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Figure A.1.

Regional Vocational and Technical School Locations with Affiliated Towns.

Figure A.1.

Regional Vocational and Technical School Locations with Affiliated Towns.

Figure A.2.

Differences in First Stage When Interview is Removed for One School Where Subscores Are Available.

Figure A.2.

Differences in First Stage When Interview is Removed for One School Where Subscores Are Available.

Table A.1.
Estimates Using Multiple Matching Estimators
CEM (1)Propensity Score (2)Inverse Propensity Weights (3)Nearest Neighbor Mahalanobis (4)
On-time graduation 0.04*** 0.053*** 0.037*** 0.049*** 
 (0.003) (0.003) (0.005) (0.003) 
N 410,176 417,215 417,215 417,215 
CEM (1)Propensity Score (2)Inverse Propensity Weights (3)Nearest Neighbor Mahalanobis (4)
On-time graduation 0.04*** 0.053*** 0.037*** 0.049*** 
 (0.003) (0.003) (0.005) (0.003) 
N 410,176 417,215 417,215 417,215 

Notes: Heteroskedasticity robust standard errors are in parentheses. Estimates of the sample average treatment effect of experiencing an RVTS in grade 9 on the probability of graduating on time from high school using multiple matching estimators. The sample consists of those members of the 2008 through 2015 cohorts who are present in the data in eighth grade. CEM: coarsened exact matching (see Iacus, King, and Porro 2012).

***p < 0.01.

Table A.2.
Reduced-form Estimates of the Effect of Attending an RVTS on Student Outcomes When Removing Potentially Endogenous Interview Score from Admissions Score
Graduated (1)Earned Certificate (2)Math Score (3)ELA Score (4)Pass Both (5)
IK bandwidth 0.051*** −0.058 0.152** 0.118 −0.022 
 (0.013) (0.035) (0.067) (0.072) (0.06) 
N 560 715 661 661 759 
Bandwidth = 6 0.051*** −0.065 0.212*** 0.154** 0.007 
 (0.013) (0.036) (0.049) (0.064) (0.058) 
N 560 560 560 560 560 
Bandwidth = 9 0.036** −0.051 0.048 −0.005 −0.022 
 (0.016) (0.035) (0.09) (0.099) (0.059) 
N 759 759 759 759 759 
Bandwidth = 12 0.012 −0.052 −0.014 −0.069 −0.034 
 (0.02) (0.035) (0.092) (0.104) (0.053) 
N 1,029 1,029 1,029 1,029 1,029 
Bandwidth = 9, controls 0.034** −0.056 0.012 0.011 −0.017 
 (0.015) (0.037) (0.062) (0.06) (0.055) 
N 758 758 758 758 758 
Graduated (1)Earned Certificate (2)Math Score (3)ELA Score (4)Pass Both (5)
IK bandwidth 0.051*** −0.058 0.152** 0.118 −0.022 
 (0.013) (0.035) (0.067) (0.072) (0.06) 
N 560 715 661 661 759 
Bandwidth = 6 0.051*** −0.065 0.212*** 0.154** 0.007 
 (0.013) (0.036) (0.049) (0.064) (0.058) 
N 560 560 560 560 560 
Bandwidth = 9 0.036** −0.051 0.048 −0.005 −0.022 
 (0.016) (0.035) (0.09) (0.099) (0.059) 
N 759 759 759 759 759 
Bandwidth = 12 0.012 −0.052 −0.014 −0.069 −0.034 
 (0.02) (0.035) (0.092) (0.104) (0.053) 
N 1,029 1,029 1,029 1,029 1,029 
Bandwidth = 9, controls 0.034** −0.056 0.012 0.011 −0.017 
 (0.015) (0.037) (0.062) (0.06) (0.055) 
N 758 758 758 758 758 

Notes: Heteroskedasticity robust standard errors clustered by application score are in parentheses. Reduced-form estimates show the impact of attending an oversubscribed RVTS on student outcomes. In these models only one school is used. The forcing variable is the admissions scores purged of the interview component, and with the mean interview score imputed so that the initial cutoff score for admission could be retained to define eligibility for admission. This increases the fuzziness of the discontinuity, but arguably removes the only potentially endogenous element of application scores. The coefficients shown are generated by local linear regression using a triangular kernel of the listed bandwidth, including cohort fixed effects. The sample consists of those members of the 2007 through 2009 cohorts who are present in the data in eighth grade. ELA: English language arts; IK: Imbens and Kalyanaraman 2012.

**p < 0.05; ***p < 0.01.

Table A.3.
Testing Functional Form Assumptions
Graduated (1)Enrolled Grade 10 (2)Earned Certificate (3)Math Score (4)ELA Score (5)Pass Both (6)
Linear, BW = IK 0.087*** 0.021 0.045*** −0.019 −0.022 −0.020 
 (0.023) (0.013) (0.011) (0.041) (0.052) (0.044) 
N 1,756 3,833 2,606 2,473 2,501 1,756 
Up to quadratic, BW = IK 0.141*** 0.040** 0.048*** −0.027 0.060 −0.054 
 (0.041) (0.017) (0.013) (0.040) (0.076) (0.077) 
N 1,756 3,833 2,606 2,473 2,501 1,756 
Linear, BW = 6 0.117*** 0.017 0.050*** −0.080 −0.006 −0.038 
 (0.026) (0.022) (0.008) (0.074) (0.045) (0.051) 
N 1,023 1,023 1,023 903 913 1,023 
Up to quadratic, BW = 6 0.120*** −0.005 0.027 −0.075 0.024 −0.083 
 (0.033) (0.043) (0.016) (0.089) (0.076) (0.091) 
N 1,023 1,023 1,023 903 913 1,023 
Linear, BW = 12 0.076** 0.028 0.046*** −0.021 −0.002 −0.021 
 (0.022) (0.017) (0.011) (0.040) (0.053) (0.043) 
N 2,108 2,108 2,108 1,885 1,906 2,108 
Up to quadratic, BW = 12 0.128*** 0.018 0.048*** −0.046 0.084 −0.037 
 (0.030) (0.024) (0.013) (0.051) (0.073) (0.071) 
N 2,108 2,108 2,108 1,885 1,906 2,108 
Linear, BW = 15 0.057** 0.030** 0.045*** −0.018 −0.020 −0.027 
 (0.023) (0.014) (0.011) (0.042) (0.052) (0.038) 
N 2,606 2,606 2,606 2,336 2,364 2,606 
Up to quadratic, BW = 15 0.127*** 0.020 0.047*** −0.030 0.061 −0.023 
 (0.029) (0.022) (0.014) (0.040) (0.076) (0.063) 
N 2,606 2,606 2,606 2,336 2,364 2,606 
Graduated (1)Enrolled Grade 10 (2)Earned Certificate (3)Math Score (4)ELA Score (5)Pass Both (6)
Linear, BW = IK 0.087*** 0.021 0.045*** −0.019 −0.022 −0.020 
 (0.023) (0.013) (0.011) (0.041) (0.052) (0.044) 
N 1,756 3,833 2,606 2,473 2,501 1,756 
Up to quadratic, BW = IK 0.141*** 0.040** 0.048*** −0.027 0.060 −0.054 
 (0.041) (0.017) (0.013) (0.040) (0.076) (0.077) 
N 1,756 3,833 2,606 2,473 2,501 1,756 
Linear, BW = 6 0.117*** 0.017 0.050*** −0.080 −0.006 −0.038 
 (0.026) (0.022) (0.008) (0.074) (0.045) (0.051) 
N 1,023 1,023 1,023 903 913 1,023 
Up to quadratic, BW = 6 0.120*** −0.005 0.027 −0.075 0.024 −0.083 
 (0.033) (0.043) (0.016) (0.089) (0.076) (0.091) 
N 1,023 1,023 1,023 903 913 1,023 
Linear, BW = 12 0.076** 0.028 0.046*** −0.021 −0.002 −0.021 
 (0.022) (0.017) (0.011) (0.040) (0.053) (0.043) 
N 2,108 2,108 2,108 1,885 1,906 2,108 
Up to quadratic, BW = 12 0.128*** 0.018 0.048*** −0.046 0.084 −0.037 
 (0.030) (0.024) (0.013) (0.051) (0.073) (0.071) 
N 2,108 2,108 2,108 1,885 1,906 2,108 
Linear, BW = 15 0.057** 0.030** 0.045*** −0.018 −0.020 −0.027 
 (0.023) (0.014) (0.011) (0.042) (0.052) (0.038) 
N 2,606 2,606 2,606 2,336 2,364 2,606 
Up to quadratic, BW = 15 0.127*** 0.020 0.047*** −0.030 0.061 −0.023 
 (0.029) (0.022) (0.014) (0.040) (0.076) (0.063) 
N 2,606 2,606 2,606 2,336 2,364 2,606 

Notes: Heteroskedasticity robust standard errors clustered by score are in parentheses. The reduced form estimates reported here were generated using ordinary least squares with an indicator for whether a student received an offer of admission from an oversubscribed regional vocational and technical school. Estimates are reported across multiple bandwidths with both quadratic and linear specifications of the forcing variable included at each bandwidth. All models include individual-level covariates to improve precision, as well as fixed effects for graduation cohort and school. BW: bandwidth; ELA: English language arts; IK: Imbens and Kalyanaraman 2012.

**p < 0.05; ***p < 0.01.

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