Global Productivity

Page 114

88

CHAPTER 2

GLOBAL PRODUCTIVITY

FIGURE 2.1 Innovation Economies characterized by formal innovation activities—such as more patents per capita and R&D expenditure—tend to grow faster after controlling for the initial productivity level. Measures of innovation are lower in EMDEs than in advanced economies—the number of new patents per capita was six times larger in advanced economies than EMDEs in 2017. Although the gap between advanced economies and EMDEs has been narrowing since 2000, the convergence in patents per capita and R&D expenditure is largely driven by China. A. Productivity growth by innovation activity

B. Innovation activities Patents per million population

Percent 3

600

Advanced economies EMDEs EMDEs ex. China

Percent of GDP 3

2

400

2

1

200

1

0 0

0 1985

Highest

Lowest

Patents per capita

Highest

Lowest

R&D expenditure

2000

2017

Patents per capita

2000

2017

R&D expenditure (RHS)

Sources: United Nations Educational, Scientific and Cultural Organization; World Bank. Note: EMDEs = emerging market and developing economies; R&D = research and development. A. Average annualized labor productivity growth grouped by the initial level of each indicator. “Highest”/“Lowest” group contains countries whose indicator is in top/bottom 25 percent. The effect of initial productivity has been partialled out. See annex 2A for detail. “Patents per capita” is the number of new patent applications per capita. The samples include 32 advanced economies and 74 EMDEs for patents per capita from 1995 to 2018, and 31 advanced economies and 49 EMDEs for R&D expenditures from 2000 to 2018. B. Aggregates are calculated using GDP weights at 2010 prices and market exchange rates. The samples include 23 advanced economies and 37 EMDEs for patents per capita, and 26 advanced economies and 40 EMDEs for R&D expenditures.

Pacific (EAP), rapid output growth has been closely linked to high investment. In the empirical literature, there is a robust cross-section association between the investment rate and labor productivity, which may even have strengthened over time (Beaudry, Collard, and Green 2005). Research based on the nonparametric estimation of global production frontiers, tracking their movement over time, also finds a major role for capital accumulation in productivity growth (Kumar and Russell 2002). Most private sector firms rely on services provided by infrastructure. Investment in infrastructure can complement new technologies, and raise productivity and well-being.4 Infrastructure needs in EMDEs remain high and relate to transport, water and sanitation, power, and telecommunications. Achieving infrastructure-related Sustainable Development Goals in low-income and middle-income countries will require average yearly investment of 2 to 8 percent of GDP during 2015-30 (Rozenberg and Fay 2019; Vorisek and Yu 2020). The contribution of capital accumulation to output growth has been higher for EMDEs than for advanced economies (chapter 1). The quality of labor. The productivity of an economy depends partly on the quality of its labor force, which can be improved in several ways. Other things being equal, a 4 For a discussion of infrastructure investment, see, for example, Aschauer (1989); Calderón, Moral-Benito, and Servén (2015); Martins (2019); Melo, Graham, and Brage-Ardao (2013); and Pereira and Andraz (2013).


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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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