Table 2.
The non-linear effect of different weather indicators at t-7 (at 12:00 local time) on different pandemic indicators.
| (I) | (II) | (III) | |
|---|---|---|---|
| (log) new cases | New cases per 100 K capita | (log) cases | |
| Temperature spline < 25 °C | − 0.0116*** (0.002) | − 2.1171*** (0.395) | − 0.0183*** (0.003) |
| Temperature spline > 25 °C | − 0.0081*** (0.002) | − 0.0617 (0.505) | − 0.0089*** (0.003) |
| Humidity | − 0.0012*** (0.000) | − 0.1541*** (0.060) | − 0.0016*** (0.000) |
| Wind speed | − 0.0052*** (0.001) | − 0.1515 (0.336) | − 0.0074*** (0.002) |
| Precipitation | 0.0244 (0.329) | − 3.2391 (71.118) | − 0.5390** (0.317) |
| Constant | 1.2745*** (0.050) | 147.0458*** (11.058) | 4.2514*** (0.077) |
| Observations | 595,251 | 595,251 | 595,251 |
| R-squared | 0.73 | 0.43 | 0.94 |
| County fixed effect | YES | YES | YES |
| State-date fixed effect | YES | YES | YES |
The outcome variables are (log) new cases (I), the number of new cases per 100,000 habitants within the last 14 days (II) and (log) cases (III). Standard deviations based on robust standard errors clustered at the county level in parentheses.
***,**,*Significance at 1, 5 and 10%, respectively; N = 595,251.