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Severity of the COVID‐19 pandemic in India

Author

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  • Katsushi S. Imai
  • Nidhi Kaicker
  • Raghav Gaiha

Abstract

The main objective of this study is to identify the socioeconomic, meteorological, and geographical factors associated with the severity of COVID‐19 pandemic in India. The severity is measured by the cumulative severity ratio (CSR)—the ratio of the cumulative COVID‐related deaths to the deaths in a pre‐pandemic year—its first difference and COVID infection cases. We have found significant interstate heterogeneity in the pandemic development and have contrasted the trends of the COVID‐19 severities between Maharashtra, which had the largest number of COVID deaths and cases, and the other states. Drawing upon random‐effects models and Tobit models for the weekly and monthly panel data sets of 32 states/union territories, we have found that the factors associated with the COVID severity include income, gender, multi‐morbidity, urbanization, lockdown and unlock phases, weather including temperature and rainfall, and the retail price of wheat. Brief observations from a policy perspective are made toward the end.

Suggested Citation

  • Katsushi S. Imai & Nidhi Kaicker & Raghav Gaiha, 2021. "Severity of the COVID‐19 pandemic in India," Review of Development Economics, Wiley Blackwell, vol. 25(2), pages 517-546, May.
    • Handle: RePEc:bla:rdevec:v:25:y:2021:i:2:p:517-546
    DOI: 10.1111/rode.12779
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    Cited by:

    1. Katsushi S. Imai & Nidhi Kaicker & Raghav Gaiha, 2020. "The Covid-19 Impact on Agricultural Market Arrivals and Prices in India: A Panel VAR Approach," Economics Discussion Paper Series 2010, Economics, The University of Manchester.
    2. Katsushi S. Imai & Nidhi Kaicker & Raghav Gaiha, 2020. "The Covid-19 Impact on Agricultural Prices in India," Discussion Paper Series DP2020-25, Research Institute for Economics & Business Administration, Kobe University, revised Dec 2020.

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    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • N35 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Asia including Middle East
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

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