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7.1 Labor Market Churning Before and During the Lockdown

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Coverage Scenario

Coverage Scenario

FIGURE 7.1 Labor Market Churning Before and During the Lockdown

Source: based on CPhS data. Note: The figure shows transition flows, in percentages, between successive survey waves among the four worker categories in the data. Panel a shows typical transition patterns before the pandemic, between August and december 2019. Panel b shows transitions during the pandemic, between december 2019 and April 2020. See annex 7A, table 7A.1 for the corresponding transition matrix. SelfEmp = self-employed; unem/OlF = unemployed or out of the labor force.

not being employed in April 2020, while those formally employed in December 2019 showed a 28 percent chance of being unemployed or out of the labor force in April 2020.

As indicated by the prepandemic flows illustrated in figure 7.1, panel a, transitions between formal and informal jobs are rare in normal times. In particular, only 1.6 percent of individuals in the informal sector move into the formal sector during a typical four-month interval. Thus, in normal times, informality is a persistent status, and upward mobility is rare. This partly justifies treating informality as a predetermined attribute in the analysis of the COVID shock.

After the lockdown, a strikingly larger share of individuals initially working in the formal sector transitioned into the informal sector or self-employment. Likewise, an unusually large share of individuals initially employed in informal wage jobs transitioned into self-employment. Overall, among individuals in formal or informal wage jobs in December 2019, about 18 percent were in self-employment in April 2020.

Transition matrices for the April 2020–December 2020 period—not presented here for the sake of brevity—show that there was a recovery in aggregate employment after May 2020. However, this aggregate recovery masks ongoing churning across job categories. Individuals continued moving out of formal or informal wage jobs into selfemployment at unusually high rates compared with pre-COVID times. Moreover, an

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