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 language | English |
|---|---|
| Place of Publication | Kobe, Japan |
| Publisher | Kobe University |
| Pages | 1-32 |
| Number of pages | 32 |
| Publication status | Published - 3 Aug 2020 |
Publication series
| Name | RIEB Discussion Paper Series |
|---|---|
| Publisher | Kobe University |
| No. | 21 |
| Volume | 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Covid-19
- Cumulative Severity Ratio
- Daily Severity Ratio
- Random-Effects Model
- Hausman-Taylor Model
- Jharkhand
- Maharashtra
- India
Research Highlights, Institutes and Platforms
- Global Development Institute
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