Global Productivity

Page 213

GLOBAL PRODUCTIVITY

CHAPTER 3

187

ANNEX 3B Robustness Mismeasurement caveats. The literature has identified several issues surrounding the reporting of adverse events. Natural disasters, physical damages, and the number of deaths may be underestimated in areas with limited natural disaster monitoring systems or overreported to secure foreign aid (Albala-Bertrand 1993). In addition, there are well-known measurement issues—particularly for LICs—pertaining to the effects of the informal sector (Jennings 2011; Kousky 2014), the lack of accounting of reconstruction (Raddatz 2009), or the effects of insurance (Felbermayr and Gröschl 2014). However, measurement has been improved by increasingly sophisticated methods for reporting natural disasters, including advanced satellite imagery (Voigt et al. 2007). Productivity is prone to measurement issues as well. Any measurement issues in variables used in the estimation of labor productivity (output and employment) and TFP (output, employment, and capital) would be reflected in those productivity measures. It is especially important in countries where services and government sectors account for a large share of the economy because of the difficulties in appropriate measurements of those sectors. Data quality, especially in EMDEs, might include imputed estimations and may be poor beyond the general measurement issues such as the difficulty in taking into account various work arrangements in measuring labor input (Brandolini and Viviano 2018; Katz and Krueger 2016). Measurement of capital inputs is complicated because of its large heterogeneity in various aspects such as tangible vs. intangible, short lived vs. long-lived assets (Hulten 2010). The capital input measure used in this study is from Penn World Table 9.1 and accounts for different types of assets on the basis of their life span (Inklaar, Woltjer, and Gallardo 2019). Endogeneity and simultaneity between events. An adverse event may be triggered by other negative shocks. This raises endogeneity concerns when estimating the impact of an adverse event on productivity. Natural disasters can fuel political unrest and conflicts, further damaging the productive capabilities of affected countries (Brancati 2007; Cavallo et al. 2013b; Nel and Righarts 2008). Financial crises and adverse external shocks, such as sharp declines in trade or commodity prices, can precipitate conflicts and wars, and lead to severe productivity and output losses (Reynaerts and Vanschoonbeek 2018). Both wars and natural disasters can lead to rapid debt accumulation, which is often associated with financial crisis (Kose et al. 2020). Among the three types of events explored in this chapter, natural disasters seem the most immune to these endogeneity issues. Endogeneity with productivity. Natural disasters are in all likelihood not caused by changes in productivity.37 However, endogeneity concerns may arise in the analysis of financial crises and wars. Subdued productivity growth may contribute to a financial

37 Even though economic activity is linked to greenhouse gas emissions and climate change, the global spatial and long temporal scale means that productivity has no impact on climate over the time scales considered in this chapter.


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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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