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Table 2 shows that female GPs improve the STEMM GPA of female students. It is not clear that these effects lead to an improvement in overall GPA, because the improved STEMM GPA could be due to students' spending less time on other subjects. To examine this, column 1 of table 5 shows the result from estimating equation (1) using non-STEMM GPA as the dependent variable. This result shows that the STEMM GPA effect in table 2 is not restricted to STEMM subjects: girls exposed to same-gender GPs perform better in non-STEMM subjects as well, though the effects are smaller. It is important to note that admission to high school and university depends not only on subject-specific GPA but also on overall GPA. Thus, a high STEMM GPA is necessary, but not sufficient, for admission to STEMM programs.^²⁵ The effect on non-STEMM GPA is consistent with the idea that STEMM role models motivate individuals to work harder to get accepted into more selective programs.

Table 5.

Effect of Same-Gender GP: Additional Outcomes

	Compulsory school non-STEMM GPA	High school non-STEMM GPA	College enrollment	College STEMM enrollment	College Medicine enrollment	College STEM enrollment
Same-gender GP	0.040^*	0.067^**	0.005	0.022^*	0.011	0.009
	(0.023)	(0.028)	(0.017)	(0.013)	(0.008)	(0.011)
Mean	4.297	4.384	0.754	0.077	0.019	0.059
Observations	8,617	8,678	8,680	8,680	8,680	8,680

	Compulsory school non-STEMM GPA	High school non-STEMM GPA	College enrollment	College STEMM enrollment	College Medicine enrollment	College STEM enrollment
Same-gender GP	0.040^*	0.067^**	0.005	0.022^*	0.011	0.009
	(0.023)	(0.028)	(0.017)	(0.013)	(0.008)	(0.011)
Mean	4.297	4.384	0.754	0.077	0.019	0.059
Observations	8,617	8,678	8,680	8,680	8,680	8,680

The table shows the $β_{1}$ coefficients obtained through estimation of equation (1) as described in the text and reproduced here for clarity: $y_{i} = α + β_{1} G P_M a t c h_{i} + τ_{t} + π_{m} + θ_{c} + ρ_{d} + ε_{i}$ ⁠. $y_{i}$ is a general term denoting the outcome listed at the top of each column, and each estimation includes municipality (⁠ $π_{m}$ ⁠), year of swap (⁠ $τ_{t}$ ⁠), birth year (⁠ $θ_{c}$ ⁠), and previous GP (⁠ $ρ_{d}$ ⁠) fixed effects. The point estimates depicted in the table should be interpreted as the effect of random assignment to same-gender GP in childhood on the outcome listed at the top of the column. Standard errors are clustered at the level of the exogenously assigned GP. Sample includes all girls born between 1988 and 1996 who were subject to at least one exogenous GP swap prior to age 15. Significant at $^{*}$ 10%, $^{* *}$ 5%, $^{* * *}$ 1%.

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