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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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    1. Wendy Olsen & Manasi Bera & Amaresh Dubey & Jihye Kim & Arkadiusz Wiśniowski & Purva Yadav, 2020. "Hierarchical Modelling of COVID-19 Death Risk in India in the Early Phase of the Pandemic," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 32(5), pages 1476-1503, December.
    2. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    3. Caitlin S. Brown & Martin Ravallion & Dominique van de Walle, 2020. "Can the World’s Poor Protect Themselves from the New Coronavirus?," NBER Working Papers 27200, National Bureau of Economic Research, Inc.
    4. Oldekop, Johan A. & Horner, Rory & Hulme, David & Adhikari, Roshan & Agarwal, Bina & Alford, Matthew & Bakewell, Oliver & Banks, Nicola & Barrientos, Stephanie & Bastia, Tanja & Bebbington, Anthony J., 2020. "COVID-19 and the case for global development," World Development, Elsevier, vol. 134(C).
    5. Vincenzo Galasso & Vincent Pons & Paola Profeta & Michael Becher & Sylvain Brouard & Martial Foucault, 2020. "Gender Differences in COVID-19 Related Attitudes and Behavior: Evidence from a Panel Survey in Eight OECD Countries," SciencePo Working papers Main hal-03594437, HAL.
    6. Daniel Susskind & David Vines, 2020. "The economics of the COVID-19 pandemic: an assessment," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 36(Supplemen), pages 1-13.
    7. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    8. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2003. "Fixed effects, random effects or Hausman-Taylor?: A pretest estimator," Economics Letters, Elsevier, vol. 79(3), pages 361-369, June.
    9. Gaiha, Raghav & Jha, Raghbendra & Kulkarni, Vani S (ed.), 2014. "Diets, Malnutrition, and Disease: The Indian Experience," OUP Catalogue, Oxford University Press, number 9780198099215, Decembrie.
    10. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    11. Bell, Andrew & Jones, Kelvyn, 2015. "Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data," Political Science Research and Methods, Cambridge University Press, vol. 3(1), pages 133-153, January.
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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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    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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