I made this photo of a pink rose at the Morris Arboretum in Philadelphia this afternoon.
I made this photo with my Fujifilm X-T2 with a long lens.
It has been a very long time since I last made a post here. I am coming back with a post about the relationship between income inequality and COVID-19.
The latest issue of The Economist has an article on this topic, which led me to three recent studies about this relationship and an interesting Twitter thread. (Do watch out for the careless conflation of wealth with income in the second tweet in the thread.) I will say a few words for each of the three studies. Before I do that, I need to issue the disclaimer that I am not a statistician or an econometrician, therefore I cannot, and will not, claim to evaluate the appropriateness of the statistical modeling in these studies.
Let’s start with “Association Between Income Inequality and County-Level COVID-19 Cases and Deaths in the US”, by Annabel X. Tan, MPH; Jessica A. Hinman, MS; Hoda S. Abdel Magid, PhD; Lorene M. Nelson, PhD, MS; Michelle C. Odden, PhD, from JAMA Network Open, doi:10.1001/jamanetworkopen.2021.8799. The authors collected data on COVID cases and deaths for a year (2020-03-01 to 2021-02-28), as well income inequality (measured by the Gini coefficient) for 3220 counties in all 50 states plus Puerto Rico and DC. Their main finding was a positive correlation between income inequality and COVID cases and deaths, which was most pronounced in the summer of 2020. Several additional variables were included as controls, such as the poverty rate, age, race, mask use, crowding, educational level, urban versus rural population share, and availability of physicians. I find it remarkable that income inequality showed up as correlated with COVID cases and deaths in the presence of all these additional variables that one would expect to be more strongly correlated with COVID outcomes.
Next, we’ll talk about “COVID‐19 and income inequality in OECD countries” by John Wildman, The European Journal of Health Economics (2021) 22:455–462 https://doi.org/10.1007/s10198-021-01266-4. The COVID variables are cumulative deaths per million and recorded daily cases per million in the early months of the pandemic. In the words of the author, “The results demonstrate a significant positive association between income inequality and COVID-19 cases and death per million in all estimated models. A 1% increase in the Gini coefficient is associated with an approximately 4% increase in cases per-million and an approximately 5% increase in deaths per-million.” The author proposes that income inequality is a proxy for other variables that correlate with bad COVID outcomes, such as “poor housing, smoking, obesity and pollution.”
Finally, let’s take a look at “The trouble with trust: Time-series analysis of social capital, income inequality, and COVID-19 deaths in 84 countries” by Frank J. Elgar, Anna Stefaniak, and Michael J.A. Wohl, Social Science & Medicine 263 (2020) 113365. Here is the abstract of the paper:
Can social contextual factors explain international differences in the spread of COVID-19? It is widely assumed that social cohesion, public confidence in government sources of health information and general concern for the welfare of others support health advisories during a pandemic and save lives. We tested this assumption through a time-series analysis of cross-national differences in COVID-19 mortality during an early phase of the pandemic. Country data on income inequality and four dimensions of social capital (trust, group affiliations, civic re- sponsibility and confidence in public institutions) were linked to data on COVID-19 deaths in 84 countries. Associations with deaths were examined using Poisson regression with population-averaged estimators. During a 30-day period after recording their tenth death, mortality was positively related to income inequality, trust and group affiliations and negatively related to social capital from civic engagement and confidence in state in- stitutions. These associations held in bivariate and mutually controlled regression models with controls for population size, age and wealth. The results indicate that societies that are more economically unequal and lack capacity in some dimensions of social capital experienced more COVID-19 deaths. Social trust and belonging to groups were associated with more deaths, possibly due to behavioural contagion and incongruence with physical distancing policy. Some countries require a more robust public health response to contain the spread and impact of COVID-19 due to economic and social divisions within them.
I find these papers extremely interesting, and I want to make them part of my economic inequality course. You could say that this post is my very rough first reaction, simply noting the main conclusions of this research, conclusions that point out a clear connection between income inequality and the COVID-19 pandemic outcomes.
At Pennypack Ecological Restoration Trust / Raytharn Farm.
At the Pennypack Ecological Restoration Trust.
At Pennypack Ecological Restoration Trust, PA, USA.
I had just finished making a video for one of my classes, when I looked out the window, saw the sky, and rushed to the best vantage point the house offers for the sunset to shoot this photo.
The 2020 Bank of Sweden Prize in Economic Sciences in Honor of Alfred Nobel was awarded today jointly to Paul Milgrom and Robert Wilson of Stanford University for their work in Auction theory. Here is the popular information document on the Nobel Prize website, complete with some really great graphics: https://www.nobelprize.org/prizes/economic-sciences/2020/popular-information/
Hearty congratulations to the winners! More from me on this blog a little later. I know a bit about auction theory and have taught parts of the theory — now I will prepare a lecture on this award to be delivered on October 23d. Details to follow.
Shot with Fujifilm X-T2, edited in Affinity Photo