| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w27391 |
| 来源ID | Working Paper 27391 |
| What Does and Does Not Correlate with COVID-19 Death Rates | |
| Christopher R. Knittel; Bora Ozaltun | |
| 发表日期 | 2020-06-22 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | We correlate county-level COVID-19 death rates with key variables using both linear regression and negative binomial mixed models, although we focus on linear regression models. We include four sets of variables: socio-economic variables, county-level health variables, modes of commuting, and climate and pollution patterns. Our analysis studies daily death rates from April 4, 2020 to May 27, 2020. We estimate correlation patterns both across states, as well as within states. For both models, we find higher shares of African American residents in the county are correlated with higher death rates. However, when we restrict ourselves to correlation patterns within a given state, the statistical significance of the correlation of death rates with the share of African Americans, while remaining positive, wanes. We find similar results for the share of elderly in the county. We find that higher amounts of commuting via public transportation, relative to telecommuting, is correlated with higher death rates. The correlation between driving into work, relative to telecommuting, and death rates is also positive across both models, but statistically significant only when we look across states and counties. We also find that a higher share of people not working, and thus not commuting either because they are elderly, children or unemployed, is correlated with higher death rates. Counties with higher home values, higher summer temperatures, and lower winter temperatures have higher death rates. Contrary to past work, we do not find a correlation between pollution and death rates. Also importantly, we do not find that death rates are correlated with obesity rates, ICU beds per capita, or poverty rates. Finally, our model that looks within states yields estimates of how a given state's death rate compares to other states after controlling for the variables included in our model; this may be interpreted as a measure of how states are doing relative to others. We find that death rates in the Northeast are substantially higher compared to other states, even when we control for the four sets of variables above. Death rates are also statistically significantly higher in Michigan, Louisiana, Iowa, Indiana, and Colorado. California's death rate is the lowest across all states. |
| 主题 | Health, Education, and Welfare ; Health ; Environmental and Resource Economics ; Environment ; Regional and Urban Economics ; COVID-19 |
| URL | https://www.nber.org/papers/w27391 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/585064 |
| 推荐引用方式 GB/T 7714 | Christopher R. Knittel,Bora Ozaltun. What Does and Does Not Correlate with COVID-19 Death Rates. 2020. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w27391.pdf（1171KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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