TY - JOUR
T1 - Migration, externalities, and the diffusion of COVID-19 in South Asia☆
AU - Lee, Jean N.
AU - Mahmud, Mahreen
AU - Morduch, Jonathan
AU - Ravindran, Saravana
AU - Shonchoy, Abu S.
N1 - Funding Information:
The authors have no financial or personal relationships with other people or organizations that could inappropriately influence this work. We thank co-editor Thomas Fujiwara and anonymous referees for helpful comments. We gratefully acknowledge support from the Bill and Melinda Gates Foundation. Mahmud's time was funded by a Wellspring Philanthropic Fund grant to the Mind and Behaviour Research Group. Morduch is funded by the Mastercard Impact Fund. Ravindran is funded by a startup grant at the Lee Kuan Yew School of Public Policy, National University of Singapore. Michelle Kempis and Anaise Williams provided excellent research assistance. An earlier version was circulated as ?Migration and the Diffusion of COVID-19 in South Asia.? This project is registered on the IPA RECOVR Research Hub (https://www.poverty-action.org/recovr-study/contagion-and-migration-south-asia). All views and any errors are our own.
Funding Information:
The authors have no financial or personal relationships with other people or organizations that could inappropriately influence this work. We thank co-editor Thomas Fujiwara and anonymous referees for helpful comments. We gratefully acknowledge support from the Bill and Melinda Gates Foundation. Mahmud’s time was funded by a Wellspring Philanthropic Fund grant to the Mind and Behaviour Research Group. Morduch is funded by the Mastercard Impact Fund. Ravindran is funded by a startup grant at the Lee Kuan Yew School of Public Policy, National University of Singapore. Michelle Kempis and Anaise Williams provided excellent research assistance. An earlier version was circulated as “Migration and the Diffusion of COVID-19 in South Asia.” This project is registered on the IPA RECOVR Research Hub ( https://www.poverty-action.org/recovr-study/contagion-and-migration-south-asia ). All views and any errors are our own.
Publisher Copyright:
© 2020
PY - 2021/1
Y1 - 2021/1
N2 - 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.
AB - 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.
KW - Bangladesh
KW - Coronavirus
KW - India
KW - International migration
KW - Lockdown
KW - Pakistan
UR - http://www.scopus.com/inward/record.url?scp=85096859370&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85096859370&partnerID=8YFLogxK
U2 - 10.1016/j.jpubeco.2020.104312
DO - 10.1016/j.jpubeco.2020.104312
M3 - Article
AN - SCOPUS:85096859370
VL - 193
JO - Journal of Public Economics
JF - Journal of Public Economics
SN - 0047-2727
M1 - 104312
ER -