Table 4.
COVID-19 fatalities per 1m population
| 2 cities (Chicago, New York City), N = 235 ZIP codes | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | |
| % Black |
14.3*** (2.0) |
6.7*** (2.0) |
5.8*** (2.0) |
3.9** (2.2) |
7.3** (3.1) |
2.7 (4.0) |
4.6 (4.2) |
2.0 (4.2) |
3.6 (4.) |
1.6 (4.5) |
− 0.1 (4.5) |
| % Hispanic |
14.9*** (2.6) |
− 0.4 (2.9) |
− 0.4 (2.7) |
− 4.4 (2.7) |
3.8 (3.8) |
1.4 (4.0) |
2.6 (4.5) |
0.9 (4.2) |
1.2 (4.3) |
− 0.1 (4.3) |
− 0.5 (4.3) |
| Adj R2 | 0.43 | 0.61 | 0.69 | 0.79 | 0.81 | 0.81 | 0.83 | 0.84 | 0.84 | 0.84 | 0.84 |
| Cases per 100k Pop | No | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Demographics | No | No | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Housing | No | No | No | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Socioeconomic | No | No | No | No | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Opportunity Atlas | No | No | No | No | No | Yes | Yes | Yes | Yes | Yes | Yes |
| Occupational | No | No | No | No | No | No | Yes | Yes | Yes | Yes | Yes |
| Transportation | No | No | No | No | No | No | No | Yes | Yes | Yes | Yes |
| SafeGraph | No | No | No | No | No | No | No | No | Yes | Yes | Yes |
| Health access | No | No | No | No | No | No | No | No | No | Yes | Yes |
| Population health | No | No | No | No | No | No | No | No | No | No | Yes |
All specifications include city fixed effects, “% Other non-white”, and a constant term. Unit of observation is ZIP code. Demographic variables include percentage in ZIP code who are male, foreign born, or in age bins (18–44, 45–64, 65–74, 75+). Housing variables include density, percentage who are renters, percent of units vacant, percentage who are in nursing homes, correctional facilities, college dorms, or military barracks (2010 Census), percent overcrowded (1.5+ per room), and percent with 0 or 1 bedroom sizes. Socioeconomic variables include percent in education bins (dropout, high school, some college, bachelor’s degree), Gini coefficient, and percent in poverty bins (0–49% FPL, 50–74%, 75–99%, 100–149%, 150–199%). Opportunity Atlas variables include income mobility and male incarceration (Opportunity Atlas). Occupation variables include percent of workers in service occupations, sales, farming, construction, production, or transport. Transportation variables include percent of workers of workers who use a car, percent who use public transportation, and percent with long commuting times (60+ minutes). Safegraph variables include percent who on average remained at home all day in each month from March to May 2020 (Safegraph). Health access variables include health professional shortage areas (HRSA; mental health, primary care), percent without health insurance, and COVID-19 tests per capita (Chicago and New York City only). Population health variables include conditional life expectancy (CDC, ages 65–74, 75–84, 85+). All control variables obtained from 2018 ACS 5-year sample unless otherwise indicated. All regressions weighted by ZIP code population from 2018 ACS 5-year sample. Heteroscedasticity-robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.10