in Differences Estimates

FIGURE 7.4 Pandemic Impact on Employment Probability: Difference in Differences Estimates

Source: based on CPhS data. Note: The difference in differences estimates include individual, district × wave, and industry × wave fixed effects. informal and self-employed denotes employment status as of december 2019. Standard errors are clustered at the individual level. N = 7,182 individuals; Prob = probability.

The insights derived from the regression analysis exceed the insights derived by reproducing the patterns observed in the raw data. Figure 7.4 shows the values of the estimated γt × Inf and γt × SelfEmp coefficients (the differential impacts across employment categories) from the preferred specification (table 7A.2, column 3). Figure 7.4, panel a, shows the differential impact of the pandemic on informal wage workers and an easy inspection of pretrends in the outcome variable across informal and formal workers. The identifying assumption is that formal and informal workers were on parallel trends in employment outcomes prior to the pandemic in India and did not experience systematically different idiosyncratic shocks after the pandemic. The lack of pretrends in figure 7.4 confirms that this is a reasonable assumption.

Figure 7.4 also shows that the differential is eliminated almost completely during the recovery period. The point estimates for August and December 2020 cannot be distinguished from zero. In other words, informal workers were exposed to a greater probability than formal workers of losing employment during the peak of the crisis, but they were also able to return to employment during the recovery. By December 2020, their probability of employment was no less than the probability of employment among formal workers. The analysis cannot capture whether the workers regain the same jobs that they had lost in April 2020. Indeed, a large part of the employment gain from June to December 2020 seems to derive from new self-employed jobs. So, even