRISRWHQWLDO

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Notes: *, **, and *** indicate significance at the 10, 5, and 1 percent level of confidence, respectively.
The table represents the estimations of local projections model for change in potential growth(as dependent variable) between the contraction event and the end of the horizon. Regressors
include the dummy variable for the contraction event, controlling for lagged potential growth before
the shock and country fixed effects. A Hodrick-Prescott filter is used for the univariate filter-based
measure of potential growth. For the regression using potential growth based on the production
function approach, sample includes 33 events in 29 advanced economies and 32 events in 31
EMDEs. For the regression using potential growth based on the multivariate filter, sample includes
19 events in 15 advanced economies and 21 events in 17 EMDEs. For the regression using potential
growth based on the univariate filter, sample includes 19 events in 15 advanced economies and 21
events in 17 EMDEs.

Definition and data. Contractions are identified
as in Huidrom, Kose, and Ohnsorge (2016) as
peak-to-trough periods when i) output growth isnegative and ii) output growth is 1 standard
deviation below the country-specific averageduring 1989-2016. Peaks are defined as the local
maxima of real output that precede thecontraction. The contraction event is the period
from the year after the output peak to the year of
the output trough. The definition of contraction
events yields up to 47 contraction events in 32
advanced economies and up to 77 contraction
events in 49 EMDEs during 1990-2016.
However, the sample used in the regression
specifications is considerably smaller because of
the lack of potential growth measures.
Methodology. A local projections model is used
to estimate the cumulative impact of output
contractions on potential output growth,following Jorda (2005) and Teulings andZubanov (2014). In impulse responses, the model
estimates the effect of short-term shocks (thecontraction event) over a horizon h while
controlling for other determinants.
pot
pot
pot
yi,t+h- yi,t-1= Ƚh + Ⱦh shocki,t + ɀh dyi,t-1+ ᖫh X i,th+ fixed effects + Ԫi,t
pot

where y i,t is potential growth. The model controls
for country-fixed effects to capture time-invariant
cross-country differences. The variable shock i,t is adummy variable for a contraction event, the main
variable of interest. Lagged potential growthpotdyi,t-1 controls for the history of potential growth.
Robustness of results. Results are reported in
Annex Table 3.4.1. They are broadly robust to the
choice of potential growth measure (production
function approach, multivariate filter, andHodrick-Prescott filter).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018



CHAPTER 3


ANNEX 3.5 Impactof reforms

Defining reform events. Two types of indicators
are used to defined major reform events: theWorld Bank’s Worldwide Governance Indicatorsand Doing Business indicators.
x Worldwide Governance Indicators. Reformspurts (setbacks) are defined as two-yearincreases (decreases) by two standard errors in
one or more indexes of government
effectiveness, regulatory quality, rule of law,and control of corruption from the Worldwide
Governance Indicators. The average of thestandards errors at time t and t-2 (the first andlast year of the event interval) is used for the
standard deviation. This yields 131 reformspurts and 116 reform setbacks for 136
emerging market and developing economies(EMDEs) and 38 advanced economies during
1996-2015.
x Doing Business Indicators. Similarly, reformspurts (setbacks) are defined as two-yearincreases (decreases) by two standard deviationin the distance to frontier of one or more of
the ten Doing Business indicators: starting abusiness, dealing with construction permits,
getting electricity, registering property, getting
credit, protecting minority investors, paying
taxes, trading across borders, enforcing
contracts, and resolving insolvency. The
standard deviation is defined as the crosscountry standard deviation in the event year.
This yields 40 reform spurts and 4 reform
setbacks for 127 EMDEs and 34 advanced
economies during 2002-17.

Methodology. Two exercises are conducted: acomparison of means and a local projection
model.
x Comparison of means. The difference between
the simple average of potential total factor
productivity (TFP) (or real investment)
growth during all reform spurt (setback)
events and simple average of potential TFP (orreal investment) growth during all “normal”
years without such events is examined (Figure
3.5.2). The averages are calculated both forthe full sample and for EMDEs only.
x Local projection model. A local projection
model as in Jorda (2005) and Teulings andZubanov (2014) is used to identify the effects
of reform events on potential TFP and real
investment growth over time. In impulse
responses, the model estimates the effect ofreform events (the dummy variable shocki,t) on
cumulative potential TFP (or real investment)
growth over a horizon h while controlling forcountry- and year-fixed effects and laggedchanges in potential TFP (or real investment)
growth:2

h shock
yi,t+h - yi,t-1 = Ƚh + Ⱦh shocki,t + ȭɀ1,j
i,t-j
J=1




h -1

2

j=1

j=1

h shockh+ȭ ɀ2,ji,t+h-j + ȭ ɀ3,j dyi,t-j+ fixed effects + Ԫi,th 
where y refers to TFP (or real investment) and dy
to its growth rate.

205

206

CHAPTER 3


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SPECIAL FOCUS 2
Education Demographics andGlobal Inequality

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018



SPECIAL FOCUS 2

Education Demographics and Global Inequality

An expected shift in the skill composition of the global labor force will have important consequences
for the future of global income inequality. Specifically, a more educated labor force from emerging
market and developing economies will likely reduce inequality between countries. It would also
diminish inequality within countries, especially in emerging market and developing economies.

Introduction
In the next two decades, new cohorts of moreeducated workers from developing countries willenter the global workforce with better skills. Thischange in educational demographics will likely
have important consequences for global income
inequality. Such formation of human capital will
also enhance potential output and growth in thelong run, a welcome development in light of the
anticipated risks in the medium term (Chapter 3).
In the last two decades, global inequality waspartly shaped by the rapid integration of rising
working-age populations in emerging market anddeveloping economies (EMDEs) into the world
economy. The information and communications
technology revolution, combined with crossborder increases in trade and financial flows, reduced the costs of communication and fragmented
production by combining high-tech capital withbest managerial practices and low-paid workers
globally (Baldwin 2016). Between 1990 and 2015,
the share of trade in global GDP rose by about 50
percent and the stock of international financial
assets relative to GDP tripled (Figure SF2.1.A).
Because of the convergence of income among
countries, notably the rapid growth of large
economies in Asia like China and India, global
inequality fell from the late 1980s on. As average
incomes across countries converged, the relative
contribution of within-country inequality to
global inequality rose (Figure SF2.1.B).1

Note: This Special Focus was prepared by Marcio Cruz, Delfin S.
Go, Franziska Lieselotte Ohnsorge, and Israel Osorio-Rodarte.
Xinghao Gong provided valuable research assistance. The analysis in
this Special Focus is mostly based on the background paper “Global
Inequality in a More Educated World” by S. Amer Ahmed, Maurizio
Bussolo, Marcio Cruz, Delfin S. Go, and Israel Osorio-Rodarte(2017).
1 Two measures of inequality are used in the analysis – the Gini
coefficient and the log mean deviation (also called Theil-L index orOver the next two decades, the working-age
population is expected to expand in EMDEs andshrink in advanced economies. This broad trend
will be accompanied by a shifting skill
composition, as the share of better-educated andmore-skilled workers rises in EMDEs. These two
factors will further change the income distribution
between countries as well as within countries by2030. Between-country distributional changes willcontinue to reflect an overall convergence incountry-level per capita GDP whereas withincountry distributional changes will be generated
by improvements in household incomes led byyounger, better-educated workers within eachcountry.
In light of these changes and their likely
impact, this Special Focus addresses the following
questions:x How has global inequality evolved during thepast three decades of rapid globalization?
x How will the next wave of demographic andeducational trends shape the global labormarket?
x What are the implications of these changes for
global inequality?

general entropy measure GE(0)). Although the Gini (1912)
coefficient of inequality is intuitive and the most widely used single
measure of inequality, it does not allow a decomposition into a
between-country and within-country component since it is not
additive across sub-groups. In contrast, the log mean deviation or
Theil index as proposed by Theil (1967) allows a decomposition into
between-country and within-country inequality (Bourguignon 1979).
In Figure SF2.1.B, the relative importance of the two components
add up to 100 percent. The fraction of global inequality accounted
for by differences of average income across countries declined from80 to 65 percent while the relative contribution of inequality withincountries increased from 20 to 35 percent during 1988-2013. See theexplanatory note of Figure SF2.1.B for details. See Annex for further
discussion.

219

SPECIAL FOCUS 2

220

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE SF2.1
 Globalization and inequality 
Two decades of rapid globalization resulted in increased trade andfinancial integration and have been accompanied by a decline in global
inequality. This is mainly due to income convergence among countries. The
relative importance of inequality within countries, however, has steadily
increased.
A. Global trade

B. Global inequality

Percent of GDP
200
Global trade
IIP assets
150

1.0

100

0.6

Mean log deviation

2015

2010

2005

2000

70

80

76

74

72

70

60
65

0.4

50

0.2

40

0

1995

80

0.8

50

1990

Index

Within-country
Between-country
Gini index (RHS)

20

24

26

28

30

supported
rapid growth in EMDEs before the global
financial crisis. These developments coincided with adecline in inequality in EMDEs, especially in the newmillennium, and the country-specific Gini coefficients—a widely used measure of inequality—for EMDE
regions, on average, fell from 41.1 in 1998 to 38.9 in2013 (Figure SF2.2.A). Despite recent improvements,
however, the average Gini coefficient in Latin America
and the Caribbean and Sub-Saharan Africa were thehighest and second highest in six EMDE regions,
respectively.

35
30

0.0
1988 1993 1998 2003 2008 2013

Sources: International Finance Statistics and World Economic Outlook, International Monetary Fund;World Bank (2016).
A. International investment position (IIP) assets are for countries with available data.
B. World Bank calculations based on data in Lakner and Milanoviü (2016) and Milanoviü (2016), using
PovcalNet (online World Bank tool, http://iresearch.worldbank.org/PovcalNet/.) For each country,
household income or consumption per capita is expressed in 2011 PPP exchange rates, and it isderived from household surveys that are represented by decile groups. The line (measured on theright axis) shows the Gini Index, which ranges from 0 (perfect equality) to 100 percent (perfectinequality). The height of the stacked bars shows an alternative measure of inequality, the GE(0)index which can be decomposed into within- and between-country inequality and increases from 0(perfect equality) with growing inequality. The red bars show the population-weighted average ofwithin-country inequality; and the blue bars show the average between-country inequality. The
numbers in the bars denote the relative contributions (in percent shares) of these two sources to total
global inequality.



Recent evolution of global inequality
Emergence of a global labor market. A “global labormarket” emerged rapidly in the 1990s, when China,
India, and the former Soviet bloc began to integrate
into the global economy. This integration increased
the global labor pool from 1.5 billion workers to 2.9
billion workers. This “great doubling” brought inworkers who were mostly low-skilled and low-wage(Freeman 2008 and 2007; Jaumotte and Tytell 2007).
Impact on inequality. The immediate impact was toalter the global capital-labor ratio, favoring or
increasing returns to capital relative to wages andraising concerns in some studies about linkages
between globalization and inequality (Pitt 2017;
Milanović 2016; Bourguignon 2015; Galbraith 2012;
OECD 2011; Lall et al. 2007). The expansion ofworld trade and investment flows benefited lowskilled workers in China, India and, to some extent,
the former Soviet bloc. Demand for the goods they
produced rose, and so did their wages. Also, increased
global economic integration accelerated diffusion andadoption of new technologies, which in turnThe opposite occurred for low-skilled workers inadvanced economies. The share of national
income accounted for by wages declined(Stockhammer 2013). Physical and financial assets
became more concentrated in the top income
brackets, increasing inequality. A number ofstudies have called attention to the rising capitalshare of total value added and the concentration ofincome and wealth at the top-end of income
distribution in advanced economies (Stiglitz 2012;
Piketty 2014; Atkinson 2015; Bourguignon
2015). On average among advanced economies,
country-specific Gini coefficients have increased
from 29.8 in 1988 to 31.8 in 2013 (Figure
SF2.2.A).
However, global income inequality declined, as
demonstrated by a decline in the global Gini index
from 69.7 in 1988 to 65.8 in 2013 (Figure
SF2.1.B). This decline can largely be explained by
the convergence of EMDEs towards advanced
economy per capita incomes during the two
decades of rapid growth, especially among thelargest emerging markets. Even so, the share ofwithin-country inequality to total global
inequality has been steadily increasing from 20
percent in 1988 to 35 percent in 2013.
Reflecting the relatively broad progress that many
countries made in the new millennium, theaverage unweighted country specific Gini in theworld declined from 40.6 to 37.8 between 1998
and 2013, after rising during 1988-1998. In fact,
this was the first decline in global inequality since
the industrial revolution (Bourguignon 2015;
World Bank 2016). However, the population
weighted average, which captures the withincountry inequality for the average person in the

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Future labor market trends. Global demographic
and educational projections foretell a second waveof substantial changes in the global labor market.
Defining skilled workers as those having nine ormore years of education, new entrants of bettereducated workers will come mainly fromdeveloping countries (Figure SF2.3.A). Based onUnited Nations population projections andpresent rates of educational enrollment (conservatively kept constant into the future), the world
will see the number of skilled workers rising from1.66 billion in 2011 to 2.16 billion by 2040, an
increase of about 500 million or 30 percent(Ahmed et al. 2017).
As in the case of the great doubling, the role of
EMDEs is prominent. Due to their growing
populations and investments in education,
developing countries will contribute all of theadditional workers to the world pool of educatedworkers. Because of aging, the overall number ofskilled workers in advanced economies is projected
to decline, from 603 million in 2011 to 601
million in 2030 and 594 million in 2050. Around2012, one skilled worker from an advanced(OECD) economy was competing in the global
labor market with two skilled workers fromdeveloping countries. In less than a generation, by2030, that ratio will be 1 to 3. This “educationwave” could constitute a shock to global labormarkets and to the labor markets within EMDEs
that may transform them once again, as the “great
doubling” did in the first wave.

A. Trends in the average Gini byregion

Index
42

36

20

34

10

32

Unweighted
Weighted

2013

38

30

2013

40

2008

40

2003

50

2008

MNA

2003

LAC
AEs

1998

ECA
SSA

1993

EAP
SAR

B. Average within-country inequality

1988

Index
60

1998

Data and methodology. The forward-looking
analysis uses two World Bank global models thatlink economies across the world to derive theglobal repercussions of education demographics.
The results of the analysis rely on income
distributions from harmonized household surveys
for over 100 countries (Ahmed et al. 2017;
Annex).

In EMDEs, average inequality for most regions has declined in the newmillennium. Despite broad-based improvement, the highest levels of
inequality are observed in LAC and SSA. Average inequality in AEs, on theother hand, has been increasing since 1988. The average country-specificinequality as measured by the Gini index has declined since 1998.

1993

Education wave and the global labor market

221

FIGURE
SF2.2 Evolution of inequality, 1988-2013 1988world,
follows a slightly different pattern. The
population-weighted average Gini fell from 40.1
in 1998 to 39 in 2008 but rose very slightly after
the financial crisis to 39.3 in 2013.

SPECIAL FOCUS 2

Source: World Bank (2016).
Note: World Bank calculations based on data in Milanoviü (2014), using PovcalNet (online WorldBank tool, http://iresearch.worldbank.org/PovcalNet/.)A. The average within-country Gini by region are simple averages in the full sample without weighting
countries by population. EAP = East Asia and Pacific; ECA = Europe and Central Asia; LAC = Latin
America and the Caribbean; MNA = Middle East and North Africa; SSA = Sub-Saharan Africa; andAEs = Advanced Economies.
B. The lines show the trend in the average within-country Gini index with and without population
weights in the full sample with an average 109 countries per benchmark year.

Large heterogeneity across regions will remain, as
reflected in the growth rates of skilled versus unskilledworkers. In most regions, the number of skilledworkers is expected to grow faster—in some cases,
much faster—than that of unskilled workers (Figure
SF2.3.B). Within EMDEs, the regions of SSA, MNA,
SAR, and LAC will have high growth in the supply ofskilled workers.
Factors analyzed for their impact on future
inequality. Changes in global inequality between
2012 and 2030 reflect not only the relative size oflabor by skill among regions and countries but also
their respective overall income growth, changes in
sectoral employment, and income shifts between
skilled and unskilled workers.
x By lifting the incomes of poor and non-poor
alike, overall growth has long been identified
as the main driver of poverty reduction(Dollar, Kleineberg and Kraay 2016). As longas per capita incomes grow faster in economies
with many poor people than in economies
with few poor people, aggregate growth will
reduce global income inequality.

222

SPECIAL FOCUS 2

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

FIGURE SF2.3
 Future supply of skilled workers New skilled worker entrants will come mainly from EMDEs, and the numberof skilled workers will generally grow faster than that of unskilled workers
for most regions. Because of aging, however, the overall number of skilledworkers in advanced economies is projected to decline by 2030.
A. Number of skilled workers

B. Cumulative growth in the numberof skilled and unskilled labor, 2012-30

Million people
500
SAR

Percent70
60
SkilledUnskilled
50
40
30
20
10
0
-10
-20
AEs EAP ECA LAC MNA SAR SSA

400

300
200

SSA
LAC
MNA
EAP
ECA
AEs

100

0
-100
2020

2025

2030

2035

2040

Source: Ahmed et al. (2017).
A. B. EAP = East Asia and Pacific; ECA = Europe and Central Asia; LAC = Latin America and the
Caribbean; MNA = Middle East and North Africa; SSA = Sub-Saharan Africa; and AEs = Advanced
Economies.
A. Skilled is defined as workers with more than nine years of education. Population projections are
based on UN (2015). Education information is from harmonized household and labor surveys for 117
countries, keeping present rates of educational attainment in the calculation of the supply of skilledworkers.
B. The growth rates are expressed as the cumulative growth for the period 2012-30.

x A higher number of skilled workers (relative
to unskilled workers) in 2030 compared with
2012 will, other things equal, reduce the skill
premium in wages and, hence, within-country
inequality, especially in EMDEs.
x As EMDEs urbanize, production, income,and the allocation of unskilled workers will
likely shift towards non-agricultural, urban
sectors. Since the agricultural sector uses
unskilled labor more intensively than urban
sectors, the process of urbanization is likely torelease more unskilled agricultural workers tourban sectors. This development will put
downward pressure on relative wages of
unskilled workers in urban sectors and reduce
the urban premium for unskilled workers.
The effect of these factors on inequality will dependon country-specific circumstances as the scenario
analysis below documents.

x Education-wave scenario. The education-wave
scenario is the baseline case. In this simulation,
population projections are from the United
Nations medium fertility scenario (UN 2015);
economic growth projections are from WorldBank (2015); and the share of skilled workers
is projected to grow in line with population
growth and assuming constant education
attainment rates. Even with constant educational attainment rates (a conservative assumption),2 the average schooling of theworking-age population will increase as
students move up from one educational grade to
the next, while older, usually less educated ones
leave the workforce—a pipeline effect or natural
progression. The larger intergenerational education gap in developing countries, combined withthe large size and growing pool of younger
cohorts relative to the older ones in thosecountries, is the key driver of the education wave.
x No-education-wave scenario. The no-education-wave scenario is a counterfactual to thebaseline scenario. It is the identical to thebaseline case except for the assumption of aconstant share of skilled workers in theworking-age population (i.e., no pipeline
effect from schooling). In contrast to theeducation-wave scenario, this assumes that the
number of skilled and unskilled workers grows
at the same rate as the working-age populationfor each country.
At the global level, the share of skilled workers in
the total workforce was about 42.7 in 2012. In the
no-wave scenario, despite keeping a constant shareof skilled workers in the working-age populationof each country, the global share of skilled workers
is expected to fall slightly to 40.1 in 2030. This isdue to differences in the demographic transition
between countries attributable to changes in thesize of the population and compositional effects ascountries with less skilled workers increase theirshare of the global working-age population. In the

Education wave and global inequality
Scenarios. The simulation period is for about a 20year span, from 2012 to 2030, comparable to the firstwave of the “great doubling” of global labor supply.
Two forward-looking simulations are defined:

2 Lutz and KC (2014) provide alternative projections with higher
improvements in the enrollment rates from the International Institutefor Applied System Analysis (IIASA). The beneficial effects ofeducation on inequality have been documented in some country
cases, such as Mexico (Lopez-Acevedo 2006) and Brazil (Blom et al.
2001).See the section on “Other factors” for further discussion.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

education-wave
scenario, the share of skilled
workers is projected to rise to 45.5 in 2030.
Education-wave scenario. Since better skills areassociated with higher income, the world underthe baseline scenario will continue to become
more equal by 2030 as EMDE per capita incomescatch up with advanced-economy per capita
incomes. The global Gini coefficient is expected to
decline from 65.8 in 2012 to 62.6 in 2030
(Figures SF2.4.A). This 3.2 percentage point
decline in the global Gini coefficient as a result of
assumed education demographics compares withthe 7.2 percentage point decline in the global Gini
coefficient during the slightly longer period 19882013, that was the outcome of a wide range ofglobal and local developments (World Bank
2016).3
This expected decline in global inequality by 2030
in the baseline scenario mainly reflects a continuing convergence in average per capita incomesin EMDEs towards advanced economy levels(Figure SF2.4.B). Hence, fast-growing EMDEs
with a large number of poor, such as India, which
accounts for 28 percent of the world’s poor in
2013, will continue to contribute to the reductionof global inequality. Within this declining trend inglobal inequality, the relative contribution of
average within-country inequality rises from 47.2
percent share in 2012 to 53.9 percent by 2030.4
No-education-wave scenario. In the no-education-wave scenario, removing the additional influxof skilled workers from the pipeline effects ofschooling and population aging into the global
labor market would enhance the skill premiumcompared to the baseline or education-wave
scenario and, hence, increase inequality. Compared with the baseline scenario, the global Gini
coefficient would be slightly higher at 63.2 in
2030 while the GE(0) index would also rise to
0.82. The relative contribution of average within3 Lakner and Milanović (2016) reported a decline of 1.7 percentage
points for the shorter period 1988-2008 and in 2005 PPPs.
4 Another index of inequality, the mean log deviation GE(0), or the
Theil-L index, also declined from 0.85 in 2012 to 0.80 by 2030. The
contribution of within-country inequality is measured as its
contribution to the GE(0) index. Note the different database used in
Ahmed et al. (2017) and World Bank (2016) as described in the
explanatory note of Figure SF2.4.A.

SPECIAL FOCUS 2223

FIGURE
SF2.4 Global inequality in 2012 and 2030
Global inequality is expected to fall further by 2030, largely reflecting acontinuing convergence of EMDE per capita incomes to advancedeconomy levels and the sectoral employment shifts due to economictransformation. Although within-country inequality will rise in importance at
the global level, the education wave will nudge down within-country
inequality, especially in EMDEs.
A. Gini coefficient
Mean log deviation
1.0

B. Global growth incidence, 2012-30
Within-country
Between-country
Gini index (RHS)

Index
66

0.8

62
52.8

0.6

45.7

46.1
58

0.4
0.2

47.2

54.3

53.9

54
50

0.0
2012

2030 No-wave 2030 Educationwave

Per capita income/consumption
annual percentage change, 2012-30
6Education wave
No wave
5
4
3
2
0

20

40

60

80

100

C. Economies with higher or lower
within-country inequality in the
education-wave scenario compared to
the no-wave scenario

D. Population-weighted average ofdifference in the Gini index between
education and no-wave scenario

Percent100

0.1

Higher inequality

Lower inequality

0.0
-0.1

80

-0.2
-0.3

60

-0.4
40

-0.5
-0.6

20

-0.7
-0.8

0
AEs EAP ECA LAC MNA SAR SSA

LAC SAR SSA MNA EAP ECA AEs

Source: Ahmed et al. (2017).
A. The quantitative levels of inequality and particularly the decomposition between and within-country
in the base year (2012) of this graph are different from those of the end year (2013) in Figure SF2.1B.
One factor is the difference in the number and composition of countries used in Ahmed et al. (2017)
and World Bank (2016). A second factor is a difference in the level of disaggregation in the household
surveys employed. Each country distribution in World Bank (2016) is represented by ten decile
groups, while Ahmed et al. (2017) use every single observation in the household survey to assemble
a global database of approximately 10 million observations. Nonetheless, the qualitative interpretationand direction of change are consistent. The line (measured on the right axis) shows the Gini Index,
which ranges from 0 (perfect equality) to 100 percent (perfect inequality). The height of the stacked
bars shows an alternative measure of inequality, the GE(0) index which can be decomposed into
within- and between-country inequality and increases from 0 (perfect equality) with growing inequality.
The red bars show the population-weighted average of within-country inequality; and the blue bars
show the average between-country inequality. The numbers in the bars denote the relative
contributions (in percent shares) of these two sources to total global inequality.
B. The global growth incidence curve indicates household income growth between 2012 and 2030 in
the no-wave and the education-wave scenarios for households at every level of income.
C. D. EAP = East Asia and Pacific; ECA = Europe and Central Asia; LAC = Latin America and the
Caribbean; MNA = Middle East and North Africa; SSA = Sub-Saharan Africa; and AEs = Advanced
Economies.
C. Figure shows the share of countries in each region in which the within-country Gini coefficient islower in the education-wave scenario than the no wave scenario (red bars “Lower inequality”) or
higher in the education-wave scenario than the no-wave scenario (blue bars “Higher inequality”).
D. The population-weighted average difference in the Gini index is negative if there is an improvementin the within-country inequality between the education-wave relative to the no-wave scenario.

country inequality at the world level would
account for 54.3 percent by 2030. Compared tothe baseline, the relative shares of between- andwithin-country inequality would change only
marginally. This is because the education wave
would improve both between-country inequality

224

SPECIAL FOCUS 2(by raising the incomes of EMDEs relative to AEs)
and within-country inequality (by lowering theskill premia of wages in EMDEs) so that the two
effects offset one another relative to the no-wave
case.
Growth incidence curves and country-specificinequality. In the global distribution of householdincome, middle-income households would be thebiggest beneficiaries of the education wave. The global
growth incidence curves illustrate household income
growth between 2012 and 2030 at every level ofhousehold income in the world under the educationwave and no-wave scenario (Figure SF2.4.B). Income
growth under the education-wave scenario is higher
almost everywhere than in the no-wave scenario,
but the difference is largest among middle-income
households.
The beneficial impact of the education wave on
within-country inequality can be seen bycomparing the Gini indices of the two scenarios.
The differences in the country-specific Gini indicesof the education-wave and no-wave scenarios
appear widely negative, meaning inequality falls
more in the education-wave scenario. By 2030,
the number of countries with lower inequality inthe education-wave is uniformly and significantly
higher than under the no wave scenario across all
regions encompassing both the EMDEs andadvanced economies (Figure SF2.4.C). The
population-weighted average of these differencesin the Gini coefficient between the educationwave- and no-education-wave-scenarios is negative(indicating less inequality in the education wavescenario) for all EMDE regions but practicallyzero for advanced economies (Figure SF2.4.D).
Among EMDEs, the benefits of the education
wave are likely to be highest in LAC, SAR, and
SSA due to the high growth of skilled workers inthese regions that takes place during the transition
phases of the intergenerational demographic gap(the difference in population size between young
and old cohorts) and the inter-generational
education gap (the difference in the average yearsof schooling between young and old cohorts).
Although inequality in many advanced economies
would improve with the education wave, thesegains would be offset by a few aging economies

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018withlarger deteriorations and populations so that
the weighted average is close to zero.
Other factors. Several important factors areoutside the scope of this analysis. They could
influence the results in either direction.
Trend improvements in educational attainment.
Especially in Africa, educational attainment has
grown steadily over the past two decades (WorldBank 2017; Ahmed et al. 2016). Many EMDEs
have already attained advanced-economy levels ofcompletion rates for “skilled labor” as defined herewith 9 or more years of schooling. (An exception
is Sub-Saharan Africa, where completion rates atlower secondary schooling are still below 45
percent.) If these trend improvements continue orif they accelerate—perhaps because greater female
empowerment leads to better education forchildren (World Bank 2012)—the supply ofskilled labor would expand more than assumed in
the scenario, growth will be higher and income
inequality lower than in the scenarios above. Thisis, of course, predicated on education deliveringlearning. The 2018 World Development Report(World Bank 2017) emphasizes that it is thelearning outcomes that are critical for increasing
productivity,
employment,
earnings,
andeconomic growth. A number of structural changes
could expand the supply of skilled labor even morethan assumed in this scenario, as suggested byresults for Sub-Saharan Africa (Ahmed et al.
2016). As jobs empower women to invest more in
their children, poverty will likely fall according to
the 2013 World Development Report (World Bank
2012).
External and domestic shocks. Internal andexternal shocks could present severe setbacks tothe scenarios outlined above (Devarajan et al.
2015, Chapters 1 and 2). Internal shocks include
conflicts and droughts while external shocks
include commodity price falls, sudden stops oreven reversals in capital inflows, and recessions inmajor trading partners.
Labor market frictions. The analysis presumes that
additional workers will be absorbed as their wages
adjust flexibly to ensure full employment. In

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

practice,such flexibility may be imperfect. This
could dampen the decline in within-country
inequality.
Other sources of income. The scenario analysis
here focuses on shocks that affect labor income.
While labor income inequality may decline,
inequality in other sources of income may grow.
This could, for example, be caused by slow growth
in investment, the scarcity of which would thenraise its returns, or job-replacing technologicalchange (Acemoglu and Restrepo 2016).
Trade. The pattern of growth and the structure ofdemand can affect growth, inequality, and poverty(Loayza and Raddatz 2010; Messina and Silva2017). Tradable and non-tradable sectors can havedifferent skill demands, and wage dispersions can
exist across workers of similar skills depending on
their sectors of employment. For wage differentials
across sectors that go beyond the broad categories
of skilled and unskilled labor and between urban
and rural unskilled labor in the analysis, therelative growth in each sector will also affect theskill premium and labor incomes, especially overlong periods.
Technological change. The nature of technicalchange will likely affect different groups ofcountries in different ways. Technological changethat is biased toward skilled workers can mitigate
or offset the distributional benefits of rising
educational attainment, especially in advanced
economies. It partly accounts for the rising college
premium in the United States despite a rapid increasein the relative number of skilled workers in the 60
years after 1939 (Acemoglu 2009 and 1998). In
contrast, in Latin America and the Caribbean andother developing countries, the growing number ofskilled workers has been accompanied by falling
education and skill-wage premia after 2000s (Cruzand Milet forthcoming; De la Torre et al. 2015;
Lopez-Calva and Lustig 2010). Also, the world isundergoing a significant technological transformation characterized by the adoption of cyberphysical systems such as robotics, 3D printing,and machine learning (Cirera et al. 2017;
Hallward-Driemeier and Nayar 2017). The paceof diffusion of these new technologies globally isan additional source of uncertainty, as they could

SPECIAL FOCUS 2

have
direct implications on income distributionacross and within countries. Yet, the evidence isstill weak that automation and trade also polarize
labor markets in developing countries (Maloneyand Molina 2016).
Alternative parameter values. The distributional
benefits of education can also be mitigated bygreater substitutability of skilled labor for capitalor for unskilled labor (de la Granville and Solow
2009). The scenario analysis above assumes thatskilled labor and capital are substitutable (througha constant elasticity of substitution or CES
function) for each other and, together, aresubstitutable with unskilled labor. In contrast,
skilled and unskilled labor could be substitutablefor each other and, together, they could beindirectly substitutable with capital. The latter
would dampen the decline in skill premia andraise global inequality compared to the educationwave scenario but would still improve inequality
compared with the no-wave scenario.

Conclusions
The next big wave of change in the global labormarket, the rising share of educated workers in
EMDEs, will likely lift global potential growth(Chapter 3) and be accompanied by a further decreasein global income inequality. This decline will be
driven by a reduction in inequality between countries,
which will largely be lowered by the convergence of
EMDE per capita incomes with advanced-economy
levels as productivity gaps close. At the global level,
the relative importance of overall within-country
inequality would steadily rise. Even so, the education
wave would decrease country-specific inequality inmost instances. The population-weighted average ofthe Gini difference between education-wave and noeducation-wave scenarios would decline for all regions
among EMDEs but not for AEs as a group.
Nonetheless, several caveats exist. Factors such as
biased technological change, the global diffusion of
new technologies, and changes in the substitutability
between factors of production may alter the results.
Over the next two decades, policies that raise current
attainment rates and learning outcomes in education
could further reduce inequality for two reasons. First,

225

226

SPECIAL FOCUS 2a sizeable pool of students will eventually translate
into a larger number of skilled workers. That,
combined with the large size and growing pool ofyounger cohorts relative to the older ones, would
amplify the effects estimated above. Second, amodest productivity increase through better
educational attainment or learning outcomes
could further reduce country-specific inequality.
Improving learning outcomes in education is apolicy challenge as discussed in the 2018 World
Development Report (World Bank 2017). This will
require systemic changes that make learning anoverriding priority, supported by diagnostics,
reforms that make schools work for learners,
motivated teachers, and the removal of politicaland technical barriers that hinder a focus onlearning.

ANNEX SF2.1 Methodology,
data, and measures ofinequality5
Methodology. To examine how education
demographics will shape future global labormarket and inequality, the analysis combines theWorld Bank’s global microsimulation model
Global Income Distribution Dynamics (GIDD) andthe global computable general equilibrium (CGE)model LINKAGE (Bourguignon and Bussolo
2013; van der Mensbrugghe 2013). Both models
employ labor data that uses a consistent definitionof skills based on the level of education as well as
corresponding wages and skill premia asconstructed from extensive household surveys.
Ensuring such consistency is key for estimating thetransmission of labor income shocks, in line witheducation demographics, into the distribution ofhousehold income.6 By doing so, the analysis
5 This annex summarizes the methodology in Ahmed et al. (2017)that underpins the results of the forward-looking analysis.
6 The GIDD microsimulation draws on per capital householdincome, which includes labor and non-labor income, to estimate
global inequality. The GIDD transmits three key shocks derived fromscenarios conducted in the LINKAGE model to household income:1) Changes in per capita growth for each country; 2) Changes inwage skill premia, defined as the ratio between the average wage ofskilled and of unskilled workers; 3) Changes in wage due to labormobility across sectors. In addition, the GIDD updates thehousehold survey data for the end year of the simulation, 2030.
Further details on GIDD methodology are provided by Bussolo,
Hoyos, and Medvedev (2010) and Ahmed et. al. (2017).

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

capturesconsistently the full distributional
change—between and within countries—due todemographic trends.
In particular, LINKAGE is a multi-sectoral, multicountry and multi-agent dynamic recursive CGE
model that is consistent with neo-classical growththeory. Aggregate growth depends on changes in
the labor force, the capital stock, and total factor
productivity. The economic impact ofdemographic change must, therefore, occur
through one of these channels, and the key growth
drivers sensitive to demographics are the labor
force and the capital stock. As a simulation is
implemented over time, the skilled and unskilledlabor forces for a given country are defined
following educational attainment rates andpipeline effects of schooling. At the same time, themodel keeps track of the young (less than 15 yearsof age), working age (15-64 years of age), and aged
(over 64 years of age) populations, following thevalues of the medium fertility scenario of theUnited Nations (2015).
Using the economy-wide effects of education
demographics over time computed in LINKAGE,
the GIDD microsimulation framework generates
income distributions under the various scenarios.
GIDD draws on household level survey data formany countries to estimate income distributions
by country that account for demographics,
household characteristics (e.g., age, gender, andeducation of different members), sector of
employment, skill premia on wages, and income.
Using the simulated income and employment
under future scenarios from LINKAGE, andaccountingforthedemographic
shiftscharacterized in the United Nations (2015) andskill implications of the assumed educational
attainment rates, GIDD generates income
distributions by country that are consistent withboth the more ‘aggregated’ changes under the
CGE simulations and what is known abouthouseholds from survey data. In the simulation,
the GIDD methodology updates the household
survey data for the terminal year by reweighting
the population characterized by the base year
household surveys using non-parametric crossentropy methods but keeping it consistent with
the United Nations’ population projections.

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

The
analysis, therefore, focuses on forces of theeducational wave that shape future supply anddemand in the labor markets and their ensuing
effects on global income distribution. On the
supply side, it considers demographic shifts,
improvement in education achievements, andpolicies that increase access to education andenable inter-sectoral mobility. On the demandside, it accounts for technological change, sectoral
patterns of growth, and trade. It then draws theeffects of these forces on global inequality by 2030,
which is the target year of the Sustainable
Development Goals (SDGs) as well as the WorldBank’s goals of ending extreme poverty andboosting shared prosperity. Because it usually takes
longer than 15 years for the stock of skilledworkers to show significant improvement from the
new inflow of younger and more educated workers
reaching the labor market, the time horizon to2030 will present only a partial effect of theeducation wave, hence a very conservative scenario.
Data. The methodology combines a large data set
from three sources. First, the population
projections come from United Nations (UN2015). Second, harmonized household surveys formany countries are employed in the GIDD
database, which covers 10.5 million individuals in
127 countries that constitute 83 percent of global
GDP and 86 percent of the global population.
Third, data in LINKAGE comes from the uniform
social accounting matrices of the Global Trade
Analysis Project, which encompasses 129 regions/countries and 57 commodities that are linked bybilateral trade and other external flows (GTAP2015).
To achieve consistency with the GIDD, LINKAGE
is modified to adopt the former’s skilled-unskilledlabor definition, whereby a skilled worker isanybody with more than nine years of education,
and an unskilled worker is anybody with less thannine years of education. This redefinition
necessitates an adjustment of the GTAP data on
value added by labor type in production, such thatthe number of workers of a given skill type in agiven sector is consistent in the 2011 benchmark
year across the two modeling frameworks.
Measures of inequality. Two measures ofinequality are used in the analysis—the Gini

SPECIAL FOCUS 2

coefficientand the log mean deviation (Theil-Lindex or general entropy measure GE(0)). The
Gini (1913) coefficient is an intuitive measure ofstatistical dispersion that represents the income orwealth distribution of a nation's residents and is
the most widely used measure of inequality. A highGini coefficient denotes great inequality; it has an
upper bound of one for perfect inequality and alower bound of zero for perfect equality. However,the Gini does not allow a decomposition into a
between-country and within-country component
since it is not additive across sub-groups.
In contrast, the log mean deviation, or Theil index
as proposed by Theil (1967), allows adecomposition into between-country and withincountry inequality (Bourguignon 1979). The
measure is equal to zero when everyone has thesame income and takes on larger positive values asincomes become more unequal.
To measure inequality by either measure, every
household observation of the 10.5 million
individuals in the database is utilized. Moreover,each household is assigned its proper weight
relative to the country’s total population so thatthe resulting frequency distribution is reflective of
the entire country. When the frequency
distributions of all countries are added up, theresulting aggregates will also be reflective of theregional and global totals. The global and regional
collections will entail reranking. That is, thebottom household may belong to Niger, and thenext one may belong to another country like
Eritrea, etc. Finally, the inequality measures use
household consumption wherever available andincome when consumption expenditure is notavailable (e.g. in many LAC economies).

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229

STATISTICAL
APPENDIX

Real GDP growth233

STATISTICAL APPENDIXGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

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236

STATISTICAL APPENDIXGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Real GDP growth (continued)$QQXDOHVWLPDWHVDQGIRUHFDVWV      
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Sources: World Bank and Haver Analytics.
Notes: e = estimate; f = forecast.
1. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights.
2. Year-over-year quarterly growth of not-seasonally-adjusted real GDP, except for Ecuador, Tunisia, and the United States, where only seasonally-adjusted data are available. Data for
Bosnia and Herzegovina are from the production approach.
Year-over-year quarterly growth in the United Kingdom is calculated using seasonally-adjusted real GDP.
Regional averages are calculated based on data from following countries.
East Asia and Pacific: China, Indonesia, Malaysia, Mongolia, Philippines, Thailand, and Vietnam.
Europe and Central Asia: Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Georgia, Hungary, Kazakhstan, the former Yugoslav Republic of Macedonia, Poland, Romania,
Russia, Serbia, Turkey, and Ukraine.
Latin America and the Caribbean: Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Guyana, Honduras, Jamaica, Mexico,
Nicaragua, Paraguay, Peru, and Uruguay.
Middle East and North Africa: Bahrain, the Arab Republic of Egypt, the Islamic Republic of Iran, Jordan, Qatar, Saudi Arabia, and Tunisia.
South Asia: India and Sri Lanka.
Sub-Saharan Africa: Botswana, Ghana, Kenya, Nigeria, South Africa, Tanzania, Uganda, and Zambia.
3. Annual GDP is on fiscal year basis, as per reporting practice in the country.
4. GDP data for Pakistan are based on factor cost. For Bangladesh, Nepal, and Pakistan, the column labeled 2017 refers to FY2016/17. For Bhutan and India, the column labeled 2016refers to FY2016/17.
For additional information, please see www.worldbank.org/gep.

STATISTICAL APPENDIXGLOBAL ECONOMIC PROSPECTS | JANUARY 2018

Data and Forecast Conventions
The macroeconomic forecasts presented in thisreport are prepared by staff of the Prospects
Group of the Development Economics VicePresidency, in coordination with staff from theMacroeconomics, Trade, and Investment Global
Practice and from regional and country offices,and with input from regional Chief Economist
offices. They are the result of an iterative processthat incorporates data, macroeconometric models,and judgment.
Data. Data used to prepare country forecasts
come from a variety of sources. National Income
Accounts (NIA), Balance of Payments (BOP), andfiscal data are from Haver Analytics; the World
Development Indicators by the World Bank; theWorld Economic Outlook, Balance of Payments
Statistics, and International Financial Statistics by
the International Monetary Fund. Population
data and forecasts are from the United Nations
World Population Prospects. Country- andlending-group classifications are from the World
Bank. DECPG databases include commodity
prices, data on previous forecast vintages, and inhouse country classifications. Other internal
databases include high-frequency indicators suchas industrial production, consumer price indexes,
house prices, exchange rates, exports, imports, andstock market indexes, based on data from
Bloomberg, Haver Analytics, OECD Analytical

House Prices Indicators, IMF Balance of Payments Statistics, and IMF International Financial
Statistics.
Aggregations. Aggregate growth for the world andall sub-groups of countries (such as regions andincome groups) is calculated as GDP-weighted
average (at 2010 prices) of country-specificgrowth rates. Income groups are defined as in theWorld Bank’s classification of country groups.
Forecast Process. The process starts with initialassumptions about advanced-economy growthand commodity price forecasts. These are used asconditioning assumptions for the first set ofgrowth forecasts for EMDEs, which are produced
using macroeconometric models, accounting
frameworks to ensure national account identities
and global consistency, estimates of spillovers
from major economies, and high-frequency
indicators. These forecasts are then evaluated toensure consistency of treatment across similar
EMDEs. This is followed by extensive discussions
with World Bank country teams, who conduct
continuous macroeconomic monitoring anddialogue with country authorities. Throughout theforecasting process, staff use macroeconometricmodels that allow the combination of judgement
and consistency with model-based insights.

237

GLOBAL ECONOMIC PROSPECTS | JANUARY 2018

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SELECTED TOPICS

241

Global Economic Prospects: Selected Topics, 2015-18

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*OREDO0RQWKO\QHZVOHWWHU*OREDO:HHNO\QHZVOHWWHUECO-AUDIT
Environmental Benefits Statement
The World Bank Group is committed to reducing its environmental
footprint. In support of this commitment, we leverage electronic
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More information about the Bank’s environmental philosophy can befound at http://www.worldbank.org/corporateresponsibility.
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