ABSTRACT
This paper examines how past pandemics impacted income inequality measured through the Gini measure of inequality net of taxes. It explores how five major pandemics, namely, SARS in 2003, H1N1 in 2009, MERS in 2012, Ebola in 2014, and Zika in 2016 impacted the distribution of income across high income, upper-middle-income and lower-middle-income countries. How the inequality across quintiles share in income is impacted was explored. We used comprehensive panel data sets covering annual observations from 1995 to 2017 for 70 countries. The generalized least square estimation shows that the pandemics have a statistically significant positive impact upon income inequality particularly for the high-income group and also for the entire set of 70 countries. However, the impact of the pandemics is negative upon the upper-middle-income group of countries. The estimation is robust controlling for additional macroeconomic variables. The study demonstrates that past pandemics may generate a policy response that impacts the distribution of income. A weakened role of the state has been responsible for worsening inequality.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
Data used for this study is available at figshare: http://doi.org/10.6084/m9.figshare.13896074.
Code availability
The STATA Software was used.
Notes
1. The choice of the variables to explore the transmission channel upon inequality is constrained by (i) availability of data across large country sets and across time; (ii) WDI data sets have large missing values; (iii) multicollinearity issues and thereby determining the best set of variables and last (iv) trying to obtain data sets which encompass all countries and across the time. As the study by Dabla-Norris et al. (Citation2015) discuss that there is no ‘one-size-fits-all approach to tackling inequality’. So, lot depends on the decision of the choice of drivers, country context, policies and institutions. Thus, it is difficult to ascertain the set of determinants of inequality particularly across diverse nations. Given the constraints the present study has identified the variables from the literature which are encompassing through cross-section and time.
2. We could not explore the impact of the past pandemics on the inequality conditions of the low-income group owing to a large set of missing observations.