Table 4.
Impact of Relative Wages on Domestic Violnece: Alternative Specifications
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Ln(female assaults) | Ln(female assaults) | Ln(female assaults) | Ln(drug admissions) | |
| Ln (female wage) | −0.781 | |||
| [0.559] | ||||
| Ln (male wage) | 0.956 | |||
| [0.516] | ||||
| Female/male wage | −0.697 | −0.964 | 0.019 | |
| [0.351] | [0.355] | [0.196] | ||
| Observations | 982 | 955 | 804 | 776 |
| R-squared | 0.96 | 0.96 | 0.96 | 0.99 |
| Robust standard errors clustered on county in brackets | ||||
| Test that female and male wages are equal and opposite in value | ||||
| F (1, 37) | 0.06 | |||
| p-value | 0.81 | |||
Notes: column 1 is based on an OLS fixed effect regression; in column 2, I instrument for the wage ratio using state-wide growth in employment by industry weighted by the county-specific shares in these industries; in columns 3 and 4 the wage ratio is derived from changes in the industrial composition of the county over time; in column 4 are results of a falsification exercise.