The Long Shadow of Informality

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C H A P T ER 5

L O NG S HA D O W O F I N F O R MA L I T Y

Investing in human capital. Policies that expand job training are especially relevant for the young, who are commonly informally employed in MNA, to facilitate their entry into more productive, formal jobs (figure 5.11; Angel-Urdinola and Tanabe 2012). Training programs may be particularly effective if they are coupled with mechanisms to increase women’s mobility, which is constrained in the region, and offer a combination of soft and hard skills (figure 5.11). The extension of training to rural areas, where education levels are low, could also be especially beneficial; the region’s training programs currently tend to serve higher-income and more educated individuals (AngelUrdinola, Semlali, and Brodmann 2010). A holistic approach that combines job training with job creation, such as through public-private sector programs, could boost informal workers’ earnings (Steel and Snodgrass 2008). In MNA, unemployment rates are higher among university graduates than among low-skilled workers. Thus, education system reforms that are coupled with private sector development (the demand side of the labor market) may be more effective at generating high-quality employment.

South Asia Employment informality in SAR is pervasive. SAR is home to the highest number of informal workers among the six EMDE regions, accounting for close to two-fifths of the world total. Output informality has declined in recent decades, however. Low labor productivity is a long-standing feature of the region’s informal sector. The pervasiveness of employment informality reflects large artisanal and agricultural sectors and the dominance of micro and small business units, often family businesses. High unemployment among the low-skilled, rural, female, and young populations pushes workers into the informal sector. High informality in the region is also associated with weak institutions and poor business climates. Policies that focus on improving the business environment and addressing skills gaps in vulnerable groups can help promote movement to the formal sector. Evolution of informality in SAR Informal employment in SAR (measured by self-employment) was 59 percent of total employment in 2010-18, the second highest among all EMDE regions, and well above the EMDE average of 42 percent. However, employment informality has also declined the most of any region since the 1990s (figure 5.12). Using an alternative measure, lack of basic pension coverage, about 90 percent of the labor force in SAR works informally. Although there is evidence that the COVID-19 pandemic has been accompanied by a movement of formal workers into the informal sector, informal workers were more vulnerable to loss of employment in the early stage of the pandemic, when lockdown measures were most stringent (World Bank 2020d). In India, lockdown measures are estimated to have tripled the urban unemployment rate in the early stages of the pandemic. The income losses associated with these lost jobs were exacerbated by the fact that some 60-85 percent of urban workers had no access to social protection benefits,


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References

17min
pages 344-353

Annex 6A Policies and informality

3min
pages 323-324

Fiscal measures

2min
page 301

Data and methodology

2min
page 300

6.1 Financial development and the informal economy

9min
pages 290-294

6.8 Informality after labor market reforms in EMDEs

2min
page 313

Conclusion

2min
page 271

References

20min
pages 272-284

Conclusion

2min
page 319

Latin America and the Caribbean

2min
page 251

South Asia

2min
page 260

Sub-Saharan Africa

4min
pages 264-265

Middle East and North Africa

2min
page 255

Europe and Central Asia

2min
page 246

East Asia and Pacific

2min
page 241

Informality in EMDEs

2min
page 237

References

24min
pages 222-234

4D.7 Regression: Changes in informality and poverty reduction

2min
page 208

competition

2min
page 206

4D.8 Regression: Changes in informality and improvement in income inequality

1min
page 209

4D.14 Regression: Developmental challenges and DGE-based output informality in EMDEs

5min
pages 216-218

Annex 4C Bayesian model averaging approach

4min
pages 200-201

4D.4 Regression: Labor productivity of formal and informal firms 4D.5 Regression: Labor productivity of formal firms facing informal

1min
page 205

Annex 4B Regression analysis

2min
page 199

Annex 4A Meta-regression analysis

2min
page 198

Informality and SDGs related to human development

2min
page 191

Informality and SDGs related to infrastructure

2min
page 193

4.3 Informality, poverty, and income inequality

5min
pages 180-182

Informality and institutions

2min
page 189

Finding the needle in the haystack: The most robust correlates

2min
page 195

Conclusion

1min
page 197

Informality and economic correlates

2min
page 179

4.2 Casting a shadow: Productivity in formal and informal firms

4min
pages 167-168

Links between informality and development challenges

2min
page 165

4.1 Informality and wage inequality

8min
pages 158-161

References

6min
pages 147-152

Conclusion

2min
page 136

Data and methodology

2min
page 129

Literature review: Linkages between formal and informal sectors

6min
pages 126-128

References

13min
pages 115-122

2B.9 World Values Survey

1min
page 114

2B.8 MIMIC model estimation results, 1993-2018

1min
page 113

Future research directions

2min
page 54

Database of informality measures

14min
pages 81-86

References

10min
pages 55-62

Key findings and policy messages

6min
pages 36-38

Definition of informality

4min
pages 79-80

Conclusion

2min
page 99

Annex 2A Estimation methodologies

9min
pages 100-103

16 Informality indicators and entrepreneurial conditions in Sub-Saharan

2min
page 35
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