Socioeconomic Disparities in the Effects of Pollution on Spread of Covid-19: Evidence from US Counties
Abstract
This paper explores disparities in the effect of pollution on confirmed cases of Covid-19 based on counties’ socioeconomic and demographic characteristics. Using daily data on all US counties over the year 2020 and applying a rich panel data fixed effect model, we document that: 1) there are discernible social and demographic disparities in the spread of Covid-19. Blacks, low educated and poorer people are at higher risks of being infected by the new disease. 2) The criteria pollutants including Ozone, CO, PM10, and PM2.5 have the potential to accelerate the outbreak of the novel corona virus. 3) The disadvantaged population is more vulnerable to the effects of pollution on the spread of corona virus. Specifically, the effects of pollution on confirmed cases become larger for blacks, low educated, and counties with lower average wages in 2019. The results suggest that welfare programs during a global pandemic should be differentially distributed among families with different socioeconomic status since the effects of these programs in reducing the spread of the pandemic is different among subpopulations. This paper is the first study to evaluate the differential effects of pollution on the spread of novel corona virus across different subpopulations based on their socioeconomic status.
Downloads
Copyright (c) 2020 Osvaldo Allen, Ava Brown, Ersong Wang
This work is licensed under a Creative Commons Attribution 4.0 International License.
Author (s) should affirm that the material has not been published previously. It has not been submitted and it is not under consideration by any other journal. At the same time author (s) need to execute a publication permission agreement to assume the responsibility of the submitted content and any omissions and errors therein. After submission of a revised paper in the light of suggestions of the reviewers, editorial team edits and formats manuscripts to bring uniformity and standardization in published material.
This work will be licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) and under condition of the license, users are free to read, copy, remix, transform, redistribute, download, print, search or link to the full texts of articles and even build upon their work as long as they credit the author for the original work. Moreover, as per journal policy author (s) hold and retain copyrights without any restrictions.