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Economic geography of contagion: a study of COVID-19 outbreak in India
We propose a mechanism based on regional inequality in economic activity to explain the heterogeneity in the spread of COVID-19 and test it using data from India. Contagion is expected to spread at a higher rate in regions characterized by greater movement of goods and services. We argue that mobili...
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Published in: | Journal of population economics 2023-04, Vol.36 (2), p.779-811 |
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creator | Chakraborty, Tanika Mukherjee, Anirban |
description | We propose a mechanism based on regional inequality in economic activity to explain the heterogeneity in the spread of COVID-19 and test it using data from India. Contagion is expected to spread at a higher rate in regions characterized by greater movement of goods and services. We argue that mobility is higher in regions with greater degree of intra-regional inequality in economic activity. Such regions are usually characterized by a core-periphery economic structure in which the periphery is dependent on the core for the supply of jobs, goods, and services. Such dependence leads to a greater degree of mobility between the core and periphery, which in turn leads to higher rate of contagion. Using nightlight data to measure regional inequality, we find evidence in support of our hypothesis. Using mobility data, we provide direct evidence in support of our proposed channel; the positive relationship between regional inequality and COVID-19 infection is driven by mobility. Our findings suggest that policy responses to contain COVID-19 contagion need to be heterogeneous across India, where the priority areas can be chosen ex ante based on a regional inequality-based criterion. |
doi_str_mv | 10.1007/s00148-022-00935-9 |
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Contagion is expected to spread at a higher rate in regions characterized by greater movement of goods and services. We argue that mobility is higher in regions with greater degree of intra-regional inequality in economic activity. Such regions are usually characterized by a core-periphery economic structure in which the periphery is dependent on the core for the supply of jobs, goods, and services. Such dependence leads to a greater degree of mobility between the core and periphery, which in turn leads to higher rate of contagion. Using nightlight data to measure regional inequality, we find evidence in support of our hypothesis. Using mobility data, we provide direct evidence in support of our proposed channel; the positive relationship between regional inequality and COVID-19 infection is driven by mobility. Our findings suggest that policy responses to contain COVID-19 contagion need to be heterogeneous across India, where the priority areas can be chosen ex ante based on a regional inequality-based criterion.</description><subject>Center and periphery</subject><subject>Contagion</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Data</subject><subject>Demography</subject><subject>Economic activity</subject><subject>Economic conditions</subject><subject>Economic geography</subject><subject>Economic inequality</subject><subject>Economic structure</subject><subject>Economics</subject><subject>Economics and Finance</subject><subject>Geography</subject><subject>Heterogeneity</subject><subject>Inequality</subject><subject>Labor Economics</subject><subject>Mobility</subject><subject>Original Paper</subject><subject>Population Economics</subject><subject>Regional development</subject><subject>Regions</subject><subject>Social Policy</subject><subject>Viral 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subjects | Center and periphery Contagion Coronaviruses COVID-19 Data Demography Economic activity Economic conditions Economic geography Economic inequality Economic structure Economics Economics and Finance Geography Heterogeneity Inequality Labor Economics Mobility Original Paper Population Economics Regional development Regions Social Policy Viral diseases |
title | Economic geography of contagion: a study of COVID-19 outbreak in India |
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