* STATA 13.0 was used for performing PCA and obtaining the rotated components and KMO statistic. For all other statistical analysis and figures, GRETL 2021b package was used.
1 Department of Economics, Sri Venkateswara College, University of Delhi, New Delhi, India
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Since COVID-19 was declared a pandemic in March 2020, countries across the world have imposed lockdowns to curtail transmission of the disease. The objective of the present article is to use statistical tools to assess how lockdown policies and stringency affected the spread of the pandemic in India. The method of principal component analysis is used for dimensionality reduction and to track the trajectory of the pandemic in the two-dimensional space. The analysis identifies four phases in the trajectory of the pandemic. A composite measure of the pandemic is constructed to see how it correlates with the stringency index. While results show a negative and statistically significant relationship between the composite index of the pandemic and the stringency index over the entire period of the study, the phase-wise analysis gives useful insights. In particular, the phase in which the pandemic index declined even as stringency index declined and the phase of sudden onset of second wave with a consequent increase in stringency measures indicate the need for policies for better management of the pandemic. Tracking new epidemiological variants of the virus and geographically localized stringency measures rather than national level lockdowns are possible ways to balance health and economy.
Health, economy, lockdown, composite pandemic index, principal component analysis
JEL Classification: I15, I18
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