A World Bank Group
Flagship Report

JUNE 2018

GlobalEconomic
Prospects

The Turning of the Tide?

JUNE 2018© 2018 International Bank for Reconstruction and Development / The World Bank
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ISSN: 1014-8906
ISBN (paper): 978-1-4648-1257-6
ISBN (electronic): 978-1-4648-1324-5
DOI: 10.1596/978-1-4648-1257-6
Cover design: Bill Pragluski (Critical Stages).
The cutoff date for the data used in this report was May 25, 2018.

In memory of Phillip Jeremy Hay, 1955-2018

Summary of Contents
Chapter 1

The Turning of the Tide? ........................................................................ 1

Special Focus 1

The Role of Major Emerging Markets in Global Commodity Demand ......59

Special Focus 2

Corporate Debt: Financial Stability and Investment Implications .............91

Chapter 2

Regional Outlooks ...............................................................................111

Boxes

Box 1.1

Long-term growth prospects: Downgraded no more? .................. 8

Box 1.2

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

Box 1.3

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

Box SF1.1 The role of the EM7 in commodity production.........................64
Box SF1.2 Commodity consumption: Implications of government policies..74

VTable of Contents
Foreword..................................................................................................................................xiii
Acknowledgments ..................................................................................................................... xv
Executive Summary.................................................................................................................. xvii
Abbreviations ........................................................................................................................... xix
Chapter 1

Global Outlook: The Turning of the Tide? ............................................................1
Summary ............................................................................................................3
Major economies: Recent developments and outlook................................................7
United States ................................................................................................ 7
Euro Area ....................................................................................................15
Japan ..........................................................................................................15
China..........................................................................................................16
Global trends ..................................................................................................... 16
Global trade ................................................................................................ 17
Financial markets ........................................................................................ 18
Commodities ............................................................................................. 19
Emerging and developing economies: Recent developments and outlook ................. 21
Recent developments ................................................................................... 21
EMDE outlook ........................................................................................... 28
Risks to the outlook........................................................................................... 32
Disorderly tightening of ﬁnancing conditions ................................................. 33
Escalating trade protectionism ...................................................................... 35
Policy uncertainty and geopolitical developments ............................................ 36
A combination of global downside risks ......................................................... 37
Region-speciﬁc downside risks ...................................................................... 37
Stronger and longer-lasting cyclical recovery ................................................... 38
Policy challenges ............................................................................................... 39
Challenges in advanced economies ................................................................ 39
Challenges in emerging and developing economies .......................................... 41
References ......................................................................................................... 50
Box 1.1 Long-term growth prospects: Downgraded no more?....................................8
Box 1.2 Low-income countries: Recent developments and outlook .......................... 24
Box 1.3 Regional perspectives: Recent developments and outlook ........................... 30
VIISpecial Focus 1 The Role of Major Emerging Markets in Global Commodity Demand ................. 59
Introduction ..................................................................................................... 61
The role of the EM7 in commodity consumption ................................................. 63
Drivers of commodities consumption .................................................................. 66
Prospects for commodities demand...................................................................... 72
Policy implications............................................................................................. 76
Conclusion ....................................................................................................... 77
Annex SF1.1 Modeling income elasticities ............................................................ 78
References......................................................................................................... 87

Special Focus 2 Corporate Debt: Financial Stability and Investment Implications ..........................91
Introduction ......................................................................................................93
Corporate debt landscape in EMDEs ....................................................................94
Corporate debt and financial stability ...................................................................96
Corporate debt and economic growth ...................................................................98
Policy implications ........................................................................................... 102
Annex SF2.1 Data and methodology: Firm-level analysis ...................................... 105
References ....................................................................................................... 107

Chapter 2

Regional Outlooks .......................................................................................... 111
East Asia and Pacific ....................................................................................... 113
Recent developments......................................................................................113
Outlook........................................................................................................115
Risks ........................................................................................................... 116
Europe and Central Asia ................................................................................. 119
Recent developments..................................................................................... 119
Outlook....................................................................................................... 121
Risks .......................................................................................................... 122
Latin America and the Caribbean ..................................................................... 125
Recent developments..................................................................................... 125
Outlook....................................................................................................... 126
Risks ........................................................................................................... 128
Middle East and North Africa .......................................................................... 131
Recent developments..................................................................................... 131
Outlook....................................................................................................... 132
Risks ........................................................................................................... 133

VIII

South Asia .......................................................................................................137
Recent developments ..................................................................................... 137
Outlook ....................................................................................................... 138
Risks ............................................................................................................ 139
Sub-Saharan Africa ..........................................................................................141
Recent developments ..................................................................................... 141
Outlook ....................................................................................................... 143
Risks ............................................................................................................ 144
References..................................................................................................... 147
Statistical Appendix..................................................................................................................149
Selected Topics ........................................................................................................................157
Figures

1.1

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

1.2

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

1.3

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

1.1.1

Growth forecasts: Global, groups and aggregates ....................................... 10

1.1.2

Growth forecasts in major economies and in comparison with actualand potential growth.............................................................................. 11

1.1.3

Growth forecasts and change in global GDP ............................................. 14

1.4

United States ........................................................................................ 15

1.5Euro Area ............................................................................................. 16

1.6

Japan ................................................................................................... 16

1.7

China................................................................................................... 17

1.8

Global trade.......................................................................................... 18

1.9

Global finance....................................................................................... 19

1.10

Commodity markets ........ …………………………………………………..20

1.11

Activity in EMDEs ................................................................................ 22

1.12

Activity in EMDE commodity exporters .................................................. 23

1.2.1

Recent developments in low-income countries .......................................... 25

1.2.2

Outlook ............................................................................................... 26

1.13

Activity in EMDE commodity importers, excluding China ........................ 28

1.14

EMDE growth prospects ........................................................................ 29

1.3.1

Regional growth .................................................................................... 30

1.15

Per capita growth and poverty in EMDEs ................................................ 32

1.16

Risks: Tilted to the downside .................................................................. 33

1.17

Downside risks: Financial stress............................................................... 34
IX

1.18

Downside risks: Trade protectionism.................................................................. 35

1.19

Downside risks: Policy and geopolitical uncertainty ............................................. 37

1.20

Downside risks: History repeating itself? ............................................................. 38

1.21

Upside risks: Longer-lasting upturn ................................................................... 39

1.22

Monetary and fiscal policies in advanced economies ............................................. 40

1.23

Structural policy in advanced economies ............................................................. 41

1.24

Policy challenges in China................................................................................. 42

1.25

EMDE monetary policy.................................................................................... 43

1.26

EMDE fiscal policy .......................................................................................... 44

1.27

EMDE structural policy.................................................................................... 46

SF1.1 Developments in commodity markets ................................................................ 61
SF1.2 Vulnerabilities to oil price fluctuations................................................................ 62
SF1.3

EM7 in the global economy ............................................................................. 63

SF1.1.1 EM7 in commodity production ......................................................................... 65
SF1.4 EM7 in commodity markets.............................................................................. 66
SF1.5 Consumption of industrial commodities and income ........................................... 67
SF1.6 Food consumption and income ......................................................................... 68
SF1.7

Estimated commodity consumption growth ....................................................... 71

SF1.8 Commodity consumption scenarios ................................................................... 73
SF1.2.1 Developments in commodity markets................................................................. 75
SF2.1 Corporate debt in EMDEs: General trends ........................................................ 95
SF2.2 Corporate debt in EMDEs: Composition ........................................................... 96
SF2.3 Corporate debt in China .................................................................................. 97
SF2.4 Corporate debt in EMDEs: Macroeconomic vulnerabilities .................................. 98
SF2.5 Corporate debt riskiness in EMDEs .................................................................. 99
SF2.6 Correlates of corporate debt and private investment growth in EMDEs ................100
SF2.7 Linkage between debt overhang and investment across firms ...............................101
SF2.8 Policy implications .........................................................................................103

X

2.1.1

EAP: Recent developments...............................................................................114

2.1.2

China ............................................................................................................115

2.1.3

EAP: Outlook and risks ...................................................................................116

2.2.1

ECA: Recent developments ..............................................................................120

2.2.2

ECA: Outlook and risks.................................................................................. 121

2.3.1

LAC: Recent developments ............................................................................. 126

2.3.2

LAC: Outlook and risks .................................................................................. 127

2.4.1

MENA: Recent developments ......................................................................... 132

2.4.2

MENA: Outlook and risks .............................................................................. 133

Tables

2.5.1

SAR: Recent developments .............................................................................. 138

2.5.2

SAR: Outlook and risks ................................................................................... 139

2.6.1

SSA: Economic activity ................................................................................... 142

2.6.2

SSA: Outlook and risks ................................................................................... 143

1.1

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

1.2.1

Low-income country forecasts ............................................................................27

1.2

List of emerging market and developing economies .............................................49

SF1.1

Estimation results .............................................................................................70

Annex SF1.1A Top 10 commodity consumers, 2016........................................................80
Annex SF1.1B Top 10 commodity consumers, 2016 .......................................................80
Annex SF1.2A Top 10 commodity producers, 2016 .........................................................81
Annex SF1.2B Top 10 commodity producers, 2016 ........................................................81
Annex SF1.3 Literature review of long-run income elasticities of demand for commodities ..82
Annex SF1.4 Economy samples, by commodity modeled ................................................83
Annex SF1.5 Estimation results for pooled mean group estimation ...................................84
Annex SF1.6 Estimation results under generalized method of moments .............................85
Annex SF1.7 Estimation results including trend .............................................................86
SF2.1 Debt overhang and investment: Baseline specification ......................................... 104
2.1.1

East Asia and Pacific forecast summary .............................................................. 117

2.1.2

East Asia and Pacific country forecasts............................................................... 117

2.2.1

Europe and Central Asia forecast summary ........................................................ 123

2.2.2

Europe and Central Asia country forecasts ......................................................... 124

2.3.1

Latin America and the Caribbean forecast summary............................................ 129

2.3.2

Latin America and the Caribbean country forecasts............................................. 130

2.4.1

Middle East and North Africa forecast summary ................................................ 135

2.4.2

Middle East and North Africa economy forecasts ............................................... 136

2.5.1

South Asia forecast summary ............................................................................ 140

2.5.2South Asia country forecasts............................................................................. 140

2.6.1

Sub-Saharan Africa forecast summary................................................................ 145

2.6.2

Sub-Saharan Africa country forecasts................................................................. 146

XI

Foreword
The current state of the global economy resembles
that of a sailor whose boat was caught on a
sandbar but is now freed by the rising tide. The
sailor is naturally relieved to be able to set
sail. But this relief must be tempered by theurgency to pilot toward deeper seas before thereceding waters beach the ship again.
As the June 2018 Global Economic Prospects
report documents, the global economy seems tobe leaving the legacy of the global ﬁnancial crisisof the past decade behind. About half the world’s
countries are experiencing an increase in
growth. This synchronized recovery may lead toeven faster growth in the near term, as stronger
growth in, say, China or the United States spills
over to other parts of the world. All the consensus
forecasts for 2018 and 2019 reﬂect optimism.
And this growth is occurring for the rightreasons—investment and trade growth, which
had been declining, have risen. Furthermore, in
the United States, Europe and Japan,
unemployment has declined, while inﬂation has
not picked up much, suggesting thatpolicymakers may have found that “sweet spot”
in the tradeoﬀ between unemployment andinﬂation. The conﬁdence indicators also remain
elevated.
But, as the report points out, the medium-term
prospects tell a diﬀerent story. Protectionist
threats cast a dark cloud over future growth. If
these threats lead to trade wars, the consequences
could be devastating. Even if they do not,uncertainty about economic policy dampens
investor sentiment. Secondly, a credit event in a
major emerging market or a sudden tightening ofmonetary policy in the United States leading to a
spike in interest rates could roil ﬁnancial markets,
causing a slowdown especially in highly indebted
countries. From the 1975 oil crisis, to the Latin
American debt crisis of the 1980s, to the Asianﬁnancial crisis of the 1990s, to the 2007-09
global ﬁnancial crisis, there has been a ﬁnancial
market crisis every ten years or so. It is now ten
years since the last crisis.
Moreover, as the analytical sections of the reportshow, increasing corporate debt in someemerging market economies has left themespecially vulnerable to interest rate and exchange
rate shocks. And the prospects for commodity
exporters will be limited as the major commodity-importing countries, especially China, shift theirdemand away from oil and other commodities.
These ominous signs reinforce the ﬁnding fromthe January 2018 edition of the Global Economic
Prospects report, namely, that while current
growth appears robust, potential growth will belower. Underlying factors such as demographics(declining labor supply in many, large countries)
and the legacy of low investment growth in thepast contribute to this limited potential growth.
The risks described above mean that actual
growth may be even lower.
The implication is that policy and institutional
reforms that build human capital (to make labor
more productive) and improve the businessclimate (to increase investment) are needed now
more than ever. The still robust pace of growthprovides political space to implement thesereforms. Now is the time to act.
Shantayanan Devarajan
Senior Director, Development Economics
Acting Chief Economist
The World Bank GroupXIII

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 andMarc Stocker, with contributions from Patrick Kirby,
Ekaterine Vashakmadze, and Collette M. Wheeler.
Additional inputs were provided by John Baffes, Alain
Kabundi, Gerard Kambou, Eung Ju Kim, Csilla
Lakatos, Peter Nagle, and Dana Vorisek.
Chapter 2 (Regional Outlooks) was supervised by
Carlos Arteta and Franziska Ohnsorge, with feedback
from Marc Stocker and Patrick Kirby. The authors
were Ekaterine Vashakmadze (East Asia and Pacific),
Yoki Okawa (Europe and Central Asia), Dana Vorisek(Latin America and the Caribbean), Lei Sandy Ye(Middle East and North Africa), Temel Taskin (SouthAsia), and Gerard Kambou (Sub-Saharan Africa).
The first Special Focus, The Role of Major Emerging
Markets in Global Commodity Demand, wasprepared by John Baffes, Alain Kabundi, Peter Nagle,
and Franziska Ohnsorge.
The second Special Focus, Corporate Debt: Financial
Stability and Investment Implications, was preparedby Eduardo Borensztein and Lei Sandy Ye.
The boxes in Chapter 1 were prepared by Carlos
Arteta, Gerard Kambou, Ayhan Kose, Franziska
Ohnsorge and Naotaka Sugawara, with contributions
from Yoki Okawa, Temel Taskin, Ekaterine
Vashakmadze, Dana Vorisek, and Lei Sandy Ye.
Research assistance was provided by Miyoko Asai, Anh
Mai Bui, Ishita Dugar, Xinghao Gong, Brent
Harrison, Julia Roseman, Shijie Shi, and Jinxin Wu.
Modeling and data work were provided by Rajesh
Kumar Danda, Julia Roseman, and Jinxin Wu.
The online publication was produced by Graeme
Littler and Mikael Reventar. Mark Felsenthal managed
media relations and dissemination. Mark Felsenthal
and Graeme Littler provided editorial support, with
contributions from Adriana Maximiliano.

The print publication was produced by Maria Hazel
Macadangdang, Adriana Maximiliano, Quinn Sutton,
and Rosalie Singson Dinglasan, in collaboration with
Luiz H. Almeida, Andrew Charles Berghauser, Adam
Broadfoot, Aziz Gökdemir, Michael Harrup, andJewel McFadden.
Many reviewers offered extensive advice andcomments. These included: Kishan Abeygunawardana,
Junaid Kamal Ahmad, Gilles Alfandari, Sara Alnashar,
Gallina Andronova Vincelette, Paloma Anos Casero,
Rabah Arezki, Dilek Aykut, Rajni Bajpai, Luca
Bandiera, Daniel Barco, Kevin Barnes, Rafael Barroso,
Robert Carl Michael Beyer, Enrique Blanco Armas,
Fernando Blanco, Monika Blaszkiewicz-Schwartzman,
Moussa Blimpo, Florian Blum, Jane Bogoev, Elena
Bondarenko, Cesar Calderon, Kevin Carey, Michael
Carson, Rodrigo Chaves, Derek Chen, Zivanemoyo
Chinzara, Ajai Chopra, Ibrahim Chowdhury, KevinChua, Punam Chuhan-Pole, Natalia Cieslik, Kevin
Clinton, Fabiano Colbano, Louise Cord, Tito
Cordella, Stefano Curto, Barbara Cunha, Simon
Davies, Annette De Kleine Feige, Agim Demukaj,
Allen Dennis, Tatiana Didier, Viet Tuan Dinh,
Ousmane Dione, Makhtar Diop, Ndiame Diop,
Anton Dobronogov, Mariam Dolidze, Jozef Draaisma,
Bakyt Dubashov, Sebastian Eckardt, Kim Alan
Edwards, Khalid El Massnaoui, Olga Emelyanova,
Wilfried Engelke, David Evans, Jorge Familiar
Calderon, Marianne Fay, Erik Feyen, Cornelius
Fleischhaker, Melissa Fossberg, Manuela Francisco,
Diego Friedheim, Nicole Frost, Adnan Ashraf
Ghumman, Frederico Gil Sander, Fernando Giuliano,
Maria De los Angeles Cuqui Gonzalez Miranda,
Poonam Gupta, Gohar Gyulumyan, Graham Hacche,
Kiryl Haiduk, Fiseha Haile Gebregziabher, Michael
Hamaide, Birgit Hansl, Marek Hanusch, Wissam
Harake, Zeina Hasra, Faya Hayati, Johannes
Herderschee, Patrick Hettinger, Sandra Hlivnjak, Bert
Hofman, Sahar Sajjad Hussain, Zahid Hussain, Elena
Ianchovichina, Stella Ilieva, Fernando Im, Amina
Iraqi, Yoichiro Ishihara, Ergys Islamaj, Ivailo V.
Izvorski, Carlos Felipe Jaramillo, Gloria Aitalohi

XVJoseph-Raji, Frederick Joutz, Priscilla FlanessKandoole, Soukeyna Kane, Atsushi Kawamoto, Majid
Kazemi, Vera Kehayova, Michel Kerf, Tehmina S.
Khan, Ewa Korczyc, Sibel Kulaksiz, Chandana
Kularatne, Marko Kwaramba, Jean Pierre Lacombe,
Sumir Lal, Luc Lecuit, Daniel Lederman, Yue Man
Lee, Tenzin Lhaden, John Litwack, Julio Ricardo
Loayza, Julie Saty Lohi, Rohan Longmore, Gladys
Lopez-Acevedo, José Roberto López-Cálix, PrakashLoungani, Sanja Madzarevic-Sujster, Shireen Mahdi,
Wael Mansour, Will Martin, Ashwaq Natiq Maseeh,
Andrew D. Mason, Warwick McKibbin, Steisianasari
Mileiva, Elitza Mileva, Deepak K. Mishra, Lalita
Moorty, Luis Francisco Morano Germani, Lili
Mottaghi, Sudip Mozumder, Arvind Nair, Evgenij
Najdov, François Nankobogo, Nur Nasser Eddin, Jean
-Pascal Nganou, Ha Nguyen, Francesca de Nicola,
Akihiko Nishio, Antonio Nucifora, Eduardo
Olaberria, Harun Onder, Kamer K. Ozdemir, John
Panzer, Catalin Pauna, Samuel Jaime Pienknagura,
Emmanuel Pinto Moreira, Ruslan Pionkivsky, Rong

XVI

Qian, Habib Rab, Martin Rama, Nadir Ramazanov,Richard Record, Alief Aulia Rezza, Daniel RieraCrichton, David Robinson, Donato de Rosa, David
Rosenblatt, Irina Rostovtseva, Miguel Eduardo
Sanchez Martin, Susana Sanchez, Apurva Sanghi, Ilyas
Sarsenov, Cristina Savescu, Marc Schiffbauer, Philip
Schuler, Ethel Sennhauser, Claudia Paz Sepúlveda,
Lazar Sestovic, Smriti Seth, Sudhir Shetty, Alex
Sienaert, Emilia Skrok, Karlis Smits, Martin Stuermer,
Abdoulaye Sy, Fulbert Tchana Tchana, Shakira Binti
Teh Sharifuddin, Hans Timmer, Emilija Timmis,
Christopher Towe, Axel van Trotsenburg, Eskender
Trushin, Robert Utz, Ralph Van Doorn, Sona Varma,
Carlos Végh, Julio Velasco, Ekaterina Vostroknutova,
Guillermo Javier Vuletin, Sashana Whyte, Pinar Yasar,
Hoda Youssef, Paolo Zacchia, Albert Zeufack, Luan
Zhao, Yongmei Zhou, and Bakhrom Ziyaev.
Regional projections and write-ups were produced incoordination with country teams, country directors,
and the offices of the regional chief economists.

Executive Summary
Global growth has eased but remains robust, although with downside risks. The possibility of financial market
stress, escalating trade protectionism and heightened geopolitical tensions continue to cloud the outlook.
Financial market stress could arise as a result of escalating investor concerns about the creditworthiness of someemerging market and developing economies or as a byproduct of faster-than-expected normalization ofmonetary policy in advanced economies. Countries with elevated corporate debt, wide current account or fiscal
deficits, or weak growth prospects would be vulnerable to jumps in global financing costs. In commodityexporting economies, in particular, the expected slowdown in commodity demand growth from major emerging
markets weighs on long-term growth outcomes.
Global Outlook. Global growth has eased but
remains robust and is projected to reach 3.1
percent in 2018. It is expected to edge down overthe next two years as global slack dissipates, tradeand investment moderate, and financing
conditions tighten. Growth in advanced
economies is forecast to decelerate towardpotential rates as monetary policy is normalized
and the effects of U.S. fiscal stimulus wane. In
emerging market and developing economies(EMDEs), growth in commodity importers willremain strong, while the rebound in commodity
exporters is projected to mature over the next two
years. For the first time since 2010, the long-term(10-year-ahead) consensus forecast for global
growth appears to have stabilized. Although thisdevelopment could signal that the legacies of the
global financial crisis are fading, past experience
cautions that long-term forecasts are often overly
optimistic. While well below levels expected adecade ago, these forecasts also remain above
potential growth estimates. Moreover, risks to theoutlook are tilted to the downside. They include
disorderly financial market movements, escalating
trade protectionism, and heightened geopoliticaltensions. EMDE policymakers should rebuild
monetary and fiscal policy buffers and be preparedfor rising global interest rates and possible
episodes of financial market turbulence. In thelonger run, adverse structural forces continue toovershadow long-term growth prospects implyingthat EMDEs need to boost potential growth bypromoting competitiveness, adaptability totechnological change, and trade openness. These
steps will help mitigate an expected growth

slowdown over the next decade, especially if longterm growth forecasts fall—once again—short of
expectations.
Regional Perspectives. A cyclical recovery isunderway in most EMDE regions that host a
substantial number of commodity exporters. Overthe next two years, the upturn in these regions is
expected to mature, as commodity prices plateau.
Robust economic activity in EMDE regions withlarge numbers of commodity importers is forecast
to continue. However, risks to the growth outlook
continue to tilt to the downside in many regions.
This edition of Global Economic Prospects includes
sections on the role of the largest emerging
markets in global commodity markets and on theimplications of high corporate debt for financial
stability and investment.
The Role of Major Emerging Markets in Global
Commodity Demand. Rapid growth among the
major emerging markets over the past 20 years hasboosted global demand for commodities. The
seven largest emerging markets (EM7) accounted
for almost all of the increase in global
consumption of metals and two-thirds of theincrease in energy consumption over this period.
As these economies mature and shift towards lesscommodity-intensive activities, their demand formost commodities may level off. While global
energy consumption growth may remain broadly
steady, global metals and foods demand growth
could slow by one-third over the next decade.
This would dampen global commodity prices. For
emerging market and developing economies that

XVIIdepend on raw materials for government andexport revenues, these prospects reinforce theneed for economic diversification and thestrengthening of policy frameworks.
Corporate Debt: Financial Stability andInvestment Implications. Average corporate debt
in emerging market and developing economies
has increased over the past decade, raisingconcerns about their financial stability andgrowth prospects. Debt service costs of EMDE

XVIII

firms are expected to rise as advanced economies
normalize monetary policy, and debt isincreasingly held by firms with riskier balance
sheets. Elevated debt may be associated with weak
investment growth, especially in large firms.
Countercyclical and macroprudential policies canaddress financial stability concerns that are raisedby these trends. Structural policies, including thestrengthening of bankruptcy regimes, areappropriate tools to address the investment
implications of sizeable corporate debt.

Abbreviations
AEadvanced economies

AfCFTA

African Continental Free Trade Area

ASEAN

Association of Southeast Asian Nations

bbl

barrelBRICS

Brazil, Russian Federation, India, China, and South Africa

CPTPP

Comprehensive and Progressive Agreement for Trans-Pacific Partnership

CVI

corporate vulnerability index

EAP

East Asia and PacificEBIT

earnings before interest and taxes

ECA

Europe and Central Asia

ECB

European Central BankEMBI

Emerging Markets Bond Index

EM7

Brazil, China, India, Indonesia, Mexico, Russian Federation, and Turkey

EMDEemerging market and developing economies

EPU

Economic Policy Uncertainty

EU

European Union

FDI

foreign direct investment

FOMC

Federal Open Market Committee

FY

fiscal year

G7

Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States

GCC

Gulf Cooperation Council

GDPgross domestic product

GEP

Global Economic Prospects

GNFS

goods and nonfactor services

GTAP

Global Trade Analysis Project

ICT

information and communication technology

IEA

International Energy Agency

IMF

International Monetary Fund

LAC

Latin America and Caribbean

LIC

low-income country

MNA

Middle East and North Africa

NAFTA

North American Free Trade Agreement

NBER

National Bureau of Economic Research

NPLs

nonperforming loans

OECD

Organisation for Economic Co-operation and Development

OPEC

Organization of the Petroleum Exporting Countries

PMI

purchasing manager’s index

XIX

XX

PPP

purchasing power parity

ppt

percentage points

RHS

right-hand side (in figures)

SAR

South Asia Region

SOEstate-owned enterprise

SSA

Sub-Saharan Africa

toetons of oil equivalent

TPP

Trans-Pacific Partnership

UNCTAD

United Nations Conference on Trade and Development

USDA

United States Department of Agriculture

WTO

World Trade Organization

CHAPTER 1

GLOBAL OUTLOOKThe Turning of the Tide?

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

CHAPTER 1

Global growth has eased, but remains robust, and is projected to reach 3.1 percent in 2018. It is expected toedge down in the next two years to 2.9 percent by 2020, as global slack dissipates, trade and investment
moderate, and financing conditions tighten. Growth in advanced economies is predicted to decelerate towardpotential rates, as monetary policy normalizes and the effects of U.S. fiscal stimulus wane. In emerging market
and developing economies (EMDEs), growth in commodity importers will remain robust, while the rebound incommodity exporters is projected to mature over the next two years. Progress in per capita income growth will be
uneven, however, remaining particularly subdued in Sub-Saharan Africa. Risks to the outlook remain tilted tothe downside. They include disorderly financial market movements, escalating trade protectionism, heightened
policy uncertainty, and rising geopolitical tensions, all of which continue to cloud the outlook. EMDE
policymakers need to rebuild monetary and fiscal policy buffers and be prepared for rising global interest rates
and possible episodes of financial market turbulence. In the longer run, EMDEs need to tackle ongoing
structural challenges and boost potential growth by promoting competitiveness, adaptability to technologicalchange, and trade openness.

Summary
Global growth remains robust but has softened inrecent months, as manufacturing activity andtrade have shown signs of moderation (Figure1.1). The ongoing withdrawal of monetary policy
accommodation in advanced economies has led tosome tightening of global financing conditions, while oil prices are substantially higher thanpreviously expected. Global inflation is trendingup, but only gradually and from low levels.
In advanced economies, activity continues to growabove potential, notwithstanding some recent
moderation, while additional fiscal stimulus
measures are expected to provide a further lift tonear-term growth in the United States. Labor
markets have improved steadily. With output gaps
nearly or already closed, inflation expectations
have crept up and monetary policy is becoming
less expansionary. Inflation, however, remains
below central bank targets in many advanced
economies.
Among emerging market and developing
economies (EMDEs), the recovery in commodity
exporters has continued, as consumption andinvestment firm. The upturn in many energy

Note: This chapter was prepared by Carlos Arteta and Marc
Stocker, with contributions from Patrick Kirby, Ekaterine
Vashakmadze, and Collette M. Wheeler. Additional inputs were
provided by John Baﬀes, Alain Kabundi, Gerard Kambou, Eung Ju
Kim, Csilla Lakatos, Peter Nagle, and Dana Vorisek. Research
assistance was provided by Anh Mai Bui, Ishita Dugar, Xinghao
Gong, Brent Harrison, Julia Roseman, and Jinxin Wu.

exporters is still lagging that of exporters of othercommodities, reflecting ongoing adjustments tothe 2014-16 collapse in oil prices and production
cuts in key oil exporters. Across commodity
exporters, inflation is generally moderating as theimpact of past currency depreciations wanes.
Activity in commodity importers continues to berobust. Growth in China is gradually slowing, but
remains resilient, while constraints to growth are
dissipating in other large commodity importers—
notably India and Mexico, where investment isrecovering. Inflation remains broadly stable so far,despite higher commodity prices and limited
remaining slack.
Notwithstanding the ongoing global expansion,
only 45 percent of countries are expected toexperience a further acceleration of growth thisyear, down from 56 percent in 2017. Moreover,global activity is still lagging previous expansions
despite a decade-long recovery from the global
financial crisis. Accordingly, after reaching 3.1
percent in 2018, global growth is projected tomoderate in 2019-20, edging down to 2.9 percent
by the end of the forecast period. Global growth
projections are above estimates of potential,
suggesting that capacity constraints will become
more binding and inflation will continue to riseduring the forecast horizon.
Growth in advanced economies is expected todecelerate toward potential rates over the forecast
period, as monetary policy stimulus is pared
down, higher energy prices weigh on consumption, and the effect of U.S. fiscal expansion

3

4

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

TABLE 1.1 Real GDP1

Percentage point differencesfrom January 2018 projections(Percent change from previous year)
2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

2.8

2.4

3.1

3.1

3.0

2.9

0.0

0.0

0.0

Advanced economies
United States
Euro Area

2.3
2.9
2.1

1.7
1.5
1.8

2.3
2.3
2.4

2.2
2.7
2.1

2.0
2.5
1.7

1.7
2.0
1.5

0.0
0.2
0.0

0.1
0.3
0.0

0.0
0.0
0.0

Japan
Emerging market and developing economies(EMDEs)Commodity-exporting EMDEs

1.4

1.0

1.7

1.0

0.8

0.5

-0.3

0.0

0.0

3.7

3.7

4.3

4.5

4.7

4.7

0.0

0.0

0.0

0.5

0.8

1.8

2.5

3.0

3.0

-0.2

-0.1

-0.1

6.1

5.9

6.2

5.8

5.8

5.7

0.1

0.1

0.0

5.2

4.9

5.3

5.1

5.1

5.1

0.3

0.0

0.0

6.5

6.3

6.6

6.3

6.1

6.0

0.1

0.0

0.0

China

6.9

6.7

6.9

6.5

6.3

6.2

0.1

0.0

0.0

Indonesia

4.9

5.0

5.1

5.2

5.3

5.4

-0.1

0.0

0.1

Thailand

3.0

3.3

3.9

4.1

3.8

3.8

0.5

0.3

0.4

1.1

1.7

4.0

3.2

3.1

3.0

0.3

0.1

0.0

-2.5

-0.2

1.5

1.5

1.8

1.8

-0.2

0.0

0.0

6.1
3.8
-0.4

3.2
2.9
-1.5

7.4
4.6
0.8

4.5
4.2
1.7

4.0
3.7
2.3

4.0
3.5
2.5

1.0
0.2
-0.3

0.0
0.2
-0.3

0.0
0.4
-0.2

Brazil

-3.5

-3.5

1.0

2.4

2.5

2.4

0.4

0.2

-0.1

Mexico

3.3

2.9

2.0

2.3

2.5

2.7

0.2

-0.1

0.1

Argentina

2.7

-1.8

2.9

1.7

1.8

2.8

-1.3

-1.2

-0.4
0.0

World

Other EMDEs
Other EMDEs excluding China
East Asia and Pacific

Europe and Central Asia
RussiaTurkeyPolandLatin America and the Caribbean

Middle East and North Africa

2.8

5.0

1.6

3.0

3.3

3.2

0.0

0.1

Saudi Arabia

4.1

1.7

-0.7

1.8

2.1

2.3

0.6

0.0

0.1

Iran

-1.3

13.4

4.3

4.1

4.1

4.2

0.1

-0.2

-0.1

Egypt2

4.4

4.3

4.2

5.0

5.5

5.8

0.5

0.2

0.0

South Asia

7.1

7.5

6.6

6.9

7.1

7.2

0.0

-0.1

0.0

India3

8.2

7.1

6.7

7.3

7.5

7.5

0.0

0.0

0.0

Pakistan2

4.1

4.6

5.4

5.8

5.0

5.4

0.3

-0.8

-0.6

Bangladesh2

6.6

7.1

7.3

6.5

6.7

7.0

0.1

0.0

0.3

Sub-Saharan Africa

3.1

1.5

2.6

3.1

3.5

3.7

-0.1

0.0

0.1

Nigeria

2.7

-1.6

0.8

2.1

2.2

2.4

-0.4

-0.6

-0.4

South Africa

1.3

0.6

1.3

1.4

1.8

1.9

0.3

0.1

0.2

AngolaMemorandum items:
Real GDP1

3.0

0.0

1.2

1.7

2.2

2.4

0.1

0.7

0.9

High-income countries

2.3

1.7

2.2

2.2

2.0

1.8

0.0

0.1

0.0

Developing countries

3.7

3.8

4.6

4.7

4.8

4.8

0.0

0.0

-0.1

4.9

4.8

5.5

5.7

5.9

6.3

0.3

0.4

0.6

4.0
3.4
2.7

4.4
3.2
2.8

5.3
3.7
4.8

5.4
3.8
4.3

5.4
3.8
4.2

5.4
3.7
4.0

0.1
0.1
0.3

0.0
0.1
0.3

0.0
0.0
0.2

Oil price5

-47.3

-15.6

23.3

32.6

-1.4

0.1

23.2

-3.1

-1.6

Non-energy commodity price index

-15.8

-2.6

5.5

5.1

0.2

0.5

4.5

-0.6

-0.7

Low-income countries
BRICS
World (2010 PPP weights)
World trade volume4
Commodity prices

Source: World Bank.
Notes: PPP = purchasing power parity; 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 World Bank documents, even if basic assessments of countries’ prospects do not differ at any given moment in time. Country classifications and lists ofemerging 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.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

wanes. A projected deceleration of capitalspending in these economies, combined with thatin China, will contribute to more moderate global
trade growth in 2019 and 2020. Shifts in thepolicy mix of advanced economies—most notably,monetary policy tightening and fiscal policy
loosening in the United States—are expected toresult in a faster-than-previously-anticipatedincrease in global interest rates, and hence in
EMDE borrowing costs.
As international trade and financial conditions
become less supportive, and the cyclical upturn incommodity exporters matures, overall EMDE
growth is projected to plateau, reaching 4.7
percent in 2019 and 2020. Over this period, only
about half of commodity exporters, and less thanhalf of commodity importers, are expected to
grow above their pre-crisis long-term averages. In
the longer term, absent policy reforms, potential
growth in EMDEs is expected to weaken,
reflecting softening productivity and demographic
headwinds. Progress in per capita income growth
will be uneven. Per capita growth in Sub-SaharanAfrica, where nearly half of the extreme poor live,
is projected to remain below or around 1 percent,while it is expected to reach 6 percent in SouthAsia, a region that includes the second largest
number of people in extreme poverty.

CHAPTER 1

5

FIGURE 1.1 Summary - Global prospects
The global economic expansion remains robust but has softened, althoughcommodity-exporting EMDEs continue to recover. Global activity still lags
previous expansions, and growth is projected to decelerate in 2019-20 astrade and investment moderate. Progress in per capita income will be
uneven and insufficient to tackle extreme poverty in Sub-Saharan Africa.
A. Global growth

B. Global manufacturing output andexport orders

C. Growth in commodity-exporting
EMDEs

D. Global GDP during expansion
periods

E. Global trade and investment
growth, volumes

F. Per capita EMDE GDP growth, byregionUncertainty around global growth projections has
risen, partly driven by the possibility of policy
shocks from major economies (Figure 1.2). Whilea synchronous upturn in large economies could
lead to further growth upgrades in the near term,risks remain tilted to the downside, with somebecoming more acute.
In particular, the possibility of financial market
disruptions has increased amid shifting monetary
policy expectations in major advanced economies.
A sudden tightening of global financing conditions, combined with disorderly exchange rate
movements, would leave highly indebted EMDEs
particularly vulnerable, with rising debt service
costs hampering investment and heightening
financial stability risks. The risk of mounting tradeprotectionism has also intensified. A worldwide
escalation of tariffs up to the limits permitted
under existing international trade rules could lead

Sources: Haver Analytics, World Bank.
A.C.E.F. Shaded areas indicate forecasts.
A. EMDEs = emerging market and developing economies. Aggregate growth rates calculated using
constant 2010 U.S. dollar GDP weights. Data for 2017 are estimates.
B. Figure shows Purchasing Managers’ Index (PMI) for manufacturing output and new export orders.
Readings above 50 indicate expansion in economic activity; readings below 50 indicate contraction.
Last observation is April 2018.
C. Simple average of GDP growth. Orange lines indicate interquartile ranges of growth in each group.
D. Global GDP levels in constant 2010 U.S. dollars, indexed to 100 at start of expansion periods.
Cycle dates based on global recessions and slowdowns identified in Kose and Terrones (2015).
Dashed line corresponds to 2018-20 forecasts.
E. Trade measured as the average of export and import volumes.
F. SAR = South Asia and SSA = Sub-Saharan Africa. GDP per capita calculated using constant 2010
U.S. dollar GDP weights.
Click here to download data and charts.

6

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.2 Global risks and policy challenges
Uncertainty surrounding the outlook remains elevated and risks are tilted tothe downside. EMDEs are susceptible to a sudden increase in borrowing
costs amid elevated debt levels, and could be severely impacted byescalating trade protectionism. Improving education outcomes could help
raise EMDE per capita income levels and growth prospects. Regional
trade agreements could rekindle stalled trade liberalization at the global
level.
A. Probability of global growth in 2019
being below/above baseline

B. EMDE debt as a share of GDP,by borrowing sector

to cumulative trade losses equivalent to thoseexperienced during the global financial crisis in
2008-09, with particularly severe consequences for
EMDEs. Other risks include the possibility ofincreasing policy uncertainty and geopoliticaltensions. A further rise in oil prices, while
beneficial for oil exporters, could amplify current
account fragilities in some oil-importing EMDEs.
The probability of an abrupt slowdown in global
growth has risen and could increase further if one
or several downside risks materialize. Many
countries would be unprepared to confront suchan outcome, in view of their depleted policy
buffers and the moderating outlook for potential
growth. In this context, both advanced economies
and EMDEs face acute policy challenges.

C. Impact of interest-rate shock on
fiscal sustainability gaps in EMDEs,
by region

D. Impact on trade from worldwide
increase in tariffs to bound levels
by 2020

E. Students proficient in math andreading, by region

F. Size of new regional trade
agreements

Sources: Bank for International Settlements, International Monetary Fund, Kose et al. (2017b),
Kutlina-Dimitrova and Lakatos (2017), World Bank.
A. Bars show the probability that global growth is 1-percentage-point above or below baseline
forecasts 18 months ahead. Probabilities for 2019 are computed from the forecast distribution of 18month-ahead oil price futures, 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). Lastobservation is May 2018.
B. Debt is defined as loans and debt securities. Sample includes 16 EMDEs.
C.E. 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.
C. Figure shows the estimated deterioration in the fiscal sustainability gap driven by a 1-standard
deviation interest rate increase. Sustainability gap is measured as the difference between the primarybalance and the debt-stabilizing primary balance. A negative bar indicates government debt is risingalong an accelerated trajectory. Sample includes 70 EMDEs.
D. Bars denote the percent deviation from baseline in 2020. Data are calculated from simulations
using the GDyn computable general equilibrium model (Ianchovichina and McDougall 2000;
Ianchovichina and Walmsley 2012). Trade-weighted aggregates include 36 advanced economies and
71 EMDEs.
E. Data for South Asia are unavailable. Dashed horizontal lines show advanced-economy average.
F. CPTPP = Comprehensive and Progressive Agreement for Trans-Pacific Partnership,
AfCFTA = African Continental Free Trade Area. Data are as of 2017.
Click here to download data and charts.

The immediate policy challenge for advanced
economies is to calibrate their fiscal, monetary,and trade policy stances to nurture the recovery
and to avoid disorderly financial adjustments. In
the longer term, they need to confront the slow
pace of potential growth and demographicpressures through structural reforms that boost
productivity, labor force participation, and fiscal
sustainability.
In EMDEs, monetary and fiscal buffers need to berebuilt in order to prepare for monetary policy
tightening in advanced economies and restore thescope for policy support against negative shocks.
In particular, rising global interest rates willheighten corporate vulnerability and raise EMDE
debt-service costs and fiscal sustainability gaps. In
the longer run, EMDE policy makers also need toconfront intensifying structural challenges andaccelerate measures to tackle poverty. The decisive
implementation of growth-enhancing structuralreforms is critical in light of the likelihood of
weaker-than-expected long-term growth outcomes—which, given past experience, is a material
possibility (Box 1.1).
For commodity exporters, prospects of a secularslowdown in demand for commodities call for
accelerated efforts to diversify and transform theireconomies as a way of boosting income per capita
and mitigating volatility. For all EMDEs, rapid
technological changes highlight the need toG LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

support skill acquisition and adaptability. This
would assist the process of integration in regionaland global value chains, as well as bolster firms’
ability to absorb new technologies and competeinternationally. For many low- and middleincome countries, improving basic numeracy,
literacy, and skills related to information andcommunication technologies remains a key
priority. Comprehensive preferential trade
agreements can help boost income per capita ofmember countries and rekindle stalled tradeliberalization at the global level. Recent regional
initiatives are a promising step toward that goal.

Major economies: Recent
developments and outlook

CHAPTER 1

7

FIGURE 1.3 Advanced economies
Despite recent signs of softening, growth in major advanced economies isstill generally solid. It is projected to moderate toward subdued potential
rates over the forecast horizon, as labor market slack diminishes andmonetary policy stimulus is gradually withdrawn.

A. GDP and demand component
growthB. Growth

C. Unemployment rate

D. Actual and potential growth in
2018-19

In advanced economies, growth remains above
potential despite signs of softening. In the UnitedStates, significant fiscal stimulus will boost near-term
activity. As the recovery matures over the forecasthorizon and monetary policy accommodation is pared
down, growth is projected to moderate toward its
potential rate. In China, growth remains solid and is
expected to gradually slow as rebalancing continues.
Although recent indicators in advanced economies
suggest some moderation, they continue to point
to solid investment and above-potential growth
this year across countries (Figure 1.3). Consumer
confidence is still high and new jobs are being
created at a solid pace. In all, advanced-economy
growth is projected at 2.2 percent for 2018—aslight deceleration from last year, as additional
fiscal stimulus in the United States is offset bymoderating growth in other major economies.
Over the forecast period, growth is expected todecelerate toward its potential rate, as output gaps
close and become positive, inflation rises towardtarget rates amid higher energy prices, and central
banks continue to remove monetary stimulus.
United States
Growth in the United States reached 2.3 percent
in 2017, supported by broad-based strength indomestic demand, especially investment. The
economy may be near its productive potential, as
both capacity utilization and the employment rate

Sources: Haver Analytics, World Bank.
A.B. Green diamonds correspond with the January 2018 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.
C. Data are seasonally adjusted. Last observation is April 2018 for the United States, and is March2018 for Japan and the Euro Area.
D. Blue bars refer to average actual growth over 2018-19 period and vertical orange lines show theminimum-maximum range of potential growth estimates based on eight different methodologies(production function approach, multivariate filter, three univariate filters—Hodrick-Prescott filter,
Christiano-Fitzgerald filter, and Butterworth filter—IMF World Economic Outlook estimates, andestimates in OECD Economic Outlook and Long-Term Baseline Projections), over 2018-19. For
further details on potential growth estimates, refer to the January 2018 edition of the Global
Economic Prospects report.
Click here to download data and charts.

are moving toward peaks attained prior to thefinancial crisis (Figure 1.4). Wage growth has
picked up slightly, but is still weak compared toprevious recoveries.
The Bipartisan Budget Act passed in earlyFebruary, which will add about 1.5 percent of
GDP in government spending to the economy
over the next three years, is the main factor behindthe forecast upgrade relative to January projections. Combined with the Tax Cuts and Jobs Act
enacted last year, additional discretionary expenditures result in a highly procyclical fiscal stance,
which is expected to cost almost 5 percent of GDP

8

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

BOX 1.1 Long-term growth prospects: Downgraded no more?

Consensus forecasts for long-term growth have recently stabilized after a series of downgrades since 2010. Although
this development could be another encouraging sign the global economy is finally enjoying a healthy expansion, longterm forecasts are often overly optimistic. While well below levels expected a decade ago, these forecasts are above
potential growth estimates. Moreover, adverse structural forces continue to overshadow long-term growth prospects.
A prolonged period of weaker growth expectations,characterized by the systematic downgrading of longterm forecasts, seems to have come to an end. For the
first time since 2010, the 10-year-ahead consensus
forecast for global growth appears to have stabilized(Figure 1.1.1). In 2018, long-term growth
expectations were upgraded for more than half ofcountries—the largest number since 2010—and there
have also been recent upgrades in short-term forecasts.
A sustained upgrading of long-term forecasts could be
another sign that the legacies of the global financial
crisis are fading. Growth is expected to remain at apost-2011 high this year, and the negative global
output gap is likely to be closed for the first time since2008 (World Bank 2018a). The recent synchronizedglobal upturn has even sparked hopes that the crisisinduced damage to potential growth—“hysteresis”
effects, which entrench weak growth after deep
recessions—could be reversed if investment,
productivity and employment continue to improve(Yellen 2016; Draghi 2018).1
However, such enthusiasm needs to be tempered byseveral considerations. First, the benign short-term
global growth outlook is predicated on highly
accommodative monetary policy by major central
banks and, in some advanced economies, significant
fiscal stimulus. Second, long-term global growthforecasts are stabilizing at levels well below those
expected a decade earlier and well below current

Note: This box was prepared by M. Ayhan Kose, Franziska Ohnsorge
and Naotaka Sugawara. Research assistance was provided by Shijie Shi.
1Hysteresis eﬀects caused by the global ﬁnancial crisis were sizable andpersistent (Ball 2014; Lo and Rogoﬀ 2015; Oulton and Sebastiá-Barriel2017). Some argue that, absent monetary and ﬁscal demand stimulus,
growth may have been much lower because of the underlying forces of“secular stagnation,” a phenomenon of a rising propensity to save, weak
demand and persistently low real interest rates (Summers 2015, 2016;
Rachel and Smith 2015).

growth rates. Third, long-term growth expectations
have in the past proven overly optimistic and above
model-based estimates of potential growth, which has
been dampened by multiple structural forces.
Against this background, this box briefly analyzes the
behavior of long-term global growth expectations toaddress the following questions:•

How have long-term global growth expectations
evolved?

•How do these expectations compare with actual
outcomes and estimates of potential growth?

•

When do long-term growth expectations tend tobe higher?

•

What does the recent stabilization in forecasts
imply for long-term prospects?

Over the past decade, the implications of rapid
technological innovations for long-term growthprospects have been a subject of intense debate. Some
claim that in the coming decades the global economy
will enjoy a surge in productivity growth driven by
new digital technologies (Brynjolfsson and McAfee2014). Others argue that growth will be much slower
because of the declining marginal impact of newtechnologies on productivity (Gordon 2016). Thisbox focuses on long-term growth prospects as
captured in 10-year-ahead growth forecasts andmodel-based potential growth estimates. It is very
difficult, if not impossible, to undertake a credible
quantitative analysis of the impact of newtechnologies on long-term productivity and growth
outcomes.
Long-term growth expectations here refer to 10-yearahead growth forecasts of real GDP from Consensus

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

CHAPTER 1

BOX 1.1 Long-term growth prospects: Downgraded no more? (continued)

Economics.2 Short-term growth forecasts are definedas 1-year-ahead consensus forecasts. All forecasts arefor annual growth and refer to averages of semiannual or quarterly projections.
Evolution of expectations
Pre-crisis upgrades, post-crisis downgrades. The
global financial crisis marked a turning point in longterm global growth expectations. From 1998 to2007, long-term expectations improved slightly(from 3 percent to 3.4 percent). During the same
period, 18 of the 38 economies’ long-term growthforecasts were upgraded. Following the 2007-09
global financial crisis, however, long-term forecasts
have steadily declined, from 3.3 percent in 2010 to
2.5 percent in 2017, reflecting a broad-based
downgrading of growth prospects. Since the crisis,long-term growth forecasts were lowered for all
economies (by about 1.4 percentage points, on
average). The evolutions of forecasts over various
horizons (from 2- to 10-year-ahead) all point togradual deterioration in global growth expectations
since the financial crisis.
The pattern of initial strength and subsequent
weakness in growth expectations is broadly shared,albeit at different speeds and intensities, among
different country groups and alternative measures ofgrowth. Emerging market and developing economies(EMDEs) enjoyed improvements in their growthprospects before the crisis, while advanced economies
began experiencing a gradual decline in growthforecasts in the early 2000s. Post-crisis, both groups
witnessed deteriorating long-term growth forecasts.
Similar trends occurred in per capita growth andmedium-term (5-year-ahead) forecasts. In addition,
2 Consensus Economics reports an average of 6- to 10-year-ahead
growth forecasts, which are labelled here as “10-year-ahead forecast.”
These forecasts are consistently available for 38 countries (20 advanced
economies and 18 EMDEs) from 1998. These 38 countries constitute 87
percent of global GDP in 2010-18. Forecasts are available for 45
countries (25 advanced economies and 20 EMDEs) for as early as 1989.
Consensus Economics has been canvassing long-term forecasts frommultiple institutions four times a year since 2015. Prior to that, longterm forecasts were made available twice a year or three times a year. The
forecast made in a particular year is deﬁned as the average of the 2-4
available forecast vintages in that year. For 2018, the forecast is theaverage of January and April vintages.

the post-crisis decline in long-term output growth
expectations was accompanied by weakening forecasts
for global investment and consumption growth.
The pattern of pre-crisis upgrades and post-crisis
downgrades in long-term forecasts was also evident insome major economies (Figure 1.1.2). In 1998, U.S.
growth was expected to be about 2.4 percent over thefollowing decade but, by 2008, the long-term growthforecasts had been revised upwards by 0.3 percentage
point. Similarly, growth in China was expected to be
7.5 percent over the following decade in 1998, but
by 2008, the long-term forecast had been increased
by 0.2 percentage point following its remarkably
strong performance in the previous decade. Although
long-term growth forecasts for Brazil and India were
upgraded in 2008 relative to expectations a decade
earlier, these upgrades did not last. By 2018, all ofthese economies’ long-term growth forecasts had
declined (0.3-2.4 percentage points) below their
1998 levels.
Recent stabilization. Since 2017, long-term growth
expectations have stabilized. In 21 of 38 economies,
long-term growth expectations improved from 2017
to 2018—the largest number of countries since 2010.
Ten-year-ahead forecasts for EMDEs registered theirfirst upgrade in 2018 following seven consecutive
years of declines.
Factors driving the evolution of forecasts. The
evolution of long-term forecasts has reflected theglobal economy’s roller coaster ride over the past two
decades. Pre-crisis strength in growth prospects inpart reflected rapid expansion of investment andinternational trade and financial flows with the
spread of information and communications
technology (Kose and Prasad 2010; World Bank
2018a). Thanks to these developments, the global
economy registered one of its best growth records
since the early 1970s in the 2003-07 period.
Tailwinds, however, turned into headwinds during
the 2009 global recession, which was followed by ananemic recovery, especially in advanced economies.
The post-crisis period was marked by widespread
unemployment and weak investment growth. In
many countries, elevated debt burdens weighed on

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BOX 1.1 Long-term growth prospects: Downgraded no more? (continued)
FIGURE 1.1.1 Growth forecasts: Global, groups, and aggregates
After a prolonged period of downgrades, long-term forecasts of global growth, per capita growth, investment, andconsumption may have stabilized in 2018, while short-term forecasts have been upgraded recently. This still leaves current
long-term forecasts considerably lower than a decade ago. Downgrades were particularly steep, but started later (after the
global financial crisis), for EMDEs than for advanced economies.
A. Ten-year-ahead global growthforecasts

B. Share of countries with upgrades in
10-year-ahead growth forecasts

C. One- to three-year-ahead global
growth forecasts

D. Global growth forecasts, by forecasthorizonE. Ten-year-ahead output growthforecasts

F. Ten-year-ahead global investment andconsumption growth forecasts

Sources: Consensus Economics, United Nations, World Bank.
Notes: Sample includes 38 countries, consisting of 20 advanced economies and 18 EMDEs, for which consensus forecasts are consistently available during 1998-2018.
These economies account for 87 percent of global GDP over 2010-18. Unless otherwise noted, annual averages of results from multiple surveys conducted in each year
are presented.
A.B.E.F. The horizontal axis refers to the year of consensus forecast surveys.
A.C.D.E. Global, advanced-economy, and EMDE growth is computed with constant 2010 U.S. dollar GDP weights.
A. Per capita global output growth is computed as the difference between 10-year-ahead global growth forecasts and population growth estimates in the years for which
forecast surveys are conducted.
B. Share of countries with positive changes in 10-year-ahead growth forecasts from the previous year.
C. Lines are based on consensus forecast surveys conducted in September or October of denoted years, except 2018, for which data are based on surveys in April.
D. Lines show the years of consensus forecast surveys.
F. Global private consumption and investment growth is computed, respectively, with constant 2010 U.S. dollar private consumption and investment weights.
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investment growth (World Bank 2017a). Over 201015, long-term prospects were further clouded by the
2011-12 Euro Area debt crisis, and by a sharp
slowdown in EMDEs that was partly related to thebursting of the commodity price boom.
These adverse cyclical effects were compounded bystructural weaknesses, namely poor productivity
growth and a broadening slowdown in the growth ofworking-age population (Didier et al. 2015; WorldBank 2018a). A slowdown in total factor
productivity growth that had begun in advanced
economies in 2004 was compounded, from 2008, by
an even steeper decline in EMDEs.3 Similarly,
3 In advanced economies, the highly synchronized slowdown in
productivity growth has been attributed to several factors, including thelack of transformative technologies, slowing improvements in educational
attainment, and the maturation of information technologies (Cette,
Fernald, and Mojon 2016; Hirata, Islamaj, and Kose 2018; Kilic Celik et
al. 2018; World Bank 2018a).

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

CHAPTER 1

BOX 1.1 Long-term growth prospects: Downgraded no more? (continued)
FIGURE 1.1.2 Growth forecasts in major economies and in comparison with actual andpotential growth
Since the global financial crisis, long-term growth forecasts have declined in all major economies. This slowdown has
followed adverse cyclical effects, compounded by structural weakness, including declines in the share of the working-age
population. For most countries, long-term growth forecasts have systematically exceeded potential growth and actual
growth over the past decade, and forecast optimism is stronger for longer-term forecasts than for shorter-term forecasts.
A. Ten-year-ahead growth forecasts inadvanced economies

B. Ten-year-ahead growth forecasts in
EMDEs

C. Global working-age population

D. Ten-year-ahead growth forecast errors

E. Global growth forecast errors, by
forecast horizon

F. Comparison of global forecasts andpotential growth

Sources: Consensus Economics, Kilic Celik et al. (2018), United Nations, World Bank.
Notes: Sample includes 38 countries (20 advanced economies and 18 EMDEs).
A.B. Years denoted show the years of consensus forecast surveys.
A.B.D.E.F. For growth forecasts, annual averages of results from multiple surveys conducted in each year are presented.
A.B.D.F. Growth in aggregate groups is computed with constant 2010 U.S. dollar GDP weights.
A. Euro Area is a weighted average of France, Germany, Italy, the Netherlands, and Spain.
C. Population-weighted averages. The working-age population is defined as people aged 15-64 years. Shaded area refers to forecasts.
D. A forecast error is defined as a difference between consensus output growth forecasts a decade earlier and actual growth, weighted by GDP. The horizontal axis refers
to the years for which growth forecasts are surveyed, with the forecast survey years in parentheses.
E. A forecast error is defined as a difference between growth forecasts at different horizons (over three years, five years, and 10 years) and actual growth. Averages andmedians are computed from available observations up to 2017.
F. Figure shows period averages of GDP-weighted global actual growth, potential growth, and growth forecasts. For 10-year-ahead growth forecasts, the horizontal axis
refers to the forecast survey years. Potential growth is measured by production function.
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in 2010, the share of the working-age populationin EMDEs began, first, to plateau and, then, started
to fall—a turning point that advanced economies
had already passed in the mid-1980s. As a result,global potential growth—the rate of change in
output an economy would sustain at full capacity
utilization and full employment—was 0.9 percentage
point lower in 2013-17 than a decade earlier (WorldBank 2018a).

The recent stabilization in long-term growth
expectations is associated with improved global
growth and trade since mid-2016, tight labor markets
and a rebound in industrial production in majoradvanced economies that also benefited their trading
partners, and recoveries in some large commodityexporting EMDEs. Indeed, global GDP is expected
to return to its potential this year for the first timesince 2008.

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BOX 1.1 Long-term growth prospects: Downgraded no more? (continued)

Comparison with outcomes and potential
growthSystematic optimism. Not surprisingly, during
2008-17, long-term global growth forecasts made adecade earlier exceeded actual growth outcomes in all
years except 2010. Growth forecasts were higher thaneventual growth outcomes in the majority ofcountries in almost all years since 2008, except
during 2010-11. Even during those two years,
forecasts were overly optimistic for around 50
percent of advanced economies and 25 percent of
EMDEs. The analysis here covers mainly the crisisand post-crisis periods that witnessed an unusualseries of negative growth shocks. However, it is
widely documented that forecasts for long-term
growth tend to be more optimistic than growth
outcomes even in data samples that include the precrisis period (Ho and Mauro 2016). Moreover, thelonger the forecast horizon, the larger the degree ofover-optimism is. On average, 10-year-ahead growthforecasts overshot by 1.2 percentage points and 5year-ahead forecasts over-estimated growth by 0.8
percentage point over the period until 2017.4
Above potential growth. Since long-term growth
expectations presumably abstract from cyclicaleffects, they should reflect forecasters’ judgment
about an economy’s potential growth. By
comparison, model-based estimates of potential
growth can be made using a number of methods. To
study whether long-term growth expectations differ
from other measures of potential growth, estimates ofpotential growth based on a production function
model are compared with 10-year-ahead growthforecasts made in the same year (Kilic Celik et al.
2018; World Bank 2018a). Ten-year-ahead forecasts
for global growth often exceed the model-based
global potential growth over the next decade.5 The
For 5-year-ahead forecasts, this is larger than the average growth
disappointments of 0.34 percentage point in World Economic Outlook
forecasts for 188 countries for 1990-2012 (Ho and Mauro 2016).
5 Estimating potential output is fraught with measurement challenges(World Bank 2018a). However, 10-year-ahead forecasts remain above
multiple model-based measures of potential growth available in Kilic
Celik et al. (2018). For commodity exporters, accounting for resource
rents can materially alter potential growth estimates and may account inpart for the diﬀerence between 10-year-ahead forecasts and cross-countryconsistent potential growth estimates.
4

gap between long-term expectations and the modelbased estimate is mostly driven by advanced
economies but long-term growth forecasts are
currently larger than potential growth in the majority
of countries.
Causes of optimism. The over-optimism in longterm growth forecasts is a result of both cyclical andstructural factors. In part, this optimism reflected an
initial underappreciation of the headwinds topotential growth, especially in advanced economies,
from demographics and weak investment andproductivity. In part, optimism was a natural
outcome of the failure to predict, or even recognize
in real time, shocks that could trigger crises orbusiness cycle turning points and their lasting impact(Juhn and Loungani 2002; Ho and Mauro 2016).6
The global financial crisis, one of the largest such
episodes in a century, was not foreseen by mostforecasters. The post-crisis period has also beenmarked by additional severe and unforeseen shocks,
such as the Euro Area debt crisis and the 2014-16 oilprice collapse. These episodes—which could not be
foreseen 10 years earlier—were followed bysubstantial and persistent downward growth revisions. They were accompanied by weak business
confidence and policy uncertainty. Long-term
forecasts adjusted gradually, as new information
revealed the lasting damage these shocks had dealt to
the global economy. Indeed, long-term growthforecast downgrades have been historically associatedwith disappointing growth outcomes: when growth
fell short of 1-year-ahead forecasts in three consecutive years (in a sample of 55 country-year episodes),10-year-ahead forecasts were, on average, downgraded by 0.2 percentage point. When comparedwith forecast changes in other years, this downgrade
was statistically significant.
Factors associated with higher long-term
forecasts
As shown in the preceding section, long-term forecast
revisions are quite common over time and across
6 The average 10-year-ahead forecast error for the growth in years up
to 2000-08 was correspondingly smaller, at 0.1 percentage point, compared with 1.2 percentage points for the sample from 2000-17.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

CHAPTER 1

BOX 1.1 Long-term growth prospects: Downgraded no more? (continued)

countries. To analyze the major factors associatedwith higher forecasts, two simple event studies areundertaken. These illustrate how forecasts are revised
during periods of strong output or investment
growth. These episodes are particularly relevant
considering that the recent stabilization in growth
expectations has also coincided with above-potential
growth in some major economies and an acceleration
in investment since mid-2016.
Sustained output growth. Sustained periods ofabove-potential growth were generally accompanied
by higher 10-year-ahead growth forecasts. The event
study sample includes 55 episodes (of which 43
concluded before the global financial crisis in 2009)
during which actual growth exceeded potential
growth in at least three consecutive years. Conversely,in 49 setback episodes, of which 17 straddled thecrisis and 24 were pre-crisis, actual growth fell shortof potential growth in three or more consecutive
years. During growth spurts, long-term growthforecasts were, on average, 0.3 percentage point (andstatistically significantly) higher than during growth
setbacks (Figure 1.1.3).
Investment surges. The event sample includes 88
episodes (of which 66 ended before 2009) in whichinvestment growth was positive in at least threeconsecutive years and 41 setback episodes in whichinvestment growth was negative for at least threeconsecutive years. Again, long-term growth forecasts
were, on average, 1 percentage point (and statisticallysignificantly) higher during investment growth spurts
than investment growth contractions.
Implications: A respite from gloom about
growth prospects?
Recent long-term growth forecasts indicate that theperiod of post-crisis gloom about growth prospects
may be coming to an end. Long-term growthforecasts currently envision global growth in 2028
at 2.6 percent—slightly higher than a year ago but
less than this year’s projected growth (3.1 percent).
If the recent stabilization of long-term growthforecasts heralds a period of sustained upgrades, it
may signal that the effects of the global financial crisis
are waning.

However, past experience cautions that long-term
forecasts may yet again turn out to be overly
optimistic. Specifically, if forecast errors of themagnitude observed in the past materialize yet again,
growth in the coming decade may turn out to bemuch weaker than current long-term growthforecasts, around 2.1 percent instead of 2.8 percent.
Over-optimism has reflected an underappreciation of
structural headwinds to potential growth as well as a
failure to forecast global recessions. Over the past
half-century, the global economy experienced arecession every decade (in 1975, 1982, 1991, and2009).7 This record suggests that it is possible thatthe global economy is due for another recession overthe next 10 years.
Yet, even if a growth forecast disappointment is not
triggered by an outright global recession, averagepotential growth over the next decade is estimated tobe slower than during 2013-17. This reflects anawareness that weak productivity growth, increasingly unfavorable demographic trends, and subdued
investment prospects are likely to weigh on global
potential growth in the coming years. Model-based
estimates suggest that average global potential growthduring 2018-27 will be about 2.5 percent, much
lower than the post-crisis average actual growth of 3
percent (World Bank 2018a).
Over a decade, such seemingly small differences ingrowth outcomes translate into significant changes in
global income and living standards. For example,
should global growth average current consensus
forecasts, incomes a decade from now would be,
cumulatively, 31 percent higher than in 2018 (but 3
percentage points less than if growth remained at its
post-crisis average pace). This income gain could turn7 In 1975, a surge in oil prices coincided with recessions in majoradvanced economies and debt crises in EMDEs. In 1982, monetary
policy tightening in major advanced economies precipitated further debt
crises in many EMDEs. In 1991, an abrupt tightening of credit in the
United States coincided with banking and currency crises in many
European countries. And in 2007-09, there were particularly deepﬁnancial crises in major advanced economies. In addition to these fourglobal recessions, the global economy experienced two major slowdowns:
during 1997-98, the Asian Crisis was followed by the Russian crisis and,in 2001, the U.S. stock market corrected in the dot-com crash (Kose andTerrones 2015).

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BOX 1.1 Long-term growth prospects: Downgraded no more? (concluded)
FIGURE 1.1.3 Growth forecasts and change in global GDP
Revisions in long-term growth forecasts are common over time and across countries. Ten-year-ahead forecasts became
higher during sustained growth spurts and investment surges. Over a decade, growth disappointments can make a majordifference to global incomes.
A. Ten-year-ahead growth forecasts
during strong growth and investment
episodesB. Global growth forecasts and potential
growthC. Cumulative change in global GDP,
2018-27

Sources: Consensus Economics, Kilic Celik et al. (2018), World Bank.
Note: For growth forecasts, annual averages of results from multiple surveys conducted in each year are presented.
A. Bars show average growth forecasts during events. *** and ** denote that average forecasts between two events are statistically significantly different at the 1 percent
and 5 percent levels, respectively. Sample includes 45 countries for which consensus forecasts are available even over the shorter period. Growth spurt and setback
events are defined as, respectively, at least three consecutive years of actual growth above and below potential growth: 55 spurts in 37 countries and 49 setbacks in 36
countries. Investment surge and slowdown events are defined as, respectively, at least three consecutive years of positive and negative investment growth from theprevious year: 88 surges in 42 countries and 41 slowdowns in 26 countries.
B.C. Growth in aggregate groups is computed with constant 2010 U.S. dollar GDP weights. Potential growth is measured by production function. Sample includes 38
countries.
B. Actual growth (2010-17) and potential growth (2018-27) are period-averages. A bar for “forecast” is an average of growth forecasts for 2018-27 surveyed in 2018. Biasin forecast is corrected in the following ways: A bar refers to an average of consensus growth forecasts for 2018-27 after an average forecast error for each time horizon(as partly shown in Figure 1.1.2.E) is adjusted; and an orange ticker shows average forecast growth corrected for the average error over 10 years.
C. Cumulative change in global GDP since 2018, when growth in every year during 2018-27 is assumed to be as defined in Panel B.
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out to be 4 percentage points lower should growthinstead average its estimated potential rate, and about
9 percentage points lower should growth fall short ofconsensus forecasts by the average historical forecast
error.
The analysis here warns that the recent stabilization
in long-term growth prospects may be fleeting. The

risk of further adverse shocks and underlying
structural weaknesses still suggest an urgent need topress ahead with growth-enhancing policy
adjustments—including reforming product and labormarkets, raising investment in human capital, andbuilding the policy buffers needed to allow anappropriate counter-cyclical response to shocks when
they materialize.

over 2018-2020 (CBO 2018a; CBO 2018b; CBO
2018c; JCT 2017). In all, the stimulus adds justover 1 percentage point to the growth forecast
over the next couple of years, but is expected tolead to budget deficits of around 5 percent of
GDP for the next decade, up from 3.5 percent in2017. As a consequence, net federal public debt,
currently at about 80 percent of GDP, is set to risein coming years (Auerbach, Gale, and Krupkin2018). As fiscal stimulus measures have been
introduced and inflation has moved toward target,
the Federal Reserve has signaled a faster pace ofpolicy tightening.
Recent trade policy changes are not expected tohave a substantial effect on U.S. growth, which is
projected to reach 2.7 percent in 2018 and edge
down to 2.5 percent in 2019. As fiscal andG LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

monetary stimulus fade, growth is forecast to slow
to 2 percent in 2020, above the mid-point of the 1
to 2.4 percent range of estimates of its potential
pace (Fernald et al. 2017; World Bank 2018a).
Euro Area
The Euro Area economy grew 2.4 percent in2017, its fastest increase since the financial crisis,
reflecting strong consumption, investment, andexports. However, data releases since the start of2018 point to decelerating activity (Figure 1.5).
Headline inflation stands at 1.2 percent, wellunder the central bank target of close to, but
below, 2 percent. Wages and inflation expectations have edged up intermittently, pointing toincipient signs of rising price pressures. The
European Central Bank (ECB) has committed to
growing its balance sheet until at least September
2018, with its policy rate remaining unchanged“well past” this date, until inflation is clearly
converging toward target (ECB 2018).
Amid continued monetary policy stimulus,
growth is projected to be 2.1 percent in 2018. It is
forecast to slow to 1.7 percent in 2019 and 1.5
percent in 2020, as slack dissipates, higher oil
prices weigh on consumption, monetary accommodation is gradually unwound, and borrowing
costs increase. Net exports are also expected to
become a drag on near-term growth, as the earlier
strengthening of the euro and improving domestic
demand translate into a narrowing of the sizable
current account surplus. Positive spillovers fromexpansionary U.S. fiscal policy are expected to belimited. Throughout the projection horizon,
growth is projected to remain above the mid-pointof the 0.7 to 1.5 percent range of potential growthestimates (ECB 2017; World Bank 2018a).
Japan
Growth in Japan reached 1.7 percent in 2017,
underpinned by supportive financial conditions
and strong exports, but contracted at the
beginning of this year. Nonetheless, unemployment is falling to levels not seen since the 1990s,
while the participation rate has increased,primarily due to greater entry of women into thelabor force (Figure 1.6). Inflation remains low,

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15

FIGURE 1.4 United States
The U.S. economy remains robust and may be near its productive
capacity. Nevertheless, wage growth remains soft, especially compared toprevious expansions. Procyclical fiscal stimulus is expected to provide a
temporary boost to growth, which has contributed to a rise in the Federal
Reserve’s policy rate projections.
A. Productive capacity

B. Wage growth during expansions

C. Federal deficit and unemployment
rate

D. U.S. Federal Reserve policy rate
projections over time

Sources: Board of Governors of the Federal Reserve System, Bureau of Labor Statistics,
Congressional Budget Office, Federal Reserve Bank of St. Louis, Haver Analytics, World Bank.
A. The dashed horizontal lines indicate the peak values for capacity utilization and the employment toworking-age population ratio in the two years prior to the global financial crisis (i.e., December 2005
to December 2007). The local peak was 81.1 percent for capacity utilization and 80.3 percent for theemployment to working-age population ratio. Last observation is April 2018.
B. Wage growth is the average hourly earnings of private, non-farm production, and nonsupervisory
employees. Wages have been indexed to the trough of the corresponding National Bureau of
Economic Research (NBER) business cycle. Last observation is April 2018.
C. Shaded area indicates forecasts. Forecast for the federal deficit based on the most recent
Congressional Budget Office (CBO) baselines. Forecast for the unemployment rate based on WorldBank calculations using an Okun’s law coefficient of 0.5.
D. Figure shows the minimum-maximum range and median of the federal funds rate projections for
2018, 2019, and 2020 released in September 2017, December 2017, and March 2018. The
projections show the median and range of FOMC participants’ (i.e., Federal Reserve Board members
and Federal Reserve Bank presidents) assessment of the midpoint of the projected appropriate target
range for the federal funds rate, or the projected appropriate target level for the federal funds rate at
the end of the specified calendar year.
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and wages and inflation expectations have been
generally stable, suggesting that monetary policy
will likely remain accommodative for some time.
Over the forecast period, growth is expected todecelerate to 1 percent in 2018, 0.8 percent in
2019, and 0.5 percent in 2020, as higher oil prices
erode real incomes, employment growth slows,
and fiscal consolidation starts to drag on growth,
notably due to the effects of the VAT hike

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FIGURE 1.5 Euro Area
While data releases since the start of 2018 point to decelerating activity,
growth is still above potential. Inflation continues to be below target,
though wage growth and inflation expectations have edged up
intermittently. The current account surplus remains sizable.
A. Composite PMIs

B. Headline and core inflation

C. Inflation expectations and wage
growthD. Euro Area current account balance

Sources: Bloomberg, European Central Bank (ECB), Haver Analytics, World Bank.
A. Purchasing Managers’ Index (PMI) readings above 50 indicate expansion in economic activity;
readings below 50 indicate a contraction. Last observation is April 2018.
B. Horizontal line represents 1.9 percent, consistent with the ECB’s inflation target of close to, but
below, 2 percent. Last observation is April 2018.
C. Long-term inflation expectations are derived from 5-year over 5-year forward swap rates, averaged
over the quarter. Wage growth is year-on-year, and includes industry and services, excluding public
administration. Last observation is 2018Q1 for inflation expectations and 2017Q4 for wage growth.
D. Aggregates calculated using constant 2010 GDP weights. Last observation is 2017Q4.
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FIGURE 1.6 Japan
Despite a contraction in activity at the start of 2018, the labor market
continues to add workers as unemployment falls and the participation rate
rises. Increases in earnings have been moderate, and core inflation
remains low.
A. Unemployment and labor
participation rates

B. Core inflation and wage growthscheduled for late 2019. The long-term growth
outlook remains constrained by an aging andshrinking labor force (World Bank 2018a).
China
Growth in China reached 6.9 percent in 2017 andhas remained solid this year (Figure 1.7; WorldBank 2018b). Activity continues to shift toconsumption, while investment growth rates
remain well below those in recent years. Industrial
production has stabilized following significant cutsin overcapacity sectors implemented over the past
two years. In the first quarter of 2018, China
recorded its first current account deficit since
2001.
During the first half of 2018, fiscal policy has
become less expansionary, while monetary andprudential policies continue to rein in excessive
credit growth, especially shadow financing. The
stock of outstanding debt is high, although thelargest component—credit to non-financial
corporations—has been declining as a share of
GDP (BIS 2018a). Tight housing market
regulations have contributed to some correction in
the housing sector. Consumer price inflation
remains below target, and producer price inflation
has moderated. Tight enforcement of capital flow
management measures continues to limit capitaloutflows and exchange rate pressures.
China’s growth is projected to edge down to 6.5
percent in 2018 and slow further to 6.3 percent
on average in 2019-20, as export growthmoderates and deleveraging takes hold. In
addition, policy accommodation is expected tofurther diminish as authorities continue to tighten
macroprudential regulation and gradually remove
their supportive fiscal stance. Downside risks to
the outlook stem from financial sector
vulnerabilities and an intensification of tradetensions amid increased protectionism in key
trading partners.

Global trends
Sources: Haver Analytics; Japan Ministry of Health, Labor, and Welfare; Japan Ministry of Internal
Affairs and Communications.
A. Last observation is March 2018.
B. Average monthly earnings are 12-month moving averages and are the average monthly earnings
of workers in companies with 30 or more employees, in all industries. The core CPI index excludes
fresh food and energy, and has been adjusted to exclude the impact of Value-Added Tax (VAT)
hikes. Last observation is April 2018 for core CPI and March 2018 for average monthly earnings.
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Global trade was robust last year, benefiting from an
upturn in capital spending and manufacturing activity. It is expected to moderate over the forecast

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

period amid decelerating global investment.
Financing conditions are expected to tighten more
rapidly than previously envisioned, along with thepossibility of faster normalization of monetary policy
in major advanced economies, in part because of
expanded U.S. fiscal stimulus measures. Capital
flows to EMDEs have eased amid rising borrowing
costs and are likely to further moderate. Oil prices
are substantially higher than previously expected, andother commodity prices have also risen. While nearterm projections for commodity prices have beenrevised up, they are expected to level off later in theforecast horizon.

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17

FIGURE 1.7 China
Growth in China remains solid and rebalancing continues, amid robust
consumption and a slowdown in investment. In the first quarter of 2018,
China recorded its first current account deficit since 2001. Stricter
enforcement of capital flow management measures has helped ease
capital outflows and exchange rate pressures. Credit growth continues todecline because of regulatory tightening.

A. Contribution to growth

B. Investment growth

C. Balance of payments

D. Credit growth

Global trade
Following a prolonged period of marked
weakness, a cyclical recovery in global
manufacturing and investment propelled global
goods trade growth to 4.6 percent in 2017, threetimes the pace observed the previous year. The
momentum remained sustained in early 2018,
despite easing export orders (Figure 1.8). Services
trade also gained strength last year. Since theglobal financial crisis, services trade has grown at afaster pace and continues to have the largest
untapped potential for future growth (Georgieva,
Loayza, and Mendez-Ramos 2018; Lodefalk
2017; Miroudot and Cadestin 2017).
Overall, growth in global trade of goods andservices combined is expected to moderate to 4.3
percent in 2018, down from a six-year high of 4.8
percent in 2017. These projections have beenrevised up due to stronger-than-expected intraregional trade growth in Asia and import demand
from major advanced economies. The additional
fiscal stimulus in the United States is expected tolift U.S. import growth, benefiting key U.S.
trading partners. Although benefits from thestrength of global trade are broad-based across
EMDE regions, they were most pronounced in
East Asia and Pacific and Eastern Europe andCentral Asia. Export growth in these two regions
peaked in 2017 and is forecast to remain robust in
2018-19. More generally, a projected decelerationof capital spending in China and in mostadvanced economies will contribute to more
moderate global trade growth over the forecasthorizon (Freund 2018; Auboin and Borino 2017).

Sources: China National Bureau of Statistics, Haver Analytics, International Institute of Finance,
People’s Bank of China, World Bank.
A. Shaded area indicates forecasts. Investment refers to gross capital formation, which includes
change in inventories.
B. Investment refers to fixed asset investment (urban area). Deflated by fixed asset investment priceindex. Last observation is 2018Q1.
C. Current account balance is based on seasonally adjusted data. Net capital flows and change inreserves are estimates. Last observation is 2018Q1 for the current account balance.
D. Credit refers to total loans in domestic and foreign currency. Last observation is 2018Q1.
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Over the medium term, structural factors—
including slower growth of global value chains anda reduced appetite for further trade liberalization—will continue to constrain global trade
growth. These factors have contributed to thedecline in the long-run income elasticity of tradeover the last decade.
On trade policy front, the outcome of some tradenegotiations is still uncertain, and the risk of
escalating trade restrictions has intensified, as new
tariff announcements by the United States have
led to retaliatory responses by major trading
partners. In other policy developments, theEuropean Union and the United Kingdom
reached agreement on guidelines for trade

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.8 Global trade
Goods trade was particularly strong in 2017, supported by solid flows in
Asia and Europe, while services trade also recovered. However, trade
growth is moderating and should continue to ease in 2019-20 as global
investment decelerates, while structural factors are still weighing on theincome elasticity of trade. Trade flows between the United States andChina have been the subject of intense policy discussions.

A. Global goods trade growth,volumes

B. Goods trade growth between major
regions in 2017, values

C. Global goods and services trade,valuesD. Global trade and investment
growth, volumes

E. Income elasticity of trade

F. Trade flows between the UnitedStates and China

Sources: CPB Netherlands Bureau for Economic Policy Analysis, International Monetary Fund, U.S.
Census Bureau, World Bank, World Trade Organization (WTO).
A. Dashed horizontal line indicates the historical median, which is computed from January 2001 to
March 2018. Last observation is March 2018.
B. Global trade growth from 2016 to 2017. Average of export and import values. Bilateral trade flows
measured using the Direction of Trade Statistics. Last observation is December 2017.
C. Trade measured as the average of export and import values. GDP measured in current U.S.
dollars. Data are 4-quarter moving averages, indexed to 100 in 2005Q4. Last observation is 2017Q4.
D. Trade measured as the average of export and import volumes. Shaded area indicates forecasts.
E. Income elasticity measured as the ratio of real trade growth to real GDP growth. Horizontal line
denotes an income elasticity of one, which would indicate a proportional relationship between income
and trade.
F. Figure shows top five traded goods categories based on 2017 trade values in U.S. dollars. Man.
denotes miscellaneous manufactured goods, plastics refers to plastic and rubber goods, and metals
is base metals.
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negotiations, the U.S.-Korea Free Trade
Agreement was successfully re-negotiated, theComprehensive and Progressive Trans-PacificPartnership (CPTPP) was signed by 11 member
countries, and leaders from more than 40 African
nations endorsed a framework establishing afuture African Continental Free Trade Area.
Financial markets
Following a prolonged period of stable andexceptionally favorable global financing conditions, prospects of a faster withdrawal of monetary
policy accommodation in advanced economies
have led to rising global borrowing costs since thestart of 2018. In particular, U.S. long-term yields
have hovered around 3 percent, their highest level
since mid-2014, as inflation expectations pickedup and markets factored in the possibility ofaccelerated interest rate hikes by the Federal
Reserve, amid expanded U.S. fiscal stimulus
measures (Figure 1.9). This reassessment—alongwith fears of escalating trade tensions and risinggeopolitical risks—contributed to bouts ofvolatility in global equity markets in the first halfof 2018. Concerns in some advanced economies
about overstretched stock valuations, as well as theincreasing use of complex derivatives allowing
investors to make bets on volatility, have also
amplified price movements (BIS 2018b).
Looking forward, global interest rates are expected
to rise at a faster pace than previously predicted, as
upward revisions to the U.S. growth outlook leadto a somewhat steeper pace of U.S. interest rate
hikes in 2019-20 (FOMC 2018). Above-trend
growth and narrowing economic slack will also
lead to further monetary policy normalization inother advanced economies. Policy interest rates inthe Euro Area and Japan are not expected toincrease before 2019, but a drawdown of net asset
purchases by major central banks is projected to
put upward pressure on global long-term yields.
In particular, the European Central Bank is
expected to bring its asset purchase program to aclose by the end of 2018, and the U.S. Federal
Reserve is on track to shrink its balance sheet by 4
percent of GDP by the end of 2020. The latter
reduction could add a cumulative 40 basis points
to U.S. long-term yields over the same period(Bonis, Ihrig, and Wei 2017).

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

A rise in global interest rates, combined with U.S.
dollar appreciation, have contributed to tighter
external financing conditions for EMDEs in2018. In particular, some EMDE currencies havefallen sharply. More generally, capital inflows to
EMDEs have decelerated. During recent periodsof financial market volatility, EMDEs experienced
portfolio outflows, reminiscent to those during
previous episodes. Credit quality has continued todeteriorate, leading to further debt rating
downgrades in several countries in 2018.
Although appetite for higher-yielding EMDE
debt has diminished and borrowing costs haveincreased, international bond issuance remains
robust, so far matching the record levels observedin 2017. The pace of international debt issuance iscurrently driven by corporate borrowing in China
and a significant uptick in sovereign issuance in
Sub-Saharan Africa.
Foreign direct investment (FDI) flows to EMDEs
continue to be subdued, as flows to China remain
below their long-term trend and the recent
recovery in commodity prices has not been
sufficient to stimulate a significant revival ofinvestment in resource sectors. Increased participation in more complex global value chains could
foster stronger FDI in many countries,
particularly in Sub-Saharan Africa (World Bank et
al. 2017; Amendolagine et al. 2017). Over theforecast horizon, capital flows to EMDEs are
expected to further moderate, as global financing
conditions continue to tighten. Investors are also
likely to increasingly differentiate among
countries, depending on their exposure to risinginterest rates and currency pressures.

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19

FIGURE 1.9 Global finance
U.S. long-term yields have increased this year, reflecting rising inflation
expectations and prospects of a faster pace of U.S. interest rate hikes. This
contributed to bouts of stock market volatility, higher borrowing costs, andcapital outflows in EMDEs. However, EMDE debt issuance remained solid,so far matching record levels reached in 2017. As global bond yields are
expected to continue to increase, capital inflows to EMDEs are likely tomoderate further.

A. U.S. yield curve since the start of
the tightening cycle in December 2015

B. Global equity market

C. Long-term U.S. and EMDE bondyields

D. EMDE portfolio flows during
selected episodes

E. EMDE international bond issuance

F. Capital inflows to EMDEs

Commodities
Crude oil prices rose 10 percent in the firstquarter of 2018 and have averaged $67 per barrel(bbl) over the first half of 2018 (Figure 1.10).
Oil demand has been robust, with consumption
increasing 1.6 million barrels per day (mb/d),or 1.6 percent, in the first quarter of 2018 froma year earlier. An agreement between mostOrganization of the Petroleum ExportingCountries (OPEC) members and some nonOPEC oil producers to extend output cuts to theend of 2018 boosted prices in late 2017 and into
2018—despite further increases in U.S. oil

Sources: Bloomberg, Dealogic, Federal Reserve Bank of St. Louis, Haver Analytics, Institute ofInternational Finance, J.P. Morgan, U.S. Department of the Treasury, World Bank.
A. Yield values from the yield curve at fixed maturities, from 3 months to 30 years. Last observation is
May 25, 2018.
B. World MSCI indices are weighted benchmarks that use large- and mid-cap securities in emerging
and developed markets, respectively, in order to reflect market conditions across relevant regions
and sectors. Volatility is measured by the VIX implied volatility index of option prices on the U.S. S&P
500. Last observation is May 25, 2018.
C. EMDE long-term yields are estimated using the U.S. 10-year treasury yield augmented by J.P
Morgan’s Emerging Market Bond spread (excluding Venezuela). Last observation is May 21, 2018.
D. Horizontal axis indicates number of days of outflows since event. The 2018 global market
correction starts on April 15, 2018. Last observation is May 25, 2018.
E. Last observation is May 2018.
F. Shaded area indicates forecasts. Total non-resident inflows. The 23 EMDEs in the sample include
Argentina, Brazil, Chile, China, Colombia, Egypt, Hungary, India, Indonesia, Lebanon, Malaysia,
Mexico, Nigeria, Philippines, Poland, Russia, Saudi Arabia, South Africa, Thailand, Turkey, United
Arab Emirates, Ukraine, and Venezuela.
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FIGURE 1.10 Commodity markets
Crude oil prices rose substantially over the first half of 2018 amid robust
demand and supply concerns related to recent geopolitical developments,
despite rising U.S. oil production. Metals prices increased in the first half ofthe year following a pickup in demand from China. Grain stocks, ingeneral, remain very high, which will continue to weigh on agricultural
prices, while soybean production has fallen substantially.

A. Crude oil prices

B. Contribution to oil consumption
growthC. Crude oil production

D. Contribution to metals demand
growth

E. Soybean production

F. Stocks-to-use ratios of main grains

Sources: Bloomberg, Energy Information Administration, International Energy Agency, U.S.
Department of Agriculture, World Bank, World Bureau of Metal Statistics.
A. Average of Brent, Dubai, and WTI. Weekly data. Last observation is May 25, 2018.
B. Shaded area (2018Q2-2018Q4) represents IEA projections.
C. Data for Saudi Arabia are unavailable before 1984. Last observation is April 2018 for Saudi
Arabia and February 2018 for the United States.
D. Last observation is March 2018.
E.F. Data reflect the May 10, 2018 update of the USDA’s World Agricultural Supply and Demand
Estimates. Years represent crop seasons (e.g., 2016 refers to 2016-17 crop season).
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production, which reached an estimated 10.6
million barrels per day in April.
Geopolitical concerns boosted the price of Brent
crude in May to $80/bbl, its highest level since2014, after the U.S. government announced that
it would reinstate sanctions on the Islamic
Republic of Iran. Although there is considerable
uncertainty regarding the ultimate impact of the
sanctions, it is possible that they will reduce
Iranian exports by several hundred thousandbarrels per day. The rise in oil prices was partiallyreversed in late May on news that Saudi Arabia
and Russia were discussing an easing ofproduction caps, by up to 1mb/d, given concerns
about weaker oil supply and higher prices.
Oil prices are expected to average $70/bbl in 2018
and $69/bbl in 2019, up $12/bbl in 2018 and$10/bbl in 2019 relative to January forecasts.
Upside price risks primarily arise from geopoliticaldevelopments involving key oil-producers in the
Middle East and North Africa—particularly thoserelated to the reinstatement of sanctions on Iran.
In addition, the recent imposition of sanctions on
República Bolivariana de Venezuela could lead tofurther declines in Venezuelan oil production,
where output has already fallen 0.9 mb/d over the
past two years. Downside price risks include aloosening of the OPEC/non-OPEC planned cuts,
which could be decided at the June OPEC
meeting; faster-than-expected U.S. shale oil
production; or lower demand for oil as a result ofhigher prices.
Metals prices, which increased 24 percent in2017 due to robust global demand andenvironmentally-driven supply cuts in China, rosemodestly in the first quarter of 2018. Prices posted
further gains in April, after the imposition of U.S.
sanctions on a large Russian aluminum producer.
Metals prices are expected to increase 9 percent in
2018, reflecting strong demand, but thenmoderate in 2019. Upside risks to prices include
stricter pollution-control policies in China orstronger-than-expected demand, since China
accounts for about half of global metals
consumption (Special Focus 1). A broadening of
sanctions on key metals producers could also leadto higher prices.
Agricultural prices gained 4 percent during thefirst half of 2018 compared to a year earlier,following three years of price stability. The priceuptick was primarily driven by lower plantings of

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

wheat and maize in the United States, as well assome weather-related disruptions to soybean
production in South America. Lower plantings
have contributed to a decline in stocks-to-use
ratios—a measure of global supply availability
relative to demand—for some grains. However,these remain high by historical standards, reducing
the likelihood of a food price spike.

Emerging and developing
economies: Recent
developments and outlook
EMDE growth is expected to reach 4.5 percent in2018. The rebound in commodity exporters has
continued, and activity in commodity importers
remains robust. Beyond this year, however, EMDE
growth is projected to strengthen only slightly,
approaching its potential pace, as the recovery incommodity exporters matures. Over the forecasthorizon, commodity exporters and importers will see
uneven progress in per capita income growth, which
is projected to remain subdued in Sub-SaharanAfrica.
Recent developments
Growth in EMDEs accelerated to 4.3 percent in2017 and has generally continued to firm in 2018.
This reflects an ongoing cyclical upturn incommodity exporters, whose contribution to
overall EMDE growth is rising, as well as robust
activity in commodity importers (Figure 1.11).
The recovery in commodity exporters has
broadened, as investment has strengthened amid
higher commodity prices, rising corporate
earnings, and supportive monetary policies.
Private consumption growth has also firmed,
benefiting from improving labor markets
and rising household income amid moderating
inflation. Trade flows have risen, although byvarying degrees. In commodity importers, growth
remains strong, supported by robust domestic
demand and solid exports. Activity in EMDEs
excluding China has firmed, led by countries
in Europe and Asia, which have particularly
benefited from the recovery of global manufacturing, investment, and trade.

CHAPTER 1

Recent economic activity data and sentimentindicators across EMDEs—including confidence,industrial production, and purchasing managers
indexes (PMIs)—have remained mostly solid.
However, some are showing signs of softening,
partly reflecting country-specific developments. In
particular, confidence has deteriorated in somelarge EMDEs that have recently experienced
financial market stress.
Commodity-exporting EMDEs
After a strong rebound in 2017, activity incommodity exporters has continued to pick up in
2018 (Figure 1.12). The recovery is expected tocontinue in a majority of countries in this group.
Almost all economies that experienced a recession
in the past two years—about 20 percent ofcommodity exporters in 2016 and about 10
percent in 2017—are expected to see positive
growth this year.
Many commodity exporters have eased monetary
policy as inflation moderates (e.g., Azerbaijan,
Brazil, Colombia, Kazakhstan, Mozambique,Peru, Russian Federation, Uganda, South Africa,
Zambia). Although fiscal consolidation continues,
its pace has generally diminished as revenues from
commodity exports increased. Higher commodity
prices and robust trade have supported theongoing recovery.
Against this backdrop, investment is rebounding
in more than two thirds of commodity exporters.
This partly reflects increased commodities
production (e.g., Chile, Nigeria, Peru ), as well aslarge infrastructure investment programs (e.g.,
Colombia, Côte d’Ivoire, Qatar, Saudi Arabia,
Senegal, United Arab Emirates). Private
consumption is also recovering (e.g., Armenia,
Azerbaijan, Brazil, Kazakhstan, Russia, South
Africa, United Arab Emirates, Zambia), boosted
by wage gains, improving labor markets, andstronger consumer purchasing power amid
moderating inflation and firming currencies. To
varying degrees, export and import growth incommodity exporters have generally continued torecover, as domestic demand strengthens andglobal trade remains robust.

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.11 Activity in EMDEs
EMDE growth has generally continued to strengthen, mainly reflecting theongoing cyclical recovery in commodity exporters. Domestic demand,
particularly investment, has firmed in commodity exporters and remains
robust in commodity importers. High-frequency indicators have for themost part remained solid, but they are showing signs of softening.

A. Growth

B. Contribution to EMDE growth

C. GDP and demand component
growthD. Business confidence

E. Industrial production growth

F. Manufacturing PMIs

Sources: Haver Analytics, Organisation for Economic Co-operation and Development, World Bank.
A.-C. Shaded areas indicate forecasts. Aggregate growth rates calculated using constant 2010 U.S.
dollar GDP weights.
B. Horizontal line indicates EMDE average.
D. Median of confidence index for Brazil, Chile, Colombia, Hungary, Indonesia, India, Mexico, Poland,
Russia, Turkey, and South Africa. Confidence is normalized through amplitude adjustments, such thatany cyclical movements have the same amplitude and the long-term average of a respective country
series is equal to 100. Last observation is April 2018.
E.F. Figures show 3-month moving averages.
E. Dashed horizontal lines indicate 1995-2017 averages. Last observation is March 2018.
F. PMI = Purchasing Managers’ Index. Readings above 50 indicate expansion in economic activity;
readings below 50 indicate contraction. Dashed horizontal lines indicate January 2012-April 2018averages. Last observation is April 2018.
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Among the largest commodity exporters,
supportive policies in Brazil continue to underpina recovery of domestic demand (World Bank
2018c). In Russia, growth has remained stable,

albeit lackluster, as the impact of oil production
cuts and policy uncertainty has been offset bymore accommodative monetary policy and higher
oil prices (World Bank 2018d). In South Africa,
the political transition and economic reform
initiatives have supported investor confidence andcontributed to stronger activity this year (WorldBank 2018e). Recent indicators for these
economies have, however, been mixed, highlighting lingering headwinds.
The cyclical recovery continues in several otherlarge commodity exporters with negative output
gaps (e.g., Azerbaijan, Colombia, Saudi Arabia,
United Arab Emirates; World Bank 2018d, WorldBank 2018f). In particular, in oil-exporting
economiesthat
implemented
significant
reductions in oil production in 2017 (e.g., Algeria,
Iraq, Kuwait), growth has been recovering thisyear, reflecting diminishing fiscal adjustment amid
substantially higher oil prices and easing oil
production cuts (World Bank 2018f). In contrast,
activity remains weak in energy exporters thatdelayed policy adjustment to the earlier terms-oftrade shock, or that face country-specificchallenges such as exchange rate misalignments,social tensions, and security issues (e.g., Equatorial
Guinea, Venezuela). In all, growth in many energy
exporters continues to lag that of exporters ofother commodities.
Activity continues to show resilience in a numberof more diversified economies and agriculture
exporters (e.g., Benin, Burkina Faso, Côte
d’Ivoire, Ethiopia, Indonesia, Malaysia, Morocco,
Senegal, Uganda; World Bank 2018e). Supported
by higher metals prices, growth among metals
exporters continues to improve, albeit at varying
degrees, reflecting country-specific conditions. In
some economies, temporary disruptions previously
weighing on growth (e.g., policy uncertainty in
Peru, mining strikes in Chile) have dissipated. In
others, new mines are coming on stream andinvestment into existing mines continues (e.g.,
Armenia, Mongolia, Zambia).
Commodity-importing EMDEs
Growth in commodity importers remains strong,
although it is moderating somewhat this year

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

(Figure 1.13). With output gaps closed, or inmany cases positive, capacity constraints are
becoming increasingly binding. Accommodative
policies and solid labor markets have continued tosupport domestic demand in a number of economies. However, with price and wage pressuresrising, and amid markedly higher oil prices, several
large commodity importers have begun to tighten
policies (e.g., Georgia, Pakistan, the Philippines,
Romania, Turkey). The moderation in activity ismost notable in countries where highly
accommodative policies are being scaled back or
financial markets have shown signs of strain.
Aggregate investment in commodity importers
excluding China remains solid, partly reflecting acyclical rebound in Mexico and Thailand, where it
was previously held back by country-specificfactors (World Bank 2018b). In India, investment
growth has firmed recently, as the effects of
temporary factors wane. Still robust sentiment andsupport from European Union structural funds
are bolstering investment in Europe and Central
Asia. Investment in EMDEs in Asia is receiving an
additional boost from pan-Asian infrastructure
initiatives, supported by the China-led Belt andRoad initiative (e.g., Bangladesh, Cambodia,
Pakistan, Sri Lanka; World Bank 2018b; WorldBank 2018g).
Trade flows have continued to firm this year,
although to varying degrees, reflecting strong
global manufacturing activity, trade, andinvestment, as well as stronger intra-regional trade,
especially in emerging Asia and Europe. Robust
investment and exports are boosting demand forimports of machinery, equipment, and intermediate goods.
Positive trade and financial spillovers fromstronger Euro Area growth and steady activity in
Russia are supporting activity in Europe andCentral Asia, and in the Middle East and North
Africa (e.g., Belarus, Bosnia and Herzegovina,
Bulgaria, Arab Republic of Egypt, Georgia,
Hungary, Jordan, former Yugoslav Republic ofMacedonia, Moldova, Poland, Romania, Tunisia).
Asian economies continue to benefit from robust
growth in China and India, including resurgent
trade and substantial infrastructure investment(e.g., Cambodia, Maldives, Sri Lanka, Thailand,

CHAPTER 1

23

FIGURE 1.12 Activity in EMDE commodity exporters
The recovery in commodity exporters continues to reflect improvements inlarge economies, but it is also broad-based across countries. Investment isstrengthening amid higher commodity prices and greater monetary policy
accommodation. Despite a notable increase in energy prices, growth inmany energy exporters continues to lag behind that of other commodity
exporters, mainly due to ongoing production cuts.
A. Contribution to growth

B. Share of commodity exporters withincreasing/decreasing growth

C. Contribution to investment growth

D. Growth

Source: World Bank.
A.-D. Shaded areas indicate forecasts.
A.B. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights.
B. Sample includes 85 commodity-exporting EMDEs. Increasing/decreasing growth are changesof 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.
C. Investment refers to fixed asset investment.
D. Simple average of GDP growth. Orange lines indicate interquartile ranges of growth in each group.
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Vietnam). In Latin America, growth in Mexico isimproving, reflecting positive spillovers fromstrong U.S. growth, which have been offsetting
the uncertainties related to the renegotiation of
NAFTA and upcoming elections.
Low-income countries
The economic recovery among low-income
countries (LICs) is firming (Box 1.2). Among
metals exporters, mining production is increasing,as new projects come onstream and investment in
the expansion of existing mines continues,
encouraged by the recovery in metals prices (e.g.,
Democratic Republic of Congo, Guinea). Oil

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

BOX 1.2 Low-income countries: Recent developments and outlook

Growth in low-income countries is expected to rise to 5.7 percent in 2018 and to an average of 6.1 percent in
2019-20, from 5.5 percent in 2017. This upswing reﬂects rising mineral production, spurred by higher oil and metals
prices, improving agricultural output, and continued infrastructure investment. However, poverty headcounts areprojected to decline only slightly. The main downside risks to the outlook are lower commodity prices, heightened
policy uncertainty, and weak implementation of reforms.
Recent developments
Economic activity has strengthened in most lowincome countries (LICs), helped by favorable external
conditions (Figure 1.2.1).1 Among metals exporters,
mining production has risen, as new projects cameon stream and investment in the expansion ofexisting mines continued, encouraged by higher
metals prices (e.g., Democratic Republic of Congo,
Guinea). Nevertheless, in some cases, high government debt levels are weighing on activity (e.g.,
Mozambique, Sierra Leone). Among non-resourceintensive countries, the economic pickup is
supported by improving agricultural output
following droughts and continuing infrastructure
investment (e.g., Rwanda, Uganda). In somecountries, rising household spending, helped by low
inflation and recovering remittance flows, has
underpinned the economic expansion, along withsome improvement in political stability (e.g., The
Gambia, Haiti). However, oil exporters (e.g., Chad)are struggling to emerge from recession as they
continue to adjust to the sharp decline in oilrevenues.
Poverty levels are high in most LICs. Nearly half ofthe population in LICs continues to live below theinternational poverty line—$1.90 a day, at 2011
purchasing power parity (PPP) exchange rates. The
proportion of the LICs’ population below thepoverty line is higher in Sub-Saharan Africa (SSA)
than in other regions, reflecting the relatively slow
decline in poverty levels among fragile countries andmetals exporters in SSA (Beegle et al 2016).

Note: This box was prepared by Gerard Kambou. Research assistance
was provided by Xinghao Gong.
1 For the current 2018 ﬁscal year, low-income economies are deﬁned as
those with a gross national income (GNI) per capita, calculated using theWorld Bank Atlas method, of $1,005 or less in 2016.

Current account deficits are widening in many
countries. They are rising among metals exporters,
reflecting the effects of a pickup in import-intensivemining investment. In non-resource-intensive countries, these deficits are expected to widen, as import
growth remains strong due to high public investment
levels. However, in oil exporters, the marked
improvement in current account deficits in 2017 is
expected to continue, helped by higher oil prices andsubdued import growth due to soft domestic
demand. Foreign reserve positions have gradually
improved. However, in many countries, foreign
reserves are well below the three-month-of-imports
benchmark, indicating continued vulnerability toterms-of-trade shocks.
Exchange rates have been broadly stable in realeffective terms, reflecting tight domestic policies insome countries. Remittances have also rebounded,following two years of decline (World Bank 2017b).
Non-oil foreign direct investment flows have risen insome countries (e.g. Ethiopia, Guinea), and portfolio
inflows have continued, led by sovereign bondissuances (e.g., Senegal). Inflation continues to fallacross LICs, helped by declining food prices,
prompting central banks in some countries to further
cut interest rates (e.g., Mozambique, Uganda).
However, inflationary pressures are high in several
countries, owing to currency depreciations (e.g.,
Democratic Republic of Congo, Ethiopia, Liberia).
Fiscal deficits have gradually narrowed across LICs.
The improvement reflects strong fiscal adjustment insome oil exporters (e.g., Chad), and an increase indomestic revenue among non-resource-intensive
countries where commodity revenues account for asmaller share of total revenue. Fiscal deficits remain
elevated among metals exporters, as governments
struggle to raise revenue and control spending.
Debt levels are high and rising across a wide range of
LICs, especially in SSA (IMF 2018). This is raisingG LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

CHAPTER 1

BOX 1.2 Low-income countries: Recent developments and outlook (continued)
FIGURE 1.2.1 Recent developments in low-income countries
The rebound in activity in low-income countries (LICs) has continued. Output and investment have picked up in oil and metals
exporters, encouraged by higher commodity prices. Fiscal and current account deficits are narrowing among oil exporters,
reflecting strong fiscal adjustment, but are rising among metals exporters due to high expenditure and import levels. In nonresource-intensive countries, rising domestic revenue is helping reduce fiscal deficits, but current account deficits are
widening, as import demand remains strong. Debt burdens are high, especially among metals exporters. The poverty
headcount is also high among metals exporters, reflecting persistently low per capita growth.
A. Growth

B. Investment growth

C. Current account balance

D. Fiscal balance

E. Government debt

F. Poverty

Sources: Haver Analytics, International Monetary Fund, World Bank.
Notes: LICs = low-income countries. Non-resource-intensive countries include agricultural-based economies and commodity importers.
A. GDP-weighted averages.
B.-E. Median of country groups.
F. Based on the international poverty line of $1.90 a day, at 2011 purchasing power parity (PPP) exchange rates. Shaded area indicates forecasts.
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concerns about debt sustainability in some countries(Devarajan 2018). Debt levels among metals
exporters are increasing, reflecting previously
undisclosed borrowing in Mozambique and low
domestic revenue in other economies (e.g., Liberia,
Sierra Leone). Although fiscal consolidation efforts
are helping to stabilize debt levels among oil
exporters, the debt burden remains high in some ofthem (e.g., Chad). A large part of Chad’s debt is
owed to commercial creditors. Debt levels among
non-resource-intensive countries are also elevated(e.g., The Gambia), and continue to rise in somecases (e.g., Ethiopia). In The Gambia, the deteriora-tion in the debt-to-GDP ratio partly reflects
governance issues, including the weak managementof state-owned enterprises. In Ethiopia, low publicsaving rates and high public investment arecontributing to the increase in government debt. The
high and rising debt levels point to the need forsignificant fiscal consolidation, as well as higher
domestic revenue in a number of LICs.
Outlook
Growth in LICs is expected to pick up to 5.7 percent
in 2018, and strengthen to an average of 6.1 percent
in 2019-20, slightly below the level reached earlier in

25

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

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

the decade (Figure 1.2.2). This upswing is predicatedon firming commodity prices and policy actions totackle macroeconomic imbalances. These forecasts
are higher than in January, and reflect a strongerthan-expected recovery in some metals exporters, as
higher metals prices help boost mining production.
In metals exporters such as Mozambique, growth willremain subdued, reflecting the effects of rising debt
levels on investor sentiment. The recovery in oil
exporters will also be slower than previously
envisioned, as the fiscal adjustment that is stillneeded to stabilize government debt is expected toweigh on growth.
Growth among non-resource-intensive countries is
expected to remain robust, supported by increasing
agricultural production, high public investment
levels, and rising remittance flows, with the larger
economies expanding at a faster pace. Although
growth in Ethiopia—the largest LIC—is projected tosoften as policy tightens to contain inflationarypressures, it will remain high. In some smaller
economies (e.g., The Gambia, Haiti), improved
political stability will allow for a modest pickup in
activity, as opportunities for reforms boost investor
sentiment; however, in fragile countries, security
concerns will continue to weigh on investment (e.g.,
Afghanistan, Burundi). In Malawi, growth isexpected to be lower than anticipated, reflecting theadverse effects of a dry spell and the spread of the fallarmyworm—a pervasive agricultural pest—on foodproduction.
Per capita GDP growth is projected to rise from 1.6
percent in 2017 to 2.3 percent in 2018, and to an
average of 2.5 percent in 2019-20. Nonetheless, theeffect on poverty alleviation seems likely to be
subdued. The poverty headcount among LICs is
projected to decrease only modestly, and decline
most slowly among fragile countries and metals
exporters in SSA. Higher population growth isworsening the poverty headcount. Furthermore,
growth for a significant proportion of LICs in SSA
centers around capital-intensive sectors, which
contribute less to poverty reduction (Bhorat and

FIGURE 1.2.2 Outlook
The ongoing recovery in LICs is expected to pick up
further this year and firm in 2019-20, reflecting a gradualrebound among oil and metals exporters and continued
robust growth in non-resource-intensive countries.
However, per capita income growth will recover only
slowly among oil exporters and remain modest amongmetals exporters.
A. GDP growth forecasts

B. Per capita GDP growth

Source: World Bank.
Note: Shaded area indicates forecasts.
A. GDP-weighted averages.
B. Median of country groups. Non-resource-intensive countries include
agricultural exporters and commodity importers.
Click here to download data and charts.

Tarp 2016). These structural constraints will prevent
faster poverty reduction unless structural reforms are
introduced to increase productivity and support
economic diversification (Chapter 1).

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

CHAPTER 1

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

TABLE 1.2.1 Low-income country forecastsa(Real GDP growth at market prices in percent, unless indicated otherwise)
2015
2016
2017e
2018f
Low Income Country,
4.9
4.8
5.5
5.7
GDPb
Afghanistan
1.3
2.4
2.6
2.2
Benin
2.1
4.0
5.6
6.0
Burkina Faso
3.9
5.9
6.4
6.0
Burundi
-3.9
-0.6
0.5
1.9
2.8
-6.3
-3.0
2.6
Chad
Comoros
1.0
2.4
2.5
2.9
6.9
2.4
3.4
3.8
Congo, Dem. Rep.
Ethiopiac
10.4
7.6
10.3
9.6
Gambia, The
4.3
2.2
3.5
5.4
Guinea
3.8
10.5
8.2
6.0
Guinea-Bissau
6.1
5.8
5.7
5.1
1.2
1.5
1.2
1.8
Haitic
0.0
-1.6
2.5
3.2
Liberia
Madagascar
3.1
4.2
4.1
5.1
2.8
2.5
4.0
3.7
Malawi
Mali
6.0
5.8
5.3
5.0
Mozambique
6.6
3.8
3.7
3.3
Nepalc
3.3
0.6
7.9
6.3
Niger
4.0
5.0
5.2
5.3
8.8
6.0
6.1
6.8
RwandaSenegal
6.5
6.7
6.8
6.8
-20.5
6.3
4.3
5.1
Sierra Leone
Tanzania
7.0
7.0
6.4
6.6
Togo
5.3
5.0
4.4
4.8
5.2
4.7
4.0
5.5
Ugandac
Zimbabwe
1.7
0.6
3.4
2.7

Percentage point differences fromJanuary 2018 projections
2018f
2019f
2020f

2019f

2020f

5.9

6.3

0.3

0.4

0.6

2.5
6.1
6.0
2.3
2.5
3.0
4.1
9.7
5.2
5.9
5.2
2.4
4.7
5.6
4.1
4.7
3.4
4.5
5.4
7.1
6.8
5.7
6.8
5.0
6.0
3.8

3.3
6.3
6.0
2.5
5.8
3.0
4.4
9.9
4.9
6.0
5.4
2.4
4.8
5.3
4.9
4.7
3.6
4.2
5.8
7.5
7.0
6.5
7.0
5.0
6.5
4.0

-1.2
0.0
0.0
0.4
-1.1
0.2
0.8
1.4
1.9
0.2
-0.1
-0.4
-0.7
0.0
-1.3
0.0
0.1
1.7
0.1
0.9
-0.1
-1.2
-0.2
-0.5
0.4
1.8

-0.6
-0.2
0.0
-0.2
-0.4
0.1
0.8
1.9
1.0
0.0
-0.2
-0.1
-0.3
0.0
-1.3
0.0
0.0
0.0
0.0
0.3
-0.2
-1.0
-0.1
-0.4
0.3
3.6

0.2
-0.4
0.0
0.0
-1.0
0.1
1.1
2.1
0.7
0.1
0.0
-0.1
-1.2
-0.1
-0.5
0.0
0.2
-0.3
0.2
0.7
0.0
-0.2
0.1
-0.4
0.5
3.8

Source: World Bank.
World Bank forecasts are frequently updated based on new information and changing (global) circumstances. Consequently, projections presented here may differ fromthose contained in other Bank documents, even if basic assessments of countries’ prospects do not significantly differ at any given moment in time.
a. Central African Rep., Democratic People’s Republic of Korea, and Somalia 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.

Risks
Risks to the outlook remain tilted to the downside.
On the external front, a large drop in commodity
prices could have a significant impact on sentimenttoward LICs, given that many of these countries
depend on extractive industries. A collapse in oiland metals prices would also severely undermine
efforts at fiscal consolidation and to rein in the
public debt burden, and crowd out poverty-reducing
expenditures.
On the domestic front, while political uncertainty
has declined in some LICs, it remains a key risk for
growth and reform momentum. For example, in
Ethiopia, political tensions could intensify following
the reimposition of the state of emergency. Risks to

debt sustainability are also high in some LICs.
Inadequate fiscal adjustment or large currency
depreciation could lead to an increase in the cost ofservicing external debt. Based on the LIC debt
sustainability framework, The Gambia and Ethiopia
are deemed to be facing high risk of debt distress.
Chad and Mozambique were rated as in debt distressby end-2017. In addition, most LICs remain highly
vulnerable to weather-related shocks, and a return ofdrought conditions could severely disrupt ongoingrecoveries. The Ebola outbreak in the Democratic
Republic of Congo could slow economic activity inthe country and the sub-region, if it spreads fasterthan anticipated to major urban centers and toneighboring countries.

27

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.13 Activity in EMDE commodity importers,
excluding China
Growth in commodity importers excluding China remains solid but ismoderating somewhat this year, partly due to capacity constraints.
Investment growth continues to be robust, particularly in EMDE commodity
importers in Europe and Asia. Export growth has generally been strong thisyear, albeit to varying degrees.
A. Contribution to growth

B. Share of commodity importers withincreasing/decreasing growth

C. Contribution to investment growth

D. Export growth

Source: World Bank.
A.-D. Shaded areas indicate forecasts. Aggregate growth rates calculated using constant 2010 U.S.
dollar GDP weights.
A.C.D. Others refer to other commodity-importing EMDEs, excluding China.
B. Sample includes 60 commodity-importing EMDEs. Increasing/decreasing growth are changes of atleast 0.1 percentage point from the previous year. Countries with a slower pace of contraction fromone year to the next are included in the increasing growth category.
C.D. EAP = East Asia and Pacific, excluding China; SAR = South Asia; ECA = Europe and Central
Asia.
C. Investment refers to fixed asset investment.
D. Data refer to trade volume of goods and non-factor services.
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exporters (e.g., Chad) are slowly emerging fromrecession, helped by rising oil prices. In nonresource-intensive countries, the pickup ineconomic activity is being supported by improving
harvests following droughts (e.g., Rwanda,
Uganda), infrastructure investment (e.g., Benin,
Senegal), and consumer spending as inflation
moderates and remittances recover (e.g., The
Gambia, Haiti). However, debt burdens are highand rising in a number of LICs, reflecting a mix offactors including the disclosure of previously
unreported debt (e.g., Mozambique), governanceissues (e.g., The Gambia), the earlier plunge in oil
prices (e.g., Chad), and low public saving (e.g.,

Ethiopia). Poverty levels are elevated, especiallyamong LICs in Sub-Saharan Africa, where nearly
half of the population lives below the poverty line.
EMDE outlook
Growth outlook
EMDE growth is expected to accelerate from 4.3
percent in 2017 to 4.5 percent in 2018 andstabilize at 4.7 percent in both 2019 and 2020,reflecting a continued, but maturing, cyclicalrecovery in commodity exporters (Figure 1.14). In
the near term, the positive spillovers of U.S. fiscal
stimulus on EMDE activity are assumed to beoffset by a faster pace of U.S. monetary policy
normalization, which contributes to higher
borrowing costs and a moderation in EMDE
capital flows. Toward the end of the forecasthorizon, the projected slowdown in advancedeconomy growth toward potential rates is expected
to put a lid on further acceleration in EMDE
growth.
As global financing conditions continue totighten, the cyclical rebound in investment in
EMDEs, especially among commodity exporters,
is projected to moderate in 2019-20. Moreover,
the ongoing monetary policy easing in commodity
exporters is expected to gradually end, while fiscal
consolidation will continue, particularly in manyoil-exporting economies. Policies in commodity
importers are expected to tighten, as capacity
constraints become more binding and pricepressures accelerate amid higher energy prices.
Growth in commodity exporters is projected toplateau toward the end of the forecast horizon.
After reaching 2.5 percent in 2018—the highest
pace since 2013—it is projected to strengthen
only slightly and stabilize at an average of 3
percent in 2019 and 2020, as output gaps close
and labor market slack gradually diminishes. By
the end of the projection period, only about halfof commodity exporters are expected to grow at or
above their pre-crisis long-term averages. Forecasts
were adjusted slightly down from January, as an
upward revision to a number of large commodity
exporters (e.g., Angola, Brazil, Kazakhstan, South
Africa) was more than offset by a downgrade inG LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018some other economies (e.g., Argentina, Nigeria,
Venezuela). This overall outlook of a maturing
cyclical recovery is also reflected in forecasts for
EMDE regions with a substantial number ofcommodity exporters (Box 1.3; Chapter 2).

CHAPTER 1

FIGURE 1.14 EMDE growth prospects
The recovery in EMDE growth is projected to mature during the forecasthorizon, as negative output gaps in commodity exporters gradually narrowand investment growth stabilizes.
A. Growth

Growth in commodity importers is expected todecelerate to 5.8 percent in 2018 and edge further
down to 5.7 percent by 2020, broadly in line with
its potential rate. A structural slowdown in China
is expected to be partly offset by a moderate
pickup in other large economies, including India
and Mexico. In commodity importers excluding
China, an upgrade to growth projections in 2018reflects an upward revision to forecasts for somelarge economies (e.g., Egypt, Mexico, Poland,
Thailand).
Growth in low-income countries is projected topick up to 5.7 percent in 2018, and stabilize at
about 6.1 percent on average in 2019-20, slightly
below the level reached earlier in the decade (Box1.2). These forecasts are higher than in January,reflecting a stronger pickup in some metals
exporters as higher metals prices help boost
mining production. Growth in non-resourceintensive countries is projected to remain solid,
supported by increasing agricultural production,
infrastructure investment, and a rebound inremittances, with the larger economies expanding
at a faster pace. In some fragile countries (e.g.,
The Gambia, Zimbabwe), political transitions willallow for a pickup in activity, as opportunities forreforms boost investor sentiment. However, therecovery will be slower than previously anticipatedamong oil exporters, as they continue to adjust to
low oil revenue and the heavy burden of external
commercial debt.
Despite the projected firming of activity in
EMDEs in the near term, underlying potential
growth—which has fallen considerably over the
past decade—appears likely to decline further overthe long term, reflecting earlier investment
weakness, softening productivity, and increasingly
adverse demographic patterns. Trends in thesefundamental drivers of long-term growth suggestthat EMDE potential growth could decrease by
0.5 percentage point on average over 2018-27.
Notwithstanding its recent turnaround, investment growth in many EMDEs is still modest

29

B. Contribution to investment growth

Source: World Bank.
A.B. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights. Shaded area
indicates forecasts.
B. Investment refers to fixed asset investment.
Click here to download data and charts.

compared to its long-term average and will not be
sufficient to offset headwinds to potential growth.
Furthermore,
tightening global
financingconditions, higher borrowing costs, moderating
capital flows, and lingering policy uncertainty may
hamper investment growth in the coming years,
further constraining potential growth (WorldBank 2018a).
Outlook for per capita income and poverty
Current near-term growth prospects areencouraging but may not be sufficient to ensure
continued progress toward global poverty
alleviation (World Bank 2016). Countries that arehome to most of the world’s poor are expected to
grow at a faster clip than other EMDEs. However,their population growth is also generally higher,
implying that per capita prospects in thosecountries are still modest, particularly where
extreme poverty is more prevalent (Figure 1.15).
That said, significant disparities exist between theoutlooks for the two regions comprising morethan 80 percent of the world’s extreme poor:
South Asia and Sub-Saharan Africa. In South Asia,
GDP per capita growth remains significantly
above EMDE averages and will likely help afurther reduction in poverty rates in coming years.
In Sub-Saharan Africa, per capita income growthin countries with high poverty headcounts willremain modest, complicating efforts to reduce

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

BOX 1.3 Regional perspectives: Recent developments and outlook

The ongoing cyclical recovery in most EMDE regions with a substantial number of commodity exporters is projected tocontinue in 2018. Thereafter, the upturn in these regions is expected to mature, as commodity prices plateau. Robust
activity in EMDE regions with large numbers of commodity importers is forecast to continue. Risks to the growth
outlook continue to tilt to the downside.
FIGURE 1.3.1 Regional growth
The ongoing cyclical recovery in most EMDE regionswith a substantial number of commodity exporters is
projected to continue in 2018, but mature thereafter ascommodity prices level off. Robust growth in EMDE
regions with large numbers of commodity importers is
projected to continue. Risks to the growth outlook
continue to tilt down.
A. Regional growth, weighted average

B. Regional growth, unweighted average

Source: World Bank.
A.B. Averages for 1990-2017 are constructed depending on data availability.
For Europe and Central Asia, the long-term average uses data for 1995-2017
to exclude the immediate aftermath of the collapse of the Soviet Union.
A. Bars denote latest forecast; diamonds correspond to January 2018 Global
Economic Prospects forecasts. Since the largest economies account for
about 50 percent of GDP in some regions, weighted averages predominantly
reflect the development in the largest economies in each region.
B. Unweighted average regional growth is used to ensure broad reflection ofregional trends across all countries in the region.
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East Asia and Pacific. Growth in the region is
projected to moderate to 6.3 percent in 2018, andto 6.1 percent on average in 2019-20. The
structural slowdown in China will slightly offset amodest further pickup in the rest of the region.
While upside surprises to global activity could leadto stronger-than-expected regional growth, risks to
the regional forecast are tilted to the downside.
They include the possibility of an abrupt tighteningof global financing conditions and intensified trade
restrictions. Highly leveraged economies andcountries with large or rapidly rising fiscal deficits
are particularly vulnerable to disruptions in real andfinancial activity.
Europe and Central Asia. Regional growth isanticipated to ease to 3.2 percent in 2018, as
idiosyncratic factors supporting the recovery insome of the largest regional economies fade. Growthis expected to decline to 3 percent by 2020, as
activity moderates in commodity importers amid
increasing
capacity
constraints
andlessaccommodative fiscal and monetary policies.
Downside risks include the possibility of adisorderly tightening of financing conditions, lowerthan-projected oil prices, and heightened policy
uncertainty. If stronger-than-expected demand fromadvanced economies were to materialize, it would
benefit trading partners in the region.
Latin America and the Caribbean. The modest
regional recovery is projected to continue, withgrowth anticipated to rise to 1.7 percent in 2018
and average 2.4 percent in 2019-20. In the nearterm, the pickup will be supported by a cyclicalrecovery in Brazil and improving conditions inChile, Colombia, Mexico, and Peru. Regional
Note: This box was prepared by Carlos Arteta with contributions
from Gerard Kambou, Yoki Okawa, Temel Taskin, Ekaterine
Vashakmadze, Dana Vorisek, and Lei Ye. Research assistance wasprovided by Jinxin Wu.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

CHAPTER 1

BOX 1.3 Regional perspectives: Recent developments and outlook (concluded)

growth through 2020 will mainly reflect firming
private consumption and investment. Downside risks
are significant, however, including negative spillovers
from a possible abrupt tightening of financing
conditions or shift in investor sentiment regarding
EMDEs, a breakdown in NAFTA negotiations or arise in U.S. trade protectionism, escalation ofdomestic policy uncertainty, and disruptions fromnatural disasters. Larger-than-expected spillovers
from the U.S. fiscal stimulus could result in stronger
regional growth.
Middle East and North Africa. Growth in the region
is expected to rebound from last year—when it
decelerated to 1.6 percent due to oil production cuts
and fiscal adjustments among oil exporters—andreach 3 percent in 2018. Activity among oil exporters
is picking up in response to an easing of fiscal stancesand momentum from the non-oil sector, while oil
importers continue to benefit from improved
competitiveness and foreign-investor confidence.
Regional growth is projected to accelerate to an
average of 3.3 percent in 2019-20, as domestic
demand and exports further improve in both oil
exporters and importers. The key downside risks aregeopolitical tensions, renewed volatility in oil prices,and slower-than-expected pace of reforms. Rapid
reconstruction progress in war-torn areas represents
an important upside risk.
South Asia. Growth in the region is projected toaccelerate to 6.9 percent in 2018, mainly reflecting
strengthening domestic demand in India as
temporary policy-driven disruptions fade. Elsewherein the region, ongoing recoveries in Bangladesh,poverty rates. Per capita GDP growth is expected
to stagnate among many oil and metals exporters
in the region, where poverty headcounts are
already high.
More generally, per capita income growth incommodity-exporting EMDEs, which has been
weak in recent years, is expected to recover

Pakistan, and Sri Lanka are expected to beaccompanied by moderating activity in Afghanistan,
Bhutan, and Maldives. Over the medium term,
growth is expected to remain strong and reach 7.2
percent by 2020 amid robust domestic demand.
Downside risks continue to predominate. They
include the possibility of fiscal slippages, delays inreforms to resolve financial vulnerabilities andimprove the health of regional banking systems, anda faster-than-expected tightening in global financing
conditions. Stronger-than-envisioned global growth
could result in better regional growth outcomes.
Sub-Saharan Africa. Regional growth is projected toaccelerate to 3.1 percent in 2018. This upswing
reflects rising oil and metals production, encouraged
by a recovery in commodity prices, and improving
agricultural production following droughts. A
rebound in consumer spending amid declining
inflation and an increase in investment also underpin
the pickup. Growth is expected to firm to an averageof 3.6 percent in 2019-20, as the recovery
strengthens in Angola, Nigeria, and South Africa—
the region’s largest economies. However, growth willremain below its long-term average and insufficient
to substantially reduce poverty. Public debt levels arehigh and rising, and debt servicing costs will absorb alarge share of government revenue in some countries.
The main downside risks include a faster tighteningof global financing conditions, lower-than-expectedcommodity prices, heightened conflicts, and weak
implementation of reforms. Renewed growth
momentum in advanced economies could provide
positive spillovers to the region.

modestly throughout the forecast horizon.
Nevertheless, it will remain appreciably below thatthat of commodity importers. Per capita income
growth will be particularly weak in a number ofoil exporters. At the projected pace, growth will beinsufficient to restart the catch-up of income percapita with advanced economies in about onethird of EMDEs.

31

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.15 Per capita growth and poverty in EMDEs
Countries with the largest number of poor are expected to grow at asomewhat faster clip in 2018-20; however, per capita growth in SubSaharan Africa is projected to remain subdued, despite some recovery. In
about one-third of EMDEs, income per capita growth will be insufficient incoming years to restart a catch-up process with advanced economies.
A. Per capita growth in EMDEs

B. Regional poverty headcounts

C. Per capita growth, by region

D. Share of EMDEs catching up toadvanced-economy GDP per capita
levels

Source: World Bank.
A.C.D. Shaded areas indicate forecasts.
B.C. 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. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights. The povertyweighted estimate of the per capita GDP growth excludes countries for which poverty head counts
were not available.
B. Blue bars indicate the number of people living on or below the international poverty line of $1.90
per day, red bars are the number of people living on or below the lower-middle income poverty line of$3.20 per day. Data as of 2016.
D. EMDEs with per capita GDP growth of at least 0.1 percentage point higher than advancedeconomy per capita GDP growth are those counted as converging. Advanced-economy growth rates
calculated using constant 2010 U.S. dollar GDP weights. Sample includes 73 EMDE commodity
exporters and 44 EMDE commodity importers.
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Risks to the outlook
Risks to the outlook remain tilted to the downside.
They include the possibility of disruptive financial
market developments and escalating trade protectionism amid elevated policy uncertainty. If a
combination of downside risks were to materialize, it
could trigger a sharper-than-expected slowdown inglobal growth, with particularly negative effects forcountries with depleted policy buffers and sizable
vulnerabilities. There is also the possibility thatgrowth in major economies may surprise on theupside, with positive spillovers to trading partners.

Baseline forecasts point to global growth at 3.1
percent this year, helped by still-solid growth inadvanced economies, robust activity in Asia, and acyclical recovery in commodity-exporting
EMDEs. However, with growth currently
surpassing its estimated potential, world economic
activity is expected to moderate in 2019 and 2020,
as major central banks remove post-crisis accommodation, global capacity constraints become
more binding, China’s structural slowdown
continues, and the upturn in commodity exporters
levels off. With the rise of global interest rates,
debt service costs will increase in both advanced
economies and EMDEs. Shifting policies in major
economies will have a significant bearing on theoutlook and risks for global growth.
Risks to the outlook are tilted to the downside,with some becoming more acute (Figure 1.16).
Following a prolonged period of exceptionally low
interest rates and elevated asset prices, financial
market risks have increased. A sudden tighteningof global financing conditions could be triggeredby a reassessment of inflation risks; by shifting
expectations about monetary policies across majoradvanced economies; or by increased concerns
about credit risks, including in EMDEs. The
impact could be particularly severe in anenvironment where debt levels have reachedrecord highs, refinancing needs are mounting, andcredit quality has deteriorated in a number of
EMDEs. An escalation of trade restrictions amongmajor economies is also a major threat to theoutlook, as it could derail the recovery in global
trade and dampen confidence and investment
worldwide. Heightened policy uncertainty andrising geopolitical tensions could also buffet
activity. The materialization of these downside
risks could lead to a sharper-than-expected global
slowdown. This could represent a significant
hurdle for many countries, especially for those thathave not rebuilt fiscal buffers.
That said, the possibility of a stronger or longerlasting upturn in major economies cannot be ruledout. This could lead to larger-than-expected crossborder spillovers in the near term, as well as
improved supply-side conditions over the mediumterm.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

A quantification of uncertainty around the global
growth outlook suggests a wide range of possible
outcomes, while confirming the predominance ofdownside risks (Ohnsorge, Stocker, and Some2016). At current market conditions, theprobability of global growth being more than 1
percentage point below baseline in 2019 isestimated at 21 percent, while that of growth
being more than 1 percentage point above baseline
is 16 percent. That range has widened from a year
ago, reflecting increased uncertainty embedded in
the distribution of key risk factors, particularly
equity and oil price futures.
Disorderly tightening of financing conditions
The risk of an abrupt tightening of global
financing conditions and associated financing
stress has increased in 2018, reflecting a possible
reassessment of inflation risks amid shifting
market expectations of advanced-economy
monetary policy, stretched asset valuations, andthe possibility of further U.S. dollar appreciation.
Such developments could have particularly severe
consequences for more indebted EMDEs facing
substantial refinancing needs in coming years. A
sudden rise in borrowing costs could be triggeredby a convergence of factors.
Inflation risksMarket participants currently ascribe a low
probability of a rapid acceleration in inflation in
major advanced economies. This follows a
prolonged period of undershooting of central
banks’ inflation targets, and reflects the view thattechnological changes and globalization could
keep inflation persistently low (Autor and Dorn
2013; Eickmeier and Kühnlenz 2013; Elsby,
Hobijn, and Şahin 2013). However, a number offactors could contribute to a more pronounced
increase in inflation than currently predicted.
First, a period of persistently low unemployment
and increased labor market churning could reinforce workers’ bargaining power, potentiallyleading to faster wage growth (Danninger 2016;
Davis and Haltiwanger 2014). At comparable
unemployment rates, wage growth in advanced
economies during the previous business cycle was

CHAPTER 1

33

FIGURE 1.16 Risks: Tilted to the downside
Global growth is expected to remain solid in the near term. However,uncertainty is elevated and downside risks have increased.
A. Probability distribution aroundglobal growth forecasts

B. Probability of global growth in 2019
being below/above baseline

Sources: Bloomberg, World Bank.
A.B. 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 6-month-ahead oil price futures, S&P
500 equity price futures, and term spread forecasts. Values for 2019 are based on 18-month-ahead
forecast distributions. Last observation is May 2018.
B. Bars show the probability that global growth is 1-percentage-point above or below baseline
forecasts 18 months ahead.
Click here to download data and charts.

considerably higher (Figure 1.17). If not matchedby similar increases in productivity growth, afaster-than-expected recovery in wage growth
could lead to an increase in current and future
expected inflation. Second, U.S. fiscal stimulus
will provide a boost to growth in an economy
already operating close to full employment,
increasing the risk of overheating. Third, theglobal output gap is expected to disappear thisyear, with potentially far-reaching implications for
inflation dynamics in traded goods (World Bank
2018a). A reassessment of inflation risks could
contribute to a sudden rise in term premiums
from current exceptionally low levels, which
would push up long-term yields and generate
substantial volatility in U.S. and global bondmarkets.
Monetary policy uncertainty
Changes in market expectations about interest rate
and balance sheet policies of major central banks
could trigger financial stress. Several factors makefinancial markets particularly vulnerable to such areassessment. Policy interest rates in the UnitedStates remain well below neutral levels, andmarket and policymaker expectations about their

34

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.17 Downside risks: Financial stress
A sudden reassessment of the pace of wage growth in advanced
economies could contribute to a jump in long-term yields, particularly in the
United States, where term premiums are negative and policy interest rates
are increasing. EMDEs remain susceptible to such risks, with both private
and public debt levels considerably higher than in the pre-crisis period.
Debt in low-income countries has been trending up, as has the number ofcountries at risk of debt distress.
A. G4 wage growth and unemployment

B. U.S. term premium and long-termyieldsC. U.S. policy interest rates, inflation,and growth

D. EMDE debt as a share of GDP, byborrowing sector

outlook still diverge. In addition, strong foreign
demand for U.S. Treasuries has played a majorrole compressing U.S. long-term interest rates,
partially offsetting the impact of a faster pace ofU.S. interest rate hikes. Unlike the bond market“conundrum” in 2005-06, when rising demand
from foreign official institutions had a similar
dampening effect, the recent increase in demand
was mostly driven by foreign private investors(Cœuré 2018). These inflows have beenencouraged by continued aggressive monetary
policy easing in the Euro Area and Japan,
contributing to a growing gap between U.S.
Treasury and comparable sovereign bond yields inthose jurisdictions—and, during 2018, to arenewed appreciation of the U.S. dollar. Shifting
expectations about advanced-economy monetary
policy could lead to sudden portfolio adjustments,
faster-than-expected increases in global interest
rates, or disorderly exchange rate developments.
Stretched asset price valuations

E. EMDE interest payments on debt asa share of GDP, by borrowing sector

F. Evolution of debt distress in LICs

A prolonged period of very low interest rates has
encouraged risk-taking in financial markets andrising asset price valuations (Lian, Ma, and Wang2017). Elevated asset prices make global financial
markets more prone to sudden adjustments andbouts of volatility (BIS 2017). The equity priceto-earnings ratio is historically high in the UnitedStates, while corporate bond spreads in bothadvanced economies and EMDEs remain
significantly below pre-crisis averages. A correctionin asset valuations could weaken growth prospects
through tighter financing conditions, lower
confidence, and negative wealth effects (Bluedorn,
Decressin, and Terrones 2013).
EMDE vulnerabilities

Sources: Adrian, Crump, and Moench (2013); Bank for International Settlements; Bloomberg; Federal
Reserve Bank of St. Louis; Haver Analytics; International Monetary Fund; World Bank.
A. The G4 includes the Euro Area, Japan, the United Kingdom, and the United States. Lastobservation is March 2018.
B. Term premium estimates from the term structure model of Adrian, Crump, and Moench (2013).
Last observation is May 25, 2018.
C. Figure shows period averages. Policy rate refers to the effective federal funds rate. Lastobservation is April 2018.
D. Debt is defined as loans and debt securities. Sample includes 16 EMDEs.
E. Interest payments include interest paid on loans and debt securities. Sample includes 12 EMDEs.
F. Figure shows the percent of low-income and developing countries eligible to access the IMF'sconcessional lending facilities that are either at risk of, or in, debt distress. The sample represents alarger group of countries than that defined in Table 1.2.1 as low-income by the World Bank.
Click here to download data and charts.

EMDEs remain vulnerable to risks of sudden
market adjustments and tighter global financing
conditions, which could be amplified by further
U.S. dollar appreciation, triggering disorderly
exchange rate developments. Credit growth has
slowed in most countries but corporate sector
vulnerabilities remain elevated, and both private
and public debt levels are considerably higher thanin the pre-crisis period. Rising borrowing costs
could substantially increase the burden of debt

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018servicing, which was compressed in recent years by
low global interest rates and risk premiums. Inturn, rising debt service costs could weaken
investment and lower medium-term growth(Special Focus 2; Borensztein and Ye forthcoming;
Drehmann, Juselius, and Korinek 2017; Jordà,
Schularick, and Taylor 2013; Lombardi,
Mohanty, and Shim 2017). A reversal in capital
inflows and sharp currency depreciations could
also increase default risks and raise financial
stability concerns among economies with external
vulnerabilities. EMDE debt denominated in U.S.
dollars remains elevated in many countries andincreased in 2017 amid favorable borrowing
conditions.
Large current account deficits, elevated short-term
external debt, and reliance on portfolio flows
render some countries particularly vulnerable torollover risk and sudden stops in capital flows. In
some oil-importing EMDEs, rising oil prices
could further exacerbate current account deficits
and associated fragilities. The transmission of
global financial shocks can be amplified in
EMDEs with pegged exchange rate regimes
compared with countries with flexible ones
(Obstfeld, Ostry, and Qureshi 2018).
Public debt burdens and vulnerabilities continue
to rise across low-income countries (LICs). Morethan 40 percent of LICs are in debt distress or athigh risk of debt distress—more than twice theshare in 2013 (IMF 2018; World Bank 2018e). In
these countries, the increase in public debt levels
has been accompanied by a substantial change increditor composition and debt instruments.
Increased reliance on commercial loans withshorter maturities has exposed debtor countries tocurrency, interest rate, and refinancing risks(Devarajan 2018; Gill and Karakülah 2018). Debt
vulnerabilities among LICs could become moreacute in the absence of measures to increase
domestic revenue mobilization, rationalize public
spending, and boost growth.
Escalating trade protectionism
The risk of escalating trade restrictions has
substantially intensified amid ongoing tradedisputes between the United States and major
trading partners. A broad-based increase in tariffs

CHAPTER 1

35

FIGURE 1.18 Downside risks: Trade protectionism
An escalation of tariffs up to legally-allowed limits could have large
negative effects on trade, particularly in EMDEs. Even the threat of shifting
trade policies, particularly in the United States, could have negative effects
on EMDE investment. The drive toward trade liberalization has slowed,
with the number of new trade agreements falling to an 18-year low in 2017.
A. Impact on trade from worldwide
increase in tariffs to bound levels
by 2020

B. U.S. trade policy uncertainty

C. Investment impact of 10-percent
rise in U.S. economic policy
uncertainty

D. New regional trade agreements

Sources: Baker, Bloom, and Davis (2016); Bloomberg; Haver Analytics; Kutlina-Dimitrova and
Lakatos (2017); World Bank; World Trade Organization.
A. Bars denote the percent deviation from baseline in 2020. Data are calculated from simulations
using the GDyn computable general equilibrium model (Ianchovichina and McDougall 2000;
Ianchovichina and Walmsley 2012). Trade-weighted aggregates include 36 advanced economies and
71 EMDEs.
B. Dashed horizontal line reflects the historical median from January 1990 to March 2018. Trade
policy-related uncertainty in the United States is based on an index presented in Baker, Bloom, andDavis (2016), and computes the frequency of articles in domestic newspapers mentioning terms
related to trade policy (e.g., import tariffs, import barriers, WTO, dumping, etc.). Last observation is
March 2018.
C. Figure shows median impact. Cumulative impulse response after 1 year on investment growth in
23 advanced economies and 18 EMDEs to a 10-percent increase in the U.S. economic policy
uncertainty (EPU). Vector autoregression estimated for 1998Q1-2016Q2 with two lags. The model foradvanced economies includes U.S. EPU, MSCI index for advanced economies (MXGS), U.S. 10-yearbond yields, aggregate real GDP and investment growth in 23 advanced economies. The model for
EMDEs includes U.S. EPU, MSCI emerging market equity price index, J.P Morgan’s Emerging
Market Bond Index Global (EMBIG), aggregate real GDP growth, and investment growth in 18
EMDEs. G7 real GDP growth, U.S. 10-year bond yields, and MSCI world equity price index are added
as exogenous variables.
D. Bars denote the number of regional trade agreements in force.
Click here to download data and charts.

worldwide would have major adverse consequences for global trade and activity (Ossa 2014;
Nicita, Olarreaga, and Silva forthcoming). An
escalation of tariffs up to legally-allowed boundrates could translate into a decline in global tradeflows amounting to 9 percent, similar to the drop
seen during the global financial crisis in
2008-09 (Figure 1.18; Kutlina-Dimitrova and36

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Lakatos 2017). The impact of increased
protectionism would be more severe in EMDEs
than in advanced economies. Highly protected
sectors, such as agriculture and food processing,would be likely to be among the most negatively
affected. Non-tariff barriers could also be raised,adding to the cost of trading across borders. Costs
associated with shipping, logistics, legal andregulatory impediments are already far
outstripping tariff costs, particularly in EMDEs(UNESCAP 2017).
If it were to materialize, a substantial escalation of
trade-restrictive measures between the UnitedStates and China could lead to economic losses forthese two economies and cascading trade costs
through global value chains (Bown 2017; Erbahar
and Zi 2017; Escaith 2017; Irwin 2017). Sectoral
dislocations associated with shifting trade patterns
could have persistent negative effects on labormarkets (Autor, Dorn, and Hanson 2016). Any
setbacks to activity in the either country would
result in significant negative spillovers for the restof the world through trade, confidence, financial,and commodity-market channels (Kose et al.
2017a; Huidrom, Kose, and Ohnsorge 2017).
Even the threat of substantial shifts in trade
policies in major economies, and associateduncertainty, could have negative consequences forfinancial markets, investment, and activity
worldwide. The impact of U.S. policy uncertainty
is particularly significant for investment in
EMDEs, especially in those with large trade or
financial market linkages with the United States(World Bank 2017a; Bhattarai, Chatterjee, andPark 2018).
Uncertainty surrounding the outcome ofnegotiations for major trade agreements and thenon-renewal of preferential schemes could haveadverse consequences for involved countries.
Despite the recent ratification of a number ofdeeper trade agreements that include comprehendsive provisions beyond the liberalization of tariffbarriers, the appetite for trade liberalization has
generally waned, particularly across majoradvanced economies. This is reflected in thenumber of new trade agreements falling to an 18year low in 2017.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

Policy uncertainty and geopoliticaldevelopments
Measures of global policy uncertainty are still
above historical norms, albeit below a peak in2016 (Figure 1.19). The risks of destabilizing
policy and political changes remain elevated,reflecting the increased polarization of public
opinion, a backlash against globalization, andrising support for populist parties across the world(Rodrik 2018; Inglehart and Norris 2016).
Electoral outcomes in a number of EMDEs andadvanced economies, including in Europe, could
lead to renewed uncertainty. Periods of significant
government changes and political instability are
generally associated with lower growth in theaffected economies (Aisen and Veiga 2011; Perotti1996). If the affected economies are sizable andtightly interconnected with trading partners (forexample, a large Euro Area member state), theresulting negative spillovers could depress activity
and investment in other countries, including
EMDEs (World Bank 2015; World Bank 2017a).
A lack of trust in governments also increases therisk of instability during economic downturns(Nunn, Qian, and Wen 2018).
Geopolitical risks remain elevated amid persistenttensions on the Korean Peninsula and intensifying
strains in the Middle East. In that region,
continued conflict, heightened tensions, andreneweduncertainties
followingthereintroduction of sanctions on Iran could
exacerbate volatility in oil markets, hamper
confidence, and further amplify instability(Karasapan 2017; Polachek and Sevastianova
2012). Security conditions remain precarious inmany Sub-Saharan African countries. In the past,
protracted periods of low commodity prices havetended to increase the probability of civil unrest inthat region, as well as in others with large numbersof commodity exporters (Bazzi and Blattman
2014; Ciccone 2018). Heightened diplomatic
tensions involving Russia’s relationship with theUnited States and the European Union could also
lead to an escalation of retaliatory measures.
Renewed intensification of geopolitical risks could
severely impact growth and development
prospects for the affected regions, and even hinder
activity at the global level.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

A combination of global downside risks
After a decade of recovery from the global
financial crisis, economic activity is still lagging
previous expansions and is expected to decelerate
in coming years (Figure 1.20). Whether the
slowdown will be gradual, as currently predicted,
or abrupt will depend on a number of factors,
including the materialization of some of theaforementioned downside risks. Currently, theprobability of a recession in major economies,
such as the United States, is low (Bauer and
Mertens 2018). However, the global economy has
experienced an abrupt slowdown or recession in
every decade, which was invariably preceded by aperiod when a significant majority of countries
were operating above capacity. This proportion isestimated to be around 50 percent in 2018, and is
expected to increase further in 2019.
The next global slowdown or recession could betriggered by the combined materialization ofseveral downside risks. For instance, a full-blown
escalation of trade-restrictive measures along witha sudden resurgence of global inflation could
negatively impact confidence and lead to
disruptive financial market developments.
Weakening growth and higher borrowing costs
could intensify debt and financial stability
concerns, while rising unemployment could
amplify political uncertainties and protectionist
tendencies.
The capacity of many countries to confront a
synchronous slowdown has diminished since theglobal financial crisis. Monetary policy inadvanced economies could face renewed
constraints, as policy interest rates are still at
historic lows, and fiscal space has deteriorated inboth advanced economies and EMDEs. Moreover,potential growth has deteriorated and long-term
investment prospects have continued to worsen,
despite a tentative stabilization of market
expectations about the long-term growth outlook(Box 1.1). These conditions render the global
economy vulnerable to adverse shocks that may
lead to a global slowdown or recession. Such an
event could further damage potential growth,particularly if accompanied by financial stress andsignificant deleveraging pressures (World Bank
2018a; Kose and Terrones 2015).

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37

FIGURE 1.19 Downside risks: Policy and geopoliticaluncertainty
Global policy uncertainty is still above historical norms, but has generally
moderated from a peak reached in 2016. The risk of unanticipated politicalswings remains elevated amid rising support for populist parties. In thepast, periods of low commodity prices were associated with an increased
incidence of conflict in commodity exporters.
A. Global economic policy uncertainty

B. Global rise of populism

C. Elections in advanced economies
and EMDEs

D. Conflict in EMDE commodity
exporters and commodity prices

Sources: Allansson, Melander, and Themnér (2017); Baker, Bloom, and Davis (2016); Election
Guide, International Foundation for Electoral Systems; national sources; Rodrik (2018); World Bank.
A. Policy uncertainty is the Economic Policy Uncertainty index computed by Baker, Bloom, and Davis(2016), and is based on the frequency of articles in domestic newspapers mentioning economic policy
uncertainty. The index is normalized to equal 100 at its January 2000-April 2018 median, as indicatedby the dashed horizontal line. Last observation is April 2018.
B. Data measures the vote share, or support, for populist parties, defined as those which pursue anelectoral strategy of emphasizing divisions between an in-group and an out-group, over time among
countries with at least one populist party, as defined and computed by Rodrik (2018). Sample
includes 8 EMDEs and 11 advanced economies.
C. Bars indicate the number of presidential and parliamentary elections held in EMDEs and advanced
economies in each year. The sum excludes local authority elections.
D. Conflicts are the two-year average of the sum of armed conflicts, or conflicts that involve two
armed and opposing actors. Commodity index is the average of energy, non-energy, and precious
metals price indexes, based on nominal U.S. dollar prices.
Click here to download data and charts.

Region-specific downside risks
There are various region-specific downside risks
that accompany the global risks discussed earlier.
Most regions face domestic policy uncertainties
associated with the possibility of fiscal slippages,
reform setbacks, and lingering financial stability
concerns.
Renewed geopolitical tensions in Europe andCentral Asia, the Middle East and North Africa,
South Asia, as well as around the South China Sea

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.20 Downside risks: History repeating itself?
Activity has recovered but still lags behind previous expansions. While theprobability of a recession in major economies, such as the United States,
remains low, it may be creeping up. Past global recessions were precededby a period when most countries operated at or above full capacity. The
next episode could be triggered by the materialization of a combination ofdownside risks, which could further weaken long-term investment
prospects.
A. Global GDP during expansion
periods

B. Probability of U.S. recession

C. Output gaps around global
recessions/slowdowns

D. Five-year-ahead forecasts ofinvestment growth

Sources: Consensus Economics, Federal Reserve Bank of New York, National Bureau of Economic
Research (NBER), World Bank.
A. Global GDP levels in constant 2010 U.S. dollars, indexed to 100 at start of expansion periods.
Cycle dates based on global recessions and slowdowns identified in Kose and Terrones (2015).
Dashed line corresponds to 2018-20 forecasts.
B. Figure shows probability of a recession in 12 months. Probabilities derived from the U.S. yield
curve model of the Federal Reserve Bank of New York. Shaded areas indicate recessions, as
identified by the National Bureau of Economic Research (NBER). Last observation is April 2018(12-month-ahead probability).
C. Output gaps calculated using multivariate filter. Methodology is described in Box 1.1 of the January
2018 edition of the Global Economic Prospects report. Grey bars indicate the two global recessions
in 1991 and 2009, and the two global slowdowns in 1998 and 2001.
D. Five-year-ahead forecasts of investment growth, where the horizontal axis is the forecast vintage.
Figure uses data surveyed for the latest available month in each year. Unweighted averages of 24
advanced economies and 21 EMDEs. Last observation is April 2018.
Click here to download data and charts.

and the Korean Peninsula, could weaken
confidence and disrupt trade, investment, andmigrant flows in these regions. A worsening ofpolitical instability or armed conflict could havesubstantial adverse effects in Sub-Saharan Africa.
Lower-than-expected commodity prices could also
derail the recovery in key commodity-exporting
economies that are important economic partners
for other countries in their regions. Finally,natural disasters, such as severe storms or
droughts, could become more frequent, buffeting

activity in many regions, including in East Asia
and Pacific, Latin America and the Caribbean,
South Asia, and Sub-Saharan Africa.
Stronger and longer-lasting cyclicalrecoveryDespite various downside risks, a more sustained
and longer-lasting recovery in major advanced
economies and EMDEs remains possible,
particularly if policy uncertainty dissipates. This
could generate larger-than-expected spillovers
through global trade and confidence channels. In
particular, positive growth surprises in the UnitedStates would be a notable boost for activity among
trading partners, including many EMDEs (Figure
1.21; Kose et al. 2017a; Huidrom, Kose, andOhnsorge 2017). A persistent period of elevatedconfidence across major economies could further
amplify the recovery, making it more synchronousand self-sustained (Angeletos, Collard, and Dellas
2017; Benhabib, Wang, and Wen 2015;
Levchenko and Nayar 2017).
Over time, the cyclical recovery could help reverse
some of the damage to potential output growthcaused by the global financial crisis (World Bank
2018a). In particular, a persistent period of weakaggregate demand since 2008 might havecontributed to the loss of skills and matchingefficiency on labor markets (Bell and Blanchflower
2010; Bell and Blanchflower 2011), weakcorporate sector performance (Nguyen and Qian2014), financing constraints (Queralto 2013), andto slowing total factor productivity growth(Oulton and Sebastiá-Barriel 2017). In the UnitedStates, these factors have accounted for asignificant share of the slowdown in potential
output growth since the crisis (Reifschneider,
Wascher, and Wilcox 2015; Summers 2014).
There is also evidence of lasting damage from thecrisis in other advanced economies and in EMDEs(Ball 2014; World Bank 2018a).
Absent the build-up of macroeconomic andfinancial imbalances, a prolonged period of strong
aggregate demand could help raise labor participation, investment and productivity growth. A
pickup in productivity in major advanced
economies would allow for additional growth
without a rise in inflation, which would help

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018sustain favorable financing conditions andgenerate positive cross-border and inter-industry
spillovers (Badinger and Egger 2016). An
investment revival in EMDEs would help
counterbalance the forces weighing down on
potential growth in those countries.

Policy challenges

CHAPTER 1

39

FIGURE 1.21 Upside risks: Longer-lasting upturn
Upside risks stem from the possibility of stronger-than-expected growth inmajor economies, particularly in the United States. Absent the build-up of
macroeconomic and financial imbalances, a longer-lasting recovery could
help repair crisis-related damages to potential growth.

A. Impact of a 1-percentage-point
increase in U.S. growth after 1 year

B. Actual and potential output growthin advanced economies and EMDEs in
the post-crisis period

Challenges in advanced economies
Advanced-economy monetary policy will gradually
become less stimulative, as output gaps become
positive and inflation picks up. Fiscal policy is
expected to be broadly neutral for growth, with thesignificant exception of the United States. As
monetary and fiscal stimuli wane in the medium
term and potential growth softens in the longer term,
the outlook is expected to weaken, highlighting theneed for structural reform to boost productivity andlabor force participation.
Monetary and financial policies
As the recovery firms and output gaps become
positive, inflation should gradually rise toward
central bank targets. The pace of this convergence,
however, is subject to considerable uncertainty.
Throughout the recovery, inflation has generally
been overestimated (Figure 1.22). Recent inflation
has been less responsive to strengthening activity
than might have been expected, perhaps reflecting
hidden slack or structural forces. Inflation
expectations may have shifted down following aperiod of persistently low and below-target actual
inflation (Kiley and Roberts 2017; Hills, Nakata,and Schmidt 2016). Globalization may have
reduced the sensitivity of inflation to domesticpressures (Auer, Levchenko, and Sauré 2017; Ihrig
et al. 2010). Trends in technology andcompetition may be suppressing wages and prices(Kurz 2017; Autor et al. 2017). Central banks areappropriately taking a gradual approach to policy
normalization.
Major central bank balance sheets remain large byhistorical standards, but have likely peaked
globally. The Federal Reserve has started towithdraw quantitative easing, while the European
Central Bank is tapering its asset purchases.
Changing market expectations about the speed of

Source: World Bank.
A. Cumulative impulse responses of a 1-percentage-point increase in U.S. growth on growth in otheradvanced economies and in EMDEs. Solid bars represent medians and error bars represent 16-84
percent confidence intervals.
B. Red dots indicate advanced economies and blue dots are EMDEs. Sample includes 34 advanced
economies and 66 EMDEs.
Click here to download data and charts.

the process could lead to sudden financial market
movements, reminiscent of the 2013 Taper
Tantrum. Careful and transparent communication
by central banks about their plans for both policy
rates and balance sheets can avoid adverse financial
market reactions, particularly in an environment
where high asset prices are based on assumptions
that monetary policy tightening will proceed in anorderly fashion.
Fiscal policy
The fiscal policy stance of advanced economies
turned from contractionary to expansionary, onbalance, between 2015 and 2017, contributing to
the upturn in growth during this period. In mostadvanced economies, the fiscal stance is expected
to be largely neutral for growth over the forecasthorizon.
The major exception is the United States, which isundertaking a substantial, and procyclical, fiscal
expansion. Fiscal stimulus is an important part ofcountercyclical policy, especially when monetary
policy is constrained (Christiano, Eichenbaum,and Rebelo 2011). However, for an economy
operating close to full potential, the benefits ofstimulating demand are reduced, while the costs

40

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.22 Monetary and fiscal policies in advanced
economies
Inflation has generally come in below forecasts in recent years, suggestingthat central banks should take a gradual approach to raising rates. Major
central bank balance sheets are close to their peak size, and managing theunwinding of unconventional policy will require careful communication.
Fiscal balances have stabilized in most advanced economies, with the key
exception of the United States, where fiscal policy will be highly
procyclical, with limited growth spillovers. Debt levels in advanced
economies have risen significantly in the past decade, which may hinder
their ability to respond to future negative shocks.
A. Euro Area Consensus inflation
forecasts

B. U.S. Consensus inflation forecasts

are magnified as interest rates rise and private
investment is crowded out. The same conditions
also limit the magnitude of positive spillovers toother countries (Blagrave et al. 2017).
More generally, many advanced economies haveadded significantly to their public debt load,
which may hinder their ability to respond tonegative shocks in the future (Romer and Romer
2017). Accordingly, they need to take advantageof the confluence of strong global growth and still
low borrowing costs to rebuild fiscal space (Koseet al. 2017b; IMF 2018).
Structural policies

C. Central bank balance sheets

E. Estimates of cross-border
spillovers from fiscal policy

D. Structural fiscal balance

F. Public debt

Sources: Consensus Economics, European Central Bank, Federal Reserve Bank of St. Louis, Haver
Analytics, International Monetary Fund, World Bank.
A.B. Series indicate date at which inflation forecast surveys were taken.
C. Annual average of monthly assets of central banks. Data use current U.S. dollar GDP weights.
D. Shaded area indicates forecasts. Structural balance is the fiscal balance adjusted for the economic
cycle and for one-off effects.
E. Average one-year response of recipient country GDP to a fiscal shock equal to 1 percent of source
country GDP, as calculated by Blagrave et al. (2017).
F. Net general government debt as a percentage of GDP. For cross-country comparability, the U.S.
figure is adjusted to exclude unfunded pension liabilities of government employees’ defined-benefit
pension plans.
Click here to download data and charts.

Potential output in advanced economies isconstrained by aging populations and weak
productivity growth (Figure 1.23). As the recovery
matures, and policy stimulus is gradually
withdrawn, growth will tend to converge toward
its slower pace of potential. Structural reforms canraise this pace by boosting labor participation andproductivity growth.
A critical challenge is to continue to support anopen and fair global trade system and pursue
further trade liberalization. One area with
untapped potential is trade in services, which
comprises a rising share of global trade despite
being subject to considerable restrictions.
Reducing barriers to services trade—for instance,by increasing regulatory cooperation and reducing
barriers to entry for foreign service providers—has
the potential to boost long-term growth prospects
while reducing policy uncertainty (Borchert,
Gootiiz, and Mattoo 2012; OECD 2017). Moregenerally, increasing trade openness should beaccompanied by actions to facilitate reemployment for workers in regions and sectors
dislocated by globalization (IMF, World Bank,and WTO 2017).
In contrast, actions to protect certain domestic
sectors, such as steel or aluminum tariffs, may
lead to net domestic job losses. The increase incosts for downstream users can reduce more jobs
than the protected sector gains (François andBaughman 2018). Such losses would be
multiplied if other countries retaliate in kind
(Akcigit, Ates, and Impullitti 2018).

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

Challenges in emerging and developing
economies
EMDE policymakers need to be able to respond to arise in inflation and cope with advanced-economy
monetary policy normalization, as well as manage
possible bouts of financial market volatility.
Deteriorating debt dynamics have reduced fiscal
space, underlining the importance of revenue
mobilization and medium-term fiscal frameworks torebuild buffers. EMDEs face various structural
challenges to boost longer-term prospects. They
include the need to intensify economic diversificationin commodity exporters, boost skills and adaptability
to confront rapid technological change, and promote
regional trade integration. China’s key policy
challenge is to manage the transition to slower but
more balanced and sustainable growth.

CHAPTER 1

FIGURE 1.23 Structural policy in advanced economies
Potential output in advanced economies is constrained by weak populationand productivity growth, suggesting that current levels of growth cannot be
maintained in the longer term.
A. Working-age population growth

B. Productivity growth

Sources: Haver Analytics, World Bank.
A. The series is a year-on-year percentage change in the working-age population, which is defined as
individuals between ages 15-64 years.
B. Productivity measures output per employed person. Last observation is 2018Q1.
Click here to download data and charts.

Policy challenges in China
Authorities in China have implemented a wide
range of reforms in recent years (IMF 2017a;
World Bank 2017c; World Bank 2018a). These
include steps to reduce excess capacity in theindustrial sector (Figure 1.24; World Bank
2018b). Notable progress has been made on
mixed-ownership reforms aimed at diversifying
the ownership structure of state-owned enterprises(SOEs). Currently, more than two-thirds ofChina's centrally administered SOEs and theirsubsidiaries have allowed outside investors,
restructured, or gone public. Following progress inopening its equity and bond markets to foreigners,
China is now taking additional steps to remove
foreign ownership limits in financial institutions
and some other sectors.
Reforms have also included stricter regulatory
policies for the housing market, as well asmonetary, financial, and regulatory measures thathave contributed to some reduction in corporate
debt as a share of GDP, even if household andpublic-sector debt have continued to increase (BIS
2018a). The authorities have also made progressin fiscal and regulatory reforms. For example, thetax burden on consumers and businesses, as well astransport logistics costs, are being further lowered
through cuts in value-added tax rates, social
security contributions, tariffs, and road tolls. In
addition, recent regulatory measures are expected41

to significantly shorten the processing time forstarting business and streamline foreign businessregistration.
The key economic policy challenge is to manage
the transition to slower but more balanced andsustainable growth. This will require continued
implementation of reforms to reduce financial
vulnerabilities, promote market competition andprivate sector development, reallocate capital andlabor toward more productive firms and sectors,
and foster innovation through stronger intellectual
property rights, as well as additional research anddevelopment. This will also necessitate further
actions to bolster household consumption,
including additional reforms to make the fiscal
system more progressive and rebalance theintergovernmental allocation of revenues andexpenditures. Reallocation of public spending
from investment to education, health, pensions,and safety nets would increase aggregate
consumption and boost human capital. Advancing
the reform of the household registration (hukou)
system, and of rural land transfers, would
contribute to a reduction of income inequality.
Encouraging market mechanisms to promote
green growth and more efficient, sustainable use ofnatural resources would enhance environmental
sustainability (World Bank 2018a; World Bank
2018h).

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.24 Policy challenges in China
China has implemented a wide range of reforms, including significant
steps to reduce excess capacity and to diversify the ownership structure ofstate-owned enterprises. While monetary and prudential policies havecontributed to some reduction of corporate debt, the stock of total debt hascontinued to increase due to still rising household and public-sector debt.
Progress on fiscal reforms includes the reduction of tax and social security
burdens on businesses.
A. Industrial capacity utilization

B. Industrial state-owned enterprises
and state-controlled enterprises with
mixed ownerships

C. Public, household, and corporate
debt

D. Social security contribution,highest mandatory tax rates

Sources: Bank for International Settlements, China National Bureau of Statistics, Haver Analytics,
Institute of International Finance, Ministry of Finance of the People’s Republic of China, Ministry of
Human Resources and Social Security of the People’s Republic of China, World Bank.
A. Last observation is 2018Q1.
B. Both lines represent industrial enterprises. State-controlled mixed ownership enterprises refer toenterprises of whose total assets the state-owned assets have a majority or dominate share. Lastobservation is December 2017.
C. Total debt comprises of credit to household and non-financial corporations and general
government debt (broad definition). 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.
Public debt, which is general government debt, includes central and local government debt and social
security funds, but excludes public enterprises. Data presented in the chart are broadly consistent
with the IMF estimates of total debt. Includes debt swaps and other debt restructuring operations.
D. Measures the sum of employer and employee contributions.
Click here to download data and charts.

EMDE monetary and financial policies
Among EMDEs more generally, median inflationin commodity exporters has been moderating
toward that of commodity importers. Policy
interest rate adjustments this year have consisted
mostly of cuts in commodity exporters, extending
easing cycles already underway in some economies(e.g., Brazil, Colombia, Kazakhstan, Peru, Russia,
Zambia; Figure 1.25). Thus far, short-term,
survey-based inflation expectations in EMDEs

have shown modest upward momentum.
However, with oil prices rising and the aggregate
EMDE output gap closing, there may be greater
upward pressure on inflation going forward.
Moreover, a closed global gap could amplify thistendency through imported inflation (World Bank
2018a).
The challenges associated with increasing inflationpressures could be compounded if monetary
policy normalization in advanced economies, andthe associated tightening of international
financing conditions, leads to capital outflows andcurrency depreciation among EMDEs (Chari,
Stedman, and Lundblad 2017; Dahlhaus andVasishtha 2014). Some countries have already had
to adjust their monetary policy stance in responseto rapid adjustments in exchange rates and capital
flows in the first half of 2018. The current policy
mix in the United States amplifies the challenge of
sudden changes in market sentiment. If theFederal Reserve were to hike policy rates more
steeply than markets expect to offset overheating
and inflationary pressures generated by the large
fiscal expansion, there could be additional pressure
for rate increases in some EMDEs. At the sametime, policymakers in EMDEs need to continue
preparing their domestic financial sectors forpotentially adverse spillovers from post-crisisbanking regulatory tightening in advanced
economies (Briault et al. 2018).
How susceptible individual countries may be tocapital flow reversals depends on their existing
vulnerabilities and other domestic factors, such as
their degree of financial openness and institutional
quality (Byrne and Fiess 2016). In anticipation ofrising borrowing costs and the possibility of
renewed, more persistent episodes of market
volatility, it is critical for EMDE policymakers tomaintain an environment where expectations of
longer-term inflation are low and stable. This
includes credible commitment to explicit inflation
targets in those countries that have implemented
such a framework. In some countries, it will also
be necessary to tackle vulnerabilities, such as
sizable current account deficits or high stocks ofcorporate debt. Although maintaining anappropriate level of exchange rate flexibility andbuilding policy buffers should be first lines of

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

defense in confronting sudden financial shocks,
EMDE policymakers also need to be prepared touse additional tools, such as intervention inforeign exchange markets, or even targeted capital
inflow management measures if other options
have been exhausted and a financial crisis isimminent (IMF 2017b). To reduce financial
stability risks associated with elevated corporate
debt, prudential policies and bankruptcy
protection regimes should be reinforced, whileaccess to equity finance should be further
developed (Special Focus 2).

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43

FIGURE 1.25 EMDE monetary policy
Policy interest rate actions in commodity exporters in the first half of 2018consisted mostly of cuts, extending easing cycles already well underway insome economies. This is consistent with moderating inflation and stillnegative output gaps. Survey-based inflation expectations are rising incommodity importers, and have stabilized in commodity exporters after an
extended period of downward adjustment.

A. Policy interest rates

B. One-year-ahead inflation
expectations

EMDE fiscal policy
Public finances are fragile in various EMDEs.
Many economies are running sizable government
deficits—a trend expected to persist over the next
two years—while adverse debt dynamics willcontinue to constrain fiscal space across EMDEs(Figure 1.26). Limited fiscal buffers leave EMDEs
short of an effective fiscal instrument should theyneed to react to a negative economic shock. In
LICs, public debt-to-GDP ratios remain below
levels observed prior to the mid-2000s following
debt relief initiatives, but have increased rapidly inrecent years. Debt vulnerabilities are compoundedin those countries by rising exposure tointernational markets, a lack of transparency, andlimited debt management capabilities. The
increased reliance on commercial loans and nontraditional sources has created debt-service
difficulties in some countries. Across EMDEs
more generally, the challenges posed byinadequate fiscal buffers are expected to be
amplified as global financing conditions tighten,
especially if procyclical U.S. fiscal measures areaccompanied by higher-than-expected U.S. andglobal interest rates.
In oil exporters, fiscal deficits narrowed in 2017,in part aided by recovering energy prices, but are
projected to remain large (e.g., Algeria, Bahrain,
Ghana, Nigeria; World Bank 2018a). Government revenue growth was positive in 2017 and is
set to accelerate in 2018. However, the improvement is not enough to bring revenues as ashare of GDP back to levels observed before the
2014-16 oil price collapse, and government debt
continues to rise.

Sources: Consensus Economics, Haver Analytics, World Bank.
A. The blue bars show the interquartile range of policy rates for each country group. Sample includes
37 commodity exporters and 26 commodity importers.
B. Figure shows median one-year-ahead inflation expectations based on a quarterly survey
conducted by Consensus Economics. Sample includes nine commodity exporters and 11 commodity
importers. Last observation is April 2018.
Click here to download data and charts.

In other commodity exporters, government
finances deteriorated following the decline incommodities prices after 2011. Fiscal balances
bottomed out in 2015-16 and are envisaged tofurther improve; however, they remain firmly
negative. Although the fiscal sustainability gap incommodity exporters is expected to narrow in
2018, the improvement is not yet sufficient toplace debt on a sustainable path. These trends
suggest that there is still significant need for fiscal
consolidation in commodity exporters. In commodity importers, robust growth has supported
government revenues. However, government
expenditure growth is expected to outpace thatof revenues, contributing to rising grossgovernment debt.
Going forward, tightening global financing
conditions will have substantial implications forfiscal policy in EMDEs. For sovereign borrowers,
public balance sheets could come under stress as
governments face rising costs in financing deficits
and rolling over maturing debt (IMF 2017b).
EMDEs with elevated external borrowing—
especially from private creditors—are vulnerable
to capital flow reversals, which can increaserefinancing risks and the burden of servicing debt

44

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.26 EMDE fiscal policy
Government debt has been rising across EMDEs, further constraining
fiscal space. In LICs, external and non-concessional debt have been
increasing, putting further strain on domestic revenues as interest
payments continue to climb. Fiscal sustainability gaps could deteriorate
across all EMDE regions in response to increasing interest rates. Tax
policy appears to be procyclical across many EMDEs, which could
exacerbate fluctuations in their business cycles.
A. Gross government debt

B. External debt in LICs

C. Non-concessional debt and interest
payments on debt in LICs

D. Fiscal balances

E. Impact of interest-rate shock on
fiscal sustainability gaps in EMDEs,
by region

F. Share of tax changes duringcontractions, 1981-2017

Sources: Haver Analytics, International Monetary Fund, Kose et al. (2017b), Végh and Vuletin (2015),
World Bank.
A.D. Shaded area indicates forecasts.
A. Figure shows the constant 2010 U.S. dollar GDP-weighted average for each country group ofgross government debt, using an unbalanced sample. The sample in 2018 includes 80 commodity
exporters and 60 commodity importers.
B.C. LICs = low-income countries.
B. External debt measures debt owed to non-residents. The unbalanced sample includes 21 LICs.
C. Figure shows median values for LICs. The unbalanced sample includes 29 LICs for nonconcessional debt and up to 15 LICs for interest rate payments, depending on data availability.
Interest rate payments include those made on government debt to domestic and foreign residents.
D. Figure shows median in each country group. Sample includes 36 energy exporters and 54 othercommodity exporters (i.e., agricultural and metals exporters), as well as 63 commodity importers.
E. 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.
Figure shows the estimated deterioration in the fiscal sustainability gap driven by a 1-standard
deviation interest rate increase. Sustainability gap is measured as the difference between the primarybalance and the debt-stabilizing primary balance. A negative bar indicates government debt is risingalong an accelerated trajectory. Sample includes 70 EMDEs.
F. A net tax hike occurs when the number of tax hikes exceeds the number of tax cuts, while a net tax
cut occurs when the number of tax hikes is less than the number of tax cuts. Tax changes aremeasured as the change in statutory rates in either the corporate income, personal income, or valueadded tax as described in Végh and Vuletin (2015). Output gaps that are more negative than -1
percent of potential GDP indicate an economic contraction. Unbalanced sample, where data for 2017
includes 16 EMDEs.
Click here to download data and charts.

(IMF 2018). Although aggregate corporate debt in
EMDEs has fallen modestly since 2016, it
remains, on average, 27 percentage points of GDP
higher than in 2006 (Special Focus 2; Beltran,
Garud, and Rosenblum 2017). Deterioration of
corporate debt profiles could lead to risingcontingent liabilities for the public sector, which
would compound the challenges associated withelevated public debt.
Although favorable global growth and recovering
revenues are likely to improve fiscal space, EMDE
policymakers need to continue to actively address
underlying
fiscalvulnerabilities.
Placing
government finances on a more sustainable path
could prevent the need for procyclical fiscal
consolidation in the presence of negative shocks—
as was the case in commodity exporters in 201617, when sizable negative output gaps wereaccompanied by contractionary fiscal stances(World Bank 2018a). Realigning government
spending with revenues could also help stabilize
growing public debt levels, while managing thecomposition of debt could ease the servicing
burden on tax revenues. The urgency tostrengthen or rebuild fiscal buffers should bebalanced against other pressing considerations.
These include protecting social safety nets andfinancing growth-enhancing investment, including
in infrastructure. Mobilizing fiscal revenues andreallocating spending toward investment andinfrastructure projects can prioritize such needs
when fiscal space is constrained, which is generally
the case in LICs. Across EMDEs, introducing
medium-term expenditure frameworks and fiscal
rules to contain deficits, as well as improving
overall governance, can build credibility tosupport revenue collection and buck the historical
trend of procyclical fiscal policy. This should becomplemented by measures to enhance debt
transparency, improve debt management capacity,and promote sustainable lending practices,
particularly in LICs.
EMDE structural policies
While EMDE growth is expected to continue toaccelerate in 2018, potential growth has declined
considerably over the past decade, and structural
challenges are intensifying. For commodity

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

CHAPTER 1

exporters, prospects of a secular slowdown in the
demand for commodities call for accelerated
efforts to diversify their economies (Special Focus
1). For all EMDEs, rapid changes in manufacturing and technology imply rising challenges andopportunities, putting ever-increasing emphasis on
education, skills, and adaptability to bolster longterm growth prospects.
Fostering diversification
Resource-rich countries need to enhance theoverall competitiveness of their economies. In
addition to fostering human and physical capitaland improving institutions and governance, theyneed to pursue policies that help diversify theireconomies away from natural resources (Gill et al.
2014). For low- and middle-income countries,
increased diversification is generally associatedwith higher levels of income per capita (Figure
1.27; Cadot, Carrère, and Strauss-Kahn 2011;
Imbs and Wacziarg 2003). For resource-intensive
countries, low levels of economic diversification
are particularly challenging, as sharp commodity
price fluctuations disproportionately impede
investment, growth, and stability in thosecountries (Bahar 2016; Hesse 2008; Lederman
and Maloney 2007; Papageorgiou and Spatafora
2012; IMF 2016). Furthermore, there appears to
be an inverse relationship between resource
intensity and education outcomes, which could
reflect a lower quality of institutions moregenerally. This can further hamper the potential
for development in resource-rich countries (WorldBank 2018i).
In the long run, the prospect of persistently
moderate commodity prices intensifies the needfor reforms to encourage economic diversification,
particularly in less diversified oil producers. Such a
process generally occurs with incremental changes
around existing sectors and comparative advantages, leveraging available skills and infrastructure(Hausmann, Hwang, and Rodrik 2007).
•

The successful diversification experience ofsome energy producers (e.g., Malaysia,
Mexico) suggests the need to support bothvertical diversification in oil, gas, and petrochemical sectors, as well as horizontal diversi-

fication beyond these sectors. Continued
commitment to reforms aimed at improving
governance and the business climate, andreducing regulatory barriers to competition
and to foreign investment, has the potential todiminish reliance on the oil sector (Callen etal. 2014; Devarajan 2017; Stocker et al.
2018).
•

Similarly, metals and agricultural exporters
can benefit from vertical diversification—thedevelopment of industries closely related toexisting production and export structures—and the expansion of high value-added
resource-based manufacturing activities. For
instance, mining and forestry have become
knowledge-intensive sectors with hightechnological content in both upstream anddownstream activities. Successful examples ofvertical diversification include Thailand,
Chile, and Uganda (Hesse 2008; Gylfason
and Nguessa Nganou 2014; Maloney andValencia Caicedo 2017).

While incremental diversification around resource
sectors can help foster learning and the adoptionof new technologies, proper regulatory andinstitutional frameworks need to be in place toattract new investments, help the development ofhigher value-added export sectors, and boost
competitiveness and participation in regional andglobal value chains. Regulations and institutions
that slow the emergence of new sectors should be
identified and reformed in order to support
efficiency-seeking and productivity-enhancing
investments, including through improved
competition policies. Rapid technological changes
also offer new opportunities for private-sector-led
growth, including in digital services and information technologies (World Bank 2018i).
Diversification can be hindered by the absence of
local market access, emphasizing the need forfurther regional integration, particularly in SubSaharan Africa (Imbs 2018).
Adapting to technological change
Despite heightened uncertainty about trade
policies in major economies, the potential forexport-led manufacturing growth remains

45

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G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 1.27 EMDE structural policy
Decreasing export concentration is generally associated with risingincome per capita. The need for increased diversification is particularly
acute among oil-exporting EMDEs. Automation creates new challenges for
manufacturing-led growth in EMDEs. Regional trade agreements offer
prospects of increased integration, particularly in Sub-Saharan Africa.
Improving basic reading and mathematics proficiency remains a major
priority in some regions.
A. Export concentration and GDP per
capita levels

C. Supply of industrial robots, byindustries worldwide

E. Impact of AfCFTA on employment,by sector

B. Export concentration, 2016

D. Size of new regional trade
agreements

F. Students proficient in math andreading

Sources: International Federation for Robotics; Saygili, Peters, and Knebel (2018); United Nations
Conference on Trade and Development (UNCTAD); World Bank.
A.B. Herfindahl-Hirschmann concentration index measures the degree of product concentration,
where values closer to 1 indicate a country’s exports are highly concentrated on a few products.
A. GDP per capita measured in Purchasing Power Parity (PPP) terms. Trend computed using a local
polynomial regression over a sample of 104 countries and over the period 1995 to 2015. Outlier data
trimmed at the 10 percent level using a density based clustering algorithm.
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.
C. Estimated annual supply of industrial robots at year-end.
D. CPTPP = Comprehensive and Progressive Agreement for Trans-Pacific Partnership, AfCFTA =African Continental Free Trade Area. Data are as of 2017.
E. Man. refers to other manufactured goods. Utilities/const. refers to utilities/construction. The
employment effects of the African Continental Free Trade Area (AfCFTA) have been estimated using
the Global Trade Analysis Project (GTAP) model. The GTAP model is a static, multi-regional, multisectoral general equilibrium model assuming perfect competition, constant returns to scale, andimperfect substitution between foreign and domestic goods and among imports from different
sources.
F. SSA = Sub-Saharan Africa, MNA = Middle East and North Africa, LAC = Latin America andCaribbean, EAP = East Asia and Pacific, ECA = Eastern Europe and Central Asia. Data for South
Asia are unavailable. Dashed horizontal lines show advanced-economy average.
Click here to download data and charts.

significant in many EMDEs, as their productivity
levels, which lag the global technological frontier,have substantial scope for convergence. A rising
share of manufacturing employment and increased
vertical specialization have generally been
associated with higher productivity and income
per capita levels (Diao, McMillan, and Rodrik
2017; Hallward-Driemeier and Nayyar 2018;
Szirmai and Verspagen 2015). Manufacturing canfoster the diffusion of technologies, particularly forcountries that are currently less integrated into
global value chains, and thus boost long-term
growth prospects.
Rapid technological changes—including increased
digitalization and the use of advanced robotics—
may significantly affect countries’ comparativeadvantages. Increased diffusion and adoption ofdigital technologies in EMDEs are likely to bepositive for growth and job creation, particularly
in countries with elevated levels of digital literacy.
Mobile and internet technologies can lower costsof market access, foster entrepreneurship, andimprove labor market efficiency, thereby helping
workers and firms match skills to jobs.
While evidence of employment-saving industrial
automation is limited in EMDEs, task-replacing
technologies could potentially contribute to labor
displacement over time, including in more
traditional manufacturing activities (Acemoglu
and Restrepo 2018; Autor and Salomons 2018;
Maloney and Molina 2016). At the same time, theincreasing services intensity of manufacturing cancreate important labor market opportunities andproductivity advancement in EMDEs (Enache,Ghani, and O’Connell 2016; Kinfemichael andMorshed 2015; WTO 2017; UNCTAD 2017a).
These trends suggest rapid changes in the types ofinvestments and skills needed for manufacturingled growth in EMDEs. Opportunities and risks
will vary across sectors, depending on the extent oftrade in international markets, the degree ofexport concentration, the level of automation, andthe importance of complementary services. Laborintensive industries, including commodity-based
and less-automated manufacturing processes,
remain important entry points for lessindustrialized economies. This applies to rapidlyG LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

expanding urban areas in Sub-Saharan Africa,
where an improved manufacturing base andgreater openness to regional and international
trade could unlock potential for higher per capita
income growth (Lall, Henderson, and Venables
2017).
For manufacturing sectors that are more easily
automated, and where trade is more concentrated,advanced technology may be more disruptive andlabor-saving, but necessary to raise efficiency andmaintain competitiveness. Successful industrialization strategies will need to focus on
strengthening international competitiveness,increase skills and adaptability, support firms’
capacity to absorb new technologies, and foster
the development of complementary services.
Promoting trade openness
Measures that reduce barriers to trade could
contribute to boosting value chain integration,
investment, and productivity. Despite the lack ofprogress in multilateral trade negotiations, newtrade agreements have been concluded or are
being negotiated, including the Comprehensive
and Progressive Agreement for a TransPacific Partnership (CPTPP), the European
Union–Mercosur trade agreement, the Regional
Comprehensive Economic Partnership between
the Association of Southeast Asian Nations(ASEAN) countries and six of their major trading partners, and the African Continental Free
Trade Area (AfCFTA). These have the potential
to boost not only intra-regional trade and incomesof member countries, but also to provide
a counterbalance against rising protectionist
sentiments.
Full implementation of the CPTPP, signed by 11
countries, together accounting for 16 percent of
global GDP and 14 percent of global trade, is
expected to provide a boost to trade flows for its
members, even if potential gains have been
reduced following the withdrawal of the UnitedStates from the original TPP (Maliszewska,
Olekseyuk, and Osorio-Rodarte 2018). The
AfCFTA was launched by countries representing a
notably smaller share of global GDP and trade;however, once ratified by its 44 members, it would

CHAPTER 1

be the largest free-trade area in terms of
population and number of countries. The
AfCFTA has the potential to substantially foster
intra-regional trade flows, contribute to greater
economic diversification, and lead to higher valueadded products and greater innovation in Africa(Saygili, Peters, and Knebel 2018; UNCTAD
2017b).
Deep regional trade agreements—those that go
beyond tariff reductions and that contain wideranging commitments in the areas of competition,
investment, services, and the protection of
intellectual property rights—are associated withlarger trade and income gains (Constantinescu etal. forthcoming; Hofmann, Osnago, and Ruta
2017). Promoting such commitments could
therefore yield sizable dividends for EMDEs.
Successful regional trade arrangements also need
to be platforms for further integration with therest of the world, as shown by the positive
experiences in Europe and Asia.
Improving education and training
Policies related to education and training
programs can be redesigned to adapt available
skills to changing development needs and newtechnologies, thereby boosting growth andemployment prospects (World Bank 2018j). As
countries become increasingly engaged in more
complex production processes, higher levels of
tertiary school enrollment and investment in skills
related to information and communication
technology (ICT) have a bigger payoff. Training
programs that are responsive to changing industry
needs are particularly important (HallwardDriemeier and Nayyar 2018). As technologies arelikely to change more quickly than national
education systems are able to adapt to them,innovative ways of imparting skills will need to be
developed, including through experimentationand impact evaluation. The importance ofequipping people with the necessary skills to adapt
to new opportunities is emphasized in the G20’s
agenda on the future of work.
For many low- and middle-income countries—
particularly in Sub-Saharan Africa and in the
Middle East and North Africa—improving basic
numeracy, literacy, and ICT-related skills remains

47

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a key priority. Even though school enrollment andaverage years of schooling have markedly increased
over the last decade, learning and the acquisitionof basic skills remain insufficient in these countries(Altinok, Angrist, and Patrinos 2018). Early
learning deficits are magnified over time and tend
to accentuate inequality, whereas higher intergenerational mobility in education is associatedwith higher growth and lower poverty (PASECG LO BAL EC O NO MIC P ROS P EC TS | J U NE 20182015; World Bank 2017d). Improving learning
outcomes requires better measurement andmonitoring, improved school practices, andgreater accountability. Helping to develop “soft”
skills that foster adaptability, as well as initiativeand problem solving, could come at a premium inview of the rapid and unforeseen changes in skills
requirements and the increasing automationof repetitive tasks.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

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49

TABLE 1.2 List of emerging market and developing economies1
Commodity exporters2

Commodity importers3

Albania*

Madagascar

Afghanistan

Algeria*

Malawi

Antigua and Barbuda

Philippines
PolandAngola*Malaysia*

Bahamas, The

Romania

Argentina

Mali

Bangladesh

Samoa

Armenia

Mauritania

Barbados

SerbiaAzerbaijan*

Mongolia

Belarus

Seychelles

Bahrain*

MoroccoBhutanSolomon Islands

BelizeMozambique

Bosnia and Herzegovina

Sri Lanka

Benin

Myanmar*

Bulgaria

St. Kitts and Nevis

Bolivia*

Namibia

Cabo Verde

St. Lucia

Botswana

Nicaragua

Cambodia

St. Vincent and the Grenadines

Brazil

Niger

China

Swaziland

Burkina Faso

Nigeria*

Comoros

Thailand

BurundiOman*

Croatia

Tunisia

Cameroon*

Papua New Guinea

Djibouti

TurkeyChad*Paraguay

Dominica

Tuvalu

Chile

Peru

Dominican Republic

VanuatuColombia*

Qatar*

Egypt

VietnamCongo, Dem. Rep.

Russia*El Salvador

Congo, Rep.*

RwandaEritrea

Costa Rica

Saudi Arabia*

Fiji

Côte d’Ivoire

SenegalGeorgia

Ecuador*

Sierra Leone

GrenadaEquatorial Guinea*

South Africa

Haiti

Ethiopia

Sudan*

Hungary

Gabon*

Suriname

India

Gambia, The

Tajikistan

Jamaica

Ghana*

Tanzania

JordanGuatemalaTimor-Leste*

Kiribati

GuineaTogo

LebanonGuinea-Bissau

Tonga

LesothoGuyanaTrinidad and Tobago*

Macedonia, FYR

Honduras

Turkmenistan*

Maldives

Indonesia*

UgandaMarshall Islands

Iran*

Ukraine

Mauritius

Iraq*

United Arab Emirates*

MexicoKazakhstan*

Uruguay

Micronesia, Fed. Sts.

Kenya

Uzbekistan

Moldova, Rep.

KosovoVenezuela*

Montenegro

Kuwait*West Bank and Gaza

Nepal

Kyrgyz RepublicZambiaPakistan

Lao PDR

Zimbabwe

Palau

Liberia

PanamaEnergy exporters.
Emerging market and developing economies (EMDEs) include all those that are not classified as advanced economies. Dependent territories are excluded. 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; theRepublic 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 ofany single commodity accounted for 20 percent or more of total goods exports. Economies for which these thresholds were met as a result of re-exports were excluded. When data were notavailable, 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.
*

1

50

CHAPTER 1

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The Role of Major Emerging Markets
in Global Commodity Demand
Rapid growth among the major emerging markets over the past 20 years has boosted global demand for commodities. The
seven largest emerging markets (EM7) accounted for almost all the increase in global consumption of metals, and two-thirdsof the increase in energy consumption over this period. As these economies mature and shift towards less commodity-intensive
activities, their demand for most commodities may plateau. While global energy consumption growth may remain broadly
steady, growth in global demand for metals and food could slow by one-third over the next decade. This would dampen
global commodity prices. China would likely remain the single largest consumer of many commodities, although consumption
growth in other EM7 countries might accelerate. For the two-thirds of emerging market and developing economies that
depend on raw materials for government and export revenues, these prospects reinforce the need for economic diversificationand the strengthening of policy frameworks.

Introduction
Global commodity demand surged in 2000-08,
driven by rapid growth in large emerging market
and developing economies (EMDEs), especiallyChina. Over this period, real energy prices rose
154 percent, metals prices increased 107 percent,and food prices rose 62 percent (Figure SF1.1).
Commodity prices peaked in 2011, and fell
sharply in 2014, driven by the collapse in the priceof crude oil. While commodity prices have since
recovered as a result of the cyclical global
economic recovery, over the longer term,
economic developments in major EMDEs will bea critical factor for the path of demand.
This Special Focus explores the role of the sevenlargest EMDEs, the EM7 (Brazil, China, India,
Indonesia, Mexico, the Russian Federation, andTurkey). Together, these economies account for
about 25 percent of global GDP and 50 percent of
the world’s population. In commodity markets,
this group about for around 60 percent of theconsumption of metals and 40 percent of theconsumption of energy and food. The EM7 havealso driven much of the increase in industrial
materials demand over the past two decades, with
China alone accounting for 83 percent of the
global increase in metals consumption and 48
percent of the increase in energy consumption.
Note: This Special Focus was prepared by John Baffes, Alain
Kabundi, Peter Nagle, and Franziska Ohnsorge. Research assistance
was provided by Xinghao Gong.

FIGURE SF1.1 Developments in commodity markets
Consumption of commodities has surged over the past 20 years. Growth inconsumption of metals, particularly aluminum, has been much faster than
GDP and population growth, while energy consumption growth has beenslower than GDP growth.

A. Real commodity prices

B. Cumulative growth in GDP,
population, energy and metals
consumption, 1996-2016

C. Average growth in GDP,
population, energy and metals
consumption, 1996-2016

D. Share of global commodity
consumption

Sources: BP Statistical Review, U.S. Department of Agriculture, World Bank, World Bureau of Metals
Statistics.
A. Deflated using the manufacturing unit value index from the January 2018 edition of the Global
Economic Prospects report.
B.-D. Metals aggregate includes aluminum, copper, lead, nickel, tin, and zinc. Energy aggregate
includes coal, crude oil, natural gas, nuclear, and renewables.
C. G7 includes Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States.
EM7 includes Brazil, China, India, Indonesia, Mexico, Russia, and Turkey.
D. Grains includes maize, rice, and wheat.
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FIGURE SF1.2 Vulnerabilities to oil price fluctuations
The oil price collapse in 2014 severely set back economic activity andworsened fiscal positions in oil-exporting countries. Oil-exporting countries
tend to have an above-average export concentration compared with other
EMDEs. Activity in oil exporters with lower levels of export concentration
recovered more quickly than in those with high export concentrations. The
deterioration in fiscal deficits was greater in oil-exporting EMDEs withhigher reliance on oil-related revenues.

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

B. Export concentration, 2016

C. GDP changes since 2014, by export
concentration

D. Change in fiscal balance since2014, by reliance on oil revenue

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
with a slower pace of contraction from one year to the next are included in the increasing growth
category.
B.-D. Figure shows average and interquartile range for the separate categories. Sample includes 31
oil-exporting EMDEs as defined in World Bank 2018a.
B.C. Export concentration is measured by a Herfindahl-Hirschmann Index, where values closer to 1
indicate a country’s exports are highly concentrated on a few products.
C. “Above average” and “below average” groups are defined by countries above or below the sample
average for export concentration in 2014.
D. Change in overall fiscal balance is measured from 2014-17. Above average and below average oilrevenue groups are defined by countries above or below the sample average of oil revenues as ashare of GDP based on 2014 data.
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EMDEs are likely to remain important drivers ofcommodity market developments, although theimportance of individual countries will change.
While China has been the main driver of growth
in industrial materials, its expected growth
slowdown and shift towards less commodityintensive activities such as services could herald
softer commodity consumption in the future.
Global growth is expected to be increasingly
driven by economies that are, at present, much lesscommodity intensive than China. Weaker

commodity consumption growth is a key factor
behind the World Bank’s forecast of modest pricegrowth over the medium-term (World Bank
2018a).
Slowing commodity demand and modest priceincreases will have important consequences for
growth and poverty alleviation among other
EMDEs. Two-thirds of EMDEs depend
significantly on agriculture and mining andquarrying for government and export revenues,
and more than half of the world’s poor live incommodity-exporting EMDEs (World Bank
2016a). This exposes these economies tocommodity price shocks (Didier et al. 2016;
Baffes et al. 2015). For example, the crude oil
price collapse in mid-2014 resulted in a growth
slowdown in 70 percent of EMDE oil exporters,with the largest impact in countries with higher
levels of export concentration (Figure SF1.2;
World Bank 2017a, 2018b). The fall in prices
weakened fiscal positions and led to sharp cuts ingovernment spending. The prospect of weaker
commodity prices intensifies the need for reforms
to encourage economic diversification incommodity exporters, and to strengthen monetaryand fiscal policy frameworks (World Bank 2018a).
This Special Focus addresses the following
questions:•

What impact have the EM7 had on
consumption of major commodities?

•

What is the role of per capita income growthin rising commodity consumption?

•

What are the prospects for global commodity
consumption?

•

What policy measures can commodity
exporters implement to boost resilience?

This Special Focus presents a comprehensive anddetailed analysis of the role of major emerging
markets in global consumption of a wide range ofcommodities. It also presents estimates for theincome elasticities of consumption for a range ofenergy, metals, and food products. In doing so, it
expands on previous research looking at the
impact of China and India on commodity

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63consumption (World Bank 2015b; Pesaran et al.
1998, 1999; Stuermer 2017). Finally, it develops a
set of stylized scenarios of consumption growthprospects based on estimated income elasticities,
together with long-term population and GDP
projections.

FIGURE SF1.3 EM7 in the global economy

The role of the EM7 incommodity consumption

A. Contribution to global growth

B. Share of global GDP

C. Share of global trade, remittances,and FDI

D. Impact of a 1-percentage-point
increase in EM7 growth on growth inother EMDEs and globally

EM7 in the global economy. The share of theEM7 in the global economy has grown rapidly.
Since 2010, the EM7 accounted for more thanhalf of global growth, 19 percent of global tradeand 18 percent of global FDI flows (Figure
SF1.3). They now account for 25 percent of
global GDP (at market exchange rates) and 50
percent of the global population.
Given their size and international integration, theEM7 economies can produce significant crossborder spillovers: estimates suggest that a 1
percentage point increase in EM7 growth isassociated with a 0.9 percentage point increase in
growth in other emerging market and developing
economies and a 0.6 percentage point increase inglobal growth at the end of two years (Huidrom,
Kose, and Ohnsorge 2017; World Bank 2016b).
Individual EM7 countries can also have global andregional impacts:•

China plays a uniquely important role among
the EM7. Growth spillovers from China havea global reach, while those of other EM7 arelargely regional (World Bank 2016a). China
has almost as large a share of global GDP (12percent) as the other EM7 combined (13percent).

•

Brazil and Mexico are the largest economies in
Latin America and the Caribbean (LAC),
accounting for 60 percent of regional GDP.
Shocks to growth in Brazil, in particular, havea statistically significant impact onneighboring EMDEs (World Bank 2016b).

•

Russia accounts for 46 percent of GDP in
Europe and Central Asia (ECA). It has
important spillovers to Central Asia andEastern Europe through long-establishedtrade, investment, and migration links.

The role of the EM7 in the global economy has grown rapidly and they now
account for 25 percent of global GDP, although they remain smaller thanthe G7. Since 2010, EM7 have accounted for more than half of global
growth, 19 percent of global trade, and 18 percent of global FDI flows.
Shocks to growth in EM7 countries can have sizeable spillovers at the
global level, as well as to other EMDEs.

Sources: United Nations Conference on Trade and Development (UNCTAD), World Bank.
A.-C. EM7 includes Brazil, China, India, Indonesia, Mexico, Russia, and Turkey. G7 includes Canada,
France, Germany, Italy, Japan, the United Kingdom, and the United States.
A.B. Aggregate growth rates and GDP shares calculated using constant 2010 U.S. dollar weights.
C. World shares of EM7 and G7 countries of trade (exports and imports of goods and services),
remittances (both paid and received), and FDI flows (inward plus outward) over respective periods.
D. Results are derived from a Bayesian vector autoregression using the methodology outlined in
Huidrom, Kose and Ohnsorge (2017). The model includes, in this order, G7 growth, the U.S. interest
rate, J.P. Morgan’s Emerging Market Bond Index (EMBI), EM7 growth, oil prices, and growth in other
EMDEs. Other EMDEs consists of 15 countries. Cumulative impulse responses of a 1-percentage
point increase in EM7 growth on growth in other EMDEs (blue) and global growth (red), at the 1-year
and 2-year horizons. Solid bars represent medians, and error bars represent 16-84 percent
confidence intervals.
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EM7 in commodity markets. The EM7 areimportant participants in commodity markets,
both as consumers and producers (Box SF1.1,
Annex Tables SF1.1, and SF1.2).1 The groupaccounts for a larger share of global consumption
than the G7 in coal, all base metals, precious
metals, and most foods (rice, wheat, soybeans;Figure SF1.4).
1 “Consumption” includes the use of commodities for ﬁnal
consumption, as well as intermediate inputs into the manufacture ofother products, including for export. To the extent that these otherproducts are exported, the source country of ﬁnal demand may notcoincide with the source country of commodity demand.

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BOX SF1.1 The role of the EM7 in commodity production

After decades of rapid growth, the EM7 have become major commodity producers. China is the world’s single-largest
producer of coal, several base metals, and fertilizers, while other EM7 are also key suppliers of several commodities. As
a result, policies that affect EM7 commodity production—such as recent trade- and security-related measures—canmove global markets.
Following several decades of rapid growth incommodity production, in part in response to risingdomestic demand, the EM7 have become majorcommodity producers. For many commodities, theirproduction exceeds that of the G7 economies by awide margin. China in particular is now a majorcommodity producer, although its consumption ofmost commodities has outpaced its production.
This box analyzes the following questions:•

What is the role of EM7 in today’s commodity
production?

•

How has this role evolved over time?

EM7’s current role in commodity production
Major producers of many commodities. The EM7
account for more than half of global production incoal, rice, and most base metals (aluminum, copper,lead, tin, and zinc). In some energy commodities (oiland natural gas), they account for more than onefifth of global production. EM7 production dwarfs
G7 production in coal, metals, rice and maize, while
it almost matches G7 production in crude oil, naturalgas, and wheat. The EM7 produce about 20 times asmuch rice as G7 economies, almost eight times asmuch aluminum, and three to five times as muchcopper, coal, and zinc.
Individual EM7 countries. Individual EM7
countries, especially China, dominate global
production of several commodities (Table SF1.2):•

China is the world’s largest producer of coal,
several metals (aluminum, refined copper, leadand gold), rice, and fertilizers.

•

India is the largest producer of cotton and thesecond-largest producer of fertilizers.

•

Russia is the second-largest producer ofaluminum and natural gas, and third largest
producer of oil.

•

Brazil is the largest producer of coffee and sugar,
the second-largest producer of soybeans, and thethird-largest producer of bauxite.

•

Indonesia is the largest producer of tin and palm
oil and the second largest producer of rubber.

•

Mexico is the largest producer of silver.

China’s production of rice and wheat is almost as
large as that of all other EM7 combined, while its
production of most base metals (aluminum, copper,lead, zinc, and tin) is a multiple of that of all otherEM7 combined.
Evolution of the EM7’s role over timeRole of the EM7 in energy and metals markets.
Between 1996 and 2016, the EM7 share of global
metals production more than doubled to 60 percent
and their share of global energy production increased
to 39 percent (Figure SF1.1.1). Over this period, theEM7 accounted for almost 90 percent of the increase
in metals production and over half of the increase inglobal energy production.
Role of China in energy and metals markets. The
growing role of the EM7 in global commodity
production largely reflects expansion in China.
China’s share of global metals production increased
to 48 percent between 1996 and 2016 (driven byaluminum), and its share of global energy production
nearly doubled, to 18 percent in 2016. Growing
domestic production dampened the impact of theincrease in China’s demand on global commodity
markets, with domestic supply accounting for ninetenths of the increase in China’s metals consumption.
China’s consumption of copper and nickel was more
dependent on imports than consumption of othermetals. While production of metals rose in the other
EM7, they lost global market share (from 16 percent
to 12 percent) to China. The EM7 share of energy
production rose slightly, driven by oil in Brazil andRussia, and coal in India and Indonesia.

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BOX SF1.1 The role of the EM7 in commodity production (continued)
FIGURE SF1.1.1 EM7 in commodity production
The EM7 are some of the largest commodity producers in the world. Their share of global production of commodities has
increased rapidly over the past 20 years, and they now account for around 60 percent of metals production, and 40 percent ofenergy and agricultural production.
A. Share of energy production, 2016

B. Share of metals production, 2016

C. Share of commodity production

Sources: BP Statistical Review, U.S. Department of Agriculture, World Bank, World Bureau of Metals Statistics.
A.B. “AEs” stands for advanced economies. “Other EM7” includes Brazil, Indonesia, Mexico, Russia, and Turkey (and excludes China and India).
A. Other AEs contains five countries. Other EMDEs is calculated as the residual of the global total.
B. Alum. refers to the metal aluminum. Other AEs contains 10 countries. Other EMDEs contains 25 countries.
C. Other EM7 includes Brazil, India, Indonesia, Mexico, Russia, and Turkey.
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Role of EM7 in agricultural commodities. In
contrast to energy and metals, the role of the EM7 inagricultural production has been fairly constant overthe last two decades, similar to the evolution of theirconsumption. The EM7 share of the three main
grains (maize, rice, and wheat) has stayed broadly flatat about 44 percent since 1996.
Role of the EM7 in other EMDEs. Some of the
EM7 are increasingly involved in production in other
EMDEs through investments, or partnerships andsubsidiaries. Sub-Saharan Africa has been one of themain beneficiaries of investment, which has beenprevalent in agriculture and metals, notably rare

China and India are particularly prominent
consumers. China is the world’s largest consumerof coal, several industrial metals (aluminum,
refined copper, and lead) and fertilizers. India is
the world’s largest consumer of palm oil, and its
second-largest consumer of coal (about onequarter of China’s consumption) and gold (forfabrication, about two-thirds of Chinese consump-earths (Deininger et al. 2011; Dollar 2016). Again,
China has been the most prominent country,
although Russia has also been a key player,
particularly in aluminum.
Conclusion
The EM7 have become some of the world’s largest
commodity producers after a period of rapid
production growth. As a result, policies that affecttheir production or ability to export commodities—
such as environmental policies to reduce pollution, ortrade-related measures—can move global commodity
markets and have spillovers to other regions.

tion). India is also the third-largest consumer of
crude oil and natural rubber.
Combined, China’s and India’s use of commodities is a multiple of the remaining five EM7.
For example, consumption in the two countries ismore than ten times the remaining EM7 in coal,
aluminum, and nickel, and more than six times in

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FIGURE SF1.4 EM7 in commodity markets
China’s share of global metals and coal consumption rose to around 50
percent in 2016, while the share of the other EM7 is smaller, but still
significant. Over the last 20 years, the EM7 account for the majority of theincrease in metals consumption, two-thirds of the increase in energy
consumption, and more than one-third of the increase in agriculturalcommodity consumption. While the global commodity intensity of GDP has
generally declined, it increased from the mid-2000s for metals, mainly due
to growth in consumption in China, and is now back at its 1965 level.
A. Share of energy and agricultural
consumption, 2016

B. Share of metals consumption, 2016

C. Contribution to average annual
growth in energy consumption

D. Contribution to average annual
growth in metals consumption

E. EM7 share of commodity
consumption

F. Change in commodity intensityof consumption growth

Sources: BP Statistical Review, U.S. Department of Agriculture, World Bank, World Bureau of Metals
Statistics.
A.-D. “AEs” stands for advanced economies. Other EM7 includes Brazil, Indonesia, Mexico, Russia,
and Turkey.
A.C. “Other AEs” contains 18 advanced economies. Other EMDEs contains 32 countries.
B.D. “Other AEs” contains 17 advanced economies. Other EMDEs contains 31 countries.
F. Commodity intensity calculated as global energy and metals use (in volumes) relative to global
GDP (in 2010 U.S. dollars), including and excluding China.
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copper, zinc, lead, and tin. China and India
consume 50 percent more crude oil than the otherfive EM7, while their maize and wheat consumption is twice as high and their rice consumption

five times as high. In turn, the EM7 account for
four times the consumption of other EMDEs incoal and metals, and a similar amount of crude oiland grains.
Evolution of the EM7 share in commodity
consumption. Over the past two decades, EM7
countries have driven the growth in global
demand, especially for energy and metals. The
EM7 accounted for 92 percent of the increase inmetals consumption, 67 percent of the increase inenergy consumption, and 39 percent of theincrease in global food consumption between
1996 and 2016. The increase in demand formetals was such that the ratio of global metals
consumption to GDP—which had been declining
prior to the 1990s—reversed trend and started torise rapidly by the turn of the century. This
reversal largely reflected developments in China,
which accounted for 83 percent of the increase inglobal consumption between 1996 and 2016, andoccurred despite rising global demand for services,which are much less materials-intensive than
goods (Tilton 1990, Radetzki et al. 2008). In
contrast, the energy intensity of global GDP
continued to decline, in line with its prior trend,
supported by efficiency improvements as well as
the shift of global demand toward services.

Drivers of commodities
consumption
Several factors have supported the growing role of
the EM7 in global commodity markets. Thissection takes a quantitative look at the role of percapita income growth and slowing population
growth, as well as prices, in driving global demandfor key commodities. The rest of the Special
Focus, considers three energy products (crude oil,coal, and natural gas) and three metals(aluminum, copper, and zinc). These make up 85
percent of energy and base metals consumption. It
also considers four foods (rice, wheat, maize, andsoybeans), which collectively cover 70 percent ofarable land.2
2 This Special Focus does not consider iron ore or non-foodagricultural commodities. The use of iron ore is more complex thanthe other metals considered here since it is an input into the
production of steel. Competitive price benchmarks for iron ore are
only available from 2005.

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Per capita incomes and consumption. Per capita
consumption of most commodities generally
plateaus as per capita income rises, and may evendecline at higher levels of income (crude oil, coal,copper, zinc, and rice; Figures SF1.5 and SF1.6).
Natural gas shows less sign of plateauing thanother commodities, which may reflect a shift inconsumer demand to cleaner fuels as incomes rise.
China has seen a much faster increase than othercountries in its per capita use of aluminum andcoal during 1965-2016, with higher consumption
for a given level of per capita income.
The increase in coal and aluminum consumption
relative to per capita income in China over theperiod 1965-2016 has also been faster than that of
the Republic of Korea, a country which
underwent rapid industrialization in the 1960s to
80s. Growth in China’s copper and zinc per capita
consumption relative to per capita income has
been broadly in line with Korea’s, while that ofcrude oil has been weaker. Per capita commodity
consumption remains significantly higher thanother EM7 across all categories except natural gas,
due to high per capita consumption in Russia.
Income elasticity of consumption. The
relationship between consumption and income iscaptured by the income elasticity of demand: thepercent increase in commodity consumption
associated with a 1 percent increase in income.
Elasticities vary significantly between the long andshort run, but tend to be larger in the long run as
adjustment of consumption to higher incomestakes time.3 The long-run elasticity is more
relevant to the multi-decade trends described inthis Special Focus.
Income elasticities can vary as per capita incomesrise and as economies mature. With risingincomes, consumer demand tends to shift towards
less resource-intensive goods and services, which
results in a fall in income elasticities (Tilton 1990;
Radetzki et al. 2008). Consumer demand also
tends to shift toward cleaner forms of energy suchas natural gas, from more polluting and inefficient
sources such as firewood and coal (Burke and3 Dahl and Roman (2004) find a short-run income elasticity for
crude oil of 0.47 and a long-run income elasticity of 0.84.

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67

FIGURE SF1.5 Consumption of industrial commodities
and income
The relationship between per capita income and industrial commodity
consumption per capita shows signs of plateauing for most commodities
as income rises. A notable exception is natural gas, which likely reflects
preferences for cleaner fuels over more polluting fuels such as coal.

A. Oil consumption per capita vs. GDP
per capita

B. Natural gas consumption per capita
vs. GDP per capita

C. Coal consumption per capita vs.
GDP per capita

D. Aluminum consumption per capita
vs. GDP per capita

E. Copper consumption per capita vs.
GDP per capita

F. Zinc consumption per capita vs.
GDP per capita

Sources: BP Statistical Review, World Bank, World Bureau of Metal Statistics.
A.-F. GDP per capita in constant 2010 U.S. dollars. Lines show the evolution of income and commodity consumption per capita over the period 1965-2016. Each data point represents one country orgroup for one year. Data for other EM7 are available from 1985-2016 for crude oil, natural gas, andcoal, and 1992-2016 for aluminum, copper, and zinc.
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Csereklyei 2016). Food consumption also tends toswitch away from grains to products with higher
protein and fat content such as meat (Salois et al.
2012). In addition, demand for industrial materials slows as economies mature and infrastructureneeds are increasingly met.

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FIGURE SF1.6 Food consumption and income•

Metals. For metals, the elasticity of income
depends on the availability of substitutes andthe range of uses. Because of its wide
applicability, demand for aluminum has beenfound to grow more than proportionately
with rising output, i.e. with an above-unitaryelasticity, while tin and lead, because ofenvironmental concerns, grow less thanproportionately, i.e., with a below-unitaryelasticity (Stuermer 2017).

•

Food commodities. Elasticities of food productsvary widely. Elasticities for grains are generally
below unity, with demand driven by
population, rather than income, beyond a
subsistence income threshold (Engel 1857;
Baffes and Etienne 2016; World Bank
2015b). Valin et al. (2014) find a medianincome elasticity of demand of close to 0.1 forrice and wheat. Elasticities are generally higher
for foods with higher fat and protein contents,
such as animal products, suggesting that
consumers switch to these types of foods asincomes rise (Salois, Tiffin, and Balcombe
2012; Valin et al. 2014, World Bank 2015b).
The use of maize and soybeans as animal feedmeans that their elasticities are driven more bydemand for meat than demand for direct
consumption, resulting in higher elasticities.5

The relationship between income per capita and food consumption percapita is more varied than that of income per capita and industrial
commodities per capita. For rice, the relationship is heterogenous between
countries, which may reflect domestic preferences or availability. Maizeand soybeans exhibit a broadly linear relationship, reflecting their use inanimal feed and biofuels, which have a relatively high income elasticity.
A. Rice consumption per capita vs.
GDP per capita

C. Maize consumption per capita vs.
GDP per capita

B. Wheat consumption per capita vs.
GDP per capita

D. Soybean consumption per capita
vs. GDP per capita

Sources: U.S. Department of Agriculture, World Bank.
A.-D. GDP per capita in constant 2010 U.S. dollars. Lines show the evolution of income and grainsconsumption per capita over the period 1965-2016. Due to data restrictions “G7” includes the UnitedStates, Japan, Canada and all EU28 countries.
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Estimates of long-run income elasticities.
Estimates of long-run income elasticities ofdemand vary by commodity, between countries,
and over time, as incomes rise (Annex Table
SF1.3).
•

Energy. For energy, most studies have foundan income elasticity of demand of less thanunity (Burke and Csereklyei 2016; Csereklyei
and Stern 2015; Jakob et al. 2011). That
implies per capita energy consumption grows
more slowly than per capita real GDP,consistent with a declining energy intensity ofdemand. Several papers find that income
elasticities of demand fall as income rises(Dahl 2012; Foquet 2014; Jakob et al. 2012).4

4 An exception is Burke and Csereklyei (2016), who ﬁnd thelong-run income elasticity of demand increases as per capita real

Estimates of price elasticities. Demand forcommodities tends to be price inelastic. Withinenergy, price elasticities for crude oil range fromzero to -0.4 (Huntington, Barrios, and Arora
2017; Dahl and Roman 2004). For metals,
Stuermer (2017) finds the largest price elasticity
for aluminum (-0.7), but smaller elasticities forcopper (-0.4), tin, and zinc (less than or equal
to -0.2). As with income elasticities, priceelasticities of demand tend to be larger in the longrun than the short-run, as consumers have more

GDP rises. This ﬁnding likely reﬂects their country sample which
includes a number of low income countries whose long-run income
elasticity of demand tends to be very low, as a result of their relianceon non-commercial fuels (i.e., biomass). Elasticities in low income
countries may also be kept artiﬁcially low by policies such as energy
subsidies (Joyeux and Ripple 2011).
5 For example, 70 percent of soybeans in the United States are used
for animal feed (USDA 2015).

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S P EC IAL FO CU S 1time to respond to changes in prices by finding
substitutes, or efficiency gains.6
Estimation of long-run income elasticities. The
remainder of this section reports estimates for the
long-run income elasticities of the energy, metals,
and agricultural commodities shown in Figures
SF1.5 and SF1.6.

at the top quartile of 2017 per capita incomes.
Aluminum and copper have the highest longrun income elasticities (0.8 and 0.7,
respectively; Figure SF1.7), while zinc is
considerably lower at 0.3.9•

Energy. Long-run income elasticities for crude
oil and coal also decline as per capita incomesrise. At the median per capita income in 2017,
the income elasticity of crude oil is 0.5, whilethat of coal is 0.6.10 The elasticity for coal,
however, drops rapidly with rising per capita
incomes as users switch from biomass, such aswood, to more efficient coal at low incomes,
and subsequently from coal toward cleaner
energy sources at high incomes. At the highest
quartile of per capita incomes in 2017, theestimated income elasticity of coal is negative.
For natural gas, in contrast, a significant nonlinear relationship between income andconsumption was not found, but rather alinear relationship was noted, with anelasticitiy of 0.4. Natural gas’ use as fuel forelectricity generation has grown rapidly, so
few countries have reached the “plateau stage”
within the sample.

•

Food commodities. The estimated elasticity ofrice consumption declines sharply as incomesrise, turning negative at the first income
quartile in 2017. For wheat, the decline inelasticities as incomes rise is less pronounced,
with the elasticity remaining positive, albeit
low, for all income levels.11 In contrast, formaize and soybeans the relationship between
income and consumption appears to be linear,and elasticities are much higher than rice and

An autoregressive distributed lag model is used toestimate the logarithm of per capita commodity
consumption (in physical units) as a function of
per capita real GDP in U.S. dollars (Annex
SF1.1).7 The sample covers up to 33 countries (21advanced economies and 12 EMDEs) for energy
and metals, with annual data from 1965-2016(Annex Table SF1.4). A different dataset, withpredominantly EMDE representation and fewer
advanced economies, is available for food, with 55
countries for rice, 35 countries for wheat, 47
countries for maize, and 32 countries for soybeans.
A quadratic term for per capita real GDP is
included to account for non-linearities in therelationship between per capita commodity
consumption and per capita income (Meier,Jamasb, and Orea 2013). The regression controls
for real commodity prices.8
Estimation results. The estimated long-run
elasticities differ widely across commodities andacross income levels (Table SF1.1; Figure SF1.7).
As expected, for most commodities long-run
elasticities decline with rising per capita income(indicated by a negative coefficient on squared per
capita income in Table SF1.1 and Annex Table
SF1.5). In general, long-run income elasticities formetals tend to be above those of energy and food.
Metals. Elasticities of metals decline withrising incomes, but remain elevated (0.4) even•

For example, Dahl and Roman (2004) ﬁnd a short-run priceelasticity of crude oil of -0.11, and a long-run price elasticity of -0.43.
7 This methodology allows for cross-country heterogeneity in shortterm coeﬃcient estimates but imposes homogeneity in long-term
coeﬃcient estimates. The Hausman test (Annex Table SF1.5) suggeststhat this assumption is appropriate.
8 To account for potential endogeneity, a Generalized Methods ofMoments (GMM) model is also estimated. The results are robust(Annex Table SF1.6). They are also qualitatively robust to including atime trend to account for potential long-term productivity growth(Annex Table SF1.7).
6

9 The estimates for the metals commodities are weaker than
Stuermer (2017), which found an elasticity of 1.5 for aluminum, 0.9
for copper, and 0.7 for zinc. The diﬀerences likely arise from the useof manufacturing output, rather than GDP, as the explanatory
variable. Using manufacturing output controls for changes in thecomposition of growth in the economy over time, which is caused by
the share of manufacturing output declining in favor of services overtime.
10 Huntington, Barrios, and Arora (2017) also ﬁnd an elasticity ofcrude oil of 0.5.
11 The elasticity at median incomes in 2017 for wheat was a little
higher, and for rice a little lower, than found by Vanin et al. (2014).

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TABLE SF1.1 Estimation results
Commodity

Log per
capitaincomeAluminum

3.50

-0.15

0.8

Zinc

2.60

-0.12

0.3

Copper

2.95

-0.12

0.7

Crude oil

2.31

-0.10

0.5

6.04

-0.31

0.6

Natural gas

0.38

...

0.4

Rice

1.39

-0.09

-0.3

Wheat

1.05

-0.04

0.3

Maize1

0.85

…

0.8

Soybeans1

0.84

...

0.8

Coal
1

Squared log Income elasticity
per capita
at 2017 medianincomeincomeNote: Results shown are a sub-set of the estimations obtained using thepooled mean group model (see Annex SF1.1). Values for log and log squared
per capita income are the coefficients for these variables as estimated by themodel. Income elasticities are calculated using these coefficients, together withmedian global per capita income in 2017. Annex Table SF1.5 displays the full setof results from the estimation, including both short-run and long-run coefficients.
1 indicates linear regression results for commodities which do not appear tohave a non-linear relationship with income.

wheat at 0.8.12 These commodities are heavily
used as animal feed (and also biofuels), so
their use is closely linked to demand for meat
which tends to have a higher income elasticity
of demand than grains.
For most commodities, the estimated long-run
income elasticities for the EM7 countries aremuch higher than for the G7. While the focus
here is on long-run trends, it is worth noting that
consumption adjusts quite slowly: the regressions
imply adjustment periods to the long-run
equilibrium of three to eight years for grains, fourto seven years for metals, and six to fourteen years
for energy.13
EM7 consumption growth in 2010-16. Thissection compares in-sample fitted growth rates

12 Figure SF1.6 suggests that the relationship for soybeans andmaize is linear. The initial regressions for these foods generated
signiﬁcant coeﬃcients for the quadratic term but not for the linear
term. The regression cannot distinguish well between a linear and aquadratic relationship, so the quadratic term was dropped.
13 In line with the literature, the model also generates modest priceelasticities, but the emphasis here is on income elasticities.

generated by the model with actual growth rates
over 2010-16 (these years are at the end of thesample period). The regressions capture well EM7
consumption growth for metals (6.9 percent) andenergy (3.3 percent) during these years. That said,
across metals, actual consumption growth of zinc
somewhat exceeds the model estimates, while thatof aluminum falls short (Figure SF1.7). Acrossenergy, actual growth of crude oil and natural gas
was somewhat stronger than the fitted values andthat of coal much less. The over-prediction of coaland underprediction of natural gas may reflect
active policy measures to rein in pollution in
China over this period. The model somewhat
over-estimates growth of rice and wheat
consumption, and slightly under-estimates growthof maize and soybeans consumption.
The role of structural growth differences. One
source of a nonlinear relationship between GDP
and commodity use is the changing compositionof output. The sectoral components of GDP differ
in their use of energy, metals, and agricultural
inputs. The GTAP (Global Trade Analysis
Project) database allows the intensity of use of
agricultural goods, energy, and metals by different
sectors of the economy to be calculated (Figure
SF1.7).14•

Metals intensity. The metals intensity of global
manufacturing was about twenty times that ofglobal services in 2011. Similarly, the metals
intensity of global investment and exports was
about seven times that of household
consumption.

•

Energy. Differences in energy intensities
between sectors are smaller, but still
pronounced; the energy intensity of
manufacturing is two-and-a half times that ofservices. The energy intensity of global
investment is much lower than that forhousehold consumption and exports.

14 The GTAP Data Base contains complete bilateral trade in goods
and services, intermediate inputs among sectors, as well as taxes andsubsidies imposed by governments for 140 regions and for 57 sectors.
The latest reference year is 2011. See Aguiar, Narayanan, andMcDougall (2016).

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018•

Agricultural commodities. Agricultural intensities tend to be slightly lower than energy andmetals intensities across all sectors, with thehighest intensity in household consumption.

This suggests that countries with manufacturingdriven growth may experience a greater increase inenergy and metals consumption for a given
increase in output than economies driven more byservices. Likewise, countries with investmentdriven or exports-driven growth will see a greater
increase in metals consumption than economies
driven by household consumption.
Different engines of growth may have accounted
for some of the under-estimation of metals
consumption growth in China, and overestimation in other EM7. For example,
investment accounted for half of cumulative
growth during 2010-16 in China, compared to
one-quarter of cumulative growth in India, thesecond-largest EM7 economy, despite bothcountries growing at similar average rates (7.5-8
percent) during this period. In addition,
manufacturing has been a more important driverof growth in China, growing twice as fast as inIndia on average over the past 10 years. This also
helps explain the higher metals intensity of GDP
in China than in its peers (World Bank 2015b).
The role of policies. Policies that favor energyintensive and industrial sectors can significantly
change the commodity intensity of demand. In
the 1980s, in Russia and the former Soviet Union
countries, the energy intensity of output(measured as energy use relative to GDP per
capita) was much higher than in their free-market
peers, particularly for energy. Countries thatindustrialized under central planning tended to
exhibit high energy intensity because resource
allocation was not determined by market
mechanisms such as price or competition (UrgeVorsatz et al. 2006, Ruhl et al. 2012). Following
the collapse of the Soviet Union, and coinciding
with rapid per capita income growth, the energy
intensity of GDP in these countries fell steadily,
although it remains elevated. China has a similar
profile, with extremely high energy intensity in the
1980s, but this has steadily declined as per capita
incomes rose.

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71

FIGURE SF1.7 Estimated commodity consumption
growthIncome elasticities of consumption decline with rising per capita incomes,
but they differ widely across commodities and across income levels.
Estimated elasticities for EM7 countries were considerably higher than forG7 countries throughout the sample. For 2010-16, the regressions capture
well EM7 commodities consumption growth at the aggregate level, but
their performance differs for individual metals, energy, and foods. Greater
reliance on industrial production instead of services may account for fastermetals consumption growth in China than in other EM7.
A. Income elasticities at 2017 income
levelsB. Income elasticities in EM7 and G7
countries, 2010-16

C. EM7 consumption growth, 2010-16

D. Commodity consumption growth,by country and group, 2010-16

E. Sectoral use of energy, metals, andagricultural inputs

F. Intensity of metals and energy
consumption

Sources: Aguiar et al. (2016), BP Statistical Review, U.S. Department of Agriculture, World Bank,World Bureau of Metals Statistics.
A.B. Income elasticity is defined as percent change in commodity consumption for each 1 percent
increase in commodity prices. Estimated based on regression coefficients in Annex Table SF1.5.
A. Blue bars indicate elasticities at median real global per capita income in 2017; vertical bars
indicate elasticities at upper and lower income quartiles. Gas, maize and soybeans have a linear
elasticity and therefore do not have vertical bars.
B. Elasticities at median incomes over 2010-16, Vertical bars are 95 percent confidence intervals.
C.D. Estimated in-sample fitted values based on regression coefficients in Annex Table 1.5.
E. Use of energy, metals, and agricultural inputs by different sectors of the economy. Calculations
show the gross value added of an input (e.g., energy) used by a sector (e.g., manufacturing) as ashare of total gross value added of that sector. Values capture both direct and indirect use. Of the 57
sectors included in the Global Trade Analysis Project (GTAP) database, manufacturing contains
sectors 19 to 42 and services contains sectors 47 to 57. For the inputs, agriculture includes sectors 1
to 12, energy includes sectors 15 to 17, 32, 43, and 44, and metals includes sectors 18, 35, and 36.
The inclusion of sector 32, petroleum and coke, in manufacturing significantly increases its energyuse; excluding this sector would reduce the energy use of manufacturing from 16 to 8.7.
F. Toe stands for tons of oil equivalent. Intensity of consumption calculated as consumption of energy
or metals (in volumes) relative to output in constant 2010 U.S. dollars. Other EM7 includes Brazil,
India, Indonesia, Mexico, Russia, and Turkey.
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Prospects for commodities
demandA hypothetical scenario is developed for the period
2018-27, and compared to the estimated values
over 2010-16 as calculated by the model. This
enables an assessment of the impact of changes in
population and income growth, shifts between
countries with different commodity intensities ofdemand, and within-country shifts as theirincomes rise. The scenario is calculated separately
for all countries in the estimation sample, andthen summed to produce a global estimate. The
sample includes advanced economies, the EM7,
and other EMDEs. Data limitations exclude manysmaller emerging markets and frontier markets,with sub-Saharan Africa (SSA) and the Middle
East and North Africa (MENA) particularly
under-represented in energy and metals.

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The assumed scenario for these fundamental
drivers would mean slower global and EM7
demand growth in 2018-27 relative to the postglobal-crisis period 2010-16 for virtually allcommodities considered here. The slowdowns
would be particularly pronounced for metals,
especially in China. Even so, the country would
remain the single largest consumer of energy andmetals (Figure SF1.8). While per capita incomesin some of the other EMDEs would grow fasterthan in China, their current levels of commodity
consumption are so much lower that theircontribution to aggregate consumption growthwould remain relatively modest.
•

Metals consumption. Global metals consumption growth would slow by 1.4 percentage
points to just under 3 percent on averageduring 2018-27. Because of still-high EM7
income elasticities and robust growth, theslowdown in EM7 consumption would be
milder, by 0.4 percentage point to 4.9
percent. Growth in aluminum and copper
would remain high, reflecting their highincome elasticity of demand, while growth inzinc would remain modest, reflecting a nearzero G7 income elasticity.

•

Energy consumption. Energy consumption
growth would remain broadly steady at 2.3
percent globally but would slow by 0.4
percentage point to 3.1 percent in EM7
economies.15 Rapid output growth in other
EMDEs would shift the composition of global
energy consumption toward more energyintensive economies. Global crude oil
consumption growth would remain broadly
steady.

•Food commodities. Consumption growth of thefoodstuffs included here would slow by 1
percentage point to 1.8 percent over 201827.16 Rice and wheat would drive theslowdown because of their low-income

Baseline scenario. The baseline assumptions for
2018-27 use existing estimates:•

UN projections for population growth. Slowing
population growth is expected to dampen
commodity consumption growth. The United
Nations (2017) project that global population
growth will slow slightly from 1.2 percent on
average during 2010-16, to a 1 percent on
average during 2018-27 (Figure SF1.8). The
slowdown is most pronounced in the EM7.

•

Real output growth matches potential growth as
estimated in World Bank (2018a). Real per
capita income growth is expected to bebroadly constant on average but slow by 0.2
percentage point in the EM7 countries.

•

Income elasticities are as in Annex Table SF1.5.
With continued per capita income growth,
the elasticities of consumption of the EM7
economies are expected to decline (except for
natural gas, maize and soybeans), by as muchas one-third for coal.

•

Real commodity prices are assumed to beconstant at current levels. This assumption
mitigates
concerns
about
potential
endogeneity arising from using World Bank
price forecasts.

15 BP (2018) expects energy growth to remain broadly steady
between 2010-16 and 2017-25, while EIA (2017) expects growth toslow over this period.
16 OECD (2017) expect a slowing in growth of consumption of
cereals of about 1 percentage point.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

elasticities and slowing population growth. In
contrast, consumption growth of maize andsoybeans would strengthen slightly.
Alternative growth paths. The baseline scenario
described in the previous section depends criticallyon per capita income growth. The implications of
upside and downside risks to the income growth
path are discussed in two alternative model-based
scenarios. Finally, policy measures—including
those unrelated to commodity demand—could
also lead to different paths of commodity
consumption (Box SF1.2).
The first is a faster-growth scenario. Kilic Celik,
Kose, and Ohnsorge (forthcoming) estimate theimpact on potential growth if countries
implemented reforms to fill investment gaps,
expand labor force participation by women andolder workers, and improve life expectancy andeducational outcomes. Each country is assumed torepeat its best ten-year improvement on record ineach of these dimensions over the next decade. For
EMDEs, this would imply raising investment byalmost 3 percent of GDP, life expectancy by 2.5
years, enrolment and secondary school completion
rates by 5-7 percentage points, and female labor
force participation by 10 percentage points. Such a
concerted reform push could lift average annual
global potential growth by 0.7 percentage point
for the next ten years.
The second is a slower-growth scenario. This
could, for example, be triggered by a financial
crisis that is followed by a deep recession. Deep
recessions leave lasting damage to output, as aresult of hysteresis effects. The latter include theloss of human capital (job skills) associated withlong-term unemployment, and the loss ofembodied technical progress implied by lower
investment. World Bank (2018b) estimates thatdeep recessions have, on average, reduced potential
growth in the following five years by 1 percentage
points.
These alternative growth paths make a significant
difference to the projections, especially for themost income-elastic products (Figure SF1.8).
•

Faster-growth scenario. In a faster-growthscenario, global metals consumption growth

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73

FIGURE SF1.8 Commodity consumption scenarios
The baseline scenario suggests that fundamental drivers would slow global
and EM7 commodity consumption growth between 2010-16 and 2018-27.
The deepest slowdowns would occur in metals consumption. Despite
China’s expected output and commodity consumption growth slowdown, it
would remain the largest consumer of energy and metal commodities
among the EM7.

A. Population growth

B. Per capita output growth

C. Income elasticities of EM7
commodity consumption

D. Scenario forecasts of global
commodity demand growth

E. EM7 commodity demand inphysical units

F. Scenario forecasts of EM7
commodity demand growth

Sources: BP Statistical Review, United Nations, U.S. Department of Agriculture, World Bank, World
Bureau of Metals Statistics.
Note: All growth rates are averaged over the period.
A. 2018-27 are based on UN Population Projections (2017).
B. 2018-27 data are forecasts of per capita potential growth based on World Bank (2018b) and UN
Population Projections (2017).
C. Predicted values based on regression coefficients in Annex Table SF1.5. Vertical lines are 95
percent confidence intervals.
D.-F. To ensure comparability, 2010-16 is model-predicted commodity demand growth. The faster
growth “reform” scenario assumes 0.7 percentage point higher output growth through 2018-27, while
the slower growth “recession” scenario assumes 1 percentage point lower output growth for the first
five years of 2018-27, based on World Bank (2018b).
E. Toe stands for tonnes of oil equivalent. Projected average annual commodity demand in billion
tons of oil equivalent for energy and in millions of tonnes for metals.
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BOX SF1.2 Commodity consumption: Implications of government policies

Government policies—with respect to infrastructure investment, pollution control, energy use, and international
trade—can have a major impact on commodity consumption.
Infrastructure investment. Significant infrastructure
investment gaps exist at the global level, and closing
these would provide both direct and indirect boosts
to commodities consumption (World Bank 2016b,
2017a). The difference between expected investment
needs and current actual investment in EMDEs isestimated at $1–$2 trillion per year (1.25 to 2.5
percent of global GDP).1 By sector, the investment
requirements are largest in electricity generation,
followed by construction and transportation. Fiscal
and structural policies such as increased public
investment, structural governance reforms, andimproved access to finance could boost investment
directly and through the crowding-in of complementary private sector investment (World Bank
2017a).
China’s Belt and Road Initiative (BRI) aims topromote economic development and integration
across countries in Asia, Europe and Africa (StateCouncil 2015). Outward foreign direct investment(FDI) from China increased substantially after thelaunch of the BRI from $28.6 billion in 2003 to$183 billion in 2016, with most of the increase going
to countries on the BRI. The majority of FDI deals
have been in manufacturing, while the construction
and infrastructure sector has seen more rapid growth(Figure SF1.2.1).
Because of the high metal-intensity of investment,such policies could boost metals consumption. In
addition, investment in electricity generation in
EMDEs could result in energy demand shifting awayfrom the decentralized use of biomass, toward
centralized generation of electricity from fossil fuels
and renewable sources of energy.
Pollution control. Environmental concerns are also
likely to shape consumption patterns in commodity
markets. For example, in energy markets, pollution
or climate-change considerations, as embodied by the1

Bhattacharya et al. (2012); McKinsey Global Institute (2013).

2015 Paris Agreement, could accelerate the use ofpolicy tools, such as carbon pricing, which favor theuse of renewable energy and discourage the use ofhighly polluting fossil fuels (World Bank 2018a).
During the past five years, global consumption ofnatural gas has increased nearly 10 percent while coalconsumption has declined 2 percent.
Subsidies. Although aimed at protecting consumers,
the use of energy subsidies can encourage energy
consumption, discourage investment in energy
efficiency and renewables, and impose large fiscal
costs. The use of energy subsidies globally was equal
to around 6.5 percent of global GDP in 2013. They
are particularly prevalent in EMDEs (13-18 percent
of GDP; IMF 2015; Rentschler 2018). The use ofenergy subsidies is high in the Middle East andNorth Africa (MENA), which accounts for half of allenergy subsidies (World Bank 2014). The energy
price collapse in 2014 provided impetus for subsidy
reform, with more than half of commodity-exporting
EMDEs doing so during 2014-2016 (World Bank
2018b). Additional subsidy reforms could further
reduce energy consumption.
Biofuels. The diversion of food commodities to the
production of biofuels will also affect demand forfood commodities. Biofuels currently account for justover 1.5mb/d, or 1.6 percent, of global liquid energy
consumption. Most biofuel production is notprofitable at current energy and agricultural prices
but is supported through various forms of mandates
and trade measures (De Gorter, Drabik, and Just
2015). Biofuels come principally in the form ofmaize-based ethanol from the United States, sugarbased ethanol from Brazil, and plant oil-based
biodiesel from Europe. Other smaller producers
include China, Indonesia, and Thailand. The policydriven diversion of food commodities to biofuels was
motivated by energy security concerns and,especially, environmental benefits (Hill et al. 2006).
However, interest has waned recently and biofuel
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S P EC IAL FO CU S 1

BOX SF1.2 Commodity consumption: Implications of government policies (continued)
FIGURE SF1.2.1 Developments in commodity markets
A number of policy actions could have unintended spillovers to commodity consumption. A renewed infrastructure push, forexample to fill infrastructure investment gaps or in the context of China’s “Belt and Road Initiative” could raise manufacturing
and construction activity and, hence, metal demand. Environmental policies to control pollution could reduce and shiftenergy demand towards cleaner fuels, including natural gas and renewables. Biofuel production is likely to slow, however,as policy makers gradually acknowledge the limited environmental benefits of biofuel policies.
A. Change in sectoral distribution ofoutward FDI deals before and after the
BRI

B. CO2 emissions from different fuels

C. Global biofuels production

Sources: BP Statistical Review, Energy Information Administration, International Energy Agency, Organisation for Economic Co-operation and Development, Ministry ofCommerce People’s Republic of China, World Bank.
A. BRI stands for Belt and Road Initiative. Change in the average annual number of outward foreign direct investment (FDI) deals received by EMDEs before and after
2013. The sample covers EMDEs.
B. CO2 emissions in kilograms (kg) per million British thermal units (mmbtu) of fuel consumed.
C. Shaded area represents OECD (2017) projections. Units are million barrels of oil equivalent per day.
Click here to download data and charts.

limited environmental and energy independence
benefits of biofuel policies (Searchinger et al.
2008; German et al. 2010). For example, biofuel
production growth exceeded 20 percent per annum
during 2001-10 but slipped to about 4 percent
during the past five years. Current projections by theOrganisation for Economic Cooperation andDevelopment and the Food and Agriculture
Organization of the United Nations (OECD/FAO)
point to even lower biofuels production growth in
the next decade (Figure SF1.2.1).
Food wastage. Although difficult to measure, bysome accounts food waste may account for a quarterof global food production, amounting to roughly$680 billion in high income countries and $310
billion in developing countries, according to the
Food and Agriculture Organization of the United
Nations (FAO 2018). Policy interventions andtechnological improvements could significantly
reduce food waste, which in turn would reducedemand for food commodities (Bellemare et al 2017;
Delgado, Schuster, and Torero, 2017).

Trade policies and sanctions. Trade-restricting
measures could have direct and indirect effects oncommodity consumption and prices. A broad-based
increase in tariffs would have major adverse
consequences for global trade and activity (Ossa
2014; Nicita, Olarreaga, and Silva, forthcoming). An
escalation of tariffs up to legally allowed bound rates
could translate into a decline in global trade flows
amounting to 9 percent (Kutlina-Dimitorva and
Lakatos 2017). Such a fall in trade volumes would
have a direct negative impact on oil consumption,
given its use in transport fuel. A 5 percent drop in
global trade could reduce international fuel oil
bunker demand by at least 180 kb/d, or roughly 5
percent (IEA 2018). A reduction in global activity
arising from trade-restricting measures would also
reduce commodity demand. Finally, the impositionof sanctions could affect prices if they disrupt
operations by major commodity-producing nations
or companies (Box SF1.1).

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could be one-third higher than under thebaseline scenario and remain virtually at its
post-crisis rates. Global and EM7 energy
consumption growth might also be 0.6-0.7
percentage point stronger than under thebaseline scenario and could rise above postcrisis rates. Aggregate food consumption
would be little changed from baseline, butthere would be further substitution away fromrice and wheat (with low income elasticities)
toward maize and soybeans (with higher
elasticities).
•

Slower-growth scenario. A slower-growthscenario would set back global metals
consumption growth, relative to baseline, by
one-third (1 percentage point) and global
energy consumption growth by almost onehalf (0.9 percentage point). Food consumption growth would, again, weaken only
marginally with offsetting changes to rice andwheat compared to maize and soybeans.

The scenarios described above are stylized, andonly show the impact of the baseline projections
for income and population changes in the sample
of countries. Prospects may differ considerablyfrom these projections, depending on trajectories
for variables not included in the model. For
example, population growth in SSA is expected to
be much higher than for advanced economies andthe EM7, although it is not captured in this
scenario. As such, these estimates could be biased
downwards. The estimates also do not allow for
the endogeneity of prices. Endogenous relative
price changes would moderate the changes, ineither direction, from the baseline paths.
Despite implying a slowdown in growth, all themodel-based projections show that consumptionof energy and other commodities expands
significantly from current levels. This, however,would in itself likely stimulate innovation and theadoption of new technologies, including efficiency
improvements that further reduce consumption(Arezki and Matsumoto 2017). An accelerated
uptake of more fuel-efficient technologies (e.g.,
electric vehicles and natural gas-powered commercial trucks) could also reduce crude oil
consumption prospects (Cherif, Hasanov, and

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

Pande 2017; International Energy Agency 2017).
The uptake of more climate-friendly technologies
will also lead to shifts in demand for the metals
and minerals that are required to manufacture newtechnologies. Countries that are key suppliers ofthese elements could benefit from thesedevelopments. Low-carbon energy systems arelikely to be more metal intensive than high-carbon
systems, although the use of commodities varies
greatly between different low-carbon technologies(World Bank 2017b).

Policy implications
The baseline scenario outlined above suggests
consumption growth of metals and staple foods
will likely slow over the next decade, and that ofenergy will remain well below pre-crisis rates.
More modest commodity consumption growth,
all else equal, would dampen pressures on prices.
Many EMDEs, especially smaller ones, are heavily
exposed to commodity markets. In four-fifths of
EMDEs, commodities account for 30 percent ofgoods exports or more, or an individualcommodity accounts for 20 percent of goods
exports. On average, export concentrations arelargest among crude oil exporters. Oil exporters
also tend to be heavily reliant on fiscal revenues
from the sector. For example, prior to the oil pricecollapse in 2014, hydrocarbon revenues accounted
for more than half of fiscal revenues in eight
EMDEs, including Nigeria and Saudi Arabia, andmore than one-quarter of revenues in four
EMDEs, including Mexico and Russia (WorldBank 2017a).
The prospect of persistently lower demandheightens the need for commodity exporters todiversify. Over the medium term, diversification
away from resource-based production would help
raise GDP per capita and improve growthprospects for commodity-exporting EMDEs.
Cross-country studies underscore that greater
diversification of exports and government revenues
bolsters long-term growth prospects and resilience
to external shocks (Lederman and Maloney 2007;
Hesse 2008; IMF 2016a). The successful
diversification experience of some energy
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benefits of both vertical diversification (e.g., incrude oil, natural gas, and petrochemical sectors)
as well as horizontal diversification. These involve
reforms to improve the business environment,
education, and skills acquisition (Callen et al.
2014).

would result in a shift to foods such as meat,
which require growing inputs of maize andsoybeans. Slowing GDP growth and industrial
rebalancing notwithstanding, China will remain
the single largest source of EM7 commodity
consumption growth.

In a majority of commodity-exporting EMDEs
fiscal reforms are necessary to establish a firmer
foundation for long-term fiscal sustainability(Mendes and Pennings 2017). The establishmentof well-managed strategic investment funds withresource revenues can help in this regard (e.g.
Chile, Norway). These funds can create opportunities for attracting private investment, deepening
domestic capital markets, and building thecapacity of governments to act as professional
long-term investors (Halland et al. 2016).

Advances in global technology, shifts in consumer
preferences, and policies to encourage cleaner fuels
could trigger much steeper slowdowns in global
use of some commodities than current trends
indicate. A rapid shift away from investmentdriven and industrial production-driven growth inChina could sharply lower its demand for metals.
Similarly, a tightening of environmental regulations could reduce coal use more than in thebaseline. Improved technologies (such as electriccars), lower costs of alternative fuels, and policies
favoring cleaner fuels, could reduce the use of
petroleum in transportation. However, they could
also increase demand for raw materials used in the
production of these technologies, such as rareearths.

Reforms to fiscal and monetary policy frameworks
could also help reduce procyclicality and foster
resilience to commodity price fluctuations(Frankel 2017). However, such policies are insufficient to mitigate the challenge of weaker
commodity consumption discussed here.

Conclusion
Based on current trends, metals and foods
consumption growth could slow by one-third overthe next decade. Energy consumption growthwould remain broadly constant at post-crisis rates,and shift towards faster-growing EMDEs.
Aluminum and copper consumption would
continue to grow steadily. Rice and wheat
consumption growth is expected to slow as
population growth slows, while rising incomes

Demand for most commodities may decelerateover the next decade as economies mature,
infrastructure needs are met, and GDP and
population growth slows. Much of future GDP
growth will come in the services sector, which is
not materials-intensive, while environmental andresource concerns and new technologies will
reduce demand for traditional raw materials, aswell as encouraging substitutions between them.
These trends have already become evident inadvanced economies, and a similar path could be
expected for the major EMDEs.

77

*

*

*

*

*   np k 1 ij , n ,*   qn l 1ij ,n ,cij ,t  


q
l 0

 ij ,k cij ,t  k  pk 1

ij ,l y2
ij ,t l



r
m 0

q
l 0

ij ,l yij ,t lγ ij ,m pij ,t  m   ij  ij ,t*   qn l 1ij ,n ,γ*   rn  m 1γ ij , nѲi,1cij ,tѲi,2Ѳi  (1   kp1 ij , k )yij , tpij , t ij

ij ,tyij2,t ,t cij ,t  i (ci ,t 1  i ,1 yt  i ,2 yt2  i ,3 pt ) kp11*ij ,k cij ,t  k  lq01*ij ,l yij ,t llq01*ij ,l yij2,t l   mr 10 γ*ij ,m pij ,t  m
 ij  ij ,t
Ѳi,1

Ѳi,2

Ѳi,3

i ,1  lq0 ij ,l / (1   kp1 ij , k ),
i ,2  lq 0ij , l / (1   kp1 ij , k )i ,3   mr 0 γ ij , m / (1   kp1 ij , k )ct 1  2 2 yt
yt

IC( i ,WORLD ,t )   c
ˆ i , j ,t  popi ,ti 1cˆi , j .t
popi , t

80

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ANNEX TABLE SF1.1.A Top 10 commodity consumers, 2016
Aluminum

CopperZinc

OilNatural Gas

1

China

54.4

China

49.7

China

48.2

United States

20.3

United States

22.0

2

United States

8.8

United States

7.7

United States

5.7

China

12.8

Russia11.0

3

Germany

3.8

Germany

5.3

India

4.8

India

4.6

China

5.9

4

Japan

3.0

Japan

4.2

Korea, Rep.

4.5

Japan

4.2

Iran

5.7

5

Korea, Rep.

2.5

Korea, Rep.

3.2

Germany

3.5

Saudi Arabia

4.0

Japan

3.1

6

India

2.4

Italy

2.5

Japan

3.4

Russia3.3

Saudi Arabia

3.1

7

Turkey1.6

Brazil2.2

Belgium

2.6

Brazil3.1

Canada

2.8

8

Italy

1.6

Taiwan, China

2.2

Spain

1.9

Korea, Rep.

2.9

Mexico2.5

9

United ArabEmirates

1.4

India

2.1

Italy

1.9

Germany

2.5

Germany

2.3

10Brazil

1.3

Turkey2.0

Turkey1.7

Canada2.4

United Kingdom

2.2

Others19.2

Others18.9

Others21.8

Others39.8

Others

39.4

ANNEX TABLE SF1.1.B Top 10 commodity consumers, 2016
Coal

Maize

Rice

Wheat

1

China

50.6

United States

30.0

China

29.8

European Union

17.6

2

India

11.0

China

22.7

India

20.3

China

15.7

3

United States

9.6

European Union

7.1

Indonesia

7.8

India

13.1

4

Japan

3.2

Brazil5.9

Bangladesh

7.3

Russia6.1

5

Russia2.3

Mexico4.0

Vietnam

4.6

United States

4.0

6South Africa

2.3

India

2.5

Philippines

2.7

Pakistan

3.4

7

Korea, Rep.

2.2

Egypt

1.5

Thailand

2.3

Egypt

2.7

8

Germany

2.0

Japan

1.4

Myanmar

2.1

Turkey2.4

9Indonesia

1.7

Canada

1.3

Japan

1.8

Iran

2.4

10

Poland1.3

Vietnam

1.3

Brazil

1.7

Indonesia

1.6

Others13.8

Others22.4

Others19.6

Others31.1

Sources: BP Statistical Review, Food and Agriculture Organization, U.S. Department of Agriculture, World Bureau of Metal Statistics.
Notes: Numbers indicate shares of global consumption. Refined consumption for aluminum, copper, and zinc.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 201881

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ANNEX TABLE SF1.2.A Top 10 commodity producers, 2016
Aluminum

CopperZinc

OilNatural Gas

1

China

55.0

China

36.2

China

45.8

United States

13.4

United States

21.1

2

Russia

6.1

Chile

11.2

Korea, Rep.

7.4

Saudi Arabia

13.4

Russia16.3

3

Canada

5.5

Japan

6.7

Canada5.1

Russia

12.2

Iran

5.7

4

United ArabEmirates

4.3

United States

5.2

India

4.5

Iran

5.0

Qatar

5.1

5

India

3.3

Russia

3.7

Japan

3.9

Iraq

4.8

Canada4.3

6

Australia

2.8

India

3.3

Spain

3.7

Canada

4.8

China

3.9

7

Norway2.3

Congo, Dem. Rep.

3.0

Peru

2.5

United ArabEmirates

4.4

Norway3.3

8Bahrain

1.7

Germany

2.9

Kazakhstan

2.4

China

4.3

Saudi Arabia

3.1

9

Saudi Arabia

1.5

Korea, Rep.

2.6

Mexico2.3

Kuwait3.4

Algeria

2.6

10

United States

1.4

Poland2.3

Finland

2.1

Brazil2.8

Australia

2.6

Others16.0

Others22.9

Others20.3

Others31.3

Others

32.1

ANNEX TABLE SF1.2.B Top 10 commodity producers, 2016
Coal

Maize

Rice

Wheat

1

China

46.1

United States

35.8

China

29.9

European Union

20.0

2

United States

10.0

China

20.8

India

22.6

China

17.1

3

Australia

8.2

Brazil8.9

Indonesia

7.6

India

13.0

4

India

7.9

European Union

5.9

Bangladesh

6.7

Russia11.2

5

Indonesia

7.0

Argentina

3.2

Vietnam

5.8

United States

6.2

6

Russia

5.3

India

2.6

Thailand

4.2

Canada3.9

7South Africa

3.9

Mexico2.6

Myanmar2.7

Ukraine3.6

8

Colombia

1.7

Ukraine

2.3

Philippines

2.5

Pakistan

3.5

9Poland

1.4

Canada1.4

Brazil1.7

Australia

2.8

10

Kazakhstan

1.2

Russia

1.3

Japan

1.6

Turkey2.8

Others

7.3

Others

15.2

Others14.7

Others16.0

Sources: BP Statistical Review, Food and Agriculture Organization, U.S. Department of Agriculture, World Bureau of Metal Statistics.
Notes: Numbers indicate shares of global production. Refined production for aluminum, copper, and zinc.

82

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ANNEX TABLE SF1.3 Literature review of long-run income elasticities of demand for commodities
Authors and Publication Year
Stuermer (2017)

Data/sample
12 advanced economies
and 3 EMDEs, annual
data, 1840-2010

Methodology

Results

Auto-regressive
distributive lag

Income elasticity of demand is estimated to be 1.5 foraluminum, 0.9 for copper, 0.7 for zinc, 0.6 for tin, and 0.4
for lead.

Burke and Csereklyei (2016)

132 countries, annual
data, 1960-2010.

Ordinary leastsquares (OLS) withpanel data, in levels
and growth rates.

Aggregate income elasticity of energy demand isestimated to be 0.7. Income elasticity is found to rise withhigher incomes, in contrast to other studies. This resultsfrom the inclusion of low income countries, which typicallyhave a much lower income elasticity of demand for energy
as they rely on non-commercial fuels (biomass).
Controlling for this results in constant elasticities acrossincome groups.

Csereklyei and Stern (2015)

93 countries, annual data,
1971-2010.

OLS in growth rates.

Average income elasticity of energy demand is estimatedto be between 0.6 to 0.8. As income rises, the rate of
growth of energy use per capita declines.

Huntington, Barrios, and Arora(2017)

Review of 38 papers
providing 258 estimates of
price and income
elasticities of energy
demand.

Review of existingstudies.

Income elasticity of oil demand is found to be 0.5 on
average, and 0.9 for natural gas.

Fouquet (2014)

UK energy use, annual
data, 1700-2000.

Vector error correction
modelLong run income elasticity for energy demand fortransport peaks at 3 before declining to around 0.3 asincome rises.

Joyeux and Ripple (2011)

30 OECD and 26 nonOECD countries, annual
data, 1973-2007

Error correction modelwith pooled meangroup estimators.

For OECD countries, income elasticity estimated to be
1.1, for non-OECD countries, income elasticity of energy
demand estimated to be 0.9.

Jakob, Haller and Marschinski(2011)

30 EMDEs and 21
advanced economies,
annual data, 1971-2005.

Difference-indifferences estimatoron panel data.

Find income elasticity of primary energy demand of 0.63
for EMDEs and 0.18 for advanced economies (althoughstatistically insignificant).

Vanin et al. (2014)

Review of 10 global
economic models for
agricultural commodities

Review of different
modeling approaches

Find median income elasticities for rice and wheat close
to 0.1. First and third quartile range of estimates range
from 0 to 0.2.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

S P EC IAL FO CU S 1

83

ANNEX TABLE SF.1.4 Economy samples, by commodity modeled
Aluminum, zinc,oil, gas

Copper

Coal

Rice

Wheat

Maize

Soybeans

Australia1 2Austria
BelgiumBrazilCanada2
China
Hong Kong SAR,
China

Australia1
Austria
BelgiumBrazilCanadaChina

Australia2
Austria
BelgiumBrazilCanada2
DenmarkArgentina3
Australia
Bangladesh
Benin3
Bolivia
Brazil3

Algeria
Argentina3
Australia
Bangladesh
Bolivia
Brazil3

Algeria
Argentina3
Australia
Bolivia
Brazil3
Cameroon3

Argentina3
Australia
Bolivia
Brazil3
CanadaChile3FinlandFinlandBurkina Faso3

CanadaCanadaChina

Denmark
FinlandFranceGermany
Greece2
India
Indonesia2
IrelandItaly
Japan
MexicoNetherlands
New Zealand
Norway2Portugal
Singapore
South Africa1
Korea, Rep.
Spain
SwedenSwitzerland
Taiwan, China
ThailandTurkeyUnited Kingdom
United States

FranceGermany
Greece
India
Italy
Japan
MexicoNetherlands
Portugal
South Africa1
Korea, Rep.
Spain
SwedenSwitzerland
Taiwan, China
TurkeyUnited Kingdom
United States

FranceGermany
Greece2
India
IrelandItaly
Japan
MexicoNetherlands
New Zealand
Norway2Portugal
South Africa
Korea, Rep.
Spain
SwedenSwitzerland
Taiwan, China
TurkeyUnited Kingdom
United States

Cameroon3
Chile3Chad
China
Chile3
Colombia
China
Ecuador3
Colombia
Egypt.3
Congo, Rep.
Guatemala3
Costa Rica3
India
Côte d'Ivoire3
Iran
Cuba
Japan
Dominican Republic3 Kenya
Ecuador3
LesothoEgypt3MexicoEl Salvador
Morocco3
Gambia, The3
Nepal3Ghana3
New Zealand3
Guatemala3
Nigeria
Guyana3
NorwayHonduras3
Pakistan3
India
Paraguay3
Indonesia3
Peru3
Iran
South Africa
Japan
Sudan3
Kenya
Taiwan, China
Korea, Rep.
Tunisia
Liberia
TurkeyMadagascar3
Uruguay3
Malawi3
ZambiaMalaysia
Zimbabwe3
Mali
MexicoMorocco3
Nepal3
Nigeria
Pakistan3
PanamaParaguay3
Peru3
Philippines
Senegal3
Sierra Leone3
Sri Lanka3
Taiwan, China
ThailandTogo3
TurkeyUnited States
Uruguay3
Venezuela

Chile3China
Colombia
Côte d’Ivoire3
Cuba
Ecuador3
Egypt3Ghana3
Guatemala3
Honduras3
India
Indonesia3
Iran
Japan
Kenya
Korea, Rep.
LesothoMadagascar3
Malawi3
MexicoMorocco3
Nepal3
Nicaragua3
Nigeria
Pakistan3
PanamaParaguay3
Peru3
Philippines
Senegal3South Africa
Taiwan, China
ThailandTurkeyUnited States
Uruguay3
Venezuela
Vietnam
ZambiaZimbabwe3

Colombia
Ecuador3
Egypt3
Guatemala3
India
Indonesia3
Iran
Japan
Korea, Rep.
MexicoMorocco3
MyanmarNigeria
Pakistan3
Paraguay3
Peru3
South Africa
Switzerland
Taiwan, China
ThailandTurkeyUnited States
Uruguay3
Venezuela
ZambiaZimbabwe3

Source: World Bank.
Note: 1 indicates metals exporter; 2 indicates energy exporter, 3 indicates agricultural exporter. An economy is defined as an exporter if exports of the commodity account for 20 percent ormore of their total exports. Greece, Portugal, and South Africa are not included in the estimation of gas consumption due to missing observations (for 17, 32, and 27 years, respectively).

84

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ANNEX TABLE SF.1.5 Estimation results for pooled mean group estimation
Aluminum

Zinc

CopperOil

Coal

Gas 1/

Gas

Rice

Wheat

Maize 1/

Maize

Soybeans 1/ Soybeans

Long runLog per capita
income3.50***

2.60*** 2.95***

2.31***

6.04***

0.30

0.38***

1.39***

1.05***

0.28

0.85***-0.65

0.84***(0.40)(0.23)(0.46)(1.28)(1.04)(0.57)(0.12)(0.20)(0.24)(0.02)(0.50)(0.04)

Squared log
per capita
income-0.15***-0.12*** -0.12*** -0.10*** -0.31***0.01-0.09*** -0.04***

0.05***(0.71)(0.02)(0.01)(0.02)(0.06)(0.05)(0.01)(0.01)(0.02)-0.31***-0.17*** -0.36*** -0.47***0.15**-0.27***-0.29***

0.03

0.01

-0.22***-0.19***-0.48***-0.68***(0.04)(0.03)(0.07)(0.03)(0.03)(0.02)(0.02)(0.03)(0.03)(0.11)(0.09)

Adjustment
coefficient-0.26***-0.28*** -0.14*** -0.07*** -0.10***-0.17***-0.17***-0.22*** -0.33***-0.19***-0.15***-0.14***-0.13***(0.03)(0.03)(0.03)(0.01)(0.01)(0.03)(0.03)(0.03)(0.04)(0.03)(0.03)(0.02)(0.02)

Log change inper capita
income-19.06**

2.90

1.04

4.28*

-13.41***31.60

0.63***

-2.28

-2.44

-1.61

0.49***-13.540.89**(9.43)(13.55)(7.20)(2.34)(3.78)(21.43)(0.20)(6.58)(6.88)(4.95)(0.14)(21.28)(0.42)

Squared log
change in percapita income

1.07**

-0.01

0.07

-0.17

0.70***

-1.51

0.08

0.07

0.15

1.33

(0.47)(0.67)(0.36)(0.11)(0.18)(1.06)(0.46)(0.38)(0.32)(1.33)

Log change inreal price0.09**

0.05

-0.03

-0.01*

-0.01

0.03*

0.03*

-0.02**

-0.01

0.02

0.01

-0.03

-0.02

(0.04)(0.03)(0.03)(0.01)(0.02)(0.02)(0.02)(0.01)(0.02)(0.15)(0.02)(0.10)(0.10)-4.56***-3.50*** -2.10*** -0.90*** -2.85***-0.86***-0.78***-0.40*** -0.53***

0.61***

0.29***

0.93***

0.36***(0.54)(0.42)(0.36)(0.08)(0.44)(0.17)(0.17)(0.07)(0.08)(0.15)(0.11)(0.18)(0.09)

5.25

7.72

3.26

3.66

4.53

3.02

5.80

2.52

1.45

1.62

5.43

5.86

2.31

0.30

0.21

0.06

0.47

0.69

Log real price(0.04)

0.10***(0.06)(0.05)(0.03)

Short runConstant
Joint
Hausmantest-statistic
p-value

0.15

0.05

0.35

0.66

0.07

0.12

0.32

log likelihood

886.27711.20743.02 3065.46 1557.88

1134.570.39

1141.82 1647.65 1141.82

1534.65

1462.82

85.70

47.73

Observations

1,668

1,658

1,275

1,683

1,366

1,366

1,443

2,692

1,781

2,372

2,372

1,500

1,500

Number ofcountries

33

33

25

33

28

30

30

55

35

47

47

32

32

0.8

0.3

0.7

0.5

0.6

...

0.4

-0.3

0.3

...

0.8

...

0.8

Memorandum
item:
Incomeelasticity at2017 medianincomeNote: *** p<0.01, ** p<0.05, * p<0.1. Standard errors in parentheses.
1/ Indicates robustness check but not baseline regression. All other regressions are baseline regressions.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 201885

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ANNEX TABLE SF.1.6 Estimation results under generalized method of moments
Aluminum

Zinc

Copper

Oil

Coal

Gas

Rice

Wheat

Maize

Soybeans

Log per capita
income3.99***

3.81***

2.57***

2.41***

4.19***

0.27***

1.49***

0.70***

0.47***

0.48***(0.21)(0.18)(0.36)(0.12)(0.25)(0.09)(0.13)(0.12)(0.03)(0.05)

Squared log per
capita income-0.17***-0.19***-0.06***-0.10***-0.19***-0.09***-0.04***(0.00)(0.01)(0.02)(0.01)(0.02)(0.01)(0.02)-0.45***-0.18***

0.00-0.05***

0.07-0.47***

-0.33

-0.04

-0.48***-1.33***(0.05)(0.04)(0.12)(0.01)(0.08)(0.13)(0.02)(0.03)(0.09)(0.15)-19.51***-18.16***-17.67***-13.60***-23.64***-4.16***-1.83***-1.46***

6.29***

10.01***(0.83)(0.77)(0.73)(0.63)(1.13)(0.87)(0.50)(0.47)(0.51)(0.97)

Adj. R2

0.86

0.81

0.80

0.96

0.90

0.84

0.91

0.91

0.12

0.11

J-statistic

0

0

0

0

0

0

0

0

0

0

1,608

1,583

1,275

1,617

1,428

1,583

2,776

1,730

2,372

1,501

33

33

25

33

28

33

55

35

47

32

Log real priceConstant

Observations
Number of countries

Note: *** p<0.01, ** p<0.05, * p<0.1. Standard errors in parentheses.
One lag of independent variables is used as instruments. The J-statistics confirm their validity.

86

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ANNEX TABLE SF.1.7 Estimation results including trend
Aluminum

Zinc

Copper

Oil

Coal

Gas

Rice

Wheat

Maize

Soybeans

4.23***

2.20***

11.06***

1.90***

4.16***

0.71***

0.52***

3.42***

1.37***

1.03***(0.45)(0.22)(0.95)(0.47)(0.99)(0.09)(0.14)(0.24)(0.24)(0.21)-0.19***-0.08***-0.57***-0.06**-0.23**-0.21***-0.03***(0.03)(0.02)(0.05)(0.03)(0.05)(0.01)(0.01)-0.21***-0.16***-0.26***-0.01***-0.02-0.25***

0.00

-0.04

-0.03

-0.02

(0.04)(0.03)(0.04)(0.00)(0.06)(0.03)(0.02)(0.03)(0.06)(0.02)

Adjustment
coefficient-0.27***-0.28***-0.16***-0.07***-0.06***-0.17***-0.24***-0.27***-0.12***-0.33***(0.03)(0.03)(0.03)(0.07)(0.02)(0.03)(0.03)(0.03)(0.02)(0.04)

Log change
in per capita
incomeSquared log
change inper capita
income-18.98*

11.17

2.13

3.69**-1.78

0.60**

0.19***

11.32**

0.80*

-2.56

(9.81)(14.16)(8.04)(2.23)(3.22)(0.21)(0.03)(5.73)(0.43)(6.79)

1.06**

-0.45

-0.04

-0.14

0.13

-0.76*

0.08(0.49)(0.71)(0.42)(0.11)(0.16)(0.41)(0.37)

Log change
in real price

0.08*

0.05*

-0.03

-0.01*

0.00

0.03

-0.09

-0.02

-0.07

0.00

(0.04)(0.03)(0.03)(0.06)(0.02)(0.02)(0.02)(0.01)(0.10)(0.02)-5.40***-3.39***-8.00***-0.92***-1.34***-1.29***

1.41***-2.94***-0.71***-0.55***(0.64)(0.41)(1.32)(0.08)(0.37)(0.27)(0.19)(0.37)(0.15)(0.08)

Joint
Hausmantest-statistic

4.46

5.45

5.01

2.99

11.07

0.82

1.21

1.20

6.34

6.27

p-value

0.22

0.14

0.17

0.39

0.01

0.66

0.55

0.75

0.10

0.10

Log
likelihood

889.59694.75755.163067.80

1546.831146.191529.00

1978.4647.31

1696.66

Observations

1,668

1,680

1,275

1,683

1,428

2692

2,372

2,775

1,500

1,781

Number ofcountries

33

33

25

33

28

33

47

55

32

35

Long runLog per
capitaincomeSquared log
per capita
incomeLog real
price
Short runConstant

Note: *** p<0.01, ** p<0.05, * p<0.1. Standard errors in parentheses.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

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SPECIAL FOCUS 2
Corporate Debt:
Financial Stability and Investment Implications

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

S P EC IAL FO CU S 2

Corporate Debt:
Financial Stability and Investment Implications
Average corporate debt in emerging market and developing economies (EMDEs) has risen over the past decade.
This trend raises concerns for their financial stability and growth prospects. Debt service costs of EMDE firms
are expected to rise as advanced economies normalize monetary policy, and debt is increasingly held by firms
with riskier balance sheets. Firm-level empirical analysis also suggests that debt overhang may be associated withweak investment, especially in large or highly leveraged firms. Countercyclical and macroprudential policies canaddress financial stability concerns. Structural policies, including the strengthening of bankruptcy regimes, areappropriate tools to address the investment implications of elevated corporate debt.

Introduction
By 2017, corporate debt in emerging market anddeveloping economies (EMDEs) had reachedlevels that significantly exceeded its average prior
to the global financial crisis as well as its longerterm average (1995-2007; Figure SF2.1). EMDE
corporate debt now also rivals the size ofgovernment debt. While the increase in corporate
indebtedness among EMDEs partly reflects
improved and deeper access to capital markets, it
raises two concerns.
First, excessive corporate debt can threaten
financial stability, leading to distress in the nonfinancial corporate sector and systematic balance
sheet difficulties in the banking sector. Most
directly, as policy interest rates rise and the cost ofdebt service increases, incidence of corporate
distress tends to intensify. Firms may also become
more vulnerable to balance sheet shocks, such as
through currency mismatches associated with U.S.
dollar appreciation.1 Deterioration in nonfinancial
corporate balance sheets may transmit to thebanking sector as well. Previous episodes of rapid
corporate debt buildup have at times coincidedwith episodes of financial stress, which can haveadverse macroeconomic consequences.2
Note: This Special Focus was prepared by Eduardo Borensztein
and Lei Sandy Ye. Research assistance was provided by Miyoko Asai,
Julia Roseman, and Heqing Zhao.
1 Large unhedged exposure in foreign exchange combined withdepreciation of currency may raise this vulnerability (Acharya et al.
2015).
2 Debt overhangs were found to have impacted investment on
European economies after the global financial crisis, and leverage wasfound to have an impact on U.S. firms during the crisis (KalemliOzcan, Laeven, and Moreno 2015; Giroud and Mueller 2017). Also,

Second, elevated corporate debt may have
implications for longer-term growth if it coincides
with a period of subdued post-crisis private
investment growth (World Bank 2017; Kose et al.
2017). Excessive corporate debt could dampen
investment and the expansion of productive
capacity necessary for healthy growth, as adisproportionate amount of corporate earnings
would need to be paid to creditors rather thanequity investors. This channel can adversely
impact the growth prospects of EMDEs, and is
the primary topic addressed in this Special Focus.
The Special Focus first discusses trends in EMDE
corporate debt and associated financial stability
risks. It subsequently assesses empirical linkages
between corporate debt and investment activity
based on firm-level data, with a focus on the “debtoverhang” channel. The analysis focuses on
nonfinancial corporations, as they are foremost in
private capital investment activity and thus aremost germane to the linkage between corporate
debt and investment.
Four questions are addressed:•

How has corporate debt evolved in EMDEs?

•

What are the financial stability risks associatedwith elevated corporate debt?

•

Does a “debt overhang” dampen capital
investment in the EMDE corporate sector?

the Republic of Korea’s Chaebol debt-driven expansion abruptly
ended and required massive corporate restructuring during the Asian
Financial Crisis. These issues were compounded by an insolvency
system that was unable to effectively resolve corporate distress.

93

94

S P EC IAL FO CU S 2•This analysis contributes to the literature on
corporate debt overhangs by analyzing the reactionof investment to debt overhang by large and small
private firms for a diverse sample of large EMDEs.
It subsequently explores cross-sectional dimensions, such as firm size, that may affect thesensitivity of investment to debt overhang acrossfirms. The literature on this linkage has thus far
focused on stock exchange listed firms, which may
not fully reflect the state of the corporate sector in
EMDEs.
The analysis points to both cyclical and structural
policy priorities:•

promotion—are warranted. Policies toencourage equity financing and promote debt/
equity balance are especially relevant for small
firms. Similarly, policies to strengthenbankruptcy regimes may both improve
investment activity by increasing investor confidence and by mitigating the macroeconomic
costs of bankruptcies when they occur.

What are the main policy implications
associated with elevated corporate debt?

This Special Focus documents the rise incorporate debt over the past decade in EMDEs,
and finds that an increasing share of debt is heldby firms with higher financial risk (e.g., lower
interest coverage ratios). Moreover, high corporate
debt has been associated with weaker investment
growth. At both the country and firm level,
private investment growth has been correlatedwith corporate debt service capacity. Moreover,
the adverse effect of debt overhangs on investment
is more pronounced among large and highly
leveraged firms. This investigation studies thismedium-term channel that may impact
investment for an extended period of time evenabsent the occurrence of a crisis.

•

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

From a cyclical perspective, the financial
stability risks highlight the need for the buildup of fiscal buffers to prevent a corporate
default surge from having systemic
consequences. Prudential regulations thatmonitor liquidity and currency risks in large
firms’ debt would also be appropriate,especially since the boom in corporate debt
has been concentrated among large (and likely
systemically important) firms.
From a structural policy perspective, in cases
where debt overhangs are slowing private
investment over an extended period, policy
measures to curb debt bias—such as thincapitalization rules or equity market

Corporate debt landscapein EMDEs
Corporate debt in EMDEs has, on average, risen
from about 60 percent of GDP in 2006 to 86
percent of GDP in 2017 (Figure SF2.1). This
increase has been especially pronounced in China,
where corporate debt reached more than 160
percent of GDP by 2017. In other EMDEs,
corporate debt has risen by more than 10
percentage points of GDP over 2006-2017.3
Trends in EMDE corporate debt are quite
heterogeneous across countries, and their rise has
been concentrated in larger EMDEs. In 2016-17,
a number of large emerging economies—especiallyin Latin America and the Caribbean (LAC) andEurope and Central Asia (ECA)—experienced
lower credit growth, partly due to higher
credit risks associated with higher debt built-up inearlier years.
A number of other features characterize recent
developments in corporate debt among EMDEs:•

EMDEs versus advanced economies. By
2017, China’s corporate debt-to-GDP ratio
far exceeded the average of advanced
economies. For other EMDEs, corporate debt
levels are still substantially below that ofadvanced economies.4

3 In China, the decline in the corporate debt-to-GDP ratio over the
past two years was primarily driven by slowing credit growth. In
other EMDEs, while credit growth slowed as well, faster nominal
GDP growth in 2017 also contributed to the decline in corporate
debt-to-GDP ratios.
4 The benchmark sample of 16 EMDEs withBank for
International Settlements (BIS) data consists of mostly large EMDEs
that comprise four-fifth of EMDE GDP.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018•

Regional dimensions. The increase incorporate debt ratios over the past decade wasmost pronounced in East Asia and Pacific(EAP) and ECA.5 Corporate debt ratios alsorose in most other regions of the world overthe past decade, and tend to range between 30
to 40 percent of GDP.

•

Corporate versus other sectors. Corporate
debt is, on average, substantially higher thanhousehold and financial sector debt in
EMDEs. By 2017, corporate debt is now
comparable in magnitude to sovereign debt
(Figure SF2.2).

•

Domestic versus foreign currency. The rise incorporate debt has been supported by bothborrowing in local and foreign currency.6
Outside of China, the contribution of foreign
currency debt has been substantial,
constituting nearly half of the growth incorporate debt over 2010-2017.

••

External versus domestic sources. More than
one-tenth of outstanding corporate debt in
EMDEs is financed by cross-border sources.7
Outside of China, about one-third ofcorporate debt is financed by cross-bordersources, consistent with the trends for
currency composition of corporate debt.
Bond versus bank debt. Bond debt remains amodest but increasing fraction of total
corporate debt, as corporates have shiftedfrom bank loans to bond issuances over the
past decade (Ohnsorge and Yu 2017; Feyen etal. 2015; Ayala, Nedeljkovic, and Saborowski
2017; World Bank 2016). As of 2017, debt
securities are estimated to be about one-fifthof EMDE corporate debt. Bond issuances in

5 In the Sub-Saharan Africa (SSA) region, growing public debt
burdens of low-income countries are of particular concern. Please see
Chapter 2 for more details.
6 The increase in foreign currency debt is not driven by nominal
exchange rate valuation. Over the period 2006-2017, the average realeffective exchange rate in the sample EMDE economies depreciatedby about 5 percent.
7 Based on data from the BIS, external sources of corporate
funding can be proxied by the sum of the stock of outstanding
cross-border bank claims and amount of outstanding international
debt securities in each country. The residual would be domestic
funding.

S P EC IAL FO CU S 295

FIGURE SF2.1 Corporate debt in EMDEs: General trends
Corporate debt in EMDEs has risen over the past decade and is now
substantially above long-term averages. The increase in corporate debt
has occurred in both commodity exporters and importers. Credit growth
has slowed in recent years, especially in a few large commodity exporters.
The increase in corporate debt has been especially pronounced among
several large EMDEs across regions.
A. Corporate debt

B. Corporate debt: EMDEs ex. China

C. Corporate debt: EMDE commodity
importers vs. exporters

D. Corporate credit growth

E. Corporate debt: Pre- andpost-crisis

F. Corporate debt in EMDE regions

Sources: Bank for International Settlements, Institute for International Finance (IIF).
A-D. Figures show GDP-weighted averages for 16 EMDEs (seven commodity importers and ninecommodity exporters) and 27 advanced economies (AEs).
E. Average annual corporate debt-to-GDP ratio. Each blue dot denotes an economy. Excludes
outliers. Pre-crisis and post-crisis denote 2003-07 and 2010-17, respectively. Dotted line denotes 45
degree line.
F. EAP ex. China = East Asia and Pacific, ECA = Europe and Central Asia, LAC = Latin America andthe Caribbean, MNA = Middle East and North Africa, SAR = South Asia, and SSA = Sub-SaharanAfrica. Figure shows GDP-weighted averages that include 4 EAPs, 8 ECAs, 11 LACs, 8 MNAs, 4
SARs, and 7 SSAs (includes expanded sample with IIF data).
Click here to download data and charts.

EMDEs tend to be fixed rate, as opposed tofloating rate bonds (Gozzi et al. 2015).
•

Maturity. Maturity of bonds and syndicatedloans in EMDEs have remained stable over96

S P EC IAL FO CU S 2

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE SF2.2 Corporate debt in EMDEs: Composition
Corporate debt in EMDEs has reached levels comparable to, if notexceeding, that of government debt. Outside of China, foreign currency
debt has contributed substantially to the rise in EMDE corporate debt inrecent years.
A. Debt across sectors, inc. China

C. Corporate debt: Domestic vs.
foreign currency contribution,inc. China

B. Debt across sectors, ex. China

D. Corporate debt: Domestic vs.
foreign currency contribution,
ex. China

over most of the post-crisis period, and has
contributed to overcapacity in some industries(Maliszewski et al. 2016).
Corporate investment growth has slowed sharply
since 2012, both in state-owned enterprises andprivate enterprises. The slowdown in the formergroup has partly reflected policy-driven capacity
cuts in highly indebted industrial sectors (WorldBank 2017).
High corporate leverage in China has been
associated with a deterioration of corporate
financial performance. Policies that were adopted
to address the associated vulnerabilities include
macroprudential measures to tighten lending
conditions for real estate, capacity reduction
targets for heavy industries, and restructuring for
weak state-owned enterprises. Use of bankruptcy
procedures has also increased (IMF 2017a;
Maliszewski et al. 2016).

Corporate debt and financial
stability
Sources: Bank for International Settlements, Institute for International Finance.
A.B. GDP-weighted averages for 16 EMDEs in A and 15 EMDEs in B.
C.D. Percentage point contribution of foreign and local currency-denominated corporate debt growthover the period denoted. GDP-weighted annual averages for 16 EMDEs in A and 15 EMDEs in B.
Click here to download data and charts.

the past decade (averaging about 7 years).
Large firms were able to issue longer-termbonds, especially in the international capital
markets (Cortina, Didier, and Schmukler,
forthcoming). For smaller firms, the use oflong-term finance remains limited comparedto advanced economies (World Bank 2015).
Corporate debt in China has risen sharply, from107 to 163 percent of GDP from 2006-2017(Figure SF2.3). Although the stock of corporate
debt has declined in the past two years, it remains
elevated by international standards. The rise has
been concentrated in the real estate, mining andconstruction sectors, and in state-owned
enterprises. This was mostly financed domesticallythrough the banking system as well as nonbank
financial intermediaries. The increase in thecorporate debt-to-GDP ratio was spurred by the
economy’s investment-intensive growth modelOver the past decade, increased access to debt,
especially non-bank credit, has partly reflecteddevelopment of EMDE financial markets.8
However, as EMDE corporate debt has risen, risks
to financial stability have grown in several
dimensions, both external and domestic.
External dimensions. During most of the postcrisis period, debt service and financing costs were
contained by low global interest rates andcompressed risk premiums. Global, rather thanfirm- and country-specific factors, have been more
important drivers of the increase in corporate debt
(IMF 2015; Feyen et al. 2015; Ayala, Nedeljkovic,
and Saborowski 2017). Countries that had
experienced a higher rise in corporate debt also

8 For example, credit registry coverage has increased in EMDEs
from an average of 4 percent of adults to 13 percent from 2006-2017,and has helped expand financial access (Love, Martínez Pería, andSingh 2013). These economies were also increasingly able to issue
debt in the home currency (Hale, Jones, and Spiegel 2016). Other
capital market developments in EMDEs are highlighted in Cortina,
Didier, and Schmukler (forthcoming); Didier and Schmukler (2014);
and Didier, Llovet Montanes, and Schmukler (2017).

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

tended to have more open capital accounts.
Higher debt is also associated with riskier
corporate balance sheets (Figure SF2.4).
There is a risk of a disorderly tightening of global
financing conditions as monetary policy
normalizes among advanced economies (Chapter
1, Arteta et al. 2015). Funding conditions for
EMDE corporates could significantly worsen, due
to higher interest rates and risk premiums, andalso the potential reversal of capital flows. Debt
service cost may be especially sensitive to interest
rates for floating rate bonds. A sharp appreciationof the U.S. dollar may also weaken balance sheets
to the extent that foreign currency liabilities are
not matched by assets. Many EMDE
multinationals have issued bonds for intracompany
financialintermediation
acrosssubsidiaries, channeling external financial
conditions into the domestic financial system(Bruno and Shin 2017; Shin 2013).
Domestic dimensions. Although moderate levelsof corporate debt can be benign, excessive levels ofdebt for individual corporations may affect bankbalance sheets and banks’ ability to extend credit,
given bank debt still constitutes about four-fifth ofoutstanding EMDE corporate debt. The potential
impact on loan supply could subsequently lower
aggregate demand and collateral values. Higher
corporate debt also has implications for the public
sector balance sheet, given the contingent liability
it may pose, especially during periods of crisis(World Bank 2016). This is especially relevant indeveloping economies, where implicit liabilities
associated with state-owned enterprises are often
not consolidated in official government debt
statistics. In the majority of EMDEs thatexperienced sharp increases in corporate debt,
public debt also rose sizably, as common factors
like low global interest rates supported the
expansion of both types of debt.
Largely accommodative financial conditions havesupported a rapid rise in bond issuances in recent
years. Although bond financing is less vulnerable
than bank financing on some grounds, such as
longer average maturity, it bears othervulnerabilities. These include weaker monitoringstandards associated with the more dispersed

S P EC IAL FO CU S 2

97

FIGURE SF2.3 Corporate debt in China
Corporate debt in China has risen sharply over the past decade, although
it has stabilized in the past two years. Leverage has been particularly
pronounced in heavy-industry sectors, such as mining and utilities. The
increase in corporate debt coincided with a deceleration in investment
growth and business conditions.
A. Corporate debt

B. Firm leverage across industries

C. Investment growth

D. Business conditions

Sources: Bank for International Settlements, Haver Analytics, Orbis.
B. Agr. = Agriculture, Cons. = Construction, Man. = Manufacturing, and ICT = Information andcommunications technology. Figure shows medians across firms in 2015. Based on Orbis data
sample for mostly non-state-owned private firms.
C. Figure shows period average annual nominal growth in fixed asset investment. “SOE” stands forstate-owned enterprises. “Private” stands for private enterprises.
D. Figure shows period averages of quarterly data. China industrial enterprise survey of 5,000
leading enterprises to rate their perception on selected topics. An index reading higher than 50
indicates improvement.
Click here to download data and charts.

nature of bond investors, allowing more firms
with weaker fundamentals to issue during benign
financing conditions but raising vulnerabilities ina downturn. In the next three years, a rising
amount of bonds maturing within one year alsoentails rollover risk if financial conditions tighten
abruptly (Figure SF2.4).
Not only have corporate debt levels risen, evidence
suggests that this debt has been disproportionately
raised by firms that are risky, as measured by their
low interest coverage ratios and other balance
sheet distress indicators (Figure SF2.5; Feyen et al.
2017). Moreover, procyclical retrenchment bysuch firms can harm macroeconomic conditions,affect lenders (via reduced borrowing demand, andhigher losses and non-performing loans) and98

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FIGURE SF2.4 Corporate debt in EMDEs:
Macroeconomic vulnerabilities
In the majority of EMDEs, the corporate debt ratio has risen in tandem withan increase in foreign currency debt. The increase in the corporate debt
ratio has been more pronounced in economies that had more open capital
account and are associated with higher corporate vulnerability. Given a
growing amount of international bonds is expected to mature in EMDEs
over the next three years, rollover risks may rise if financial conditions
tighten abruptly.
A. Change in corporate debt: Total vs.
foreign, 2006-post-crisis peak

B. Change in corporate debt: Financial openness

C. Corporate Vulnerability Index: Highand low debt

D. International corporate bonds
maturing in one year: EMDEs

risky debt from 25 to 31 percent (Chow 2015;
Beltran, Garud, and Rosenblum 2017). Thesevulnerabilities may be mitigated to some extent,
however, by improvement in corporate profitability in 2017 (IMF 2018).
Leverage in the EMDE corporate sector is highly
heterogeneous and has been concentrated in a
number of industrial sectors, such as construction
and utilities. Domestically-owned firms exhibit
higher leverage than multinationals, which canaccess funds via intra-company borrowing acrossaffiliates within the conglomerate (e.g., Desai,
Foley, and Forbes 2008). Large firms account fornearly four-fifth of corporate debt.9 Exchangelisted firms account for about one-quarter of debt.
High concentrations of debt in large andinterconnected firms can amplify systemic risks,even if corporate debt were moderate in aggregate.

Corporate debt andeconomic growth
Analytical linkages

Sources: Bank for International Settlements, Chinn-Ito Index, Feyen et al. (2017), Haver Analytics,
Institute for International Finance, World Bank.
A. Post-crisis peak is country- and indicator-specific and denotes the highest corporate/foreign currency corporate debt-to-GDP ratio in each country over 2010-17. Each dot refers to an economy.
Excludes outliers.
B. Median corporate debt change from 2006-post-crisis peak year, which is country-specific. High/low
financial openness cutoff is based on the median capital account restrictiveness index of Chinn and
Ito (2006, updated to 2015), and for each country is measured over the average of 2010-15. Includes
16 EMDEs.
C. The corporate vulnerability index (CVI) tracks financial conditions of the non-financial corporate
sector. 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 toassets, and market-to-book ratio. The CVI ranges from 0 (i.e., firms in a particular country are notfinancially vulnerable in any of the seven indicators) to 1 (i.e., all firms in a particular country arefinancially vulnerable in all seven indicators). For more details, see Feyen et al. (2017). Y-axis denotes medians. Includes 16 EMDEs for 2010-17. High/low debt cutoff is based on medians.
D. Denotes amount of international bonds outstanding with remaining maturity of 12 months in eachyear denoted (data as of 2018Q1). Includes 54 EMDEs.
Click here to download data and charts.

impact government finances via cyclical revenue
weakness. This suggests that higher corporate
leverage can make the corporate sector more
vulnerable to weaker growth or higher debt service
costs. Stress tests on EMDE corporates haveshown that a combination of exchange rate shocks
andweaker-than-expected
growthcould
significantly erode firms’ interest coverage ratios
and an interest rate shock may boost the share ofElevated corporate debt in EMDEs not only posesrisks for financial stability, it also poses the risk ofdampening investment and long-term growth.10
The increase in China’s corporate debt has raised
concerns regarding investment efficiency, especially among state-owned enterprises (Maliszewski
et al. 2016). In India, high corporate leverage has
been concentrated in a number of industries (e.g.,
mining, transportation, construction), and may
have been a significant factor behind weak private
investment growth (Das and Tulin 2017). In
Brazil, high corporate leverage also contributed to

9 Large firms are defined as those with assets greater than $50
million, similar to the criteria used by the European Union. Results
are not sensitive to alternative measures of large firms, such as thosedefined by the International Finance Corporation (IFC) (larger than
$15 million). In robustness checks of the empirical analysis, thesample was broken into small, medium, and large firms based on the
IFC criteria, but there is no significant differences between small andmedium-sized firms.
10 See Acharya et al. (2015); World Bank (2016); IMF (2015);
Feyen et al. (2017); de Mooij and Hebous (2017); Demirgüç-Kunt,
Martinez-Peria, and Tressel (2015); Alter and Elekdag (2016); Brown
and Lane (2011); Beltran, Garud, and Rosenblum (2017); Corsetti etal. (2015); Alfaro, Asis, Chari, and Panizza (2017); and Occhino andPescatori (2015).

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

weak investment during 2014-early 2017 (IMF
2017b).
Indeed, since 2011, EMDEs in general haveexperienced weak private investment growth.
Further, countries that had more elevatedcorporate debt in the 2011-17 period showed
lower average private investment growth (Figure
SF2.6).11
Although debt flows may help finance investment,
an excessively large stock of debt may eventuallyconstrain investment by creating conflicts ofinterest between equity and debt holders (Myers
1977). This conflict arises because the larger afirm’s debt, the greater the extent to which equity
holders need to share the fruits of that investment
with debt holders. This reduces the attractivenessof investment from the perspective of the equity
holders, possibly leading to underinvestment evenin value-enhancing investment projects.
In the subsequent firm-level analysis, the measureof debt overhang is defined as the ratio of total
debt to earnings before interest and taxes (EBIT),
where total debt is the sum of current liabilities
and long-term debt. This measure includes bothbonded and bank debt, and conforms to the basic
insight that a firm is more likely to experiencedebt overhang when its debt relative to earnings ishigh (Myers 1977). The measure of debt overhang
used here more closely accounts for a firm’s debt
relative to earnings capacity than a simple measureof leverage.12 The analysis confirms that firms withhigh debt overhang tend to have lower net
investment rates (Figure SF2.6).
While the theory that corporate debt overhang
dampens investment dates back several decades,
the empirical literature on the linkage in EMDEs
11 This relationship does not appear to have been driven bydifferences in cross-country growth, as countries with a higher
corporate debt-to-real-GDP growth ratio, a proxy for “corporate debt
efficiency,” also experienced lower private investment growth. A
similar metric was used to assess investment efficiency for China by
Maliszewski et al. (2016).
12 This analysis draws on Borensztein and Ye (forthcoming). Other
works that have used this measure to proxy for debt overhang include
IMF (2018); Chen and Lu (2016); and Kalemli-Ozcan, Laeven, andMoreno (2015). In the baseline specification, results on leverage areconsistent with literature that uses leverage as a proxy for a debt
constraint and finds a negative relationship between leverage andinvestment (Das and Tulin 2017; Magud and Sosa 2015).

S P EC IAL FO CU S 2

99

FIGURE SF2.5 Corporate debt riskiness in EMDEs
Not only has corporate debt become more elevated, but the share of debt
held by high-risk firms has also increased. Corporate leverage isparticularly high in industrial sectors, such as utilities and mining. Leverageis also significantly higher in domestic firms as compared to multinationals,
which have greater access to internal capital markets via affiliates.
A. Corporate Vulnerability Index

B. Share of debt held by high risk
firms (ICR < 2)

C. Industry leverage (ex. China)

D. Leverage: Domestic vs. foreign
ownership

E. Debt-to-sales ratio

F. Net investment rate

Sources: Feyen et al. (2017), Haver Analytics, Orbis, World Bank.
A. The corporate vulnerability index (CVI) tracks financial conditions of the non-financial corporate
sector. 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 toassets, and market-to-book ratio. The CVI ranges from 0 (i.e., firms in a particular country are notfinancially vulnerable in any of the seven indicators) to 1 (i.e., all firms in a particular country arefinancially vulnerable in all seven indicators). For more details, see Feyen et al. (2017). Includes 47
EMDEs. Medians. Vertical lines indicate interquartile range.
B. Denotes share of total debt held by firms with interest coverage ratio (ICR) less than 2 (thresholdfor “risky” firms). Based on a balanced sample of firms for 13 EMDEs.
C.D. Firm total debt scaled by sales. Median across firms in 2015. Based on all available firm-level
data in Orbis for 13 EMDEs.
C. Agr. = Agriculture, Cons. = Construction, ICT = Information and communications technology, andMan. = Manufacturing.
E.F. Sales-weighted averages of debt-to-sales ratio and net investment rate based on a fullybalanced sample of firms over 2008-15.
Click here to download data and charts.

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FIGURE SF2.6 Correlates of corporate debt and private
investment growth in EMDEs

broad sample of European firms in the aftermathof the financial crisis.13

Increased corporate debt in EMDEs has coincided with a period of weak
private investment growth after 2011. Elevated corporate debt has been
associated with weaker private investment growth, both at themacroeconomic and microeconomic levels. This relationship is not driven
by differences in country-level growth performance or firm-level earnings.

This analysis attempts to expand upon thisliterature by studying the reaction of investment
to debt overhangs by both large and small private
firms for a diverse sample of large emerging anddeveloping economies, and subsequently exploring
two cross-sectional dimensions that may affect thesensitivity of investment to debt overhangs: sizeand leverage.

A. Private investment growth: EMDEs

C. Private investment growth: Highand low corporate-debt-to-real-GDP
growth ratio, 2011-17

B. Private investment growth: Highand low corporate debt, 2011-17

D. Debt to earnings in low and highinvestment firms

Building on the macroeconomic trends andcorrelates highlighted earlier, the next section will
analyze the extent to which future profits are put
at risk by high levels of debt and may discourage
investment at the micro-level. The analysis
employs data covering a large sample of companies
that include both large, publicly-traded andsmaller, privately-owned firms for a diverse groupof EMDEs.
Empirical findings

Sources: Bank for International Settlements, Haver Analytics, International Monetary Fund, Institutefor International Finance, Orbis, Oxford Economics, World Bank.
A. GDP-weighted average of 12 EMDEs (available data among BIS corporate debt sample
countries). Data are estimates for some EMDEs. Long-term average refers to 1995-2008. Period
average of annual growth rates.
B. High-low denotes country-year observations of corporate debt-to-GDP ratio above/below themedian. Includes 16 EMDEs. Data are not available for 2016-17 for some economies. Y-axis denotes
median private investment growth.
C. High-low denotes country-year observations of corporate debt-to-GDP ratio to real GDP growth
above/below the median. Includes 16 EMDEs. Data are not available for 2016-17 for some
economies. Y-axis denotes median private investment growth.
D. Low and high investment rates denote the bottom and top one-thirds, respectively, of theinvestment rate distribution. Inverse of median EBIT (3-year smoothed average) to debt ratio in 2015.
Investment denotes net investment. Based on all available data in Orbis for 13 EMDEs.
Click here to download data and charts.

is more recent. A few papers report that leveragecontributes to weak investment growth in EMDEs(e.g., World Bank 2017; IFC 2016; Magud andSosa 2015; Das and Tulin 2017). At the firmlevel, Magud and Sosa (2015) and IFC (2016)
introduce a debt variable for a cross section oflisted firms in various EMDEs, and found anegative relationship between leverage andinvestment. Kalemli-Ozcan, Laeven, and Moreno(2015) test the effect on fixed investment ofcorporate debt (relative to current earnings) for a

Firm-level fixed effects panel estimation isconducted to estimate the relationship between
debt service capacity (inverse of “debt overhang”)
and investment activity. Net investment for abroad cross-section of private and public firms in
13 EMDEs is modelled as a function of the ratioof EBIT to total debt, in addition to a number ofstandard correlates that are associated withinvestment (e.g., sales growth, cash flows), basedon 2007-2015 data. The analysis includes fixed
effects at the firm- and country-industry-yearlevels, which further control for other observed
and unobserved factors that may impact
investment activity, such as macroeconomic
shocks (See Annex SF2.1 for more details on thedata and empirical methodology). In the baseline
specification, the analysis examines therelationship between debt service capacity andinvestment, conditional upon leverage.
Linkage between corporate debt and investment. The
results suggest that debt overhangs are negatively
associated with investment across EMDE firms. In
13 Kalemli-Ozcan, Laeven, and Moreno (2015) is grounded on asimilar framework but focuses on European firms in a crisis setting.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

other words, debt service capacity is positively(and significantly) associated with net investment(Table SF2.1). This relationship is robust for
samples that include and exclude China, although
the sensitivity is smaller for the China sample.14
Furthermore, the relationship is not sensitive tothe inclusion of cash flow or leverage as
explanatory variables in the regression equation,although the magnitude decreases slightly once
controlling for these two variables. The result is
not driven by volatility in earnings over time (seeAnnex SF2.1).
In the full sample, the magnitude of thecoefficient implies that an increase in debt service
capacity from the 10th percentile to the 90th
percentile is associated with about 1.4 percentage
point higher net investment to sales ratios. In the
China and non-China samples, this interquartile
increase is associated with about 1 percentage
point and 2 percentage points higher investment
rates, respectively. These sensitivities amount toabout one-third of the average level of net
investment-to-sales ratio in both the China andnon-China sample.
In aggregate, debt overhang is associated with 16
percent of the decline in the net investment-tosales ratio in the sample from 2011-2015. Thiseffect was concentrated in the China sample,
however, where deterioration in debt service
capacity is higher than the non-China sample andis associated with about one-fifth of the decline ininvestment from 2011-15.
Small and large firms. The analysis also examines
whether the debt overhang-investment sensitivity
varies across small and large firms, as a large
literature in macroeconomics and finance has
established the importance of size for determining
a firm’s access to credit (e.g., Chodorow-Reich
2014; Gertler and Gilchrist 1994). Large firms,
defined as firms with assets above $50 million,
tend to enjoy wider access to both bank credit andbond markets, and thus may be more likely to

14 The firm-level data for China contained only a limited numberof state-owned enterprises. Thus, the data are more reflective of thedebt service capacity to investment sensitivity among firms in the
non-state-owned private sector.

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101

FIGURE SF2.7 Linkage between debt overhang andinvestment across firms
Investment is more sensitive to corporate debt service capacity amonglarge firms and firms that are highly indebted.
A. Small and large firms

B. High and low leverage firms

Sources: Orbis, World Bank.
A. Denotes sensitivity of net investment to debt service capacity (in response to one percentage point
increase in debt service capacity), based on the specification in eq. (1) in Annex for small and large
firms. Large firms are defined as firms with assets greater than $50 million and include one fifth of thesample. See text for more details.
B. Denotes sensitivity of net investment on debt service capacity (in response from one percentage
point change in debt service capacity) based on the specification in eq. (1) in Annex, under low andhigh leverage. High-low leverage cutoff is based on the median within a country-industry pair, andthus the share of highly leveraged firms is 50 percent. See text for more details.
Click here to download data and charts.

increase their liabilities and run into a debt
overhang when a serious shock hits. This isevident by the disproportionate amount of debt
they hold. Large firms may also be more exposed
to international financial and goods markets, andthus be more sensitive to debt service costs
associated with fluctuations in global financing
conditions. Focusing on large firms is also
warranted for policy implications, as a growing
literature has shown that large firms’ performancecan have a systemic impact and is more correlatedwith aggregate growth of an economy (Gabaix2011), can be more sensitive to macroeconomic
shocks (Alfaro et al. 2017), and serve as a key
channel for foreign shocks transmission (diGiovanni, Levchenko, and Mejean 2014, 2018).
By estimating the baseline equation for small andlarge firms separately, the analysis finds that the
debt overhang effect is present among both groups(Figure SF2.7). The coefficients for large firms inboth the overall and non-China sample are larger
than those of smaller firms, although thecoefficient is not significant for China’s large
firms. Estimates of the full regression show thatthe debt overhang impact on investment amonglarge firms is twice that of small firms. Thissuggests that larger firms are more sensitive to debt

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S P EC IAL FO CU S 2overhang, and that the consequences from theirdisproportionate undertaking of leverage may
outweigh the advantage they have in terms ofbetter access to finance.
Low and highly indebted firms. Since the effect ofdebt overhangs may be nonlinear, the analysis
examines whether the sensitivity varies across highand low-leverage firms. The threshold for highand low levels of debt is defined as the medianwithin a country-industry pair, given that leveragelevels may be to some extent driven by thebusiness structure and operational needs of anindustry. The debt overhang sensitivity is found to
be larger for firms with high debt levels, andmoreover, the effect of debt overhang is nearly
three times higher in high-debt firms than lowdebt firms (Figure SF2.7). These results suggestthat the sensitivity of investment to debt overhang
can vary significantly, conditional upon preexisting leverage levels. At high levels of debt, thedebtor-equity holder conflict becomes more
prominent, as a greater proportion of positive netpresent value (NPV) projects needs to be paidback to creditors. This means that debt service
capacity becomes more binding, and causes higher
cutbacks in investment when debt is high.15
Overall, the results suggest that the debt overhang
channel is a vulnerability for investment across
EMDE firms. This linkage is especially pronounced in large firms and highly leveraged
firms.16

Policy implications
This Special Focus points to both financial
stability and growth-related challenges facing
policymakers in countries where corporations
exhibit high debt levels. To reduce financial

15 An alternative to exogenously-specified debt thresholds is toallow for endogenous thresholds in the relationship between debt
service capacity and investment. Threshold regressions following
Hansen (1999) based on a balanced sample also suggests a similar
nonlinear relationship between debt service capacity and investment
under low and high levels of debt to sales ratio.
16 The analysis also experiments with sensitivity of debt service
capacity to investment across countries of varying financial
development, creditor rights protection, and public debt levels. The
analysis does not find consistent evidence that this sensitivity varies
significantly along these lines.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

stability risks associated with elevated corporate
debt, cyclical and prudential policies need to be
the primary lever. To lift investment activity andmitigate the medium-term consequences ofcorporate debt overhang, structural policies geared
toward promoting financial development areappropriate.
Cyclical policies
Fiscal policy. Corporate distress, such as defaults
arising from debt overhang, can provoke thegovernment to provide sizable financial support
and contribute to larger public debt burdens(World Bank 2016). This can cause publicborrowing costs to rise and fiscal space to shrink,and can force governments to tighten fiscal policy
during times of weak growth. Fiscal space in
EMDEs has deteriorated during the post-crisis
period, even as corporate debt ratios have risen(Figure SF2.8). This suggests that the risk ofcorporate debt distress is an additional argument
for boosting or at least maintaining fiscal buffers
in the present environment as insurance against
corporate distress.
Prudential policy. The analysis suggests that large
firms have taken on a disproportionate share of
aggregate debt stock, raising the possibility that
there could be financial stability implications if
these firms faced balance sheet distress. This
argues for increased stress testing of corporate
balance sheets and greater monitoring of thelargest firms, especially their foreign exchange
hedging and liquidity management. These types ofpolicies can increase the scope for adequate
preparation for possible corporate distress. They
can help to reduce the potential disruptions that
could result from tightening advanced-economy
financial conditions and increased volatility ofinternational financial flows. Preemptive policies
that improve bank risk management and lending
practices, such as liquidity requirements in the
Basel III accord or caps on foreign currency
exposure on bank balance sheets, would help
constrain bank risky borrowing (BIS 2013). These
policies help prevent EMDE corporates fromtaking on excessive debt under benign financing
conditions and periods of high corporate
profitability.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

S P EC IAL FO CU S 2103Structural policies

FIGURE SF2.8 Policy implications

The foregoing analysis illustrates the potential forexcessive corporate debt to dampen private
investment. There are a number of structural
policy options that can help reduce this risk:

Fiscal space has deteriorated in EMDEs since the crisis, which may
increase the costs of financial support in cases of systemic corporate
distress. Policies to promote equity market development in EMDEs,
including strengthening corporate shareholder rights, can help achieve amore balanced debt/equity mix. Strengthening bankruptcy protection,
which lags behind global best practices in EMDEs, may help containcorporate distress costs from debt overhang.

•

•

•

•

Most tax systems favor the use of debt overequity by providing tax deductibility forinterest payments. Policies such as “thincapitalization rules,” which limit the amountof debt companies can issue relative to equity,
have been found to be effective in lowering
debt ratios and reducing financial distressunder certain conditions (de Mooij andHebous 2017).
The quality of debt could be increased by
improving credit information and collateralregistries to shorten collateral recovery times
and reduce default losses. These policies help
improve credit-relevant information flows andbreak down information asymmetries, andthereby help channel more credit to thosefirms that lack access to credit, especiallyamong small- and medium-sized enterprises(SMEs).
Many EMDEs have not developed theirequity markets to full potential in part becauseof regulatory burdens that discourage newlistings and weaknesses in corporate governance and shareholder rights that undermine
the integrity and liquidity of stock markets.
Addressing these shortcomings would
strengthen equity markets and mitigate debt
biases. Equity financing helps increase firms’
resilience, improves their creditworthiness,and lessens the risk of large-scale, broad-based,
and correlated corporate retrenchments.
Promoting a more balanced debt/equity mix
and incentivizing equity financing may beparticularly relevant for small firms, which
tend to rely mostly on bank and internalfinancing.
An excessive accumulation of corporate debt
can occur when explicit or implicit state
guarantees are too generous, and whenbankruptcy regimes do not allow quick andfair debt workouts for companies. Overall,A. Fiscal sustainability gap: EMDEs

B. Equity market concentration

C. Bankruptcy rights protection:
EMDEs

D. Corporate shareholder rights:
EMDEs

Sources: International Monetary Fund, World Bank.
A. Simple averages. A sustainability gap is defined as the difference between the actual fiscal
balance and the debt-stabilizing balance (Kose et al. 2017). Sustainability gaps are measured undercurrent conditions. The year of global recession (2009) is shaded in gray.
B. Number of listed companies per 1,000,000 people.
C.D. AE = Advanced Economies, EAP = East Asia and Pacific, ECA = Europe and Central Asia,
LAC = Latin America and the Caribbean, SAR = South Asia, and SSA = Sub-Saharan Africa.
Denotes year 2017. Distance to frontier score based on World Bank Doing Business report.
C. Distance to frontier score for strength of insolvency resolution. AE, EAP, ECA, LAC, MNA, SAR,
SSA include 37, 20, 19, 28, 16, 8, and 44 economies, respectively.
D. Distance to frontier score for strength of shareholder rights protection. AE, EAP, ECA, LAC, MNA,
SAR, SSA include 37, 20, 21, 29, 16, 8, and 44 economies, respectively.
Click here to download data and charts.

EMDE bankruptcy protection law lags
international best practices, implying scopefor policy reforms in this area. Historicalexperience suggests strengthening bankruptcy
protection can boost investment activity andfacilitate responsible corporate risk-taking,helping to relieve the costs of debt overhang(e.g., Gopalan, Mukherjee, and Singh 2016;
World Bank 2014). For small firms, thesepolicies should also promote long-term
financing, which has been limited in EMDEs(World Bank 2015). Recent reforms in

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bankruptcy procedures have occurred inseveral EMDEs, including the introduction ofa new bankruptcy law in Egypt, strengtheningof secured creditors’ rights in India, andsetting up new restructuring mechanisms in
Poland (IMF 2017c; World Bank 2018b).

TABLE SF2.1 Debt overhang and investment: Baseline specification
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

VARIABLES

all

all

all

all

ex China

ex China

ex China

ex China

China

China

China

China

Debt overhang(inverse)

0.020***

0.018***

0.017***

0.017***

0.033***

0.028***

0.030***

0.027***

0.009***

0.009***

0.007***

0.007***(0.002)(0.002)(0.003)(0.003)(0.006)(0.005)(0.006)(0.006)(0.002)(0.002)0.068***

0.034

0.045

0.013

Cash flows(0.026)

Leverage
Maturity
Sales growth(0.027)-0.013***-0.013***(0.002)(0.002)(0.031)-0.013***(0.032)(0.002)(0.002)-0.106***-0.088***-0.108***-0.089***(0.002)0.105**(0.043)-0.013***-0.081*** -0.068*** -0.083*** -0.068***(0.002)0.126***(0.042)-0.017***-0.016***(0.005)(0.005)-0.045*** -0.039*** -0.047*** -0.040***(0.013)(0.013)(0.013)(0.013)(0.020)(0.020)(0.020)(0.020)(0.012)(0.012)(0.012)(0.012)0.013***

0.013***

0.014***

0.013***-0.001-0.002-0.001-0.0020.024***

0.024***

0.024***

0.024***(0.001)(0.001)(0.002)(0.001)(0.001)(0.001)(0.002)(0.003)(0.003)(0.003)(0.003)(0.001)-0.057*** -0.083*** -0.059*** -0.083***-0.050***-0.082***-0.052***-0.083***-0.057*** -0.076*** -0.054*** -0.073***(0.005)(0.005)(0.005)(0.005)(0.007)(0.008)(0.007)(0.008)(0.005)(0.006)(0.006)(0.006)

Observations

453,793453,793453,793453,793

241,173

241,173

241,173

241,173

212,620

212,620

212,620

212,620

R-squared

0.361

0.362

0.361

0.362

0.353

0.354

0.353

0.354

0.388

0.389

0.388

0.389

Size

All right hand side variables are lagged by one year. Clustered standard errors by firm in parentheses.
*** p<0.01, ** p<0.05, * p<0.1
Notes: Dependent variable is net investment to sales ratio. Debt overhang (inverse) denotes the ratio of earnings before interest and taxes (EBIT) to total debt. Cash flows is EBIT-to-sales
ratio, Leverage is total debt-to-sales ratio, Maturity is the ratio of long-term debt to total debt, Size is log of sales. EBIT is three-year smoothed average. Regressions include firm and countrysector-year fixed effects. Regression sample includes 129,687 firms.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

S P EC IAL FO CU S 2Annex SF2.1 Data and methodology: Firm-level analysis
Data
The firm-level analysis is based on data fromORBIS, produced by Bureau van Dijk Electronic
Publishing (BvD). The sample contains firm-levelbalance sheet information in 13 large EMDEs
across Africa, Asia, Europe, and Latin
America. The countries include Brazil, China,
Colombia, Hungary, India, Malaysia, Mexico, thePhilippines, Poland, the Russian Federation,
South Africa, Thailand, and Turkey. The balance
sheet information comes from regulatory andother sources (e.g., local chambers of commerce).
The sample is an unbalanced panel based on datafor 2007-2015. In contrast to most other major
firm-level databases (e.g., Worldscope), most firms
in the sample are non-publicly-listed firms (morethan 95 percent). About 90 percent of firms in thesample have an asset size below $50 million (thecutoff for “large firm”). Industry-level information
is available based on the NACE Rev. 2 classification.
A limitation of the Orbis dataset is that it does notcomprise the full universe of firms in the EMDE
sample considered, and hence may not necessarilyreflect the entire corporate sector in these
economies. Nevertheless, compared to otherstandard firm-level datasets, it covers a muchlarger sample of private firms, which are importantdrivers of economic activity in the EMDE
corporate sector.17
The primary aim of the firm-level analysis is totake advantage of the dataset’s highly granularcross-sectional structure and employ a rich set ofinteractive fixed effects. It also aims to control forfactors that are intrinsic to industry operations or
demand, as well as to explore heterogeneity incorporate debt behavior across firms.
The dataset comprises those firms in the ORBIS
database that have available data on fixed assets,
17 Based on a balanced sample for the sample as a whole, however,their trends in debt and net investment broadly reflect that of theaggregate (Figure SF2.5). The empirical results are also robust to
estimation based on a balanced sample.

long-term corporate debt, earnings before interestand taxes (EBIT), and total assets (above $5
million) in at least one year over the sample
period. A cleaning procedure similar to KalemliOzcan, Laeven, and Moreno (2015) is conducted
to generate a usable dataset, including thefollowing:
1. drop company-years that simultaneously lackdata on total assets, sales, and employment.
2. drop entire company for all years if total
assets, employment, sales, tangible fixed assets,or fixed assets is negative in any given year.
3. drop companies
organizations

denotedasnon-profit

4. change value to “missing” if long-term debt or
current liabilities are negative.
This yields an unbalanced sample of 434,256
firms. In the non-China sample, the number offirms in each country is not dominated by any
particularly country.18 All observations are
winsorized (transformed by limiting extreme
values) at the 1 percent level to prevent the impact
of extreme outliers.
Methodology
Investment is measured from data on the stock of
fixed assets. Thus, investment is measured on a net
basis, calculated as the annual difference in fixed
assets (deflated in real terms, scaled by real sales).
Total debt is defined as the sum of long-term debt
plus current liabilities. The primary debt overhangvariable is measured as the ratio of a rolling threeyear average of earnings before interest and taxes(EBIT) to current total debt, which is an indicatorof the size of accumulated debt relative to expected

18 The sample comprises 6,758 firms in Brazil, 225,699 firms in
China, 11,245 firms in Colombia, 6,677 firms in Hungary, 19,886
firms in India, 21,268 firms in Malaysia, 1,246 firms in Mexico,
5,345 firms in the Philippines, 19,487 firms in Poland, 87,402 firms
in Russia, 228 firms in South Africa, 19,711 firms in Thailand, and9,304 firms in Turkey. In the full baseline regression, constraints ondata availability across all variables yields a firm sample of about
130,000 firms.

105

106

S P EC IAL FO CU S 2

proﬁts (Myers 1977). In the regression framework,
this variable is expressed as the ratio of EBIT tototal debt rather than its reciprocal to avoid
problems in cases where EBIT may be equal to or
close to zero.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

+ 1Overhangcij,t-1 + Xcij,t-1´ + i + cjt + cijt (1)variables in the corporate ﬁnance literature. cijt isthe error term. The standard errors in thebenchmark speciﬁcation are clustered at the ﬁrm
level, but the results are robust to clustering at thecountry-industry level. Given that the debt
overhang measure includes EBIT as well as total
debt, it may be correlated to some extent with cash
ﬂow and leverage. Thus, these two variables areincluded sequentially to check the robustness ofthe debt overhang sensitivity.

where cijt denotes the net investment rate of ﬁrm i,
industry j, country c, and year t. Overhangcijt
denotes the benchmark measure of ﬁrm debt
overhang as described earlier. In other words,
Overhangcijt measures the debt-service capacity of aﬁrm. A higher value of 1 thus implies a higher
sensitivity of investment to debt-service capacity.
Xcij,t-1 denotes a vector of control variables, which
include ﬁrm size (log of total sales in U.S. dollars),sales growth, cash ﬂows (EBIT-to-sales ratio),leverage (debt-to-sales ratio), and debt maturity(ratio of long-term debt to total debt). Long-term
debt is deﬁned in the dataset as debt held by eachﬁrm with residual maturity greater than one year.
These variables are considered standard control

Given the well-known volatility of EBIT, a threeyear rolling average is used in calculating thisvariable. The result is also robust to a measure ofdebt overhang where each ﬁrm’s sample average
EBIT is used for all years. All variables on theright-hand side are lagged by one period. The
speciﬁcation also includes ﬁrm ﬁxed eﬀects, i,and country-industry-year ﬁxed eﬀects, cjt , tocontrol for ﬁrm-level time invariant heterogeneity
and a rich set of unobserved and observed timevarying factors at the country-industry level,
respectively. These factors may include, forexample, industry demand eﬀects or macroeconomic shocks. The estimations are also
conducted for China and non-China separately.

To examine the sensitivity of investment to debt
overhang, the baseline estimating equation is asfollows:
cijt

=

0

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

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CHAPTER 2REGIONALOUTLOOKS

Growth in the East Asia and Pacific region is expected to remain solid, slowing marginally to 6.3 percent in2018 and to an average of 6.1 percent in 2019-20, broadly as previously projected. This modest easing reflects
a structural slowdown in China that is only partly offset by a maturing cyclical pickup in the rest of the region.
While upside surprises to global activity could lead to stronger-than-expected regional growth, risks to theforecast remain tilted to the downside and include intensified trade restrictions and an abrupt tightening of
global financing conditions.

Recent developments
Growth in the East Asia and Pacific region
accelerated slightly to 6.6 percent in 2017,reflecting solid exports and strong domestic
demand (World Bank 2018a; Figure 2.1.1).
Conditions are mostly favorable for the region in
2018, including robust global trade, moderateborrowing costs, and sustained capital inflows.
Regional financial markets have generally
remained buoyant, despite volatility in early andmid-2018 related to the prospects of fastermonetary policy tightening in advanced
economies and escalating trade tensions. Bond
spreads in some countries have increased,following bouts of volatility in stock markets, but
remain close to the low levels that prevailed in
2017.
Domestic monetary conditions have tightenedsomewhat and tighter prudential policies have
kept credit growth in check. Several major
economies have renewed their fiscal consolidation
efforts in 2018 (e.g., China, Indonesia, the Lao
People’s
Democratic
Republic,
Malaysia,
Vietnam).
Note: The author of this section is Ekaterine Vashakmadze.
Research assistance was provided by Brent Michael Harrison andJinxin Wu.

Growth across the region remains solid. Exports
continue to increase both in volume and value
terms, benefiting from the recovery in global
investment and trade, as well as stronger trade andinvestment integration within Asia and between
Asia and Eurasia (Chapter 1). Private consumption continues to be supported by solid
consumer confidence and rising household wealth,amid moderate inflation.
While inflation has generally picked up among
commodity importers, it has been on a downward
trend in commodity exporters as the impact ofpast currency depreciations wane. Output gaps
have generally closed, but economic slack remains
in several commodity exporters (e.g., Mongolia,
Papua New Guinea). With the exception ofChina, where investment continues its policyguided deceleration, investment spending in theregion has remained strong, partly reflecting
improved business confidence, continued capital
inflows, and higher earnings (e.g., Cambodia, Lao
PDR, Vietnam).
In China, a solid rebound of exports amid robust
consumption growth helped output to expand in2017 at a slightly faster-than-expected pace
(Figure 2.1.2; World Bank 2017a). Domestic
demand has remained solid in 2018, reflecting
robust consumption growth and recovering
private fixed asset investment. Tighter regulations,especially of the shadow banking sector, have

114

CHAPTER 2.1

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 2.1.1 EAP: Recent developments
Growth in the region accelerated in 2017, reflecting solid exports anddomestic demand, and has continued to be solid this year. Regional
financial markets have generally remained buoyant despite volatility inearly and mid-2018. With the exception of China, where investment
continues its policy-guided deceleration, investment spending in the region
has remained strong. Inflation is generally in line with targets.
A. Growth

B. Export growth

C. Emerging market bond spreads

D. Equity prices

E. Investment

F. Inflation

Sources: Haver Analytics, International Monetary Fund, World Bank.
Note: EAP stands for East Asia and Pacific. Commodity importers ex. China include Cambodia,
Fiji, Philippines, Solomon Islands, Thailand, Vietnam, and Vanuatu. Commodity exporters include
Indonesia, Lao PDR, Mongolia, Malaysia, Myanmar, Papua New Guinea, and Timor-Leste. 19902017 average for commodity exporters excludes Myanmar and Timor-Leste due to data limitations.
Aggregate growth rates are calculated using constant 2010 U.S. dollar GDP-weights.
A.E. Data in shaded area are forecasts.
B. Data include only goods and reflect contributions to year-on-year 12-month moving average
growth. Aggregate growth rate for EAP excluding China excludes Cambodia, Fiji, Lao PDR, Mongolia,
Myanmar, Solomon Islands, Papua New Guinea, Timor-Leste, Vanuatu, and Vietnam due to data
limitations. Last observation is February for China and March 2018 for EAP excluding China.
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
May 24, 2018.
D. Last observation is May 25, 2018.
E. Investment refers to total fixed investment. Aggregate growth rate for EAP excluding China
excludes Fiji, Myanmar, Solomon Islands, Papua New Guinea, and Timor-Leste due to data
limitations.
F. Average year-on-year growth. The figure shows the midpoints of targeted ranges in 2018 inIndonesia (2.4-4.5 percent), the Philippines (2-4 percent), Vietnam (4 percent), China (3 percent), andThailand (1-4 percent). For Malaysia, the midpoint of Bank Negara’s 2018 forecast of 2-3 percent isused. Last observation is April 2018.
Click here to download data and charts.

continued to reduce housing price growth andstabilize credit growth in the first half of 2018.
The stock of corporate debt, which peaked in2016 at 167 percent of GDP, has continued to
decline as percent of GDP in the first half of2018, but remains high by international standards(BIS 2018). Tighter enforcement of capital flows
helped ease capital outflows and exchange ratepressures. The renminbi appreciation has extended
into 2018. China recorded its first current accountdeficit since 2001 in the first quarter of 2018,consistent with external rebalancing.
In commodity-exporting economies, the investment-led cyclical recovery has continued in
response to higher commodity prices and low
financing costs. That said, the pace of growth isincreasingly reflecting country-specific factors. In
Indonesia, the strength observed last year has
continued into 2018, led by rising investment on
the back of higher commodity prices andaccelerated infrastructure spending (World Bank
2017b). Growth continues to recover in
Mongolia, supported by strong coal production
and vigorous private investment. In Malaysia,
growth is moderating after a strong rebound lastyear. However, it remains robust and exports havecontinued to increase in the first half of 2018
(World Bank 2017c).
Activity in commodity-importing economies
excluding China remains strong, broadly in linewith its underlying potential rate. In Thailand,
activity remained solid in the first half of the year,
following a sharp cyclical recovery in 2017,supported by firming exports (World Bank
2018b). Growth in the Philippines and Vietnam
remains robust, but capacity constraints (e.g., highcapacity utilization rates) limit further acceleration, especially in the Philippines (World Bank
2017d).
Overall, the region benefits from solid
fundamentals, including moderate domestic andexternal imbalances and significant policy buffers(World Bank 2018a). However, some countries in
the region continue to face financial sector
vulnerabilities, with elevated levels of debt (e.g.,
China, Lao PDR, Malaysia, Mongolia, Papua
New Guinea, Thailand), still-fast credit growthG LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018(e.g., China, the Philippines, Vietnam), highforeign participation in local-currency sovereign
bond markets (e.g., Indonesia, Malaysia), andsizable fiscal deficits (e.g., Cambodia, Lao PDR,
Mongolia, Vietnam).

Outlook
Regional growth is expected to gradually moderatefrom 6.3 percent in 2018 to 6.1 percent on
average in 2019-2020, broadly unchanged fromJanuary forecasts (Tables 2.1.1 and 2.1.2; Figure
2.1.3). The slowdown in regional growth is largely
due to the gradual structural slowdown in China,
the region’s largest economy. Activity in the rest of
the region is expected to peak in 2018 and remain
steady around its potential rate in 2019 and 2020.
The outlook is predicated on broadly stablecommodity prices in the next two years, solid but
moderating global demand, and a gradualtightening of global financing conditions.
Growth in China is projected to slow from 6.5
percent in 2018 to 6.3 percent on average in
2019-20. Policy support is expected to ease, led byregulatory and macroprudential tightening. Fiscal
policies are expected to become lessaccommodative to contain financial risks andencourage a continued rebalancing of theeconomy from investment to consumption andfrom industry to services. Growth in the rest of
the region is projected to reach 5.4 percent in2018 and remain broadly unchanged at 5.3
percent in both 2019 and 2020, as the cyclicalrecovery in these economies matures.
Growth in commodity exporters is expected toremain broadly stable at about 5.3 percent in
2019, in line with its potential, with significant
cross-country divergence. This forecast is slightly
above that of January, reflecting an upwardrevision to a number of commodity exporters(e.g., Malaysia, Mongolia), which more than offset
a downgrade in some other economies (e.g., Papua
New Guinea, Timor-Leste). The downgrade in
growth projections for Papua New Guinea is due
to a massive earthquake that hit the country in
February and led to the temporary suspension of
production of natural gas at the Hides gas field.
Output gaps in most commodity exporting

EAST ASIA AND PACIFIC

115

FIGURE 2.1.2 China
In China, a strong rebound of exports amid robust consumption growth
helped output to expand in 2017 at a slightly faster-than-expected pace.
Tighter macroprudential policies have continued to reduce housing pricegrowth and moderate credit growth in 2018. China recorded its first current
account deficit since 2001 in the first quarter of 2018, consistent withongoing external rebalancing.
A. Contributions to growth

B. Credit growth

C. Housing prices

D. Balance of payments

Sources: Haver Analytics, The People’s Bank of China, World Bank.
A. Investment refers to gross capital formation, which includes change in inventories. Data in shaded
area are forecasts.
B. Total social financing by uses. Last observation is 2018Q1.
C. The National Bureau of Statistics of China surveys house prices in 70 cities and divides them into
three tiers. The first tier includes Shanghai, Beijing, Guangzhou, and Shenzhen. The second tierincludes 31 provincial capital and sub-provincial capital cities. The third tier includes 35 other cities.
Lines indicate February 2011-April 2018 averages. Last observation is April 2018.
D. Current account balance is based on seasonally adjusted data. Last observation is 2018Q1.
Net capital flows and change in reserves are estimates.
Click here to download data and charts.

economies are expected to close over the forecasthorizon, as the adjustment to low commodity
prices runs its course and investment growthstabilizes.
Growth in commodity importers is projected tomoderate and converge with its potential rate ofabout 5.3 percent in 2019 and 2020. In
commodity importers excluding China, an
upgrade to growth projections in 2018 reflects an
upward revision to Thailand due to stronger
exports, which are nevertheless projected toremain below the regional average.
For both commodity exporters and importers,
capacity constraints and price pressures are

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CHAPTER 2.1

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 2.1.3 EAP: Outlook and risks
Regional growth is expected to moderate from 6.3 percent in 2018 to 6.1
percent on average in 2019-20, largely due to the gradual structural
slowdown in China. Activity in the rest of the region is projected to stabilize
as the cyclical rebound matures. Growth in commodity importers is
projected to converge with its potential rate of about 5.2 percent andremain around this level in 2019-20. Domestic vulnerabilities, related toelevated domestic debt and external financing needs in some countries,
would amplify the impact of external shocks, especially where policy
buffers are limited.
A. Growth

C. Total debt

B. Growth by groups

D. Fiscal balances of 2018

Sources: Bank of International Settlements, Haver Analytics, International Monetary Fund, WorldBank.
Note: EAP stands for East Asia and Pacific.
A.B. Commodity importers ex. China include Cambodia, Fiji, Philippines, Solomon Islands, Thailand,
Vietnam, and Vanuatu. Commodity exporters include Indonesia, Lao PDR, Malaysia, Mongolia,
Myanmar, Papua New Guinea, and Timor-Leste. Shaded areas are forecasts. 1990-2017 average forcommodity exporters excludes Myanmar and Timor-Leste due to data limitations. Aggregates arecalculated using 2010 U.S. dollar GDP-weights.
C. The highest debt-to-GDP ratio since 1995Q1. The peak occurred in 1997Q4 in Thailand, 1998Q4
in Malaysia, 2001Q4 in Indonesia, and 2016Q4 in China. Last observation is 2017Q3.
D. Data reflect World Bank staff forecasts.
Click here to download data and charts.

expected to intensify over the forecast horizon, inpart reflecting higher oil prices, leading to further
tightening of monetary policy in the region.
Despite the projected robust activity in the region
in the near term, underlying potential growth—which has fallen considerably over the past
decade—is likely to decline further over the longterm, reflecting increasingly adverse demographic
patterns and a projected slowing pace of capital
accumulation, which is needed to rein in credit
growth (World Bank 2018a, 2018b).

Risks
While upside surprises to global activity could leadto stronger-than-expected regional growth, risks to
the outlook remain tilted to the downside.
Increased protectionist tendencies in some large
economies continue to create uncertainty about
the future of established trading relationships. The
imposition of trade restrictions by advanced
economies would disproportionately affect themore open economies in the region.
The economic impact of tariffs on imports to
China, that have been discussed by the U.S.
administration would likely be manageable
provided they do not lead to escalation (Chapter
1; World Bank 2018a). However, there is a riskthat such measures, may trigger retaliatory action
and lead to broader trade restrictions. A significant
disruption to activity in China would have large
regional effects (World Bank 2016, 2018c). Risinggeopolitical tensions, including in the Korean
Peninsula and the South China Sea, could weighon investor sentiment, leading to financial market
volatility and softer regional investment (WorldBank 2018a).
In addition, a faster-than-expected tightening of
global financing conditions and associated financing stress—triggered, for instance, by changes
in market expectations of advanced-economy
monetary policy—could reduce capital inflows,
heighten financial market volatility, and placepressure on regional exchange rates and asset
prices. Rising borrowing costs could substantially
increase the burden of debt servicing, which wascontained in recent years by low global interest
rates and risk premiums.
If a combination of downside risks were tomaterialize, it could trigger a sharper-thanexpected slowdown in regional growth. Domestic
vulnerabilities—elevated domestic debt and large
external financing needs in some countries—
would amplify the impact of external shocks,
especially where policy buffers are limited, anddampen growth.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

117

EAST ASIA AND PACIFICTABLE 2.1.1 East Asia and Pacific forecast summary
Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)

EMDE EAP, GDP1

2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

6.5

6.3

6.6

6.3

6.1

6.0

0.1

0.0

0.0

(Average including countries with full national accounts and balance of payments data only)2
6.5

6.3

6.6

6.3

6.1

6.0

0.1

0.0

0.0

GDP per capita (U.S. dollars)

5.8

5.6

5.9

5.7

5.5

5.5

0.1

0.0

0.1

PPP GDP

6.4

6.3

6.5

6.2

6.1

6.0

0.1

0.1

0.1

Private consumption

6.7

6.8

6.9

7.0

6.8

7.0

-0.1

-0.2

0.1

Public consumption

8.9

9.3

7.5

7.6

7.5

7.4

-0.2

0.9

0.9

Fixed investment

6.5

6.6

5.8

5.5

5.3

5.5

-0.3

-0.5

-0.2
1.1

EMDE EAP, GDP2

Exports, GNFS3

0.5

3.2

7.3

5.7

6.0

5.8

1.6

1.5

Imports, GNFS3

0.8

5.4

5.7

5.8

6.1

6.4

0.6

0.8

1.1

Net exports, contribution to growth

-0.1

-0.6

0.5

0.0

0.0

-0.2

0.2

0.2

-0.1

Memo items: GDP
East Asia excluding China

4.9

4.9

5.3

5.4

5.3

5.3

0.1

0.0

0.1

China

6.9

6.7

6.9

6.5

6.3

6.2

0.1

0.0

0.0

Indonesia

4.9

5.0

5.1

5.2

5.3

5.4

-0.1

0.0

0.1

Thailand

3.0

3.3

3.9

4.1

3.8

3.8

0.5

0.3

0.4

Source: World Bank.
Note: 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 Democratic People’s Republic of Korea and dependent territories.
2. Sub-region aggregate excludes Democratic People’s Republic of Korea, dependent territories, Fiji, Kiribati, the Marshall Islands, the Federated States of Micronesia, Myanmar, Nauru,
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.

TABLE 2.1.2 East Asia and Pacific country forecasts1
Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)
2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

Cambodia

7.0

7.0

6.8

6.9

6.7

6.6

0.0

0.0

-0.1

China

6.9

6.7

6.9

6.5

6.3

6.2

0.1

0.0

0.0

Fiji

3.6

0.4

3.8

3.5

3.4

3.3

0.0

0.1

0.1

Indonesia

4.9

5.0

5.1

5.2

5.3

5.4

-0.1

0.0

0.1

Lao PDR

7.3

7.0

6.7

6.6

6.9

6.9

0.0

0.0

0.0

Malaysia

5.0

4.2

5.9

5.4

5.1

4.8

0.2

0.1

0.1

Mongolia

2.4

1.5

5.1

5.3

6.4

6.5

2.2

-0.9

1.0

Myanmar

7.0

5.9

6.4

6.7

6.9

7.1

0.0

0.0

0.2

Papua New Guinea

5.3

1.9

2.2

-1.7

4.0

3.0

-4.2

1.6

-0.4

Philippines

6.1

6.9

6.7

6.7

6.7

6.6

0.0

0.0

0.1

Solomon Islands

3.7

3.5

3.2

3.0

2.9

2.8

0.0

0.1

0.1

Thailand

3.0

3.3

3.9

4.1

3.8

3.8

0.5

0.3

0.4

Timor-Leste

4.0

5.3

-1.8

2.2

4.2

4.0

-2.0

-0.8

-1.0

Vietnam

6.7

6.2

6.8

6.8

6.6

6.5

0.3

0.1

0.0

2

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 significantly differ at any given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars.
2. Non-oil GDP. Timor-Leste’s total GDP, including the oil economy, is roughly four times its non-oil economy and is highly volatile as a result of sensitivity to changes in global oil prices andlocal production levels.
For additional information, please see www.worldbank.org/gep.

Growth in the Europe and Central Asia region is anticipated to ease to 3.2 percent in 2018, down from 4.0
percent in 2017, as one-off supporting factors wane in some of the region’s largest economies. By 2020, growthis expected to gradually moderate to 3.0 percent due to less supportive external conditions, intensifying capacity
constraints, and less accommodative fiscal and monetary policy in commodity importers. Growth in commodity
exporters is expected to continue strengthening amid higher commodity prices. Regional risks remain tilted tothe downside, reflecting the possibility of a disorderly tightening of financing conditions, renewed policy
uncertainty, and rising trade protectionism.

Recent developments
Regional growth was strong in 2017, reaching 4.0
percent, with broad-based recoveries across bothcommodity importers and commodity exporters(Figure 2.2.1).1 Despite robust activity in late2017 and early 2018, momentum has eased amid
moderating export growth and less accommodative policies.
For commodity importers, the significant pickup
in activity in 2017 was driven by strengthening
demand from the Euro Area and disbursements of
EU structural funds in Central Europe, but thesefactors have started to wane gradually.2 In Turkey,
growth sharply accelerated to 7.4 percent in 2017from 3.2 percent in 2016, as it rebounded fromthe 2016 failed coup attempt and benefited fromsupportive policy measures including tax cuts,
public transfers, and credit support measures forsmall and medium-sized enterprises (World Bank

Note: The author of this section is Yoki Okawa. Research
assistance was provided by Ishita Dugar.
1 Commodity importers are Bulgaria, Belarus, Bosnia andHerzegovina, Croatia, Georgia, Hungary, Kosovo, Former Yugoslav
Republic of Macedonia, Moldova, Montenegro, Poland, Romania,
and Serbia. Commodity exporters are Albania, Azerbaijan, Armenia,
Kazakhstan, Kyrgyz Republic, Russian Federation, Tajikistan,
Turkmenistan, Uzbekistan, and Ukraine.
2 Central European countries are Bulgaria, Croatia, Hungary,
Poland and Romania.

2018d). The effect of supportive fiscal measuresin Romania, which fueled a strong pickup in
growth in 2017, have gradually faded in 2018.
Meanwhile, activity is improving in commodity
importers which experienced weak growth in 2017
due to domestic issues, such as rising politicaltensions (e.g., FYR Macedonia) and weaker public
investment (e.g., Serbia).
Commodity exporters in the region continue toexperience a cyclical upturn, supported by higher
oil prices, a pickup of domestic demand, andstrengthening export growth. In Russia, growth
turned positive in 2017 after two years ofcontraction, reaching 1.5 percent. The improvement was marked by robust real wage gains, which
supported a recovery in private consumption amid
declining inflation and stabilizing labor markets.
Rising confidence encouraged a significant
rebound in investment growth—especially in themining, transport, and manufacturing sectors—
following four years of contraction. The recovery
in Russia generated positive spillovers toneighboring economies in Central Asia, South
Caucasus, and Eastern Europe.3 New U.S.
sanctions announced in April against Russian

3 Eastern Europe countries are Belarus, Moldova, and Ukraine.
South Caucasus countries are Armenia, Azerbaijan and Georgia.
Central Asia countries are Kazakhstan, Kyrgyz Republic, Tajikistan,
Turkmenistan, and Uzbekistan.

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CHAPTER 2.2

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 2.2.1 ECA: Recent developments
Growth in the region strengthened in 2017, but high-frequency indicators
suggest slowing momentum in 2018. Economic sanctions on Russia led tosome increase in bond spreads, as in the previous episode in 2014.
Investment in commodity-importing economies was particularly strong in
2017, but is expected to moderate in 2018. Fiscal policy is loosening andinflation expectations have risen in many commodity importers. Current
account positions have deteriorated in some cases.
A. Contribution to regional growth

B. Bond spread for Russia after
sanction

C. Investment

D. Structural fiscal balance

organizations and individuals led to a depreciationof the Russian ruble and to increasing bondspreads.
In Kazakhstan, activity also rebounded in 2017,supported by expanding oil production andrecovering activity in the non-oil sector (WorldBank 2018e). Growth in Kazakhstan was further
boosted by rising output from the new Kashagan
oil field, which is exempt from the production
cuts agreed to by some OPEC and non-OPEC
countries. In Azerbaijan, curbs on oil production
were offset by stronger non-oil sector activity andfiscal stimulus measures. While slow progress withstructural reforms and lingering geopoliticaluncertainty dampened confidence and growth in
Ukraine in 2017, conditions have started to
improve in 2018.
Inflation, current account, and publicfinances

E. Inflation expectations

F. Current account balances

Sources: Consensus Economics, International Monetary Fund, J. P. Morgan, World Bank.
A. Aggregate growth rates calculated using 2010 U.S. dollar GDP weights.
B. Index value of Emerging Market Bond Index (EMBI) spread for Russia. EMBI spread is a measureof sovereign bond risk premiums. Index values are normalized to 100 (as reflected by the horizontalline) for the official date of the announcement of sanctions from the United States. Official dates are
March 6 for 2014 sanctions and April 6 for 2018 sanctions. Last observation for the 2018 sanction is
May 23, 2018.
C. Total investment growth for each group. Shaded area indicates forecasts.
D. Values are general government structural balance as a percent of potential GDP. Median foreach group.
E. Average one-year-ahead inflation forecasts for given time from Consensus forecasts.
F. Current account balance as a percent of GDP for selected countries.
Click here to download data and charts.

The recovery in some commodity importers has
been associated with persistent or widening
imbalances. Inflation rates are above or close totarget in some countries, and closing output gaps
are contributing to rising domestic inflationpressures (e.g., Romania, Turkey). Inflation
expectations are trending upward in the largest
countries in Central Europe (e.g., Bulgaria,
Croatia, Hungary, Poland, Romania), as well as inTurkey. Current account deficits have either
worsened or remain persistently large amid risingoil prices and robust imports, while fiscal policy
continues to be procyclical in somecommodity importers (e.g., Romania, Turkey).
Among commodity exporters, inflation has
generally moderated, reflecting the unwinding
effects of past exchange rate depreciations or
persistent economic slack (e.g., Azerbaijan,
Kazakhstan, Russia). Current account positions
have improved, supported by a rebound in oil
prices, and the stabilization of inflation haveallowed monetary policy to ease in some countries.
In contrast, Uzbekistan, which devalued its
currency in September 2017, subsequently tightened its monetary policy.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

Outlook
Growth in the region is projected to moderatefrom 4.0 percent in 2017—which was significantly above potential—to 3.2 percent in 2018and 3.0 percent in 2020 (Figure 2.2.2). The
modest recovery continues among commodity
exporters, supported by a further recovery in oil
prices, but only partially offsets a slowdown incommodity importers. Despite the moderation,
growth is expected to remain slightly above
potential over the forecast horizon. The outlook
for the region is predicated on stabilizing oil
prices; more moderate, yet still-robust, growth in
the Euro Area; an orderly tightening of global
financing conditions; and an absence of risinggeopolitical tensions.
Growth for commodity importers is expected tomoderate from 5.9 percent in 2017 to 4.3 percent
in 2018. Monetary and fiscal policies are expected
to tighten as economies operate above capacity.
Tighter labor market conditions and higher oil
prices are expected to lead to rising inflation andtighter monetary policy, while past fiscal stimulus
measures are expected to gradually unwind.
External conditions are expected to become lesssupportive as well. Euro Area imports areprojected to decelerate gradually, leading to moremodest export growth in Central Europe, theWestern Balkans, and Turkey. Global interest
rates are expected to rise, increasing borrowing
costs and affecting net capital inflows to theregion, while rising oil prices could exacerbate
current account vulnerabilities in some countries.
In Turkey, delays in fiscal consolidation and theextension of the credit support program is
expected to temper the expected slowdown in
2018, amid tightening financing conditions andcurrency pressures. Inflation continues to be above
target. In Central Europe, the positive effects
from the accelerated disbursement in 2017 of
EU structural funds—which are equivalent tomore than 4 percent of GDP for some countries—
are expected to wane in 2018. Procyclical fiscal
measures in Romania are projected to continue
in 2018.

E URO PE AND CE NTRAL AS IA

121

FIGURE 2.2.2 ECA: Outlook and risks
Growth is expected to moderate towards potential over the projection
period. Extensive trade openness, large current account deficit andelevated corporate debt levels leave the region vulnerable to external
shocks.
A. Actual and potential growth

B. Growth forecast

C. Output gap

D. Working-age population growth

E. Trade openness

F. Corporate debt

Sources: Bank for International Settlements, International Monetary Fund, Institute of International
Finance (IIF), United Nations, World Bank.
A. Blue bars refer to GDP weighted average actual growth and vertical orange line show minimummaximum range of potential growth estimates based of five different methodologies (production
function approach, multivariate filter, IMF World Economic Outlook five-year-ahead forecast, Consensus Forecasts, and potential growth estimates in OECD Economic Outlook and OECD Long-Term
Baseline Projections).
A.B. Shaded areas indicate forecasts.
B.C. Aggregate growth rates calculated using 2010 U.S. dollar GDP weights.
D.E. Bars indicate 25th and 75th percentiles.
D. Annual population growth for age 15-64 given period. Forecasts are taken from the medium
forecast by the United Nations.
E. Value of trade over GDP in 2016 for each region. 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.
F. The data used are IIF end-of-period estimates of non-financial corporate debt as apercentage of GDP.
Click here to download data and charts.

122

CHAPTER 2.2

Among commodity exporters, the recovery fromweak or negative growth in 2014-16 is expected tocontinue in 2018-20. In Russia, growth isprojected to remain unchanged in 2018 at 1.5
percent as the effects of rising oil prices andmonetary policy easing are offset by oil production
cuts and heightened uncertainty associated withthe latest sanctions. As dampening factors wane,
growth in Russia is anticipated to strengthen to
1.8 percent in 2019-20, providing some support
to activity in Central Asia, the South Caucasus
region, and Eastern Europe (World Bank 2018f).
Assuming an easing of geopolitical tensions andprogress in structural reforms, growth is projected
to pick up in Ukraine. Azerbaijan is projected toemerge from two years of disappointing growth,
mainly in response to fiscal stimulus measures
supported by higher oil prices and expanded
natural gas production. However, in Kazakhstan,
growth is expected to slow in 2018, as the effect of
the opening of the Kashagan oil field fades.
Over the long term, potential growth in the region
is expected to decline further. Slower growth in
the working-age population is expected to weighon potential growth across the region. Delays orreversals to needed structural reforms have affectedlong-term growth prospects in a number ofcountries (e.g., Azerbaijan, Croatia, Russia,
Ukraine). In Uzbekistan, far-reaching structuralreforms—including exchange rate liberalization,
tax reform, privatization of state owned
enterprises, and banking sector reform—are
expected to improve long-term growth prospects.

Risks
The outlook continues to be subject toconsiderable risks. While stronger-than-expected
growth among major trading partners remains apossibility, risks remain tilted to the downside.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

These include a disorderly tightening of financing
conditions, heightened currency pressures, andrenewed geo-political tensions and policy
uncertainty.
A disorderly tightening of global financial
conditions combined with a further appreciationof the U.S. dollar could trigger a sharp
deterioration of external financing conditions andlead to a reversal of capital flows and weakening
activity, particularly in countries with growing
vulnerabilities. Current account deficits remain
substantial in a number of countries (e.g.,
Georgia, Kazakhstan, Kyrgyz Republic, Romania,
Turkey, Ukraine), and are financed by volatile
portfolio investment flows in some cases (WorldBank 2018g, 2018h). Filling external financing
needs could become challenging, while currencypressures could intensify. Despite recent progresses
in reforms, banking sectors remain vulnerable toexternal shocks (e.g., Azerbaijan, Kazakhstan,
Moldova, Tajikistan).
An escalation of policy uncertainty andgeopolitical tensions could also negatively affectactivity in the region. Moreover, intensification ofpolicy disagreements between some EU members
and EU institutions—including in areas such as
immigration policy and constitutional issues—
could deter international investors. The region is
also vulnerable to a rise in global protectionism,given its openness to trade and integration in
global supply chains (World Bank 2018i).
Over the medium term, a weaker-than-expectedenergy price outlook would undermine therecovery in large energy-exporting countries,
including Kazakhstan, Russia, and Uzbekistan.
The slowdown could generate negative spillovers
to neighboring countries, such as Armenia,
Belarus, Georgia, Kyrgyz Republic, Moldova, andTajikistan.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

123

E URO PE AND CE NTRAL AS IA

TABLE 2.2.1 Europe and Central Asia forecast summary
Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)

EMDE ECA, GDP1
EMDE ECA, GDP excl. Russia

2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

1.1

1.7

4.0

3.2

3.1

3.0

0.3

0.1

0.0

3.6

2.9

5.5

4.2

3.9

3.8

0.6

0.1

0.1

(Average including countries with full national accounts and balance of payments data only)2
EMDE ECA, GDP2
GDP per capita (U.S. dollars)
PPP GDP

1.0

1.6

4.0

3.2

3.1

3.0

0.3

0.1

0.1

0.6

1.2

3.6

2.8

2.8

2.7

0.3

0.1

0.0

0.8

1.6

3.9

3.2

3.1

3.0

0.3

0.1

0.1

Private consumption

-2.4

1.1

4.4

3.1

3.2

3.1

-0.2

-0.1

-0.2

Public consumption

0.1

3.1

1.5

1.5

1.4

1.3

0.2

-0.2

-0.3

Fixed investment

0.4

-0.2

6.8

5.2

4.8

4.7

1.5

0.9

0.9

Exports, GNFS3

3.9

3.6

6.5

4.8

4.7

4.7

0.1

0.0

0.1

Imports, GNFS3

-5.5

3.4

9.0

5.5

5.5

5.2

0.0

0.1

0.0

Net exports, contribution to growth

3.0

0.2

-0.4

0.0

0.0

0.0

0.0

0.0

0.0

Commodity exporters4

-2.0

0.3

2.0

2.0

2.3

2.3

-0.1

0.0

0.0

Commodity importers5

4.5

3.0

5.9

4.3

3.8

3.7

0.6

0.1

0.1

Memo items: GDP

Central Europe6

3.7

3.2

4.8

4.2

3.7

3.5

0.2

0.2

0.3

Western Balkans7

2.1

3.1

2.5

3.2

3.4

3.8

-0.1

-0.2

0.0

Eastern Europe8

-7.6

0.8

2.5

3.3

3.6

3.5

0.2

0.1

0.0

South Caucasus9

1.7

-1.6

2.0

2.6

4.0

3.7

0.7

1.5

0.4

Central Asia

3.3

3.3

4.7

4.4

4.2

4.0

0.6

0.1

-0.3

Russia

-2.5

-0.2

1.5

1.5

1.8

1.8

-0.2

0.0

0.0

Turkey

6.1

3.2

7.4

4.5

4.0

4.0

1.0

0.0

0.0

Poland

3.8

2.9

4.6

4.2

3.7

3.5

0.2

0.2

0.4

10

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.

124

CHAPTER 2.2

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

TABLE 2.2.2 Europe and Central Asia country forecasts1
Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)
2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

Albania

2.2

3.4

3.8

3.6

3.5

3.5

0.0

0.0

0.0

Armenia

3.2

0.2

7.5

4.1

4.0

4.0

0.3

0.0

0.0

Azerbaijan

1.1

-3.1

0.1

1.8

3.8

3.2

0.9

2.3

0.6

Belarus

-3.8

-2.5

2.4

2.9

2.7

2.5

0.8

0.3

0.1

Bosnia and Herzegovina

3.1

3.1

3.0

3.2

3.4

4.0

0.0

0.0

0.5

Bulgaria

3.6

3.9

3.6

3.8

3.6

3.6

-0.1

-0.4

-0.3

Croatia

2.3

3.2

2.8

2.6

2.7

2.8

0.0

-0.1

-0.2

Georgia

2.9

2.8

5.0

4.5

4.8

5.0

0.3

0.1

0.0

Hungary

3.1

2.0

4.0

4.1

3.2

3.0

0.3

0.1

0.1

Kazakhstan

1.2

1.1

4.0

3.7

3.3

2.8

1.1

0.5

-0.2

Kosovo

4.1

4.1

4.4

4.8

4.8

4.8

0.0

0.0

0.1

Kyrgyz Republic

3.9

4.3

4.6

4.2

4.8

5.0

0.0

0.0

0.4

Macedonia, FYR

3.9

2.9

0.0

2.3

2.7

3.0

-0.9

-1.2

-1.0

2

Moldova

-0.4

4.5

4.5

3.8

3.7

3.5

0.0

0.1

0.2

Montenegro

3.4

2.9

4.4

2.8

2.5

2.1

0.0

0.0

0.0

Poland

3.8

2.9

4.6

4.2

3.7

3.5

0.2

0.2

0.4

Romania

3.9

4.8

7.0

5.1

4.5

4.1

0.6

0.4

0.6

Russia

-2.5

-0.2

1.5

1.5

1.8

1.8

-0.2

0.0

0.0

Serbia

0.8

2.8

1.9

3.0

3.5

4.0

0.0

0.0

0.0

Tajikistan

6.0

6.9

7.1

6.1

6.0

6.0

1.1

0.5

0.3

Turkey

6.1

3.2

7.4

4.5

4.0

4.0

1.0

0.0

0.0

Turkmenistan

6.5

6.2

6.5

6.3

6.3

6.3

0.0

0.0

0.0

Ukraine

-9.8

2.3

2.5

3.5

4.0

4.0

0.0

0.0

0.0

Uzbekistan

7.9

7.8

5.3

5.0

5.1

5.5

-0.6

-1.2

-1.0

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 significantly 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 at constant prices is based on production approach.
For additional information, please see www.worldbank.org/gep.

Growth in Latin America and the Caribbean is projected accelerate moderately, from 0.8 percent in 2017 to
1.7 percent in 2018 and 2.3 percent in 2019, largely reflecting accelerating growth in commodity exporters. A
cyclical recovery is underway in Brazil, and conditions are improving in Chile, Colombia, Mexico, and Peru.
Downside risks to the growth outlook are significant, however. External risks include an abrupt tightening offinancing conditions and an escalation of trade protectionism. Domestic risks, including policy uncertainty anddisruptions from natural disasters, also stand to inhibit growth.

Recent developments
Growth in Latin America and the Caribbean has
been accelerating, driven by generally favorable
domestic and external financing conditions,strengthening growth in the United States, andhigher prices of key commodities relative to a year
ago. Except in Brazil and, to a lesser degree,
Colombia, negative output gaps are nearly closed.1
Private consumption was the main contributor toregional growth of 0.8 percent in 2017, and isestimated to have strengthened further in early2018 amid supportive confidence and the effect ofprevious interest rate cuts. Regional investment
has been recovering after a deep, prolonged
contraction, supported by a strong recovery incommodity prices last year (Figure 2.3.1).
Robust global demand has boosted exports andhelped narrow current account deficits as a shareof GDP in some countries (e.g., Brazil, Mexico).
At the regional level, however, import growth isoutpacing export growth, owing to the recovery ofdomestic demand in commodity exporters, and as
a result net exports still contribute slightly
negatively to regional growth.
Note: This section was prepared by Dana Vorisek. Brent Harrison
provided research assistance.
1 Output gaps are calculated, using a multivariate filter, for seven
LAC economies: Argentina, Bolivia, Brazil, Chile, Colombia,
Mexico, and Peru.

In Brazil, Argentina, and Chile—three of thelargest commodity-exporting economies—industrial production growth was considerably higher inthe first quarter of 2018 than a year before, andretail sales growth was higher in Brazil and Chile,
supporting activity. However, a drought isdisrupting agricultural production in Argentina,
and the recent market volatility may haveinhibited activity in the second quarter. In
República Bolivariana de Venezuela, an economic
and humanitarian crisis continues, and anincreasing number of Venezuelans are migrating
to neighboring countries.
In Mexico, the largest commodity-importing
economy in the region, high-frequency indicators
have been mixed. Trade is becoming more
supportive of growth, and the contraction in
investment in 2017 is fading, but sluggish retailsales point to slightly moderating private
consumption growth.
In the Caribbean, strong external demand isbenefiting most services-exporting economies (e.g.,
the Dominican Republic, Jamaica, St. Lucia,
Grenada). Despite the hurricanes in the autumn of
2017, tourist arrivals to the Caribbean reached an
all-time high last year.
Inflation is decelerating in most LAC economies,
with the key exceptions of Argentina and theextreme case of Venezuela. Median inflation incommodity exporters is well below its historical

126

CHAPTER 2.3

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 2.3.1 LAC: Recent developments
Growth in LAC is accelerating, driven in large part by a cyclical recovery inBrazil and improving conditions in other large commodity-exporting
economies. Investment is picking up after an extended period ofcontraction, while private consumption is strengthening amid supportive
confidence and the effect of previous interest rate cuts, despite an uptick inunemployment. Net exports in the region are still contributing negatively to
growth, in part due to rapid import growth as domestic demand rises.

A. GDP growth

C. Confidence

E. Inflation

B. Investment growth

D. Unemployment rate

F. Export and import volume growth

average. Policy interest rates in almost allcommodity exporters have been cut during thefirst half of 2018. Brazil, Colombia, and Peru havecut rates repeatedly. Recent monetary policy
statements, however, suggest that the easing cycle
may be coming to an end. Among commodity
importers, inflation has eased somewhat since
early 2018 (e.g., in Mexico, El Salvador, Jamaica),
after accelerating rapidly in 2017 on fuel and foodprice increases.
Although external financing conditions remain
supportive, sovereign bond yields have risenmodestly in the large economies in the region
since the start of 2018, consistent with the trend
across emerging markets. Yields have risen by alarger amount in Argentina, where the central
bank hiked interest rates sharply in April and May
in response to currency pressures.
Fiscal deficits in the region have narrowed slightly
relative to levels seen during the commodity priceplunge, yet are still high. There is significant needfor fiscal consolidation, especially in light of highdebt levels in many countries (Végh et al. 2018).
Brazil’s government debt, for instance, recently
reached record levels, and critical pension reform
legislation has been delayed until after the newadministration takes office in early 2019.
Government debt is also high in El Salvador,
Uruguay, Venezuela, and most Caribbean
countries. In Grenada and Jamaica, however, fiscal
rules have provided the discipline needed to begin
reducing debt.

Outlook
Sources: CPB Netherlands Bureau for Economic Policy Analysis, Haver Analytics, International
Labor Organization, Oxford Economics, World Bank.
A. 2010 GDP-weighted averages. Sample includes 13 commodity exporters and three commodity
importers. Last observation is 2017Q4.
B. Investment is gross fixed capital formation. Aggregate investment rates calculated using constant2010 investment-weighted averages. Last observation is 2017Q4.
C. Last observation is May 2018 for Brazil and April 2018 for Mexico.
D. Regional average weighted by size of labor force in 2014. Sample includes Argentina, Belize,
Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Peru, and Uruguay. Lastobservation is 2018Q1.
E. Lines show medians of 14 commodity exporters and eight commodity importers, and horizontal
lines the averages from January 2000 to present. Last observation is April 2018.
F. Sample includes 13 economies. Last observation is March 2018.
Click here to download data and charts.

Regional growth is projected to accelerate during
the forecast horizon, to 1.7 percent in 2018 and to
2.5 percent by 2020, still below the long-term(1990–2017) average of 2.7 percent. This outlook
is lower than that produced in January, mostly due
to large downward revisions to projections for
Venezuela, but also to downgrades for Argentina(Tables 2.3.1 and 2.3.2). Regional growth through2020 will come almost exclusively from private
consumption and investment (Figure 2.3.2).
Accelerating private consumption growth in theregion reflects the effect of previous interest ratecuts and supportive consumer confidence in someG LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

LATIN AMERICA AND CARIBBEAN

127

large economies. Investment growth in LAC is
expected to reach 3.7 percent in 2018, and to firm
to 4.6 percent in 2020. The investment recovery
will be supported by a broad-based cyclicalrecovery in Brazil, rising copper prices and fading
disruptions in the mining industry (e.g., Chile,Peru), large infrastructure projects (e.g.,
Argentina, Colombia, Panama, Peru), and stable
capital inflows.

FIGURE 2.3.2 LAC: Outlook and risks

In most large commodity exporters, including
Brazil, Chile, Colombia, and Peru, growth isprojected to accelerate in 2018 and 2019. In these
economies, the recovery is expected to reflectupward momentum in private consumption,
continued acceleration in investment growth, and,in all except Colombia, a modest contribution
from net exports. In Argentina, on the other
hand, growth is expected to slow in 2018 asmonetary and fiscal tightening, together with theeffects of the drought on the agricultural sector,
counter strong momentum at the start of the year.
In Ecuador, growth is expected to moderate
during the forecast horizon in the context ofgradual fiscal consolidation. For oil exporters
across the region, the upward revision to oil prices
will provide a boost to growth.

A. Regional growth

B. Capital inflows to LAC

C. Per capita GDP growth andpotential growth

D. Economic policy uncertainty

E. Primary balance adjustment
needed to stabilize government debt

F. Export losses in case of tariff hikes
to WTO bound rates

Growth in commodity importers, which are
geographically concentrated in the Mexico andCentral America and the Caribbean subregions, isalso expected to strengthen in 2018, in part due torising demand for exports as growth picks up in
the United States. In Mexico, a reversion topositive investment growth is also projected tosupport growth through the forecast horizon,
while private consumption growth is expected tostall at a lower rate than in recent years. The
outlook for Central America is mixed, withgrowth in some agricultural exporters (e.g., Costa
Rica, Guatemala) expected to acceleratemoderately through 2020 and that in commodity
importers (El Salvador, Panama) expected tostabilize or decelerate.
In the Caribbean, post-hurricane reconstruction,robust tourism, and supportive commodity
prices are expected to lift growth in 2018.
Some commodity-reliant economies (Suriname,
Trinidad and Tobago) are expected to register
their highest growth rates since before the 2014–

Growth in Latin America and the Caribbean is projected to continue toaccelerate during the forecast horizon, driven almost exclusively bydomestic demand—in particular, private consumption and investment.
Although per capita GDP growth is projected to rise after a long period ofcontraction, it will only marginally exceed that in advanced economies by
2020, resulting in stalled convergence. Significant downside risks to thegrowth outlook remain, including an abrupt tightening of external financing
conditions, increased trade protectionism, policy uncertainty, and theeffects of natural disasters.

Sources: Baker, Bloom, and Davis (2016); Haver Analytics; Institute of International Finance;
Kutlina-Dimitrova and Lakatos (2017); Végh et al. (2018); World Bank.
A. Bars show contribution of each of the components of GDP to regional growth.
A.C. GDP-weighted averages.
B. Sample includes Argentina, Brazil, Chile, Colombia, Mexico, and Venezuela. Estimatesas of May 2018.
C. Bars show annual per capita growth and lines average potential growth during 2016–20.
D. For Brazil, the index is normalized to equal 100 at its 1991–2011 median. For Mexico, the index isnormalized to equal 100 at its 1996–2016 median. Horizontal lines show medians during these
periods. Last observation is April 2018.
E. Calculated using methodology described in Végh et al. (2018). Venezuela, not shown in the figure,is estimated to need a primary balance adjustment of 26 percentage points of GDP to stabilize debt.
F. Based on simulations using the GDyn computable general equilibrium model. Results show
cumulative decline by 2020, relative to a business-as-usual scenario, assuming that tariff hikes startin 2018. The scenario is defined as a worldwide increase in tariffs up to legally allowed bound rates
coupled with an increase in the cost of traded services of 3 percent. World Trade Organization (WTO)
bound tariffs are the maximum tariffs under WTO commitments.
Click here to download data and charts.

128

CHAPTER 2.3

16 oil and metals price drop. Rapid developmentof an offshore oil industry is expected to boost
Guyana’s growth sharply in 2020.
Despite the cyclical recovery underway in theregion, potential growth is expected to moderate
in the medium term, averaging 2.3 percent in
2018–22, compared to an estimated 2.7 percent
in 2013–17 (World Bank 2018c). This projection
reflects slower labor force growth and capital
accumulation, as well as continued weakness intotal factor productivity, and raises doubts about
the region’s ability to deliver sustained progress on
per capita income convergence with advanced
economies. Per capita GDP growth in the region
is projected to exceed that in advanced economies
only in 2020, following a long stretch ofcontraction, but remain well below the EMDE
average. This outlook reinforces the need forreforms to counter less favorable demographics,
boost investment growth after the extended
period of weakness, and raise persistently low
productivity (World Bank 2018c).

Risks
Risks to the regional growth outlook continue tobe predominantly downside, through external anddomestic channels. However, the possibility offavorable spillovers as the United States
implements fiscal stimulus cannot be ruled out.
Externally, an abrupt tightening of financing
conditions or changes in investor sentiment
regarding EMDEs as advanced economies
unwind monetary policy accommodation, such asthat experienced by Argentina recently, could set
back capital inflows and growth in the region.
This is a particular risk for countries with large
current account deficits (e.g., Argentina, Bolivia,
Nicaragua, Panama) or significant fiscal adjustment needs (e.g., Argentina, Brazil), and for thosewhere credit quality has deteriorated. A marked
tightening of the external financing environment
or a softening of global commodity prices could
also contribute to a growth slowdown, which may
not be sufficiently addressed with countercyclicalfiscal policy given the lack of fiscal space (Végh et
al. 2018).

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

Downside risks also emanate from international
trade channels. Adverse outcomes of the NAFTA
renegotiations could hold back growth in Mexico.
Additional trade-restricting actions by China andthe United States could have negative effects on
the region through trade, confidence, financial,and commodity market channels, and may
encourage policy support for increased protectionism (Huidrom, Kose, and Ohnsorge 2017;
Kose et al. 2017). Protectionism in the form of
increases in actual tariffs to bound tariffs would
reduce exports from LAC significantly (KutlinaDimitrova and Lakatos 2017). However, for somespecific agricultural products, such as soybeans,
and maize, tariff increases by China on U.S.
exports could raise demand for LAC exports.
Furthermore, the region has recently become
more active in pursuing new trade agreements,
most prominently between Mercosur and theEuropean Union.
On the domestic front, a key downside risk is anescalation of policy uncertainty. The mediumterm policy environment in the two largest
economies in the region, Brazil and Mexico, could
shift following presidential and legislativeelections in the second half of the year. Significant
delays in key reforms could lead to suddenchanges in investor sentiment and derail a stillfragile investment recovery.
Recent years have also demonstrated thevulnerability of the region to floods, droughts,
hurricanes, earthquakes, and wildfires, which
threaten to become more common in the medium
to long term as climate conditions change (Bello2017).
An upside risk to the regional outlook is thepossibility of stronger-than-expected favorable
spillovers from the United States as it implements
fiscal stimulus. This would tend to benefit Mexico
and Central America the most. However, any
boost would likely be short-lived given that U.S.
fiscal stimulus is slated to fade later in the forecasthorizon, and that the stimulus will occur in thecontext of expected monetary policy tightening.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

129

LATIN AMERICA AND CARIBBEANTABLE 2.3.1 Latin America and Caribbean forecast summary
Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)

EMDE LAC, GDP1

2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

-0.4

-1.5

0.8

1.7

2.3

2.5

-0.3

-0.3

-0.2

(Average including countries with full national accounts and balance of payments data only)2
-0.4

-1.5

0.8

1.7

2.3

2.5

-0.3

-0.3

-0.2

GDP per capita (U.S. dollars)

-1.5

-2.6

-0.3

0.7

1.3

1.5

-0.3

-0.3

-0.2

PPP GDP

0.2

-0.9

1.1

1.9

2.4

2.6

-0.3

-0.3

-0.2

-0.3

-1.7

1.4

2.1

2.5

2.7

0.0

-0.2

-0.2

EMDE LAC, GDP2

Private consumption
Public consumption

0.9

0.0

-0.4

-0.2

0.2

0.7

-0.2

-0.7

0.0

Fixed investment

-5.5

-6.0

-0.9

3.7

4.0

4.6

1.1

0.4

0.9

Exports, GNFS3

4.3

1.3

2.0

3.2

3.7

3.9

-0.7

-0.3

0.1

Imports, GNFS

-2.0

-2.9

4.8

4.3

4.1

4.6

0.8

-0.1

0.6

1.3

0.9

-0.6

-0.2

-0.1

-0.2

-0.3

-0.1

-0.2

-1.8

-3.2

0.2

1.3

2.1

2.3

-0.6

-0.4

-0.4

Mexico and Central America

3.4

3.1

2.2

2.5

2.7

2.8

0.1

-0.1

0.1

Caribbean6

3.7

2.6

2.4

3.5

3.5

3.8

0.0

0.0

0.4

Brazil

-3.5

-3.5

1.0

2.4

2.5

2.4

0.4

0.2

-0.1

3

Net exports, contribution to growthMemo items: GDP
South America4
5

Mexico

3.3

2.9

2.0

2.3

2.5

2.7

0.2

-0.1

0.1

Argentina

2.7

-1.8

2.9

1.7

1.8

2.8

-1.3

-1.2

-0.4

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.
For additional information, please see www.worldbank.org/gep.

130

CHAPTER 2.3

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

TABLE 2.3.2 Latin America Caribbean country forecasts1
Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)

Argentina

2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

2.7

-1.8

2.9

1.7

1.8

2.8

-1.3

-1.2

-0.4

Belize

3.8

-0.5

1.2

2.0

1.9

1.7

-0.2

0.2

0.0

Bolivia

4.9

4.3

4.2

3.9

3.6

3.4

0.1

0.2

0.1

Brazil

-3.5

-3.5

1.0

2.4

2.5

2.4

0.4

0.2

-0.1

Chile

2.3

1.3

1.5

3.3

3.4

3.5

0.9

0.7

0.7

Colombia

3.0

2.0

1.8

2.7

3.3

3.6

-0.2

-0.1

0.2

Costa Rica

3.6

4.2

3.2

3.4

3.6

3.6

-0.2

0.1

0.1

Dominican Republic

7.0

6.6

4.6

5.0

4.7

4.6

0.1

0.0

-0.1

Ecuador

0.1

-1.6

3.0

2.2

1.5

0.9

1.4

0.6

-0.1
0.3

El Salvador

2.4

2.6

2.3

2.3

2.2

2.2

0.5

0.4

Grenada

6.4

3.7

4.5

3.3

2.8

2.8

1.1

0.7

0.7

Guatemala

4.1

3.1

2.8

3.1

3.3

3.3

-0.3

-0.2

-0.2

2

Guyana

3.1

3.4

2.1

3.8

3.8

29.0

0.0

0.1

25.3

Haiti3

1.2

1.5

1.2

1.8

2.4

2.4

-0.4

-0.1

-0.1

Honduras

3.8

3.8

4.8

3.5

3.6

3.8

-0.1

0.1

0.3

Jamaica

0.9

1.4

0.5

1.7

1.9

2.0

-0.1

-0.1

0.0

Mexico

3.3

2.9

2.0

2.3

2.5

2.7

0.2

-0.1

0.1

Nicaragua

4.8

4.7

4.9

4.7

4.5

4.4

0.3

0.1

0.0

Panama

5.6

5.0

5.4

5.6

5.6

5.6

0.0

0.0

-0.1

Paraguay

3.0

4.0

4.3

4.3

4.2

4.2

0.3

0.2

0.2

Peru

3.3

4.0

2.5

3.5

3.8

3.8

-0.3

0.0

-0.2

St. Lucia

2.0

0.9

2.1

2.8

2.3

2.3

0.6

0.5

0.5
-0.1

St. Vincent and the Grenadines

1.4

1.9

1.0

2.1

2.5

2.7

-0.6

-0.3

Suriname

-2.6

-5.1

0.1

1.1

1.7

2.1

-1.1

0.5

0.9

Trinidad and Tobago

1.5

-6.0

-2.3

1.6

1.9

1.2

-0.3

-0.3

-0.4

Uruguay

0.4

1.7

2.7

3.3

3.1

2.9

0.5

-0.1

-0.3

Venezuela

-6.0

-16.5

-14.5

-14.3

-7.0

-4.0

-10.1

-7.6

-4.9

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 significantly differ at any given moment in time.
1. GDP at market prices and expenditure components are measured in constant 2010 U.S. dollars.
2. A recent rebasing of El Salvador's GDP, from 1990 to 2014, has resulted in significant changes to historical growth rates compared to January 2018.
3. GDP is based on fiscal year, which runs from October to September of next year.
For additional information, please see www.worldbank.org/gep.

Growth in the Middle East and North Africa (MENA) region is projected to pick up to 3 percent in 2018 from
1.6 percent in 2017 as oil exporters ease fiscal adjustments amid firming oil prices. The region is also expected
to benefit from a favorable global environment, post-conflict reconstruction efforts, and from oil importers’reforms to boost domestic demand and increase foreign investment. The outlook for growth in MENA is
expected to improve slightly in both 2019 and 2020. Positive surprises in trading partner activity orreconstruction efforts could further raise growth prospects. Geopolitical tensions or possible renewed volatility in
oil prices could cloud the outlook.

Recent developments
Growth in the Middle East and North Africa(MENA) region improved in early 2018. Oil
exporters were recovering following a year of
declining oil production and fiscal tightening(Figure 2.4.1).1 Oil importers’ growth was robustin 2017, and high-frequency data indicate that
this momentum is continuing into 2018. Many
countries in the MENA region are pursuingbroad-based reforms that should eventually
improve productivity, but growth continues to bechallenged by geopolitical tensions and fiscal
adjustment.
Low oil production led to slow growth for oil
exporters in 2017, as members and non-membersof the Organization of the Petroleum ExportingCountries (OPEC) adhered to agreement on
production limits intended to support global oil
prices. Generally subdued oil revenues since 2014
Note: This section is prepared by Lei Sandy Ye. Research
assistance is provided by Julia Roseman.
1 The World Bank’s Middle East and North Africa aggregate
includes 16 economies. Bahrain, Kuwait, Oman, Qatar, Saudi
Arabia, and the United Arab Emirates comprise the Gulf
Cooperation Council (GCC); all are oil exporters. Other oil exporters
in the region are Algeria, Iran, and Iraq. Oil importers in the region
are Djibouti, Egypt, Jordan, Lebanon, Morocco, Tunisia, and WestBank and Gaza. The Syrian Arab Republic, Yemen, and Libya are
excluded from regional growth aggregates due to data limitations.

have been associated with tightening fiscal policies
and diversification of revenues, such as theintroduction of value-added taxes (VAT) in Saudi
Arabia and the United Arab Emirates in 2018.
Non-oil sectors showed modest growth, including
in services and manufacturing. In 2018, a numberof oil exporters have eased fiscal adjustment plans,in response to somewhat more buoyant oil prices
and improved terms of trade, including by
expanding capital expenditure plans in Algeria andSaudi Arabia.
Growth in large oil importers has been supported
by broad-based improvements in domestic andexternal demand, reflecting progress in policy
reforms, higher business confidence, and an
improved global economy. In the Arab Republicof Egypt, the region’s largest oil importer,
investment and net exports have improved,
supported by the stability of the exchange rate andstronger domestic demand. Morocco and Tunisia
have also further benefited from more favorable
agricultural production. International reserves
have grown in Egypt and Morocco, aided bycapital inflows, although they have declined in
Tunisia due to a rising current account deficit andcentral bank interventions in the foreign exchange
market. Other smaller oil importers still facesluggish growth that hinders progress on theirlabor market challenges.

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CHAPTER 2.4

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 2.4.1 MENA: Recent developments
The MENA region is improving from a year of weak growth in 2017,associated with oil production reductions as well as fiscal adjustments in
response to subdued oil prices. As oil prices have firmed, terms of trade
have improved in large GCC oil exporters in the past year. Among the oil
importers, industrial production has markedly improved, boosted byenhanced competitiveness and external conditions. Inflation in the region
has been generally contained.

A. Growth

B. Fiscal break-even prices: Oil
exporters

C. Real effective exchange rate: GCC

D. Industrial production growth: Oil
importers

E. International reserves: Oil importers

F. Inflation

Inflation is well-contained across most of the
MENA region. It is averaging less than 3 percent
in the Gulf Cooperation Council (GCC) in2018, despite edging upwards recently due to
VAT introduction in its two largest economies.
In Egypt, inflation has subsided substantially in
2018, falling to 13 percent in April from a peakof more than 30 percent in July 2017, allowing
the central bank to implement two interest ratecuts this year to support activity (Central Bankof Egypt 2018). In Tunisia, inflation has risenmarkedly as the dinar has depreciated, leading thecentral bank to hike rates in March, although rates
remain negative in real terms. In the Islamic
Republic of Iran, inflation edged downwards
to about 8 percent in April from 10 percent at
the end of last year, as declining food prices
have offset upward pressure from currency depreciation.
Financing conditions in the MENA region arestable, while the financial sector is deepening
throughout the region. Partly to finance fiscal
deficits, international sovereign bond issuance rose
further in 2018, both in the GCC and amongmajor oil importers. The inclusion of Saudi Arabia
in the FTSE Emerging Markets Index (effective
next year) is expected to attract foreign equity
investors. Deeper and more liquid financial sectors
have also supported FDI inflows, even in the faceof elevated geopolitical uncertainty.

Outlook

Sources: Bank for International Settlements, International Monetary Fund, Haver Analytics, WorldBank.
A. Aggregate growth rates calculated using constant 2010 US dollar GDP weights.
B. Non-GCC includes Algeria, Iraq, and Iran. GCC includes Bahrain, Kuwait, Qatar, Oman, Saudi
Arabia, and the United Arab Emirates. Unweighted averages.
C. CPI-based broad indices for Saudi Arabia and the United Arab Emirates. PPI-based index for
Kuwait. Last observation is April 2018.
D. Industrial production indexes of Egypt, Jordan, Tunisia, and West Bank and Gaza. Unweighted
averages. Figure shows average of year-on-year 3-month moving average growth rates.
E. International reserves. Last observation is April 2018.
F. Unweighted averages. Last observation is April 2018.
Click here to download data and charts.

GDP growth in the region is projected tostrengthen to 3.0 percent in 2018, and rise slightly
higher in 2019-2020, with oil exporters continuing their recovery from the collapse of oil
prices, and oil importers experiencing a smaller
acceleration. The outlook assumes continued
policy reforms and oil prices remaining above their2017 average.
In 2018, growth in oil exporters is expected to rise
substantially to 2.7 percent due to additional
government spending, enabled by increased
domestic revenues and firm oil prices. In the
GCC, 2018 growth will be further supported by

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018higher fixed investment, bolstered by public
investment programs and improved demand.
Growth will remain stable during 2019-20,
propelled by steady growth in private consumption, infrastructure investment programs likethose related to the Dubai Expo 2020 or Qatar’s
World Cup 2022, and the expiration of OPEC+
agreement. Growth in non-GCC exporters is
expected to be supported by higher capital
expenditures. Fiscal balances in oil exporters are
expected to improve as oil prices are forecast to
stay firm and revenue-enhancing measures, such as
VAT and energy subsidy reforms, are implemented. These measures are expected to improve
the non-oil share of government revenue in oil
exporters. Higher oil prices are also expected tosupport remittance inflows (World Bank 2018j).
Growth in oil importers is expected to rise to 4.0
percent in 2018, as business and consumer
confidence are spurred by business climate reforms
and improving external demand. Policies to relax
foreign investment restrictions have supported
higher capital flows, and are expected to boost
foreign investment and trade flows, in partthrough relaxing financial constraints in firms(Kiendrebeogo and Minea 2017; Wood and Yang2016). Tourism growth is also expected to
improve upon stable security conditions.
However, fiscal consolidation is expected to be an
important headwind for activity among oil
importers. In smaller oil importers (e.g., Jordan,
Lebanon), external and fiscal imbalances remain aconstraint to higher growth in the short-term.
Reform programs, such as World Bank-supported
initiatives to improve urban investment capacity
or electricity performance, are expected to improve
growth potential (World Bank 2017e, 2018k).
Similarly, public-private partnerships and bilateralagreements within the region are expected tosupportprivatesectorparticipationininfrastructure
investment,whichbenefits
economic activity (Figure 2.4.2, Arezki et al.
2018; Calderon and Serven 2004). Additional
plans in energy subsidy reforms or tax revenue
enhancement across oil importers will support
further fiscal adjustment.

MID D LE E AS T AN D NO RTH AFRIC A

133

FIGURE 2.4.2 MENA: Outlook and risks
The short-term outlook in MENA is positive. Public-private partnerships are
expected to support private sector participation in infrastructure
investment. However, geopolitical tensions may deter the recovery of
tourism in oil importers. Upside risks are associated with the possibility ofhigher-than-expected activity in key trading partners.
A. Public-private partnershipinvestment: MENA

B. Tourism: Oil importers

C. Exports exposure to the Euro Area

D. Euro Area activity expectations:2018

Sources: Consensus Economics, Haver Analytics, International Monetary Fund, World Bank.
A. Denotes public-private partnership physical investment in infrastructure projects. Sum ofinvestments from 2015-16 based on available data.
B. Figure shows 6-month moving averages of growth of tourism arrivals for Egypt, Jordan, andMorocco. Last observation is April 2018.
C. Denotes share of exports to the Euro Area as a ratio to total exports in each country group. Data
are for goods exports value as of 2017.
D. Dates in legend denote month and year in which Consensus forecast is generated. Columns
denote growth rates in respective indicators.
Click here to download data and charts.

Risks
Risks to the outlook are diverse, but tilt to thedownside. Key downside risks include renewedvolatility in oil prices, an intensification ofgeopolitical tensions, and a slower-than-expected
pace of reforms. Nonetheless, favorable spillovers
from stronger than expected activity in key trading
partners and recovery in war-torn areas cannot be
ruled out.
On the downside, the recent rise in oil prices may
not be sustained in the short term, potentially due
to higher-than-expected U.S. shale production

134

CHAPTER 2.4(Chapter 1). This would reduce fiscal space in oil
exporters and complicate fiscal management
reform across many economies. Tighter fiscal
policy in oil exporters may lead to spillovers to
oil importers via external linkages (e.g., FDI
and remittances). Volatility in oil prices may also
affect oil importers through their current accountexposure to higher oil prices.
The amplification of security concerns or
escalation of geopolitical tensions may cloud oil
importers’ tourism prospects, which have strengthened considerably in the past year. Intra- andinterregional tensions in the region may also affectinvestor confidence and access to finance, such as
through higher sovereign spreads.
Continued progress in reforms could facechallenges to implementation. Among oil
importers, potential social discontent about higher
energy prices may lead to delayed implementationof fiscal adjustments. This issue may be further
compounded by the high debt levels (in somecases exceeding 100 percent of GDP) among
several economies in the region. The loss of
momentum in these reforms could negatively
impact longer-term growth in the region.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

On the upside, positive growth surprises in key
advanced and emerging economy trading partners
would provide an important support to growth in
MENA. Oil-importing economies in the Maghreb
region are dependent on the Euro Area for trade,
remittances, or financial flows. Stronger-thanexpected external demand could mitigate
headwinds to growth associated with domestic
policy uncertainty in smaller oil importers, orfrom potential spillovers associated with reduced
FDI and remittance flows from GCC economies
to oil importers.
Stronger-than-expected impacts from reconstruction programs and rising infrastructure investment
in war-torn countries, such as Iraq, could lead to asustained economic recovery. Associated spillover
effects could unlock the potential for higher
growth among other countries in the region. This
would also allow the restoration of access tohealth, water, or food (Devarajan and Mottaghi
2017a; World Bank 2018l) to these economies,
and improve the conditions of neighboring hosteconomies (e.g., Djibouti, Jordan, Lebanon) by
providing more resources for public services forboth host residents and refugees (Devarajan andMottaghi 2017b).

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018135

MID D LE E AS T AN D NO RTH AFRIC ATABLE 2.4.1 Middle East and North Africa forecast summary
Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)

EMDE MENA, GDP

1

2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

2.8

5.0

1.6

3.0

3.3

3.2

0.0

0.1

0.0

0.0

0.0

(Average including economies with full national accounts and balance of payments data only)2
EMDE MENA, GDP2

2.6

4.8

1.8

3.0

3.3

3.3

0.1

GDP per capita (U.S. dollars)

0.7

2.9

0.1

1.4

1.8

1.9

0.1

0.0

0.0

PPP GDP

2.6

5.1

2.1

3.2

3.4

3.5

0.1

-0.1

0.0

Private consumption

-0.4

1.5

3.2

3.4

3.5

3.5

0.4

0.2

0.2

Public consumption

1.4

-5.1

1.0

1.3

1.4

1.6

-0.3

-0.5

-0.2

Fixed investment

1.6

-2.1

0.8

5.1

3.6

4.8

0.0

-2.5

-1.2

Exports, GNFS

3

2.5

10.0

3.4

3.7

4.1

4.0

0.0

0.5

0.3

3

-2.1

-1.2

4.1

3.7

3.1

3.4

0.4

-0.2

0.1

2.0

5.1

0.2

0.5

0.9

0.8

-0.1

0.4

0.2

Oil exporters4

2.7

5.5

1.2

2.7

3.1

2.9

-0.1

0.1

0.0

GCC countries5

3.6

2.5

0.2

2.1

2.7

2.7

0.1

0.0

0.0

Saudi Arabia

4.1

1.7

-0.7

1.8

2.1

2.3

0.6

0.0

0.1

Iran

-1.3

13.4

4.3

4.1

4.1

4.2

0.1

-0.2

-0.1

Imports, GNFS

Net exports, contribution to growthMemo items: GDP

3.6

3.0

3.8

4.0

4.4

4.6

0.1

0.1

0.1

Egypt

4.3

4.2

4.6

5.3

5.7

5.8

0.4

0.1

0.0

Fiscal year basis7

4.4

4.3

4.2

5.0

5.5

5.8

0.5

0.2

0.0

Oil importers

6

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 Libya, Syria, and 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, Iran, Iraq, 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.

136

CHAPTER 2.4

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

TABLE 2.4.2 Middle East and North Africa economy forecasts1
Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)

Algeria

2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

3.7

3.3

1.6

3.5

2.0

1.3

-0.1

-0.5

-0.3

Bahrain

2.9

3.2

3.9

1.7

2.1

2.1

-0.3

0.5

0.4

Djibouti

6.5

6.5

7.0

6.5

6.4

6.3

-0.5

-0.6

-0.7

4.3

4.2

4.6

5.3

5.7

5.8

0.4

0.1

0.0

Egypt

4.4

4.3

4.2

5.0

5.5

5.8

0.5

0.2

0.0

Iran

-1.3

13.4

4.3

4.1

4.1

4.2

0.1

-0.2

-0.1

Iraq

4.8

11.0

-0.8

2.5

4.1

1.9

-2.2

2.4

0.0

Fiscal year basis

2

Jordan

2.4

2.0

2.1

2.2

2.4

2.4

0.0

0.0

-0.1

Kuwait

0.6

3.5

-2.9

1.9

3.5

3.0

0.0

0.0

-0.5

Lebanon

0.8

2.0

2.0

2.0

2.0

2.0

-0.2

0.0

0.0

Morocco

4.5

1.2

4.0

3.0

3.5

3.7

-0.1

0.3

0.5

Oman

4.7

5.4

0.7

2.3

2.5

2.9

0.0

0.0

0.4

Qatar

3.6

2.2

1.6

2.8

3.2

2.8

0.2

0.2

-0.2

Saudi Arabia

4.1

1.7

-0.7

1.8

2.1

2.3

0.6

0.0

0.1

Tunisia

1.0

1.2

1.9

2.4

2.9

3.4

-0.3

-0.4

-0.6

United Arab Emirates

3.8

3.0

2.0

2.5

3.2

3.3

-0.6

-0.1

0.0

West Bank and Gaza

3.4

4.7

3.1

2.5

2.3

2.3

-0.5

-0.6

-0.6

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 economies’ prospects do not significantly 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, Syria, and Yemen due to data limitations.
2. The fiscal year runs from July 1 to June 30 in Egypt; e.g., the column labeled 2017 reflects the fiscal year ended June 30, 2017.

Growth in South Asia is projected to accelerate to 6.9 percent in 2018 from 6.6 in 2017, mainly reflecting
fading disruptions to economic activity in India. Growth in the rest of the region is expected to stabilize at 5.6
percent in 2018. Over the forecast horizon, growth is projected to reach 7.1 percent on average in 2019-20,
reflecting broad-based strengthening across the region. Despite the possibility of upside surprises to global
activity, risks to the outlook are still tilted to the downside. Downside risks relate to both domestic factors,
especially policy slippages amid sizable fiscal adjustment needs, and external factors, including the possibility ofa faster-than-expected tightening of global financial conditions and increased global trade tensions.

Recent developments
Growth in South Asia slowed but remained strong
at an estimated 6.6 percent in 2017 (Figure
2.5.1). Growth in the region has improved
markedly since mid-2017 and continued to firmin early 2018, reflecting improved consumer andinvestor sentiment, higher investment, andfirming exports (e.g., Bangladesh, India, Sri
Lanka). Growth in South Asia continues to rely
on domestic demand, with firming but modest
support from export growth (e.g., Bangladesh,
India). Import growth is accelerating amid
strengthening domestic demand, while higher
energy prices are also contributing to a further
deterioration of trade and current accountbalances (e.g., India, Nepal, Pakistan).
Domestic and external financial market
conditions have been generally supportive, but
sovereign bond spreads have increased in 2018
amid rising inflation expectations and monetary
policy normalization in advanced economies.
Monetary policy in the region has remained
broadly accommodative and supported fast credit
growth (e.g., Bangladesh, Pakistan); however, theNote: This section was prepared by Temel Taskin with
contributions from Ekaterine Vashakmadze. Brent Harrison
provided research assistance.

State Bank of Pakistan recently hiked its policy
rate to reduce growing external pressures.
Inflation has been increasing in the region
recently, and is close to or above targets in somecountries (e.g., India, Sri Lanka). In many
countries, budget deficits continue to be sizable orhave widened further in 2018 reflecting both
weaker-than-expected revenues and expansionary
policies (e.g., Bangladesh, Nepal) with fiscal
policies being generally pro-cyclical in the region.
India’s GDP growth bottomed out in the middleof 2017 after slowing for five consecutive quarters,
and has since improved significantly, with
momentum carrying over into 2018 on the backof a recovery in investment. Although investment
growth was still moderately lower in 2017 than in
2016, high-frequency indicators suggest that it
accelerated into 2018. The temporary disruptions
caused by the implementation of the Goods andServices Tax dissipated by mid-2017, andmanufacturing output and industrial production
have continued to firm since then (World Bank
2018m).1
Growth in the region excluding India has been
mixed in the first half of 2018. In Bangladesh,

1 World Bank (2018m) presents a comprehensive section on the
structure of Goods and Services Tax.

138

CHAPTER 2.5

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 2.5.1 SAR: Recent developments
Growth in South Asia moderated in 2017 to an estimated 6.6 percent.
Economic activity in 2018 continues to rely mainly on domestic demand,with improved but modest support from export volume growth, despite astrong rebound in global trade. Current account balances havedeteriorated due to higher imports and rising oil prices. Strong domestic
demand has supported credit growth, and inflation is above or close tocentral bank targets. China’s investment has been rising in the region,
especially through the China-Pakistan Economic Corridor.
A. GDP growth

B. Exports

C. Current account balances

D. Credit growth

E. Inflation

F. FDI, Pakistan

Sources: Haver Analytics, International Monetary Fund, Pakistan Board of Investment, World Bank.
A. SAR stands for South Asia Region. Aggregate growth rates calculated using constant 2010 U.S.
dollar GDP weights. Shaded area indicates forecasts. Data for 2018 are forecasts.
B. Data refers to trade volume of goods and non-factor services. Shaded area indicates forecasts.
Data for 2018 are forecasts. Data for Bangladesh, India, and Pakistan are based on fiscal year.
Data for Sri Lanka are based on calendar year.
C. Shaded area indicates forecasts. Data for Bangladesh, India, and Pakistan are based on fiscal
year. Data for Sri Lanka are based on calendar year.
D. Last observation is March 2018.
E. Last observation is April 2018.
F. 2018 (FY2017/18) figures are from July through February.
Click here to download data and charts.

growth has rebounded following the natural
disasters of mid-2017 (e.g., severe floods andlandslides), and activity has remained strong andbroad-based in 2018. In Sri Lanka, activity in2018 has been supported by a recovery ininvestment, especially in the construction andagriculture sectors, and related activities, following
a slowdown in 2017 driven in part by adverse
weather conditions.
Pakistan’s GDP growth rose in FY2017/18,
supported by infrastructure projects funded by the
China-Pakistan Economic Corridor (CPEC),
improvements in energy supply, and persistentprivate consumption growth. In Bhutan, growthhas been moderating, partly owing to delays inhydropower projects. However, growth is still
strong, at 5.8 percent in FY2017/18. In
Afghanistan, the recovery continues to be
disrupted by security challenges and politicaluncertainty.

Outlook
Growth in South Asia is forecast to pick up to 6.9
percent in 2018, mainly reflecting the fading
effects of temporary factors that weakened activity
in India (Figure 2.5.2). The forecast is broadly
unchanged from January 2018. Domestic demandis the key driver of growth in the region, althoughfirming exports should provide additional support
in 2018 (World Bank 2018n). The baseline
scenario assumes a moderating recovery in global
trade, higher commodity prices, and graduallytightening global financing conditions.
Growth in India is projected to accelerate to 7.3
percent in FY2018/19 and 7.5 percent on averagein 2019-20, reflecting robust private consumption
and firming investment, broadly in line with
January projections. In the rest of the region,
growth will remain stable at about 5.6 percent in2018 and throughout the forecast horizon as
ongoing recoveries in Bangladesh, Pakistan, andSri Lanka are offset by slower growth inAfghanistan, Bhutan, and Maldives. In Pakistan,
GDP growth is estimated to rise to 5.8 percent in
FY2017/18, before moderating to 5.0 percent in
FY2018/19, reflecting tighter policies to improve
macroeconomic stability. In Bangladesh, growth isexpected to recover from the effects of natural
disasters in FY2017/18 and reach 6.7 percent in
FY2018/19, supported in part by robust export
growth and remittances. Sri Lanka’s GDP isG LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

projected to grow 4.6 percent on average over theperiod 2018-20, reflecting a recovery from theeffects of last year’s natural disasters on
agriculture, as well as robust consumption andinvestment growth. After the strong rebound in
FY2016/17 from the effects of the devastating
earthquakes in FY2015/16, Nepal’s GDP growthis forecast to moderate to 4.6 percent in FY
2017/18 and average 4.3 percent in 2019-20. In
Bhutan and Maldives, growth will continue tobenefit from construction and services, especially
tourism, and average 7.4 and 5 percent
respectively over the forecast horizon. In
Afghanistan, growth will remain subdued due tocontinued security challenges and politicaluncertainty.
Per capita growth rates in the region are strong,
and are expected to help bring down poverty incoming years, particularly in India. Nonetheless,addressing underlying structural weaknesses andmacroeconomic vulnerabilities remain key
challenges in the region (Farole and Pathikonda
2016; World Bank 2018c).

Risks
Risks to South Asia outlook are tilted to thedownside, although upside surprises to global
growth remain a possibility in the short-term.
These include domestic policy slippages, renewed
security challenges, and natural disasters. The
outlook could also be adversely affected byexternal shocks such as an abrupt tightening of
global financial conditions and escalating tradeprotectionism, even though the region is relatively
less open to trade. Since South Asia is net oil
importer, a higher-than-expected rise in oil prices
might amplify macroeconomic vulnerabilities andweigh on economic activity.
In a number of countries, a further deteriorationin fiscal balances (e.g., India, Maldives, Pakistan,
Sri Lanka), a continued buildup of debt, andwidening current account deficits (e.g., Pakistan),present significant vulnerabilities to a tightening ofdomestic or external financing conditions (Basu,
Eichengreen, and Gupta 2015). Furthermore, asetback in the implementation of reforms toresolve weakening corporate and financial sector

SOUTH ASIA

139

FIGURE 2.5.2 SAR: Outlook and risks
Growth in the region is predicted to pick up to 6.9 percent in 2018, andstabilize at around 7.1 percent over the medium term. Domestic demand
will continue to be the main driver of growth. Natural disasters andpersistent droughts remain a downside risk for economic activity. The
region continues to face significant fiscal vulnerabilities.
A. Growth

B. Share of countries where droughts
starting after 2015 persisted

C. Fiscal balances

D. Debt

Sources: Bank for International Settlements, Emergency Events Database (www.emdat.be, Brussels,
Belgium), Institute of International Finance, International Monetary Fund, World Bank.
A. SAR stands for South Asia Region.
A.C. Shaded areas represent forecast. Data for Bangladesh, India, and Pakistan are based on fiscal
year. Data for Sri Lanka is based on calendar year.
D. The peak is defined as the highest debt-to-GDP ratio since 2005Q1. It is identified to have occurred in 2009Q3 in India, 2017Q2 in Pakistan, in 2017Q3 in Bangladesh, and 2017Q3 in Sri Lanka.
2017 data reflects 2017Q3. Total debt comprised of credit to non-financial corporations, households,
and general government debt. All data are based on calendar year.
Click here to download data and charts.

balance sheets could hold back the investment
recovery currently underway and dampen credit
growth in the region.
An increase in political uncertainty (e.g.,
Afghanistan, Bangladesh, Pakistan, Sri Lanka) andfurther deterioration in the security environment
in some countries (e.g., Afghanistan) might
dampen confidence and set back growth. In recent
years, the number of people and geographical areas
affected by natural disasters such as drought,
floods, and earthquakes have risen in the region. A
rise in the prevalence of natural disasters,
including those caused by climate change, could
disrupt infrastructure, agricultural output, andeconomic activity in general (e.g., Bhutan, Nepal,
Sri Lanka).

140

CHAPTER 2.5

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

TABLE 2.5.1 South Asia forecast summary(Real GDP growth at market prices in percent, unless indicated otherwise)

Percentage point differencesfrom January 2018 projections

2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

7.1

7.5

6.6

6.9

7.1

7.2

0.0

-0.1

0.0

EMDE South Asia, GDP1, 2(Average including countries with full national accounts and balance of payments data only)3
EMDE South Asia, GDP3

7.1

7.5

6.7

6.9

7.2

7.2

0.0

0.0

0.0

GDP per capita (U.S. dollars)

5.8

6.2

5.4

5.6

5.9

6.0

-0.1

-0.1

0.0

PPP GDP

7.1

7.5

6.7

6.9

7.1

7.2

0.0

-0.1

0.0

Private consumption

5.5

8.4

7.6

6.6

6.9

7.0

-0.6

-0.2

-0.1

Public consumption

2.6

13.8

6.7

9.7

8.8

8.5

0.0

-0.4

-0.7

Fixed investment

5.5

4.7

10.3

7.6

7.7

7.7

1.5

0.7

0.0

Exports, GNFS4

-5.0

0.9

4.5

5.7

6.1

6.1

0.2

-0.4

-0.6

Imports, GNFS4

-3.8

0.3

6.2

7.5

6.5

6.1

2.1

0.8

0.2

Net exports, contribution to growth

-0.1

0.1

-0.6

-0.7

-0.4

-0.3

-0.5

-0.3

-0.2

15/16

16/17

17/18e18/19f

19/20f

20/21f

18/19f

19/20f

20/21f

5.4

5.8

5.6

5.6

5.6

5.7

-0.2

-0.3

-0.3

Memo items: GDP2
South Asia excluding India
India

8.2

7.1

6.7

7.3

7.5

7.5

0.0

0.0

0.0

Pakistan (factor cost)

4.6

5.4

5.8

5.0

5.4

5.4

-0.8

-0.6

-0.6

Bangladesh

7.1

7.3

6.5

6.7

7.0

7.0

0.0

0.3

0.3

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 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
Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)2015
Calendar year basis

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

1

Afghanistan

1.3

2.4

2.6

2.2

2.5

3.3

-1.2

-0.6

0.2

Maldives

2.2

6.2

6.2

5.5

4.5

4.9

0.6

-0.5

-0.1

Sri Lanka

5.0

4.5

3.1

4.8

4.5

4.5

-0.2

-0.6

-0.6

Fiscal year basis1

15/16

16/17

17/18e18/19f

19/20f

20/21f

18/19f

19/20f

20/21fBangladesh

7.1

7.3

6.5

6.7

7.0

7.0

0.0

0.3

0.3

Bhutan

7.3

7.4

5.8

5.4

6.0

8.7

-1.5

-1.6

1.1

India

8.2

7.1

6.7

7.3

7.5

7.5

0.0

0.0

0.0

Nepal

0.6

7.9

6.3

4.5

4.2

4.2

0.0

-0.3

-0.3

Pakistan (factor cost)

4.6

5.4

5.8

5.0

5.4

5.4

-0.8

-0.6

-0.6

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 significantly 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. The fiscal year runs from July 1 through June 30 in Bangladesh, Bhutan, and Pakistan, from July 16 through July 15 in Nepal, andApril 1 through March 31 in India.
For additional information, please see www.worldbank.org/gep.

Growth in Sub-Saharan Africa is projected to pick up to 3.1 percent in 2018, from 2.6 percent in 2017. This
upswing reflects rising oil and metals production, encouraged by higher commodity prices, improving
agricultural conditions, and increasing domestic demand. Growth is expected to firm to an average of 3.6
percent in 2019-20, as the recovery strengthens in Angola, Nigeria, and South Africa—the region’s largest
economies. Nevertheless, growth will remain below its long-term average, with continued weak convergence ofper capita income towards average emerging market and developing economies levels. Tighter global financing
conditions and weaker-than-expected commodity prices are the main external downside risks to the regional
outlook. Domestic risks include heightened conflicts, delayed fiscal adjustment, and weak implementation of
structural reforms.

Recent developments
The economic recovery in Sub-Saharan Africa(SSA) has strengthened, following a moderate
rebound in 2017 (Figure 2.6.1). Purchasing
managers’ indexes indicate firming manufacturing
activity in several countries (e.g., Ghana, Kenya,
Nigeria, Zambia). Renewed government commitment to critical macroeconomic and governancereforms in Angola, South Africa, and Zimbabwe
has boosted investor confidence. Mining
production has risen in metals exporters, with newmines coming on stream and investment into
existing mines increasing, encouraged by higher
metals prices (e.g., Democratic Republic ofCongo, Zambia), although, in some cases, highgovernment debt levels are weighing on growth(e.g., Mozambique, Sierra Leone). Mining
production in South Africa has also been weaker
than expected. Among non-resource-intensive
countries, the pickup in economic activity is
supported by improving agricultural conditions
and infrastructure investment in some (e.g.,
Rwanda, Uganda); in others, it has reflected risingconsumer spending, helped by low inflation and arebound in remittances (e.g., The Gambia,
Kenya). However, growth in oil production has
Note: The author of this section is Gerard Kambou. Research
assistance was provided by Xinghao Gong.

moderated in some oil exporters due to maturing
oil fields (e.g., Angola, Nigeria).
Current account deficits are rising, but there are
significant differences between countries. Amongoil exporters, current account deficits are expected
to narrow further this year as the terms-of-trade
continue to improve. Nevertheless, Nigeria could
see its current account surplus decline, as import
growth rebounds. In metals exporters, current
account deficits are narrowing moderately,reflecting the effects of a pickup in importintensive mining investment in some countries.
Among non-resource-intensive countries, current
account deficits are widening, as import growth
remains strong due to high public investment
levels and rising fuel imports. Global financial
market conditions have been favorable and helped
to finance the current account imbalances. Whileforeign direct investment flows are rebounding
moderately, portfolio inflows have continued at asolid pace, helped by several large sovereign-bondissuances (e.g., Angola, Côte d’Ivoire, Kenya,
Nigeria, Senegal).
Exchange rates have been broadly stable in realeffective terms, reflecting tight domestic policies insome countries, and rising foreign financing.
Foreign reserve levels have increased, boosted by
portfolio inflows, and supportive policies in somecases, including among the Central African

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CHAPTER 2.6

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

FIGURE 2.6.1 SSA: Economic activity
Economic activity in Sub-Saharan Africa rebounded in 2017, helped by aturnaround in the region’s largest economies, and has continued tostrengthen. Recent indicators suggest that metals production and fixed
investment growth have picked up in the region, as commodity prices
stabilized. However, oil production has risen at a slower pace in some oil
producers, partly due to maturing fields. While current account deficits are
increasing, due to a pickup in import growth, fiscal deficits are narrowing
helped by higher oil prices and an increase in domestic revenue in somecases.
B. Oil production

A. GDP growth

C. Metals production

E. Current account balance

D. Investment growth

F. Fiscal balance

Sources: International Energy Agency, World Bank, World Bureau of Metal Statistics.
Note: SSA = Sub-Saharan Africa.
A. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights.
B. Nigeria oil production includes condensates. Last observation is April 2018.
C. Index rebased on metric ton measurement. Last observation is March 2018.
D.-F. Median of country groups. Non-resource-intensive countries consist of agricultural exporters
and commodity importers.
Click here to download data and charts.

Economic and Monetary Community (CEMAC)
countries where fiscal consolidation has takenplace. However, reserve coverage is below thethree-months-of-imports benchmark in many
countries, especially those that have been hit hardby the decline in commodity prices. Inflation
continues to fall, helped by declining food prices,
prompting central banks in some countries tofurther cut interest rates (e.g., Uganda, Zambia);
and, in others, to signal a gradual easing cycle(e.g., Kenya). Nevertheless, inflation has been in
double digits in several countries, owing tocurrency depreciations (e.g., Angola, Ethiopia),and high food inflation due to supply disruptions(e.g., Nigeria, Sudan). In these countries, policy
has been tight.
Fiscal deficits have narrowed. Among oil
exporters, the improvement reflects the recovery in
oil prices and expenditure adjustments incountries in the CEMAC region (e.g., Chad,
Republic of Congo). Progress in boosting non-oil
revenue remains limited (e.g., Angola, Nigeria). In
non-resource-intensive countries, where commodity revenues represent a small share of total
revenues, domestic revenue has increased, helping
to reduce the fiscal deficit. However, in metals
exporters, fiscal deficits are widening, due toweaker domestic revenue mobilization and risingexpenditure.
Large fiscal deficits have resulted in high public
debt levels in the region (World Bank 2018o).
Median debt levels among metals exporters arerising, reflecting previously undisclosed borrowing
in some cases (e.g., Mozambique) and high public
investment in others (e.g., Zambia). Among oil
exporters, fiscal consolidation is contributing to a
gradual stabilization of government debt, but the
debt burden remains high (e.g., Gabon, Ghana),
and some countries are in debt restructuring (e.g.,Chad, Republic of Congo). Debt levels are
relatively low in Nigeria, but high and rising in
Angola, due in part to exchange rate depreciation.
Low public saving rates and high public
investment are contributing to an increase in debt
levels in some non-resource-intensive countries(e.g., Ethiopia); in others, governance issues are an
important contributory factor (e.g., The Gambia).
Countries in the region are increasingly shifting
away from traditional multilateral and bilateralsources of debt toward bond issuances and nonParis Club bilateral creditors, which are resulting
in higher debt service costs in some countries (e.g.,
Ghana, Zambia). International bonds have started

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

to mature, and large repayments are expected overthe period 2020-25, which is likely to pose asignificant refinancing challenge to the region. To
contain further increases in government debt in
the region, sustained fiscal consolidation, higher
domestic revenue mobilization, and stronger
growth will be necessary.

Outlook
Growth in Sub-Saharan Africa is projected to pickup to 3.1 percent in 2018, slightly below January
forecasts, and to firm to an average of 3.6 percent
in 2019-20, as the recovery strengthens in theregion’s largest economies (Figure 2.6.2). These
forecasts are predicated on the expectations that
oil and metals prices will remain stable, externalfinancial market conditions will continue to besupportive, and governments in the region will
implement reforms to tackle macroeconomic
imbalances and boost investment.
•

Among the region’s largest economies,
Nigeria’s growth forecasts are lower than in
January. While the oil sector is expected tocontinue to support the recovery, oil
production is likely to be less than thegovernment’s projections, due to capacity
constraints. Growth in the non-oil industrial
sectors is also likely to remain subdued as
structural constraints slow efforts to attract
long-term investments. The growth forecasts
for Angola and South Africa were revisedslightly upward. In Angola, the revisions
reflect the expectation that a more efficient
allocation of foreign exchange, rising natural
gas production, and improved businesssentiment would help support the rebound ineconomic activity. In South Africa, the pickup
in business confidence is expected to help
sustain the ongoing recovery in investment.

SUB-SAHARAN AFRICA

FIGURE 2.6.2 SSA: Outlook and risks
Growth in the region is expected to pick up this year, and firm in 2019-20,
reflecting a gradual recovery in the region’s largest economies, andcontinued robust growth in non-resource-intensive countries. However, percapita income growth will remain below its long-term average, and also
below the EMDE average, reflecting the slow pace of per capita growth inoil and metals exporters. Excessive reliance on commercially-priced debt
could pose a significant refinancing risk to the region. Longer-thanexpected droughts would slow the recovery in the region.

A. Growth

B. Growth per capita

C. Composition of public and publicly
guaranteed external debt over time

D. Share of countries where droughts
starting after 2015 persist

Sources: Emergency Events Database (www.emdat.be; Université Catholique de Louvain, Brussels,
Belgium), World Bank.
Note: SSA = Sub-Saharan Africa.
A.B. Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights. Shaded areas
represent forecasts.
Click here to download data and charts.

exporters, growth is projected to moderate but
remain solid in Ghana, as the effects of highoil production gradually dissipate. However,
the recovery will be slower than anticipatedamong oil exporters in the CEMAC region,
reflecting the need for continued fiscal
consolidation to stabilize debt levels.
••

Elsewhere, rising mining output as new
projects come on line, combined with stable
metals prices, are expected to boost activity insome metals exporters (e.g., Democratic
Republic of Congo, Zambia); in others,
growth is expected to remain subdued as highgovernment debt levels weigh on the private
sector (e.g., Mozambique). Among oil

143

In non-resource-intensive countries, growth isexpected to remain robust, supported by
improving agricultural conditions, infrastructure investment, and household demand.
Low inflation, a rebound in private sector
credit growth, and rising remittance flows are
expected to boost consumer spending. The
larger countries will continue to grow faster(e.g., Côte d’Ivoire, Ethiopia) than the smaller

144

CHAPTER 2.6

ones, due to their stronger policies andinstitutional capacity. In Malawi, for instance,
growth is expected to be lower than
anticipated, reflecting the adverse impact of adry spell and the spread of the fallarmyworm—a pervasive agricultural pest—on
food production.
Although per capita income growth in the region
will turn positive, it will remain well below its
long-term average, and also below the emerging
market and developing economy (EMDE) average(Chapter 1). The weak convergence of per capita
income toward EMDE levels reflects the slower
pace of per capita growth among oil and metals
exporters. The region’s poverty headcount, at theinternational poverty line ($1.90/day in 2011
purchasing power parity exchange rates), is
projected to decline only slightly over the 2018-20
period, and decrease more slowly among metals
exporters and fragile countries. Renewed progresson poverty reduction will require a sustained
acceleration in per capita income growth.
Structural reforms that increase productivity andsupport export diversification would be critical tothese efforts. (Chapter 1; Bhorat and Tarp 2016;
Fosu 2018).

Risks
Risks to the regional outlook remain tilted to thedownside. On the external front, a faster-thanexpected tightening of monetary policy among
advanced economies could diminish investor
appetite for higher risk assets in frontier markets,
which would be particularly difficult for countries
that rely on foreign debt financing to support large
current account deficits. Sudden capital outflows
could trigger large currency depreciations in somecountries. A sharp decline in commodity prices
would have a significant adverse impact on theregion, given the heavy dependence of many

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

economies on commodity exports. A possible
trigger could be a slowdown in Chinese growth
given the risks posed by interest rate hikes or tradetensions with the United States. A collapse in oiland metals prices would severely undermine
efforts at fiscal consolidation, derail progress inreining in the region’s debt burden, andundermine investor confidence.
On the domestic front, political transitions haveopened opportunities for reforms in several major
Sub-Saharan African countries (Angola, South
Africa, Zimbabwe) that, if implemented, could
bolster the regional outlook. Policy reforms in
Nigeria to improve the business environment
could advance faster than expected, andsignificantly boost non-oil sector growth.
However, the risk of worsening politicalinstability, and a concurrent weakening of neededreforms, remains high. Indeed, some of theregion’s largest economies, such as Ethiopia andNigeria, are particularly vulnerable to an uptick insocial unrest. Risks to debt sustainability are alsohigh in the region. Heavy reliance oncommercially-priced debt could lead to debt
service difficulties in some countries, including
Ghana, Nigeria, and Zambia (interest paymentson government debt as a share of tax revenue in2017 was estimated at more than 40 percent in
Ghana, and more than 25 percent in Nigeria andZambia). Meanwhile, the Ebola outbreak in the
Democratic Republic of Congo has been assessed
as a very high health risk, and could affecteconomic activity in the country as well as in the
sub-region, if it spreads rapidly to major urban
centers and into neighboring countries. The
recurrence of drought is a further significant
downside risk. Droughts that started after 2015
have lasted longer in Sub-Saharan Africa than inother EMDE regions. A sudden return of drought
conditions could severely disrupt the ongoing
economic recovery in the region.

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

TABLE 2.6.1 Sub-Saharan Africa forecast summary

Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)

EMDE SSA, GDP1

145

SUB-SAHARAN AFRICA

2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

2020f

3.1

1.5

2.6

3.1

3.5

3.7

-0.1

0.0

0.1

(Average including countries with full national accounts and balance of payments data only)2
EMDE SSA, GDP2
GDP per capita (U.S. dollars)

3.1

1.5

2.6

3.1

3.5

3.7

-0.1

0.0

0.2

0.4

-1.2

-0.1

0.4

0.8

1.0

-0.1

0.0

0.1

3.3

1.7

2.9

3.4

3.7

3.9

-0.1

0.0

0.1

Private consumption

5.8

0.6

2.0

2.6

2.8

2.9

0.0

0.1

0.1

Public consumption

-2.3

1.4

2.6

2.5

2.9

3.0

0.0

0.2

0.3

Fixed investment

1.5

0.4

6.0

6.8

7.4

7.6

0.0

0.3

0.4

Exports, GNFS3

2.7

3.6

3.1

3.2

3.5

3.8

0.0

0.1

0.3

Imports, GNFS

2.0

-0.9

2.5

3.0

3.3

3.4

0.1

0.2

0.2

0.2

1.4

0.2

0.1

0.1

0.2

0.0

0.0

0.1

SSA excluding Nigeria,
South Africa, and Angola

4.6

4.3

4.7

4.9

5.3

5.5

-0.1

0.2

0.3

Oil exporters4

2.9

-0.4

1.5

2.3

2.6

2.8

-0.5

-0.2

-0.2

PPP GDP3

Net exports, contribution
to growth
Memo items: GDP

CFA countries

3.9

2.8

3.3

4.1

4.5

4.9

-0.2

-0.1

0.0

CEMAC

1.7

-0.9

-0.2

1.4

2.3

3.0

-0.5

-0.1

0.0

WAEMU

6.2

6.6

6.6

6.4

6.3

6.4

0.0

-0.1

-0.1

2.1

-0.5

1.0

1.7

2.0

2.2

-0.1

-0.2

0.0

2.7

-1.6

0.8

2.1

2.2

2.4

-0.4

-0.6

-0.4

5

SSA3
NigeriaSouth Africa

1.3

0.6

1.3

1.4

1.8

1.9

0.3

0.1

0.2

Angola

3.0

0.0

1.2

1.7

2.2

2.4

0.1

0.7

0.9

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, Republic of Congo, Gabon, Ghana, Nigeria, and Sudan.
5. Includes Benin, Burkina Faso, Cameroon, Central African Republic, Chad, Republic of Congo, Côte d’Ivoire, Equatorial Guinea, Gabon, Mali, Niger, Senegal, and Togo.
For additional information, please see www.worldbank.org/gep.

146

CHAPTER 2.6

G LO BAL EC O NO MIC P ROS P EC TS | J U NE 2018

TABLE 2.6.2 Sub-Saharan Africa country forecasts1
Percentage point differencesfrom January 2018 projections(Real GDP growth at market prices in percent, unless indicated otherwise)
2015

2016

2017e

2018f

2019f

2020f

2018f

2019f

Angola

3.0

0.0

1.2

1.7

2.2

2.4

0.1

0.7

2020f
0.9

Benin

2.1

4.0

5.6

6.0

6.1

6.3

0.0

-0.2

-0.4

Botswana2

-1.7

4.3

1.8

3.0

3.3

3.8

-1.7

-1.5

-1.0

Burkina Faso

3.9

5.9

6.4

6.0

6.0

6.0

0.0

0.0

0.0

Burundi

-3.9

-0.6

0.5

1.9

2.3

2.5

0.4

-0.2

0.0

Cabo Verde

1.0

3.8

4.0

4.2

4.0

4.0

0.6

0.2

0.2

Cameroon

5.7

4.5

3.2

3.9

4.1

4.3

-0.2

-0.2

0.0

Chad

2.8

-6.3

-3.0

2.6

2.5

5.8

-1.1

-0.4

-1.0

Comoros

1.0

2.4

2.5

2.9

3.0

3.0

0.2

0.1

0.1

Congo, Dem. Rep.

6.9

2.4

3.4

3.8

4.1

4.4

0.8

0.8

1.1

Congo, Rep.

2.6

-2.8

-4.6

0.7

4.6

-1.2

-1.6

3.1

-2.7

Côte d’Ivoire

8.8

8.3

7.8

7.4

7.2

7.2

0.2

0.0

0.0

Equatorial Guinea

-9.1

-9.0

-2.7

-6.4

-7.0

-0.5

-0.4

-2.8

3.7

Ethiopia2

10.4

7.6

10.3

9.6

9.7

9.9

1.4

1.9

2.1

Gabon

3.9

2.1

0.6

2.6

3.7

3.9

0.2

0.0

0.2

Gambia, The

4.3

2.2

3.5

5.4

5.2

4.9

1.9

1.0

0.7

Ghana

3.8

3.7

7.8

6.9

6.7

5.4

-1.4

1.2

-0.1

Guinea

3.8

10.5

8.2

6.0

5.9

6.0

0.2

0.0

0.1

Guinea-Bissau

6.1

5.8

5.7

5.1

5.2

5.4

-0.1

-0.2

0.0

Kenya

5.7

5.9

4.9

5.5

5.9

6.1

0.0

0.0

0.2

Lesotho

5.6

2.3

3.1

1.8

2.6

2.8

-2.2

-1.6

-1.4

Liberia

0.0

-1.6

2.5

3.2

4.7

4.8

-0.7

-0.3

-1.2

Madagascar

3.1

4.2

4.1

5.1

5.6

5.3

0.0

0.0

-0.1

Malawi

2.8

2.5

4.0

3.7

4.1

4.9

-1.3

-1.3

-0.5

Mali

6.0

5.8

5.3

5.0

4.7

4.7

0.0

0.0

0.0

Mauritania

1.4

2.0

3.5

3.6

4.6

5.2

0.6

0.0

0.6

Mauritius

3.5

3.8

3.9

4.0

4.1

3.8

0.2

0.4

0.1

Mozambique

6.6

3.8

3.7

3.3

3.4

3.6

0.1

0.0

0.2

Namibia

6.0

1.1

-1.0

1.5

2.3

3.0

-1.5

-1.2

-0.5

Niger

4.0

5.0

5.2

5.3

5.4

5.8

0.1

0.0

0.2

Nigeria

2.7

-1.6

0.8

2.1

2.2

2.4

-0.4

-0.6

-0.4

Rwanda

8.8

6.0

6.1

6.8

7.1

7.5

0.9

0.3

0.7

Senegal

6.5

6.7

6.8

6.8

6.8

7.0

-0.1

-0.2

0.0

Seychelles

3.5

4.5

4.2

4.0

3.8

3.5

0.2

0.3

0.0

Sierra Leone

-20.5

6.3

4.3

5.1

5.7

6.5

-1.2

-1.0

-0.2

South Africa

1.3

0.6

1.3

1.4

1.8

1.9

0.3

0.1

0.2

Sudan

4.9

4.7

4.3

2.6

3.1

3.5

-1.1

-0.6

-0.2

Swaziland

0.4

1.4

1.9

1.1

1.7

1.8

-0.8

-0.1

0.0

Tanzania

7.0

7.0

6.4

6.6

6.8

7.0

-0.2

-0.1

0.1

Togo

5.3

5.0

4.4

4.8

5.0

5.0

-0.5

-0.4

-0.4

Uganda2

5.2

4.7

4.0

5.5

6.0

6.5

0.4

0.3

0.5

Zambia

2.9

3.8

3.9

4.1

4.5

4.8

-0.4

-0.5

-0.2

Zimbabwe

1.7

0.6

3.4

2.7

3.8

4.0

1.8

3.6

3.8

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 significantly 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.

G L O B A L E CO N O MI C P R OS P E C TS | J U NE 2 0 18

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———. 2018g. “Making the Recovery
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World Bank, Washington, DC

STATISTICAL
APPENDIXS T A TI S T I C A L A P P E N D IX

G L O B A L E CO N O MI C P R OS P E C TS | J U NE 2 0 18

151

Real GDP growth
Annual estimates and forecasts1

Quarterly growth2

2015

2016

2017e 2018f

2019f

2020f

16Q4

17Q1

17Q2

17Q3 17Q4 18Q1e

World

2.8

2.4

3.1

3.1

3.0

2.9

2.6

2.9

2.8

3.1

3.2

..

Advanced economies

2.3

1.7

2.3

2.2

2.0

1.7

1.8

2.2

2.1

2.4

2.5

..

United States

2.9

1.5

2.3

2.7

2.5

2.0

1.8

2.0

2.2

2.3

2.6

2.9

Euro Area

2.1

1.8

2.4

2.1

1.7

1.5

1.9

2.1

2.4

2.7

2.8

2.5

Japan

1.4

1.0

1.7

1.0

0.8

0.5

1.5

1.4

1.5

1.9

1.8

0.9

United Kingdom

2.3

1.9

1.8

1.4

1.5

1.7

2.0

2.1

1.9

1.8

1.4

1.2

3.7

3.7

4.3

4.5

4.7

4.7

4.3

4.6

4.4

4.9

4.9

..
6.6

Emerging market and developing economies

6.5

6.3

6.6

6.3

6.1

6.0

6.5

6.5

6.6

6.6

6.5

Cambodia

7.0

7.0

6.8

6.9

6.7

6.6

..

..

..

..

..

..

China

6.9

6.7

6.9

6.5

6.3

6.2

6.8

6.9

6.9

6.8

6.8

6.8

Fiji

3.6

0.4

3.8

3.5

3.4

3.3

..

..

..

..

..

..

Indonesia

4.9

5.0

5.1

5.2

5.3

5.4

4.9

5.0

5.0

5.1

5.2

5.1

Lao PDR

7.3

7.0

6.7

6.6

6.9

6.9

..

..

..

..

..

..

Malaysia

5.0

4.2

5.9

5.4

5.1

4.8

4.5

5.6

5.8

6.2

5.9

5.4

Mongolia

2.4

1.5

5.1

5.3

6.4

6.5

11.0

4.1

6.0

6.5

3.7

6.0

Myanmar

7.0

5.9

6.4

6.7

6.9

7.1

..

..

..

..

..

..

Papua New Guinea

5.3

1.9

2.2

-1.7

4.0

3.0

..

..

..

..

..

..

Philippines

6.1

6.9

6.7

6.7

6.7

6.6

6.7

6.5

6.6

7.2

6.5

6.8

Solomon Islands

3.7

3.5

3.2

3.0

2.9

2.8

..

..

..

..

..

..

Thailand

3.0

3.3

3.9

4.1

3.8

3.8

3.0

3.4

3.9

4.3

4.0

4.8

Timor-Leste

4.0

5.3

-1.8

2.2

4.2

4.0

..

..

..

..

..

..

Vietnam

6.7

6.2

6.8

6.8

6.6

6.5

6.8

5.1

6.2

7.5

7.7

7.4

East Asia and Pacific

1.1

1.7

4.0

3.2

3.1

3.0

2.1

3.0

3.8

5.5

3.7

..

Albania

2.2

3.4

3.8

3.6

3.5

3.5

4.3

4.0

4.4

3.6

3.4

..

Armenia

3.2

0.2

7.5

4.1

4.0

4.0

..

..

..

..

..

..

Azerbaijan

1.1

-3.1

0.1

1.8

3.8

3.2

..

..

..

..

..

..

Belarus

-3.8

-2.5

2.4

2.9

2.7

2.5

-1.7

0.4

1.7

3.0

4.3

..

Bosnia and Herzegovina

3.1

3.1

3.0

3.2

3.4

4.0

3.5

3.4

2.8

3.0

3.0

..

Bulgaria

3.6

3.9

3.6

3.8

3.6

3.6

4.3

3.6

3.9

3.8

3.0

3.4

Croatia

2.3

3.2

2.8

2.6

2.7

2.8

3.5

2.6

3.0

3.3

2.0

..

Georgia

2.9

2.8

5.0

4.5

4.8

5.0

2.8

5.3

4.9

4.4

5.4

..

Hungary

3.1

2.0

4.0

4.1

3.2

3.0

1.9

4.3

3.3

3.9

4.4

4.4

Kazakhstan

1.2

1.1

4.0

3.7

3.3

2.8

..

..

..

..

..

..

Kosovo

4.1

4.1

4.4

4.8

4.8

4.8

..

..

..

..

..

..

Kyrgyz Republic

3.9

4.3

4.6

4.2

4.8

5.0

..

..

..

..

..

..

Macedonia, FYR

3.9

2.9

0.0

2.3

2.7

3.0

3.3

0.0

-1.3

0.2

1.2

..

Moldova

-0.4

4.5

4.5

3.8

3.7

3.5

..

..

..

..

..

..

Montenegro

3.4

2.9

4.4

2.8

2.5

2.1

..

..

..

..

..

..

Poland

3.8

2.9

4.6

4.2

3.7

3.5

3.4

4.7

4.2

5.4

4.4

5.1

Europe and Central Asia

Romania

3.9

4.8

7.0

5.1

4.5

4.1

4.8

5.7

6.1

8.8

6.7

4.0

Russia

-2.5

-0.2

1.5

1.5

1.8

1.8

-0.3

0.6

2.5

2.2

0.9

1.3

Serbia

0.8

2.8

1.9

3.0

3.5

4.0

2.5

1.2

1.5

2.2

2.5

4.5

Tajikistan

6.0

6.9

7.1

6.1

6.0

6.0

..

..

..

..

..

..

Turkey

6.1

3.2

7.4

4.5

4.0

4.0

4.2

5.4

5.4

11.3

7.3

..

Turkmenistan

6.5

6.2

6.5

6.3

6.3

6.3

..

..

..

..

..

..

Ukraine

-9.8

2.3

2.5

3.5

4.0

4.0

4.6

2.8

2.6

2.4

2.2

3.1

Uzbekistan

7.9

7.8

5.3

5.0

5.1

5.5

..

..

..

..

..

..

152

S T A TI S T I C A L A P P E N D IX

G L O B A L E CO N O MI C P R OS P E C TS | J U NE 2 0 18

Real GDP growth (continued)
Annual estimates and forecasts1

Quarterly growth2

2015

2016

2017e

2018f

2019f

2020f

16Q4

17Q1

17Q2

17Q3

17Q4

18Q1e

-0.4

-1.5

0.8

1.7

2.3

2.5

1.7

2.6

1.9

2.3

3.6

..

Argentina

2.7

-1.8

2.9

1.7

1.8

2.8

-1.1

0.6

3.0

3.8

3.9

..

Belize

3.8

-0.5

1.2

2.0

1.9

1.7

..

..

..

..

..

..

Bolivia

4.9

4.3

4.2

3.9

3.6

3.4

3.7

3.3

3.8

4.3

5.2

..

Brazil

-3.5

-3.5

1.0

2.4

2.5

2.4

-2.5

0.0

0.4

1.4

2.1

..

Chile

2.3

1.3

1.5

3.3

3.4

3.5

0.3

-0.4

0.5

2.5

3.3

4.2

Colombia

3.0

2.0

1.8

2.7

3.3

3.6

1.3

1.3

1.6

2.5

1.8

2.2

Costa Rica

3.6

4.2

3.2

3.4

3.6

3.6

4.6

3.5

3.4

2.8

3.0

..

Dominican Republic

7.0

6.6

4.6

5.0

4.7

4.6

5.3

5.5

3.1

3.1

6.5

..

Ecuador

0.1

-1.6

3.0

2.2

1.5

0.9

1.0

2.7

3.0

3.3

3.0

..

El Salvador

2.4

2.6

2.3

2.3

2.2

2.2

3.1

3.5

0.3

3.2

2.5

..

Grenada

6.4

3.7

4.5

3.3

2.8

2.8

..

..

..

..

..

..

Guatemala

4.1

3.1

2.8

3.1

3.3

3.3

3.2

3.2

2.2

2.7

2.9

..

Guyana

3.1

3.4

2.1

3.8

3.8

29.0

5.3

2.5

-0.7

4.5

..

..

Haiti3

1.2

1.5

1.2

1.8

2.4

2.4

..

..

..

..

..

..

Honduras

3.8

3.8

4.8

3.5

3.6

3.8

4.2

5.5

3.5

5.9

4.3

..

Jamaica

0.9

1.4

0.5

1.7

1.9

2.0

1.4

0.1

-0.1

0.8

1.1

..

Mexico

3.3

2.9

2.0

2.3

2.5

2.7

3.3

3.3

1.8

1.6

1.5

1.3

Nicaragua

4.8

4.7

4.9

4.7

4.5

4.4

4.4

7.5

4.6

3.2

4.3

..

Panama

5.6

5.0

5.4

5.6

5.6

5.6

..

..

..

..

..

..

Paraguay

3.0

4.0

4.3

4.3

4.2

4.2

3.4

7.1

1.1

3.0

..

..

Peru

3.3

4.0

2.5

3.5

3.8

3.8

3.1

2.3

2.6

2.7

2.2

3.2

St. Lucia

2.0

0.9

2.1

2.8

2.3

2.3

..

..

..

..

..

..

St. Vincent and the Grenadines

1.4

1.9

1.0

2.1

2.5

2.7

..

..

..

..

..

..

Suriname

-2.6

-5.1

0.1

1.1

1.7

2.1

..

..

..

..

..

..

Trinidad and Tobago

1.5

-6.0

-2.3

1.6

1.9

1.2

..

..

..

..

..

..

Uruguay

0.4

1.7

2.7

3.3

3.1

2.9

3.5

4.1

2.8

1.9

2.0

..

Venezuela
Algeria

-6.0
2.8
3.7

-16.5
5.0
3.3

-14.5
1.6
1.6

-14.3
3.0
3.5

-7.0
3.3
2.0

-4.0
3.2
1.3

..
5.9
..

..
4.5
..

..
1.6
..

..
2.0
..

..
0.6
..

..
..
..

Bahrain

2.9

3.2

3.9

1.7

2.1

2.1

1.7

4.1

4.0

4.1

3.4

..

Djibouti

6.5

6.5

7.0

6.5

6.4

6.3

..

..

..

..

..

..

Egypt3

4.4

4.3

4.2

5.0

5.5

5.8

4.0

4.5

5.0

5.2

5.3

..

Iran

-1.3

13.4

4.3

4.1

4.1

4.2

17.1

16.0

4.2

4.6

0.5

..

Iraq

4.8

11.0

-0.8

2.5

4.1

1.9

..

..

..

..

..

..

Jordan

2.4

2.0

2.1

2.2

2.4

2.4

2.0

2.2

2.0

1.9

1.8

..

Kuwait

0.6

3.5

-2.9

1.9

3.5

3.0

2.9

-3.8

-2.1

-3.0

-2.5

..

Lebanon

0.8

2.0

2.0

2.0

2.0

2.0

..

..

..

..

..

..

Morocco

4.5

1.2

4.0

3.0

3.5

3.7

..

..

..

..

..

..

Oman

4.7

5.4

0.7

2.3

2.5

2.9

..

..

..

..

..

..

Qatar

3.6

2.2

1.6

2.8

3.2

2.8

1.7

2.4

0.3

1.9

1.8

..

Saudi Arabia

4.1

1.7

-0.7

1.8

2.1

2.3

2.1

-0.5

-0.8

-0.4

-1.2

..

Tunisia

1.0

1.2

1.9

2.4

2.9

3.4

..

..

..

..

..

..

United Arab Emirates

3.8

3.0

2.0

2.5

3.2

3.3

..

..

..

..

..

..

West Bank and Gaza

3.4

4.7

3.1

2.5

2.3

2.3

..

..

..

..

..

..

Latin America and the Caribbean

Middle East and North Africa

S T A TI S T I C A L A P P E N D IX

G L O B A L E CO N O MI C P R OS P E C TS | J U NE 2 0 18

153

Real GDP growth (continued)
Annual estimates and forecasts1

Quarterly growth2

2015

2016

2017e

2018f

2019f

2020f

16Q4

17Q1

17Q2

17Q3

17Q4

18Q1e

7.1

7.5

6.6

6.9

7.1

7.2

6.7

6.0

5.6

6.3

7.0

..

Afghanistan

1.3

2.4

2.6

2.2

2.5

3.3

..

..

..

..

..

..

Bangladesh3,4

6.6

7.1

7.3

6.5

6.7

7.0

..

..

..

..

..

..

Bhutan

6.2

7.3

7.4

5.8

5.4

6.0

..

..

..

..

..

..

India

8.2

7.1

6.7

7.3

7.5

7.5

6.8

6.1

5.7

6.5

7.2

..

Maldives

2.2

6.2

6.2

5.5

4.5

4.9

..

..

..

..

..

..

Nepal3,4

3.3

0.6

7.9

6.3

4.5

4.2

..

..

..

..

..

..

Pakistan3,4

4.1
5.0

4.6
4.5

5.4
3.1

5.8
4.8

5.0
4.5

5.4
4.5

..
5.4

..
3.4

..
3.0

..
2.9

..
3.2

..
..

3.1

1.5

2.6

3.1

3.5

3.7

0.6

1.0

2.1

2.3

2.7

..

Angola

3.0

0.0

1.2

1.7

2.2

2.4

..

..

..

..

..

..

Benin

2.1

4.0

5.6

6.0

6.1

6.3

..

..

..

..

..

..

Botswana3

-1.7

4.3

1.8

3.0

3.3

3.8

4.3

0.9

1.0

1.1

6.5

..

Burkina Faso

3.9

5.9

6.4

6.0

6.0

6.0

..

..

..

..

..

..

Burundi

-3.9

-0.6

0.5

1.9

2.3

2.5

..

..

..

..

..

..

Cabo Verde

1.0

3.8

4.0

4.2

4.0

4.0

..

..

..

..

..

..

Cameroon

5.7

4.5

3.2

3.9

4.1

4.3

..

..

..

..

..

..

Chad

2.8

-6.3

-3.0

2.6

2.5

5.8

..

..

..

..

..

..

Comoros

1.0

2.4

2.5

2.9

3.0

3.0

..

..

..

..

..

..

Congo, Dem. Rep.

6.9

2.4

3.4

3.8

4.1

4.4

..

..

..

..

..

..

Congo, Rep.

2.6

-2.8

-4.6

0.7

4.6

-1.2

..

..

..

..

..

..

Côte d'Ivoire

8.8

8.3

7.8

7.4

7.2

7.2

..

..

..

..

..

..

Equatorial Guinea

-9.1

-9.0

-2.7

-6.4

-7.0

-0.5

..

..

..

..

..

..

Ethiopia3

10.4

7.6

10.3

9.6

9.7

9.9

..

..

..

..

..

..

Gabon

3.9

2.1

0.6

2.6

3.7

3.9

..

..

..

..

..

..

Gambia, The

4.3

2.2

3.5

5.4

5.2

4.9

..

..

..

..

..

..

Ghana

3.8

3.7

7.8

6.9

6.7

5.4

4.5

6.7

9.4

9.7

8.1

..

Guinea

3.8

10.5

8.2

6.0

5.9

6.0

..

..

..

..

..

..

Guinea-Bissau

6.1

5.8

5.7

5.1

5.2

5.4

..

..

..

..

..

..

Kenya

5.7

5.9

4.9

5.5

5.9

6.1

6.1

4.9

4.9

4.7

5.0

..

Lesotho

5.6

2.3

3.1

1.8

2.6

2.8

..

..

..

..

..

..

Liberia

0.0

-1.6

2.5

3.2

4.7

4.8

..

..

..

..

..

..

Madagascar

3.1

4.2

4.1

5.1

5.6

5.3

..

..

..

..

..

..

Malawi

2.8

2.5

4.0

3.7

4.1

4.9

..

..

..

..

..

..

Mali

6.0

5.8

5.3

5.0

4.7

4.7

..

..

..

..

..

..

Mauritania

1.4

2.0

3.5

3.6

4.6

5.2

..

..

..

..

..

..

Mauritius

3.5

3.8

3.9

4.0

4.1

3.8

..

..

..

..

..

..

Mozambique

6.6

3.8

3.7

3.3

3.4

3.6

..

..

..

..

..

..

Namibia

6.0

1.1

-1.0

1.5

2.3

3.0

..

..

..

..

..

..

Niger

4.0

5.0

5.2

5.3

5.4

5.8

..

..

..

..

..

..

Nigeria

2.7

-1.6

0.8

2.1

2.2

2.4

-1.7

-0.9

0.7

1.2

2.1

2.0

Rwanda

8.8

6.0

6.1

6.8

7.1

7.5

..

..

..

..

..

..

Senegal

6.5

6.7

6.8

6.8

6.8

7.0

..

..

..

..

..

..

Seychelles

3.5

4.5

4.2

4.0

3.8

3.5

..

..

..

..

..

..

Sierra Leone

-20.5

6.3

4.3

5.1

5.7

6.5

..

..

..

..

..

..

South Asia

3,4

3,4

Sri Lanka
Sub-Saharan Africa

154

S T A TI S T I C A L A P P E N D IX

G L O B A L E CO N O MI C P R OS P E C TS | J U NE 2 0 18

Real GDP growth (continued)
Annual estimates and forecasts1

Quarterly growth2

2015

2016

2017e

2018f

2019f

2020f

16Q4

17Q1

17Q2

17Q3

17Q4

18Q1e

South Africa

1.3

0.6

1.3

1.4

1.8

1.9

1.0

1.1

1.4

1.3

1.5

..

Sudan

4.9

4.7

4.3

2.6

3.1

3.5

..

..

..

..

..

..

Swaziland

0.4

1.4

1.9

1.1

1.7

1.8

..

..

..

..

..

..

Tanzania

7.0

7.0

6.4

6.6

6.8

7.0

5.5

5.7

7.8

6.8

..

..

Togo

5.3

5.0

4.4

4.8

5.0

5.0

..

..

..

..

..

..

Uganda3

5.2

4.7

4.0

5.5

6.0

6.5

2.8

4.6

6.5

7.5

6.6

..

Zambia

2.9

3.8

3.9

4.1

4.5

4.8

3.9

3.1

3.6

4.5

5.0

..

Zimbabwe

1.7

0.6

3.4

2.7

3.8

4.0

..

..

..

..

..

..

Sub-Saharan Africa (continued)

Sources: World Bank and Haver Analytics.
Notes: e = estimate; f = forecast.
1. Aggregate growth rates calculated using constant 2010 U.S. dollars GDP weights.
2. Year-over-year quarterly growth of not-seasonally-adjusted real GDP, except for Ecuador, the Euro Area and the United Kingdom. Data for Bosnia and Herzegovina arefrom the production approach.
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, FYR 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, Egypt, Iran, Jordan, Kuwait, Qatar, and Saudi Arabia.
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, Bhutan, Nepal, and Pakistan, the column labeled 2017 refers to FY2016/17. For India, the column labeled 2016refers to FY2016/17.
For additional information, please see www.worldbank.org/gep.

S T A TI S T I C A L A P P E N D IX

G L O B A L E CO N O MI C P R OS P E C TS | J U NE 2 0 18

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.

House Prices Indicators, IMF Balance of Payments Statistics, and IMF International Financial
Statistics.

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

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
the forecasting process, staff use macroeconometric models that allow the combinationof judgement and consistency with model-based
insights.

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.

155

G L O B A L E CO N O MI C P R OS P E C TS | J U NE 2 0 18

S E L E CTE D TO P I C S

Global Economic Prospects: Selected Topics, 2015-18
Growth and Business Cycles
Global output gap
Is the global economy turning the corner?

January 2018, Box 1.1

Recent developments and outlook

June 2018, Box 1.2

Recent developments and outlook

January 2018, Box 1.2

Recent developments and outlook

June 2017, Box 1.1

Recent developments and outlook

January 2017, Box 1.1

Recent developments and outlook

June 2016, Box 1.1

Graduation, recent developments, and prospects

January 2015, Chapter 1

Recent developments and outlook

June 2018, Box 1.3

Recent developments and outlook

January 2018, Box 1.3

Recent developments and outlook

June 2017, Box 1.2

Recent developments and outlook

January 2017, Box 1.2

Recent developments and outlook

June, 2016, Box 1.2

What is potential growth?

January 2018, Box 3.1

Low-income countries

Regional perspectives

Potential growth

Understanding the recent productivity slowdown: Facts and explanations January 2018, Box 3.2
Moving together? Investment and potential output

January 2018, Box 3.3

The long shadow of contractions over potential output

January 2018, Box 3.4

Productivity and investment growth during reforms

January 2018, Box 3.5

East Asia and PacificJanuary 2018, Box 2.1.1

Europe and Central Asia

January 2018, Box 2.2.1

Latin America and the Caribbean

January 2018, Box 2.3.1

Middle East and North Africa

January 2018, Box 2.4.1

South Asia

January 2018, Box 2.5.1

Sub-Saharan Africa

January 2018, Box 2.6.1

Investment developments and outlook: East Asia and PacificJanuary 2017, Box 2.1.1

Europe and Central Asia

January 2017, Box 2.2.1

Latin America and the Caribbean

January 2017, Box 2.3.1

Middle East and North Africa

January 2017, Box 2.4.1

South Asia

January 2017, Box 2.5.1

Sub-Saharan Africa

January 2017, Box 2.6.1

Recent investment slowdown

Regional integration and spillovers
East Asia and PacificJanuary 2016, Box 2.1.1

Europe and Central Asia

January 2016, Box 2.2.1

Latin America and the Caribbean

January 2016, Box 2.3.1

Middle East and North Africa

January 2016, Box 2.4.1

South Asia

January 2016, Box 2.5.1

Sub-Saharan Africa

January 2016, Box 2.6.1

157

158

S E L E CTE D TO P I C S

G L O B A L E CO N O MI C P R OS P E C TS | J U NE 2 0 18

Global Economic Prospects: Selected Topics, 2015-18
Growth and Business Cycles
Other topics
Long-term growth prospects: Downgraded no more?

June 2018, Box 1.1

Education demographics and global inequality

January 2018, SF 2

Weak investment in uncertain times: Causes, implications and policy responses

January 2017, Chapter 3

Implications of rising uncertainty for investment in EMDEs

January 2017, Box 3.2

Implications of the investment slowdown in China

January 2017, Box 3.3

Interactions between public and private investment

January 2017, Box 3.4

Quantifying uncertainties in global growth forecasts

June 2016, SF 2

Who catches a cold when emerging markets sneeze?

January 2016, Chapter 3

Sources of the growth slowdown in BRICS

January 2016, Box 3.1

Understanding cross-border growth spillovers

January 2016, Box 3.2

Within-region spillovers

January 2016, Box 3.3

Recent developments in emerging and developing country labor markets

June 2015, Box 1.3

Linkages between China and Sub-Saharan Africa

June 2015, Box 2.1

What does weak growth mean for poverty in the future?

January 2015, Box 1.1

What does a slowdown in China mean for Latin America and the Caribbean?

January 2015, Box 2.2

How resilient is Sub-Saharan Africa?

January 2015, Box 2.4

Commodity Markets
The role of the EM7 in commodity production

June 2018, SF1, Box SF1.1

Commodity consumption: Implications of government policies

June 2018, SF1, Box SF1.2

With the benefit of hindsight: The impact of the 2014–16 oil price collapse

January 2018, SF1

From commodity discovery to production: Vulnerabilities and policies in LICs

January 2016, Chapter 1

After the commodities boom: What next for low-income countries?

June 2015, Chapter 1, SF

Low oil prices in perspective

June 2015, Box 1.2

Understanding the plunge in oil prices: Sources and implications

January 2015, Chapter 4

What do we know about the impact of oil prices on output and inflation? A brief survey

January 2015, Box 4.1

Globalization of Trade and Financial Flows
Arm’s-Length trade: A source of post-crisis trade weakness

June 2017, SF

The U.S. economy and the world

January 2017, SF

Regulatory convergence in mega-regional trade agreements

January 2016, Box 4.1.1

Can remittances help promote consumption stability?

January 2016, Chapter 4

Potential macroeconomic implications of the Trans-Pacific Partnership Agreement

January 2016, Chapter 4

Regulatory convergence in mega-regional trade agreements

January 2016, Box 4.1.1

China’s integration in global supply chains: Review and implications

January 2015, Box 2.1

What lies behind the global trade slowdown?

January 2015, Chapter 4

G L O B A L E CO N O MI C P R OS P E C TS | J U NE 2 0 18

S E L E CTE D TO P I C S

Global Economic Prospects: Selected Topics, 2015-18
Monetary and Exchange Rate Policies
Corporate Debt: Financial Stability and Investment Implications

June 2018, SF2

Investment-less credit booms

January 2017, Box 3.1

Recent credit surge in historical context

June 2016, SF1

Peg and control? The links between exchange rate regimes and capital account policies

January 2016, Chapter 4

Negative interest rates in Europe: A glance at their causes and implications

June 2015, Box 1.1

Hoping for the best, preparing for the worst: Risks around U.S. rate liftoff and policy options

June 2015, SF1.1

Countercyclical monetary policy in emerging markets: Review and evidence

January 2015, Box 1.2

Fiscal Policies
Debt dynamics in emerging market and developing economies: Time to act?

June 2017, SF

Having fiscal space and using it: Fiscal challenges in developing economies

January 2015, Chapter 3

Revenue mobilization in South Asia: Policy challenges and recommendations

January 2015, Box 2.3

Fiscal policy in low-income countries

January 2015, Box 3.1

What affects the size of fiscal multipliers?

January 2015, Box 3.2

Chile’s fiscal rule—An example of success

January 2015, Box 3.3

Narrow fiscal space and the risk of a debt crisis

January 2015, Box 3.4

Development Economics Prospects Group (DECPG):
Selected Other Publications on the Global Economy, 2015-18
Commodity Markets Outlook

Column1

Oil Exporters: Policies and Challenges

April, 2018, SF

Investment weakness in commodity exporters

January 2017, SF

OPEC in historical context: Commodity agreements and market fundamentals

October 2016, SF

Energy and food prices: Moving in tandem?

July 2016, SF

Resource development in an era of cheap commodities

April 2016, SF

Weak growth in emerging market economies: What does it imply for commodity markets?

January 2016, SF

Understanding El Niño: What does it mean for commodity markets?

October 2015, SF

How important are China and India in global commodity consumption

July 2015, SF

Anatomy of the last four oil price crashes

April 2015, SF

Putting the recent plunge in oil prices in perspective

January 2015, SF

High-Frequency Monitoring

Column1

Global Monthly newsletter
Global Weekly newsletter

159

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G

lobal growth remains robust in 2018 but is expectedto ease over the next two years and, over the longer-term,
further as potential growth softens. Emerging market
and developing countries face considerable risks, such asincreased protectionism and disorderly financial market
movements, as well as major structural challenges,
including those related to competitiveness, adaptability
to new technologies, and global integration to boost
long-term prospects.
In addition to discussing global and regional economic
developments and prospects, this edition of Global
Economic Prospects includes two Special Focus essays ofcritical importance for emerging and developing economies:
an analysis of their increasing role in global commodity
markets, and an assessment of their corporate debt burdens.
Global Economic Prospects is a World Bank Group Flagship
Report that examines global economic developments andprospects, with a special focus on emerging market anddeveloping countries, on a semiannual basis (in January andJune). The January edition includes in-depth analyses of
topical policy challenges faced by these economies, while
the June edition contains shorter analytical pieces.

ISBN 978-1-4648-1257-6
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