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Table 10 Differences in RD estimates of test scores by household income

From: The effect of age at school entry on college admission and earnings: a regression-discontinuity approach

 

(<5 MWs)–(5–10 MWs)

(5–10 MWs)–(>10 MWs)

(<5 MWs)–(>10 MWs)

Polyn.

CCT procedure

IW procedure

CCT procedure

IW procedure

CCT procedure

IW procedure

degree

Diff.

z-stat

Diff.

z-stat

Diff.

z-stat

Diff.

z-stat

Diff.

z-stat

Diff.

z-stat

 

Male

0

0.145

1.538

−0.034

−0.601

0.042

0.583

0.049

0.855

0.187**

2.019

0.015

0.309

1

0.190

1.594

0.120

1.301

0.054

0.547

0.052

0.758

0.244**

2.218

0.172**

1.989

2

0.217

1.572

0.163

1.461

−0.015

−0.108

0.077

0.734

0.202

1.484

0.240**

2.129

 

Female

0

0.044

0.763

0.006

0.138

0.113*

1.825

0.062

1.416

0.157**

2.544

0.068**

1.990

1

0.136

1.472

0.042

0.604

0.060

0.620

0.145**

2.040

0.196**

2.439

0.187***

2.700

2

0.157

1.269

0.118

1.314

0.062

0.487

0.108

1.260

0.219*

1.795

0.226***

2.751

  1. This table shows the differences in RD estimates of test scores between household income ranges using different local-polynomial degrees (per row) and different bandwidth selection procedures (per column). The first panel on the left shows differences in estimates between candidates from households that receive less than five minimum wages (<5 MWs) per month and candidates from households that receive between five and ten minimum wages (5–10 MWs) per month. The second panel in the center shows differences in estimates between candidates from households that receive between five and ten minimum wages (5–10 MWs) per month and candidates from households that receive more than ten minimum wages (>10 MWs) per month. The third panel on the right shows differences in estimates between candidates from households that receive less than five minimum wages (<5 MWs) per month and candidates from households that receive more than ten minimum wages (>10 MWs) per month. The CCT procedure is proposed by Calonico et al. (2014). The IW procedure is proposed by Imbens and Kalyanaraman (2012). All functions are estimated using a triangular kernel. Data come from applications for undergraduate programs at UFPE from 2002 to 2005. The sample is restricted to those who graduated from high school in the same year and were under 18.5 years old
  2. ***, **, * represent statistical significance at the 1, 5, and 10 % levels, respectively
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