tetano
Editor, Senior Moderator
Can Public Policy
. 2021 Dec 1;47(4):537-553.
doi: 10.3138/cpp.2021-033.
Economic Inequality and COVID-19 Deaths and Cases in the First Wave: A Cross-Country Analysis
James B Davies[SUP] 1 [/SUP]
Affiliations
Abstract
in English, French
The cross-country relationship of coronavirus disease 2019 (COVID-19) case and death rates with previously measured income inequality and poverty in the pandemic's first wave is studied, controlling for other underlying factors, in a worldwide sample of countries. If the estimated associations are interpreted as causal, the Gini coefficient for income has a significant positive effect on both cases and deaths per capita in regressions using the full sample and for cases but not for deaths when Organisation for Economic Co-operation and Development (OECD) and non-OECD sub-samples are treated separately. The Gini coefficient for wealth has a significant positive effect on cases, but not on deaths, in both sub-samples and in the full sample. Poverty generally has weak positive effects in the full and non-OECD samples, but a relative poverty measure has a strong positive effect on cases in the OECD sample. Analysis of the gap between COVID-19 first-wave cases and deaths per capita in Canada and the higher rates in the United States indicates that 37 percent of the cases gap and 28 percent of the deaths gap could be attributed to the higher-income Gini in the United States according to the full-sample regressions.
Keywords: COVID-19; cases; deaths; income; inequality; poverty; wealth.
. 2021 Dec 1;47(4):537-553.
doi: 10.3138/cpp.2021-033.
Economic Inequality and COVID-19 Deaths and Cases in the First Wave: A Cross-Country Analysis
James B Davies[SUP] 1 [/SUP]
Affiliations
- PMID: 36039094
- PMCID: PMC9395158
- DOI: 10.3138/cpp.2021-033
Abstract
in English, French
The cross-country relationship of coronavirus disease 2019 (COVID-19) case and death rates with previously measured income inequality and poverty in the pandemic's first wave is studied, controlling for other underlying factors, in a worldwide sample of countries. If the estimated associations are interpreted as causal, the Gini coefficient for income has a significant positive effect on both cases and deaths per capita in regressions using the full sample and for cases but not for deaths when Organisation for Economic Co-operation and Development (OECD) and non-OECD sub-samples are treated separately. The Gini coefficient for wealth has a significant positive effect on cases, but not on deaths, in both sub-samples and in the full sample. Poverty generally has weak positive effects in the full and non-OECD samples, but a relative poverty measure has a strong positive effect on cases in the OECD sample. Analysis of the gap between COVID-19 first-wave cases and deaths per capita in Canada and the higher rates in the United States indicates that 37 percent of the cases gap and 28 percent of the deaths gap could be attributed to the higher-income Gini in the United States according to the full-sample regressions.
Keywords: COVID-19; cases; deaths; income; inequality; poverty; wealth.