Table A2.
COVID-19 lockdowns and air pollution – Lagged dependent variable estimation.
| Bandwidth | Air pollution: NO2 |
Air pollution: PM2.5 |
||||
|---|---|---|---|---|---|---|
| Optimal bandwidth | Optimal bandwidth +10 days | Optimal bandwidth −10 days | Optimal bandwidth | Optimal bandwidth +10 days | Optimal bandwidth −10 days | |
| Lockdown = 1 | −0.421∗∗∗ (0.125) |
−0.552∗∗∗ (0.121) |
−0.208∗ (0.115) |
−0.639∗∗ (0.311) |
−0.586∗∗ (0.286) |
−0.520 (0.332) |
| Lagged dependent variable | 0.646∗∗∗ (0.026) |
0.648∗∗∗ (0.025) |
0.628∗∗∗ (0.027) |
0.707∗∗∗ (0.013) |
0.719∗∗∗ (0.013) |
0.696∗∗∗ (0.014) |
| Means before lockdowns | 23.281 | 23.281 | 23.281 | 64.824 | 64.824 | 64.824 |
| Controls | Yes | Yes | Yes | Yes | Yes | Yes |
| Country and time FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Observations | 209,825 | 245,188 | 174,500 | 76,939 | 86,714 | 67,043 |
Notes: ∗∗∗p < 0.01, ∗∗p < 0.05, ∗p < 0.1. Results of RDD using the optimal bandwidths based on Imbens and Kalyanaraman (2012). Clustered standard errors in parentheses are robust to within-day and within-country serial correlation. Control variables are daily temperature and rainfall (humidity for station-based data).