The informal sector: Compounding the damage of Covid-19

M. Ayhan Kose, Franziska Ohnsorge, Shu Yu 27 January 2022

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The informal sector on average accounts for about one-third of GDP and employment in emerging market and developing economies (EMDEs) (Figure 1). The livelihoods of the poor in many of these economies depend on informal economic activity (Kanbur and Keen 2015, Dix-Carneiro et al. 2021). Three features of the informal sector have compounded the damage of Covid-19 on activity: (i) their predominant presence in the service sector, (ii) limited savings and access to social safety nets, and (iii) the lack of effective policy support (Ohnsorge and Yu 2021). Widespread informality now threatens to hold back the recovery in EMDEs. 

Figure 1 Informality in emerging market and developing economies

   

Sources: Elgin et al. (2021a).
Note: Bars are simple averages. Informal output is proxied by dynamic general equilibrium (DGE) model-based estimates in percent of official GDP. Self-employment shares are in percent of total employment. Orange lines represent world averages between 1990-2018.

Significant impact of Covid-19 on the informal sector

The pandemic hit the informal sector particularly hard, especially in EMDEs (World Bank 2020, Goldfajn and Yeyati 2021). The lockdowns that closed most of service sector activities affected informal firms the most as they are over-represented in these sectors. While less than one-third of firms in the manufacturing sector are informal, about three quarters of firms in service sectors are informal. In a sample of ten countries with available data, informal employment losses were two to three times larger than job losses among formal employees in mid-2020 and, in contrast to job losses among formal employees, they were not fully reversed by mid-2021 (ILO 2022). 

Adverse income shocks are hard for informal workers to weather, largely due to their lower earnings, their lack of access to social insurance programs, and their limited savings (Ohnsorge and Yu 2021). Unemployment benefits only cover about 4% of the population in EMDEs with above-median informality, significantly less than in other EMDEs (Figure 2). About two-fifths of the population in EMDEs with above-median informality would be driven into poverty if they had to cover direct out-of-pocket payments for an unexpected health care emergency – such as a Covid-19 hospitalisation.

Figure 2 Social insurance

Source: World Bank, World Development Indicators.
Note: *** indicates the group differences are not zero at 10% significance level. Bars are simple group mean for EMDEs. “Above-median informality” is the highest half of EMDEs and “below-median informality” is the lowest half over 1990-2018. Adequacy of social insurance programs is measured in percent of the total welfare of beneficiary households.

Informality constraining policy support

Pervasive informality has also constrained the governments’ ability to provide policy support. Fiscal support packages were smaller in countries with high informality than elsewhere. On average, on-budget fiscal support in EMDEs in the upper quartile by employment informality was 1.5 percentage points of GDP below in those in the lower quartile by employment informality (Figure 3). In part, that may have reflected the inability of EMDEs with pervasive informality to generate sufficient government revenues (World Bank 2019) (Figure 4). 

Figure 3 Fiscal support

  

Sources: Elgin et al. (2021a), IMF (2021). 
Note: Bars are simple averages of on-budget additional spending or foregone revenues in response to COVID-19 in percent of GDP since January 2020, which will cover implementation in 2020, 2021, and beyond. “High informality” and “Low informality” are the quarter of EMDEs with the highest and lowest informality by self-employment in percent of total employment averaged over the period 2000-18. *** indicates significantly higher values at least at the 10% level.

Figure 4 Government revenues and expenditures

Sources: World Development Indicators, International Monetary Fund (Government Finance Statistics), Ohnsorge and Yu (2021).
Notes: Bars show simple averages for emerging market and developing economies (EMDEs; with populations above 3.5 million) with above-median (below-median) output informality. Informality is proxied by dynamic general equilibrium (DGE)-based estimates of informal output in percent of GDP. All fiscal indicators and informality measures are from 2000-18. “***” indicates the group differences are not zero at 10% significance level.

In addition, monetary stimulus, which usually works through the formal financial system, struggles to gain traction when informality is widespread. Formal financial systems tend to be shallower in EMDEs with larger informal sectors (Figure 5). For example, fewer than 20% of firms in EMDEs with above-median informality were able to use banks to finance their investment – almost ten percentage points less than in EMDEs with below-median informality. 

Figure 5 Firms’ access to bank finance

  

Source: Ohnsorge and Yu (2021).
Note: Bars show the (simple) average shares of firms using banks to finance investment for EMDEs with above-median (below-median)  informality over the period 2000-18. *** denotes that the group differences are not zero at 10 percent significance level. 

Informality dampening cycles

The cyclical behaviour of the informal economy raises additional concerns. Historically, output informality has tended to undergo business cycles just like the formal economy (Elgin et al. 2021b). When these cycles are triggered by disruptions in the formal economy, informal economy output tends to move in the same direction as formal economy output, but in a more muted manner. Specifically, a 1% cyclical shock to formal output raises informal output less than proportionately, by about 0.8 percentage points. 

These findings suggest that, historically at least, informality may have been a blessing during recessions by dampening downturns. In recoveries, however, the blessing appears to have turned into a curse by holding back expansions. This implies that widespread informality may now hold back the recovery from the pandemic in EMDEs.

Policy implications

Informality adds to the challenges of dealing with the pandemic and ensuring a robust recovery. Fiscal resources need to be used to strengthen the public health system to contain and treat the virus and support the livelihoods of informal sector participants during Covid-19 outbreaks (Djankov and Panizza 2020). Existing safety nets, including those with deep reach into informal sectors (e.g. food aid or in-kind transfers) can be broadened to support activity in these sectors. Larger policy support and complementary measures might be required in countries with more widespread informality because of the greater increases in unemployment, poverty, and inequality they experienced (Cuesta and Hannan 2021). 

More innovative measures may be needed to support informal workers and informal firms. Short-term relief measures should be balanced with long-term development policies. Some of these policies may also lay the foundation for more comprehensive reforms to strengthen social safety nets for future crises: 

  1. Utilise flexible platforms and technologies to reach informal workers. Existing national social registries, as well as new online platforms, mobile payment devices, and databases involving health and energy sectors, have been used during the pandemic to reach vulnerable populations with support (World Bank 2020, Bosio et al. 2020). 
  2. Facilitate access to finance to informal firms. Governments could work with the bank and nonbank financial sectors to facilitate access to credit during times of economic stress (CGAP 2020). The collateralisation of property (and other assets) and online or mobile banking could help owners of informal firms to tap financial resources.
  3. Keep the relief broad-based but for an appropriate period. In EMDEs where informality is pervasive and most of the population is either poor or near-poor, cash transfers may be the best response in the short-run (Furceri et al. 2020). Simple untargeted transfers instead of carefully targeted transfers can be considered during times of severe economic stress. However, prolonged relief runs the risk of overheating the economy during the recovery and may burden government budgets.
  4. Building back better. Facilitating the progress in digitalisation would allow informal participants to adapt their economic activities more quickly to future crises (Goldfajn and Yeyati 2021). Government agencies could better identify gaps in the safety net and integrate data from various sources to understand where people and firms need support the most before the next crisis (CGAP 2020). The shifting patterns of work caused by the pandemic, such as the rise in the gig, temporary, and remote work arrangements, have additional policy implications for labour markets (ILO 2022).

Authors’ note: The findings, interpretations, and conclusions expressed in this column are entirely those of the authors. They do not necessarily represent the views of the World Bank, its Executive Directors, or the countries they represent.

References

Bosio, E, F Jolevski, J Lemoine and R Ramalho (2020), “Survival of Firms in Developing Economies during Economic Crisis”, in S Djankov and U Panizza (eds.), COVID-19 in Developing Economies, a VoxEU.org eBook, CEPR Press.

CGAP (2020), “Relief for Informal Workers: Falling through the Cracks in the COVID-19 Crisis”, Washington DC: CGAP.

Cuesta, J P and S A Hannan (2021), “Recovering from Pandemics: Policies and Structural Features Matter”, VoxEU.org, 12 August.

Djankov, S and U Panizza (2020), COVID-19 in Developing Economies, a VoxEU.org eBook, CEPR Press.

Dix-Carniero, R, P Goldberg, C Meghir and G Ulyssea (2021), “Informality and the Effect of Trade in Developing Countries”, VoxEU.org, 5 March.

Elgin, C, M A Kose, F Ohnsorge and S Yu (2021a), “Understanding Informality”, CEPR Discussion Paper 16497.

Elgin, C, M A Kose, F Ohnsorge and S Yu (2021b), “Growing Apart or Moving Together? Synchronization of Informal and Formal Economy Cycles”, CEPR Discussion Paper 16498.

Furceri, D, P Loungani, J Ostry and P Pizzuto (2020), “Pandemics and Inequality: Assessing the Impact of COVID‑19”, in S Djankov and U Panizza (eds.), COVID-19 in Developing Economies, a VoxEU.org eBook, CEPR Press.

Goldfajn, I and E Yeyati (2021), Latin America: The Post-Pandemic Decade, a VoxEU.org eBook, CEPR Press.

ILO (2022), World Employment and Social Outlook (Trends 2022), Geneva: International Labour Organization.

IMF (2021), Fiscal Monitor Database of Country Fiscal Measures in Response to the COVID-19 Pandemic, Washington, DC: International Monetary Fund.

Kanbur, R and M Keen (2015), “Rethinking Informality”, VoxEU.org, 5 June.

Ohnsorge, F and S Yu (2021), The Long Shadow of Informality: Challenges and Policies, Washington, DC: World Bank.

World Bank (2019), Global Economic Prospects 2019 January: Darkening Skies, Washington, DC: World Bank.

World Bank (2020), Global Economic Prospects 2020 June, Washington, DC: World Bank.

World Bank (2022), Global Economic Prospects 2022 January, Washington, DC: World Bank.

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Topics:  Covid-19 Development Labour markets

Tags:  COVID-19, informality, emerging markets, social insurance, developing countries

Chief Economist of EFI and Director of Prospects Group, World Bank

Manager of the Prospects Group in the Equitable Growth, Finance, and Institutions Vice Presidency of the World Bank

Post-doc, University of Rochester / PhD, University of Groningen

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