{"title":"Tracking the impact of government response to COVID-19 epidemic: Evidence from India","authors":"Kaibalyapati Mishra","doi":"10.1101/2023.11.27.23299097","DOIUrl":null,"url":null,"abstract":"This paper tries to quantify the impact of government policy intervention on the death due to COVID-19 in India at national, regional and sub-national levels. The data used for this study are collected from the Oxford COVID-19 Government Response Tracker (OxCGRT), a longitudinal database of daily government response from Jan 28th, 2020, when the first COVID case was diagnosed in India till December 31st, 2022. Here, <em>stringency</em> measures, which gauge the severity of interventions such as lock-downs and travel restrictions, indicative of government control; and <em>containment</em> measures, representing a spectrum of actions aimed at preventing or limiting virus transmission and the <em>overall government support</em>, providing a holistic assessment of the government’s efforts in mitigating the virus’s spread. Using the Panel Corrected Standard Error (PCSE) method, this paper finds out that the stringency and overall government support interventions by the government have been successful in reducing the death counts by 25% and 23% respectively however the containment intervention alone has failed to reduce the death at all levels. Exploring regional variations, event study plots reveal nuanced temporal dynamics. The daily and 24-day lagged dependent variables, representing overall government response and stringency measures, reveal a consistent impact post-intervention at the all-India level. Both current and lagged variables show a reduction in COVID-19 deaths, with a more pronounced effect emerging after a four-day lag. Event-study plots with a 24-day lagged dependent variable confirm the anticipated negative impact of overall government response on deaths. However, the pattern diverges for stringency and overall government interventions compared to daily death counts.","PeriodicalId":501072,"journal":{"name":"medRxiv - Health Economics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Health Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2023.11.27.23299097","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper tries to quantify the impact of government policy intervention on the death due to COVID-19 in India at national, regional and sub-national levels. The data used for this study are collected from the Oxford COVID-19 Government Response Tracker (OxCGRT), a longitudinal database of daily government response from Jan 28th, 2020, when the first COVID case was diagnosed in India till December 31st, 2022. Here, stringency measures, which gauge the severity of interventions such as lock-downs and travel restrictions, indicative of government control; and containment measures, representing a spectrum of actions aimed at preventing or limiting virus transmission and the overall government support, providing a holistic assessment of the government’s efforts in mitigating the virus’s spread. Using the Panel Corrected Standard Error (PCSE) method, this paper finds out that the stringency and overall government support interventions by the government have been successful in reducing the death counts by 25% and 23% respectively however the containment intervention alone has failed to reduce the death at all levels. Exploring regional variations, event study plots reveal nuanced temporal dynamics. The daily and 24-day lagged dependent variables, representing overall government response and stringency measures, reveal a consistent impact post-intervention at the all-India level. Both current and lagged variables show a reduction in COVID-19 deaths, with a more pronounced effect emerging after a four-day lag. Event-study plots with a 24-day lagged dependent variable confirm the anticipated negative impact of overall government response on deaths. However, the pattern diverges for stringency and overall government interventions compared to daily death counts.