Table 4.
Regression results for moderating effects.
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Dependent variable: TSGIa | |||||||||||||||||||||
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(7) | (8) | (9) | (10) | (11) | (12) | (13) | (14) | ||||||||||||||
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Timelag_3 | P value | Timelag_7 | P value | Timelag_3 | P value | Timelag_7 | P value | Timelag_3 | P value | Timelag_7 | P value | Timelag_3 | P value | Timelag_7 | P value | ||||||
| Policy | 1.48 | .26 | 3.591 | .004 | 0.111 | .02 | 0.403 | .001 | 0.737 | .33 | 1.574 | <.001 | −0.783 | .45 | −2.387 | .006 | ||||||
| Cases | −13.713 | .01 | −15.357 | .004 | −13.505 | .01 | −16.682 | .006 | −13.088 | .009 | −14.507 | .002 | −13.624 | .009 | −15.191 | .004 | ||||||
| Policy*lnIncome | −0.136 | .27 | −0.335 | .004 |
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| Policy*Gini |
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−1.455 | .26 | −3.188 | .001 |
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| Policy*lnPopulation |
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−0.011 | .58 | −0.064 | <.001 |
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| Policy*Sexratio |
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0.009 | .42 | 0.025 | .005 | ||||||
| Control FEb | Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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| State FE | Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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| Day FE | Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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Yes |
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| Constant | 56.145 | <.001 | 57.803 | <.001 | 56.144 | <.001 | 57.791 | <.001 | 56.144 | <.001 | 57.784 | <.001 | 56.143 | <.001 | 57.770 | <.001 | ||||||
| Observations | 5048 |
|
4933 |
|
5048 |
|
4933 |
|
5048 |
|
4933 |
|
5048 |
|
4933 |
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| R 2 | 0.827 |
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0.819 |
|
0.827 |
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0.82 |
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0.827 |
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0.819 |
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0.827 |
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0.819 |
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aTSGI: Twitter sentiment geographical index.
bFE: fixed effect.