Global Productivity

Page 314

288

CHAPTER 5

GLOBAL PRODUCTIVITY

FIGURE 5.13 Drivers of productivity growth in ECA Investment growth in ECA has fallen in the post-GFC period, reflecting external headwinds, such as a commodity price plunge, and idiosyncratic factors, including conflict in pockets of the region and financial pressures in large economies. The workforce is aging, and the working-age share of the population is declining. The role of the state remains large, and control of corruption weak. A. Investment growth: Actual vs. Consensus Economics forecasts Percent 15

Current 10-year Consensus forecast

B. Share of regional GDP accounted for by economies with growing working-age populations Percent 100

ECA ECA excl. Russian Federation and Turkey

75

10 50

5

25 0

0 2003-08 average

C. Assessment of transition to a competitive market economy, 2019 Index, 10 = Frontier 8

1995-99

2013-18 average

Min-max range

Median

6

2003-08

2013-19

2020-22

D. Control of corruption, 2017 Interquartile range

Index 0.5

Average

0.0

4 -0.5

2

-1.0

South Caucasus

Eastern Europe

Central Asia

Western Balkans

Central Europe

ECA

0

-1.5 EMDEs

ECA

WBK and EE, SC, and CE CA

Sources: Consensus Economics; European Bank for Reconstruction and Development; Kraay (2018); United Nations; World Bank. Note: CA = Central Asia; CE = Central Europe; ECA = Europe and Central Asia; EE = Eastern Europe; EMDEs = emerging market and developing economies; GFC = global financial crisis; SC = South Caucasus; WBK = Western Balkans. A. Investment is measured as gross fixed capital formation. Actual growth aggregate calculated using GDP weights at 2010 prices and market exchange rates. Consensus forecasts aggregate calculated as a simple average of surveys for periods indicated based on data availability. Unbalanced sample includes 8 ECA economies because of data availability. B. The working-age population is defined as people ages 15-64. Unbalanced sample includes 23 ECA economies. C. Figure shows the distance to the frontier for achieving a full transition to a competitive market economy, as measured by EBRD (2019). Economies with higher index levels are closer to the frontier, where scores range from 1 to 10, with 10 denoting the synthetic frontier. Sample includes 24 ECA economies. D. The indicator reflects perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as “capture” of the state by elites and private interests, as measured by the Worldwide Governance Indicators. Index is on a scale of -2.5 (weak) to 2.5 (strong). Sample includes 23 ECA economies and 150 EMDEs.

Human capital development in ECA, however, is likely to slide as a result of the COVID-19 pandemic because of severe disruption to schooling at all levels, which has affected nearly 90 million schoolchildren. In previous crises, the number of out-of-school children doubled in some ECA countries despite declining demographic trends, and income disparities increased as vulnerable groups faced higher rates of dropout and depressed skills development (Shmis et al. 2020). Extended school closures are expected to reduce the learning-adjusted years of schooling in ECA from 10.4 years to between


Turn static files into dynamic content formats.

Create a flipbook

Articles inside

Annex 7B Marginal productivity gap

4min
pages 452-453

References

14min
pages 456-463

Annex 7A Data and methodology

6min
pages 448-451

References

13min
pages 421-428

Sectoral productivity gaps

2min
page 432

Annex 7C Firm TFP data, estimates, and methodology

5min
pages 454-455

Annex 6C Commodity-driven productivity developments: Methodology

2min
page 420

Conclusion and policy implications

2min
page 412

Drivers of productivity: Technology vs. demand shocks

2min
page 391

Annex 6A SVAR identification of technology drivers of productivity

8min
pages 413-416

PART III Technological Change and Sectoral Shifts

0
pages 383-386

Effects of demand shocks

2min
page 397

Figure 6.1 Global labor productivity surges and declines

7min
pages 388-390

Sub-Saharan Africa

2min
page 350

Figure 5.22 Factors supporting productivity growth in MNA

7min
pages 333-335

Figure 5.19 Drivers of productivity growth in LAC

9min
pages 325-328

South Asia

4min
pages 337-338

Conclusion

2min
page 363

Figure 5.13 Drivers of productivity growth in ECA

10min
pages 314-317

Middle East and North Africa

2min
page 329

Latin America and the Caribbean

2min
page 318

Figure 5.12 Drivers of productivity growth in ECA in regional comparison

5min
pages 312-313

Europe and Central Asia

2min
page 305

Figure 5.7 Drivers of productivity growth in EAP

3min
page 301

PART II Regional Dimensions of Productivity

0
pages 281-284

Sources of, and bottlenecks to, regional productivity growth

4min
pages 290-291

Figure 5.1 Evolution of regional productivity in EMDE regions

4min
pages 288-289

East Asia and Pacific

2min
page 295

References

12min
pages 274-280

Evolution of productivity across regions

2min
page 287

Annex 4F Productivity measurement: PPP vs. market exchange rates

4min
pages 268-269

Annex 4C Beta-convergence testing

2min
page 257

Figure 4.4 Convergence club memberships

2min
page 242

Annex 4D Estimating convergence clubs: Commonalities in productivity levels

7min
pages 258-260

Testing for convergence and its pace

4min
pages 236-237

Conclusion and policy implications

7min
pages 253-255

Convergence clubs

7min
pages 239-241

Annex 3B Robustness

2min
page 213

Conclusion

2min
page 204

Figure 3.8 Episodes across different types of events

4min
pages 193-194

Annex 3A Data, sources, and definitions

2min
page 206

How has productivity convergence evolved?

2min
page 231

Figure 3.4 Episodes of war

2min
page 187

What policies can mitigate the effects of adverse events?

2min
page 203

Figure 3.5 Correlations between war frequency and productivity growth

7min
pages 188-190

Figure B3.1.1 Severity of pandemics, epidemics, and climate disasters

6min
pages 179-181

Figure B3.1.3 Impact of epidemics

6min
pages 184-186

Annex 2A Partial correlations

2min
page 146

Figure 3.2 Episodes of natural disaster

4min
pages 175-176

Box 3.1 How do epidemics affect productivity?

1min
page 178

Adverse events: Literature and stylized facts

2min
page 171

Conclusion

2min
page 145

Figure 2.13 Developments in financial and government technology

2min
page 143

Figure 2.12 EMDE infrastructure and education gaps

2min
page 142

Policy priorities

4min
pages 140-141

Figure 2.11 Post-GFC slowdown of the drivers of productivity growth

10min
pages 136-139

References

12min
pages 101-108

Analyzing the effects of drivers

1min
page 128

Developments in drivers of productivity

2min
page 134

Figure 2.1 Innovation

5min
pages 114-115

Box 2.1 Review of recent firm-level total factor productivity literature

8min
pages 130-133

Summary of stylized facts

2min
page 126

Long-run drivers

4min
pages 112-113

Box 1.1 Productivity: Conceptual considerations and measurement challenges

9min
pages 85-88

Conclusion

2min
page 96

Annex 1A Cyclical and technology-driven labor productivity developments

1min
page 100

Figure B1.1.1 Labor productivity decomposition and natural capital in EMDEs

7min
pages 89-91

References

13min
pages 65-70

Key findings and policy messages

4min
pages 32-33

Future research directions

2min
page 64

Synopsis

2min
page 39

PART I Productivity: Trends and Explanations

0
pages 71-74

Evolution of productivity

2min
page 78

Sources of the slowdown in labor productivity growth after the GFC

2min
page 83

Implications of COVID-19 for productivity

11min
pages 34-38
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.