Global Productivity

Page 412

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CHAPTER 6

GLOBAL PRODUCTIVITY

Conclusion and policy implications This chapter offers several novel findings. First, long-term, “technological” drivers of productivity have accounted for a considerable portion of labor productivity variation since 1980: for about 40 percent of the 1-year-ahead forecast error variance of labor productivity and 60-75 percent of the 5- to 10-year-ahead forecast error variance. Second, employment has typically fallen, at least initially, after technology-driven productivity improvements. These employment losses were larger but less persistent in advanced economies than in EMDEs. Third, although demand shocks may unwind faster than technology shocks, their impact on productivity can be long-lasting. These findings point to two policy priorities. Although technological progress is generally beneficial in the long term, it may initially be disruptive to employment (Arntz, Gregory, and Zierahn 2016; Autor 2015; World Bank 2019). The appropriate policy response is three-pronged: first, policies to encourage and support the training and retraining of workers to equip them with the skills required by new technologies; second, policies to mitigate the negative effects on transitioning workers; and, third, demand management to maintain full employment. The COVID-19 pandemic and resulting global recession may trigger another wave of restructuring and technological innovation, as firms adjust to social distancing and new restrictions on doing business or search for efficiency savings to remain competitive. EMDEs, in particular, will need to ensure that workers are equipped with skills to complement new technologies, rather than be replaced by them (World Bank 2018a). Universities, vocational training facilities, on-the-job training, and continued learning are often underprovided in many EMDEs, and there are potentially high social returns to their expansion. Many EMDEs also need to make improvements at earlier stages of education in order to build a foundation for the more advanced education that will enable workers to adapt to skill requirements associated with new technologies (World Bank 2018a, 2019). Adequate social protection can help those displaced by technological change to transition into new industries. For example, in LICs, fewer than 20 percent of workers are covered by social insurance, in part because of large informal sectors in these economies (World Bank 2019). Encouraging private savings, including through initiatives that expand financial inclusion, and expanding unemployment insurance programs in the formal and informal sectors can strengthen the safety net. The lasting productivity damage that even short-term demand shocks can cause calls for room to allow active deployment of fiscal and monetary policy to support activity. This will require the shoring up of fiscal positions once economic recovery from the pandemic is well established, a strengthening of monetary and fiscal policy frameworks, and effective supervision and regulation to ensure a resilient financial system (chapter 1; Kose et al. 2020). For commodity exporters, the creation or expansion of sovereign wealth funds, as well as better prioritization of spending, could help avoid procyclical spending in response to commodity price fluctuations (Mohaddes and Raissi 2017).


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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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