Fig 1.
Adjusted relationship between inequality and policy stringency from February 1, 2020 to April 14, 2020.
This figure plots the relationship between stringency of country-level COVID-19 policies and inequality, controlling for countries’ population, GDP per capita, and exposure to the disease. Stringency is measured by the Oxford Covid Government Response tracker program, ranking countries’ daily policy on a standardized scale ranging between 0 (not stringent at all) to 100 (highly stringent). We limit the range to the period between February 1st, 2020 after the disease had already been discovered outside of China, but before April 14th, 2020, the day before our survey data was initiated. The index is comprised of seven indicators of lockdown, such as school closures and restrictions in movement, which are consistent with our survey questions below. We measure inequality using the SWIID database (Solt, 2019).
Fig 2.
Estimated effects of income inequality on agreement with government’s responses to the COVID-19 pandemic (by policy).
This figure reports the coefficients of the income quintile of belief that their government’s responses to the COVID-19 pandemic was effective. Quintile 5 (richest income quintile) is used as the reference category. Control variables include age groups, gender, urban dummy, country dummies, and COVID-19 infection rates. The full regression results are presented in Table A.1 in Appendix A of S1 File. Panel A. Believe government response to the pandemic is effective. Panel B. Believe shutting down schools is effective. Panel C. Believe shutting down public transport is effective. Panel D. Believe shutting down non-essential businesses is effective. Panel E. Believe limiting mobility outside home is effective. Panel F. Believe forbidding mass gatherings is effective. Panel G. ‘Believe in introducing fines for citizens that don’t respect public safety measures.’ Panel H. ‘Believe in requiring masks to be worn outside by everyone.’
Fig 3.
Estimated interactions between Gini index and income quintile.
This figure presents the estimates of the interactions between Gini index and income quintiles in regressions of ‘Believe in the approach of the government in response to the pandemic’. The Gini index of each country is reported in parentheses. The full regression results using the pooled sample are reported in Table A.7 in Appendix A of S1 File.
Fig 4.
The proportion of the indirect impacts to the total impacts of being in the poorest quintile and overall assessment of government responses through several mediating variables (%) (point estimates and the 95% confidence interval).
This figure presents the estimates of the indirect effects using “medeff” command in Stata [39].