Tracking the impact of government response to COVID-19 epidemic: Evidence from India

Kaibalyapati Mishra
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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.
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追踪政府应对COVID-19疫情的影响:来自印度的证据
本文试图在国家、地区和次国家层面量化政府政策干预对印度COVID-19死亡人数的影响。本研究使用的数据来自牛津COVID-19政府反应追踪器(OxCGRT),这是一个纵向数据库,记录了从2020年1月28日印度确诊首例COVID-19病例到2022年12月31日的每日政府反应。在这里,严格措施,衡量封锁和旅行限制等干预措施的严重程度,表明政府控制;遏制措施,代表了旨在防止或限制病毒传播的一系列行动和政府的总体支持,全面评估了政府为缓解病毒传播所做的努力。使用小组校正标准误差(PCSE)方法,本文发现政府的严格干预和整体政府支持干预分别成功地将死亡人数减少了25%和23%,但单独的遏制干预未能减少各级的死亡人数。探索区域差异,事件研究情节揭示细微的时间动态。代表政府总体反应和严格措施的每日和24天滞后因变量揭示了在全印度层面干预后的一致影响。当前变量和滞后变量均显示COVID-19死亡人数减少,滞后四天后效果更为明显。具有24天滞后因变量的事件研究图证实了政府总体应对措施对死亡的预期负面影响。然而,与每日死亡人数相比,政府干预的严格程度和总体情况有所不同。
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