Labor market implications of COVID-19 in India

Faculty Member: 

Award:
Neil Himwich

Proposal Description:

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, where some of the hardest-hit by the pandemic have been low-skilled migrant workers. Tens of millions of these low-wage workers lost their jobs during multiple pandemic-induced lockdowns, when they left cities en masse, returning to rural villages to make ends meet. Even as the pandemic continues, these individuals seek to rebuild their lives, both in rural villages and through returning to cities.
This research project examines the evolution of labor market outcomes among low-skilled Indian migrant workers in the aftermath of Covid-19 and seeks to identify public policies that can ease their integration back into labor markets. A central focus is on labor market impacts for members of historically disadvantaged social groups, including women. We are collecting survey data to understand the evolution of labor market and economic outcomes of migrants that returned home to rural villages 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 surveys and administrative data to identify how individual characteristics (including skills, previous job, and migrant demographic characteristics) and location characteristics (both where the migrant was based and his/her return village) relate to 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 will also help identify and collate primary data from multiple sources for our 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 and involves researchers at Yale, other universities and India.

Requisite Skills and Qualifications:

The RA will write code to clean and process survey and/or administrative data, potentially conducting initial analysis and presenting summary statistics or related output in tables and graphs. He/she will also review data sources and potentially collate primary data from websites, and s/he may conduct desk-based research and writing to explore the feasibility of specific research ideas. The potential RA should have skill and experience using econometrics software such as R or STATA to run econometric analysis. Hindi skills are valuable.