in Differences Estimates

though employment rates are close to pre-COVID levels, the quality of the employment recovery may not be the same.

Figure 7.4, panel b, displays the estimated differential impacts of the pandemic among self-employed individuals. The difference in the probability of job loss is much smaller and, in fact, is not statistically different from zero among the self-employed.

Estimates of the results of equation 7.1 using per capita household income as the dependent variable are presented in annex 7A, table 7A.3. Figure 7.5 displays the estimated differential impacts on informal households (panel a) and self-employed households (panel b). As with figure 7.4, the point estimates plotted in figure 7.5 correspond to the regression specification with household, district-month, and industry-month fixed effects (annex 7A, table 7A.3, column 3).

Consider first the early COVID-19 period (until May 2020). Like employment, there is a large overall negative impact on per capita household income, with an additional penalty among informal workers. The incomes of formal and informal workers fell by 59 percent and 78 percent, respectively, by April 2020 relative to February 2020 (see annex 7A, table 7A, column 1, which only controls for household fixed effects). This larger loss among informal households, as in the case of employment, partly arises

FIGURE 7.5 Pandemic Impact on Per Capita Household Income: Difference in Differences Estimates

Source: based on CPhS data. Note: The difference in differences estimates include household, district × month, and industry × month fixed effects. informal and self-employed denotes employment status of the household head as of december 2019. Standard errors are clustered at the household level. N = 4,623 households. The dependent variable is the log of total per capita household income.

because informal workers are concentrated in industries and occupations that are more widely affected by the COVID crisis: the magnitude of the coefficient on Informal × April 2020 in table 7A.3, column 3, which controls for industry-month and districtmonth fixed effects, is 40 percent lower compared with the magnitude in column 1.

Figure 7.5 highlights the same points discussed in the case of employment.10 Thus, relative to February 2020, the informal-formal income gap was zero before the crisis, but it rose dramatically in April and May 2020. Controlling for industry and occupation reduces the magnitude of this difference. As with employment, there is an equally sharp recovery in household incomes. In fact, informal households recovered more quickly than formal workers. Controlling for district-month and industry-month fixed effects, the estimated informal-formal income difference in June, July, and August 2020 (relative to February 2020) is positive and statistically significant. In other words, the incomes of informal households relative to formal worker incomes had improved from the preCOVID baseline.

RURAL-URBAN DIFFERENCES IN THE IMPACTS ON FORMAL AND INFORMAL WORKERS

Rural and urban areas both experienced unprecedented employment loss in the early COVID-19 period, but there is limited evidence on the differential incidence of the shock in rural areas relative to urban areas. A regression analysis conducted separately on the rural and urban subsamples indicates that the observed differential impact of the COVID-19 shock on the informal sector was driven by urban areas.

First, consider how the estimated differential employment impact in urban areas mirrors the impact on the overall sample (annex 7A, table 7A.4). The regression specification without any wave-specific fixed effects (column 1) establishes a sharp increase in the probability of job loss among each employment group in urban areas in April relative to December 2019. The estimated decline among formal workers (the reference group) is 13 percentage points, with an additional decline of 26 percentage points among informal wage workers. This differential is no longer significant by August and December 2020. This result is robust to the inclusion of wave-specific industry, occupation, and district effects.

The income impact in urban areas, too, is similar to the impact observed on the overall sample (annex 7A, table 7A.5). Relative to February 2020, the estimated difference in the per capita income of households headed by informal and formal wage workers is significantly negative in April and May 2020 and significantly positive in June and August 2020.

There was a sharp increase in the probability of job loss in April 2020 in rural areas as well. The decline among the reference group is estimated at 26 percentage points (annex 7A, table 7A.6, column 1). In this case, however, the differential between informal and formal wage workers (as well as the self-employed) is statistically not significant. Moreover, relative to February 2020, the estimated difference in the per capita income of households