G2LM|LIC - COVID-19 Returned Indian Migrant Panel
Data Set Description
On March 24, 2020, the Indian Government announced a nationwide lockdown to curb the spread of Covid-19, effective with a few hours of notice. For an estimated 40 million migrant workers in the country, this resulted in loss of income, food shortages, and uncertainty about the future. Over 10 million returned to rural homes in one of the largest internal migrations in the country's history. Once returned, they faced stays in government-run quarantine centers, stigma, and uncertain labor prospects. Over the next year, migrants navigated shifting mobility restrictions aimed at mitigating the spread of the pandemic, widespread outbreaks, and patchwork of social protection schemes in order to make ends meet.
In order to understand the long-term labor and well-being effects of the pandemic on this population, the research team conducted a panel survey across four rounds with a random sample of 8,265 migrants that had returned to Bihar and Chhattisgarh shortly after the nationwide lockdown in March 2020. The team constructed a post-lockdown sample frame drawing from the approximate population of returned migrants, drawing from government records that attempted to catalogue all entrants in a given time period. These phone surveys included a repeated set of questions on employment and earnings, migration, access to social protections, and coping strategies, as well as single-wave modules on quarantine experiences, health behaviors and beliefs, household composition, migration networks, and discrimination.
Sampling and Data Collection Protocols:
In both Bihar and Chhattisgarh, state government officials collected contact details of returning migrants from April to June 2020 for contact tracing and quarantine purposes. In total, across both states, the research team had access to a private government data of approximately 450,000 migrant names and contact details. In order to create a survey sample, the gender of respondents based on names was coded, obvious duplicates eliminated, respondents under the age of 18 dropped, and a sample that was stratified by gender was randomly drawn to ensure that roughly 50 percent of respondents were returning female migrants. In Chhattisgarh, the sample was also stratified by division.
In total, 8,265 migrants were surveyed across four survey rounds: April to June 2020; July to August 2020; January to March 2021; and June to July 2021. In the first round, enrollment of approximately 5,000 migrants was targeted. In subsequent rounds, the researchers attempted to re-interview approximately 4,000 of these respondents, drawing randomly from each initial state sample frame. Up to four observations per respondent were collected (an average of 2.37 observations per respondent, with 23.41% of migrants participating in all waves of the panel).
If it was impossible to reach respondents from a previous round, participants were replaced with other migrants of the same gender, drawn randomly from the initial state sample frames. Respondents were called on mobile phones, consent to speak with them for approximately 30 minutes was secured, and their responses in digital survey modules were recorded. In an effort to reduce panel attrition, small phone recharge credits as participation incentives in waves 2-4 of the panel were offered. In order to further increase rapport with respondents, the researchers attempted to conduct female migrant interviews with female trained enumerators, and employed local Bihari and Chhattisgarhi survey teams that spoke regional dialects.
The questionnaires focused on different aspects of welfare as the pandemic in India has evolved. The following list below details important topics of the surveys.
- Pre-Lockdown Work Details (Employment, Earnings)
- Experiences Post-Migration (Harassment, Food Prices, Shortages, Bank Accounts)
- Awareness and Perceptions of COVID-19
- Migration Networks
- Social Networks
- Political Participation
- Impact of COVID-19
Scope of Data Set
Time Periods: April 2020 - July 2021
Researchers working with the “G2LM|LIC - COVID-19 Returned Indian Migrant Panel” are obligated to acknowledge the data base and its documentation within their publications, including the DOI, by using this reference.
- Pande, Rohini (Yale University)
- Allard, Jenna (Yale University)
- Moore , Charity Troyer (Yale University)
- Neggers, Yusuf (University of Michigan)
- Jagnani, Maulik (University of Colorado – Denver)
- Schaner, Simone (University of Southern California)
Access to the data is provided to non-for-profit research, replication and teaching purposes. The data is available from the Research Data Center of IZA (IDSC).
Please contact IDSC for any access requests.