Table 7.
County-level robustness tests.
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|
Dependent variable: TSGI_countya | |||||||||
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|
(29) | (30) | (31) | (32) | ||||||
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Timelag_3 | P value | Timelag_3 | P value | Timelag_7 | P value | Timelag_7 | P value | ||
| Policy | 3.422 | <.001 | 21.31 | <.001 | 2.354 | .45 | −3.194 | .34 | ||
| Cases | −0.013 | .01 | −0.0154 | .02 | −1.889 | <.001 |
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| Policy*lnElderly |
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−6.256 | <.001 |
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| Policy*lnPopulation |
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−0.390 | .07 |
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| lnDeaths |
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−0.953 | .004 | ||
| Policy*lnHospitalbeds |
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3.626 | .10 | ||
| Control FEb | Yes |
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Yes |
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Yes |
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Yes |
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| Constant | 56.24 | <.001 | 56.258 | <.001 | 59.496 | <.001 | 59.145 | <.001 | ||
| Observations | 26,923 |
|
26,923 |
|
26,923 |
|
26,923 |
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||
| R 2 | 0.308 |
|
0.143 |
|
0.380 |
|
0.356 |
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||
aTSGI: Twitter sentiment geographical index.
bFE: fixed effect.