Table 3.
The results of asymmetric Fourier causality test for COVID-19 cases
Null hypothesis | lnCases ↛ lnPM2.5 | lnCases+ ↛ lnPM2.5 – | lnCases+ ↛ lnPM2.5+ | ||||||
---|---|---|---|---|---|---|---|---|---|
Cities | Test statistics | p | k | Test statistics | p | k | Test statistics | p | k |
New York | 7.837 | 9 | 1 | 7.676 | 12 | 3 | 4.971 | 7 | 3 |
Los Angeles | 18.720 | 12 | 1 | 28.949* | 12 | 3 | 17.133 | 10 | 1 |
Chicago | 21.032*** | 12 | 3 | 22.533** | 12 | 1 | 17.436 | 12 | 1 |
Phoenix | 18.074 | 12 | 1 | 24.059** | 10 | 1 | 6.712 | 8 | 1 |
Philadelphia | 13.337 | 8 | 1 | 19.378** | 10 | 2 | 8.805 | 10 | 2 |
San Antonio | 11.571 | 11 | 1 | 25.552** | 11 | 2 | 9.318 | 12 | 2 |
San Diego | 4.057 | 9 | 1 | 5.206 | 10 | 2 | 4.650 | 10 | 1 |
San Jose | 8.677 | 12 | 1 | 23.261** | 12 | 2 | 6.760 | 10 | 1 |
Optimal lag lengths and frequencies are selected by AIC. The maximum lag length set at 12 using the Schwert’s (1989) approach ()
*, **, and ***statistical significance at 1%, 5%, and 10% levels, respectively)