Global Productivity

Page 333

GLOBAL PRODUCTIVITY

CHAPTER 5

307

FIGURE 5.22 Factors supporting productivity growth in MNA Productivity levels relative to advanced economies are the highest in MNA’s capital-intensive mining sector. Evidence for the Arab Republic of Egypt and for Morocco suggests that productivity growth in North Africa has been largely limited to within-sector productivity gains. A. Sectoral productivity levels, 2017 Percent of advanced economy median 160 120

B. Within- and between-sector contributions to productivity growth

MNA

EMDEs

Percentage points 5 4

Construction

Other service

Agriculture

Transport

Utilities

Manufacturing

1

Trade

2

0

Finance

3

40

Mining

80

Within sectors Between sectors

0 -1 1990s 2003-08 2013-17 1990s 2003-08 2013-17 Egypt, Arab Rep.

Morocco

Sources: Groningen Growth Development Center Database; Haver Analytics; International Labour Organization; Penn World Table; World Bank. Note: Productivity is defined as real GDP per worker (at 2010 market prices and exchange rates). Country group aggregates for a given year are calculated using constant 2010 U.S. dollar GDP weights. Data for multiyear spans show simple averages of the annual data. EMDEs = emerging market and developing economies; MNA = Middle East and North Africa. A. Medians across economies in each sector. Horizontal line indicates 50 percent. Sample includes 12 MNA economies. B. The within-sector productivity contribution shows the initial real value added-weighted productivity growth contribution, holding employment share fixed; the between-sector contribution measures the productivity growth from a cross-sectoral shift of employment.

Other drivers of labor productivity growth. Weak productivity in the MNA region has been associated with underdevelopment of the private sector, overreliance on the public sector, and lack of economic diversification (Devarajan and Mottaghi 2015). •

Large public sector. On average, about one-fifth of the region’s workforce is employed in the public sector, and public-private sector wage gaps are among the highest in the world (Purfield et al. 2018; Tamirisa and Duenwald 2018). The education system is targeted toward government employment, with few high-quality private sector jobs (World Bank 2018k). These dynamics hold back the adoption of technology from abroad (Mitra et al. 2016; Raggl 2015; Samargandi 2018). In the GCC, weak productivity growth has been associated with low mobility of highskilled foreign workers (Callen et al. 2014).

Restrictive business climate. Poor governance quality, large informal sectors, and cumbersome tax policy and administration hampered the reallocation of resources from low-productivity to higher-productivity firms (Nabli 2007; World Bank 2016d). Non-GCC economies in MNA rank especially low in the World Bank’s Worldwide Governance Indicators, such as regulatory quality and government effectiveness. Private firms often face challenges in access to finance, yet providing access to formal finance is associated with labor productivity growth being 2 percentage points higher in MNA firms (Blancher, Bibolov, and Fouejieu 2019).

Anemic private sector. Firm productivity in MNA has been restricted by low firm turnover and creation. Only six limited liability companies were created annually for


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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
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