Economics Research RA: Labor market implications of COVID-19 in India

Covid-19 is expected to lead to the first increase in global poverty in the 21st century. A large share of this increase will come from India. Low skilled workers, who typically lost their jobs during lockdown, are particularly vulnerable to falling back into poverty. Estimates suggest that close to ten million people returned from their workplace to their village during or just after the lockdown.

This research project examines the evolution of labor market outcomes of low skilled Indian workers in the aftermath of Covid-19 and seeks to identify public policies that can ease their integration back into the labor market. A central focus is on labor market impacts for members of historically disadvantaged social groups, especially women. We have survey data on the evolution of labor market and economic outcomes of return migrants in two North Indian states and administrative data on participation in workfare program in the villages that the rural migrants have returned to. Over the next year, we will use a combination of additional surveys and administrative data to identify how individual characteristics (including skills, previous job) and location characteristics (both where the migrant was based and his/her return village) influence labor market outcomes. We are particularly interested in predictors of upward or downward mobility induced by Covid-19 and how local job markets and public policy affect this.

The candidate selected for this RA-ship will work with both survey and administrative datasets and also help identify and collate primary data from multiple sources. across one or more COVID-19/migrants-focused studies to answer questions focused on how to increase migrants’ economic well-being and economic activity, and to understand the labor market implications of the pandemic in India. This position is data heavy and may require the selected candidate to access, process and clean large administrative data sets; develop code to track primary data quality for ongoing survey data collection; process and clean survey data; code and/or produce tables or figures such as heat maps from primary or secondary data. The project is collaborative involving researchers at Yale, other universities and India.