The initial spread of COVID-19 halted economic activity as countries around the world restricted the mobility of their citizens. As a result, many migrant workers returned home, spreading the virus across borders. We investigate the relationship between migrant movements and the spread of COVID-19 using district-day-level data from Bangladesh, India, and Pakistan (the 1st, 6th, and 7th largest sources of international migrant workers). We find that during the initial stage of the pandemic, a 1 SD increase in prior international out-migration relative to the district-wise average in India and Pakistan predicts a 48% increase in the number of cases per capita. In Bangladesh, however, the estimates are not statistically distinguishable from zero. Domestic out-migration predicts COVID-19 diffusion in India, but not in Bangladesh and Pakistan. In all three countries, the association of COVID-19 cases per capita and measures of international out-migration increases over time. The results show how migration data can be used to predict coronavirus hotspots. More broadly, the results are consistent with large cross-border negative externalities created by policies aimed at containing the spread of COVID-19 in migrant-receiving countries.
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COVID-19 and the Future of Microfinance: Evidence and Insights from Pakistan
The initial spread of COVID-19 halted economic activity as countries around the world restricted the mobility of their citizens. As a result, many migrant workers returned home, spreading the virus across borders. We investigate the relationship between migrant movements and the spread of COVID-19 using district-day-level data from Bangladesh, India, and Pakistan (the 1st, 6th, and 7th largest sources of international migrant workers). We find that during the initial stage of the pandemic, a 1 SD increase in prior international out-migration relative to the district-wise average in India and Pakistan predicts a 48% increase in the number of cases per capita. In Bangladesh, however, the estimates are not statistically distinguishable from zero. Domestic out-migration predicts COVID-19 diffusion in India, but not in Bangladesh and Pakistan. In all three countries, the association of COVID-19 cases per capita and measures of international out-migration increases over time. The results show how migration data can be used to predict coronavirus hotspots. More broadly, the results are consistent with large cross-border negative externalities created by policies aimed at containing the spread of COVID-19 in migrant-receiving countries.
Can Migration Patterns Help Predict the Spread of COVID-19 in South Asia?
Within one week in March, the lockdowns ordered by South Asian governments to combat the COVID pandemic dramatically reversed rural-to-urban migrant flows. Our team’s early analysis shows that migration patterns may help predict the location of COVID outbreaks.
What is the Impact of Investing in Financial Systems?
What is particularly useful about this very readable review is the synthesis of evidence on both households and firms, which tend to be covered separately by most researchers. As Tim notes, evidence from diaries about how many households must juggle their finances just to meet some basic goals around managing consumption, investment and risk, is suggestive about how firms manage theirs.