Table 2.
OLS regression models predicting grades in maths.
| (1) | (2) | (3) | |
|---|---|---|---|
| Female | −0.150*** | −0.154*** | −0.153*** |
| (0.034) | (0.033) | (0.033) | |
| Feminine generics | −0.069* | −0.077** | −0.061* |
| (0.038) | (0.038) | (0.036) | |
| Female × Feminine generics | 0.120** | 0.139*** | 0.107** |
| (0.051) | (0.050) | (0.048) | |
| Age | −0.001 | ||
| (0.001) | |||
| Higher education | 0.073*** | ||
| (0.025) | |||
| Above average income | 0.065** | ||
| (0.030) | |||
| Political party fixed effects | Y | ||
| Immigrant | 0.068** | ||
| (0.033) | |||
| Immigration age | −0.005 | ||
| (0.004) | |||
| Female × Feminine generics × Immigration age | −0.011* | ||
| (0.007) | |||
| Female × Immigration age | 0.007 | ||
| (0.005) | |||
| Feminine generics × Immigration age | 0.007 | ||
| (0.005) | |||
| Constant | 0.698*** | 0.655*** | 0.700*** |
| (0.019) | (0.038) | (0.019) | |
| N | 759 | 759 | 926 |
| Adjusted R2 | 0.029 | 0.066 | 0.032 |
SEs in parentheses; Regression (3) includes immigrants; *p < 0.1, **p < 0.05, ***p < 0.01.