Table 8 displays our baseline estimates and the $p$-values obtained from the permutation exercises. The asterisks accompanying the estimates correspond to the level of statistical significance of our baseline estimates and are included to facilitate the interpretation of the results. The $p$-values produced by the permutation exercises greatly resemble those obtained in the baseline estimation. We can therefore reject the null hypothesis that any combination of treatment would generate the same magnitude of treatment effects as that displayed in table 2.

Table 8.

$P$-Values of Permutation Test

High school academic trackHigh school STEMM credentialCompulsory school STEMM GPAHigh school STEMM GPA
Baseline estimate 0.052*** 0.039** 0.084** 0.109***
% less than baseline 0.010 0.053 0.053 0.020
Number of replications 300 300 300 300
High school academic trackHigh school STEMM credentialCompulsory school STEMM GPAHigh school STEMM GPA
Baseline estimate 0.052*** 0.039** 0.084** 0.109***
% less than baseline 0.010 0.053 0.053 0.020
Number of replications 300 300 300 300

Authors' estimation of equation (1) as described in the text and reproduced here for clarity: $yi=α+β1GP_Matchi+τt+πm+θc+ρd+εi$. $yi$ is a general term denoting the outcome listed at the top of each column, and each estimation includes municipality ($πm$), year of swap ($τt$), birth year ($θc$), and previous GP ($ρd$) fixed effects. The table shows the proportion of times the estimates from the permutation tests are smaller than the baseline estimate. We run 300 simulations in which we randomly assign GPs to children. Standard errors are clustered at 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. The asterisks accompanying the estimates correspond to the level of statistical significance of our baseline estimates, and are included to facilitate the interpretation of the results. Significant at $*$10%, $**$5%, $***$1%.

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