Severity of the covid-19 pandemic in India: the case of 3 states: Maharashtra, Jharkhand & Meghalaya

Nidhi Kaicker, Katsushi S. Imai, Raghav Gaiha

Research output: Preprint/Working paperDiscussion paper

Abstract

This is the first econometric analysis of severity of Covid-19 pandemic measured using two related but distinct measures of mortality up to 21 June, 2020: one is the Cumulative Severity Ratio (CSR) and the other is Daily Severity Ratio (DSR). The CSR measures the additional pressure on our fragile and ill-equipped healthcare system, and the DSR helps monitor the progression of fatalities. Another important contribution of this analysis is the use of rigorous econometric methodology: random effects models and Hausman-Taylor models. Although the rationales vary, they yield a large core of robust results. The specifications are rich and comprehensive despite heavy data constraints. The factors associated with the CSR and DSR include (lagged) Covid-19 cases, income, age, gender, multi-morbidity, urban population density, lockdown phases and their interactions with three states, Maharashtra, Jharkhand and Meghalaya, weather including temperature and rainfall and their interactions with the two state dummies. Given the paucity of rigorous econometric analyses, our study yields policy insights of considerable significance.
Original languageEnglish
Place of PublicationKobe, Japan
PublisherKobe University
Pages1-32
Number of pages32
Publication statusPublished - 3 Aug 2020

Publication series

NameRIEB Discussion Paper Series
PublisherKobe University
No.21
Volume2020

Keywords

  • Covid-19
  • Cumulative Severity Ratio
  • Daily Severity Ratio
  • Random-Effects Model
  • Hausman-Taylor Model
  • Jharkhand
  • Maharashtra
  • India

Research Beacons, Institutes and Platforms

  • Global Development Institute

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