Severity of the Covid-19 pandemic in India. The case of three states: Maharashtra, Jharkhand and Meghalaya
Nidhi Kaicker, Katsushi S. Imai, Raghav Gaiha
This is the first econometric analysis of the severity of the 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 the Daily Severity Ratio (DSR). The CSR measures the additional pressure on India’s fragile and ill-equipped healthcare system, 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 within three states, Maharashtra, Jharkhand and Meghalaya, and 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.
Covid-19, Cumulative Severity Ratio, Daily Severity Ratio, random-effects model, Hausman–Taylor model, Jharkhand, Maharashtra, India
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