RESUMEN
The present study examines covariates of food security and the impact of Covid-19 induced shocks, among households in India using a nationally representative survey. Using a 2SLS panel regression model, we find an important role of incomes, relative food prices, household characteristics, as well as mobility restrictions in response to the rising number of infections in a given region in explaining varying food expenditure shares prior to and during the Covid-19 pandemic. The disproportionate burden of the pandemic induced lockdowns on the disadvantaged and minorities calls for effective action on the part of policymakers to boost aggregate demand, fix supply chains and reduce food price volatility.
RESUMEN
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.
