scholarly journals Quantile Treatment Effects in the Regression Discontinuity Design: Process Results and Gini Coefficient

2010 ◽  
Author(s):  
Markus Frölich ◽  
Blaise Melly
Keyword(s):  
Design Process ◽  
Gini Coefficient ◽  
Treatment Effects ◽  
Regression Discontinuity ◽  
Regression Discontinuity Design ◽  
Quantile Treatment Effects

scholarly journals QUANTILE TREATMENT EFFECTS IN REGRESSION KINK DESIGNS

2020 ◽  
Vol 36 (6) ◽  
pp. 1167-1191
Author(s):  
Heng Chen ◽  
Harold D. Chiang ◽  
Yuya Sasaki
Keyword(s):  
Economic Policy ◽  
Statistical Inference ◽  
Treatment Effects ◽  
Regression Discontinuity ◽  
Regression Discontinuity Design ◽  
Simulation Studies ◽  
Quantile Treatment Effects ◽  
Economic Journal ◽  
Education Effects ◽  
Empirical Illustration

The literature on regression kink designs develops identification results for average effects of continuous treatments (Nielsen et al., 2010, American Economic Journal: Economic Policy 2, 185–215; Card et al., 2015, Econometrica 83, 2453–2483), average effects of binary treatments (Dong, 2018, Jump or Kink? Identifying Education Effects by Regression Discontinuity Design without the Discontinuity), and quantile-wise effects of continuous treatments (Chiang and Sasaki, 2019, Journal of Econometrics 210, 405–433), but there has been no identification result for quantile-wise effects of binary treatments to date. In this article, we fill this void in the literature by providing an identification of quantile treatment effects in regression kink designs with binary treatment variables. For completeness, we also develop large sample theories for statistical inference, present a practical guideline on estimation and inference, conduct simulation studies, and provide an empirical illustration.

scholarly journals The Effects of “Girl-Friendly” Schools: Evidence from the BRIGHT School Construction Program in Burkina Faso

2013 ◽  
Vol 5 (3) ◽  
pp. 41-62 ◽  
Author(s):  
Harounan Kazianga ◽  
Dan Levy ◽  
Leigh L Linden ◽  
Matt Sloan
Keyword(s):  
Primary School ◽  
Burkina Faso ◽  
Test Scores ◽  
Treatment Effects ◽  
Regression Discontinuity ◽  
School Construction ◽  
Regression Discontinuity Design ◽  
School Program ◽  
Percentage Points ◽  
Standard Deviations

We evaluate a “girl-friendly” primary school program in Burkina Faso using a regression discontinuity design. After 2.5 years, the program increased enrollment by 19 percentage points and increased test scores by 0.41 standard deviations. For those caused to attend school, scores increased by 2.2 standard deviations. Girls' enrollment increased by 5 percentage points more than boys' enrollment, but they experienced the same increase in test scores as boys. The unique characteristics of the schools are responsible for increasing enrollment by 13 percentage points and test scores by 0.35 standard deviations. They account for the entire difference in the treatment effects by gender. (JEL I21, I28, J16, O15)

scholarly journals Absorptive Capacity and the Growth and Investment Effects of Regional Transfers: A Regression Discontinuity Design with Heterogeneous Treatment Effects

2013 ◽  
Vol 5 (4) ◽  
pp. 29-77 ◽  
Author(s):  
Sascha O Becker ◽  
Peter H Egger ◽  
Maximilian von Ehrlich
Keyword(s):  
Absorptive Capacity ◽  
Treatment Effects ◽  
Regression Discontinuity ◽  
Income Growth ◽  
Regression Discontinuity Design ◽  
Heterogeneous Treatment Effects ◽  
Per Capita ◽  
Average Treatment Effects ◽  
Capita Income Growth ◽  
The Eu

Researchers often estimate average treatment effects of programs without investigating heterogeneity across units. Yet, individuals, firms, regions, or countries vary in their ability to utilize transfers. We analyze Objective 1 transfers of the EU to regions below a certain income level by way of a regression discontinuity design with systematically varying heterogeneous treatment effects. Only about 30 percent and 21 percent of the regions—those with sufficient human capital and good-enough institutions—are able to turn transfers into faster per capita income growth and per capita investment, respectively. In general, the variance of the treatment effect is much bigger than its mean. (JEL C21, F35, H23, H77, R11)

Sign in / Sign up

Export Citation Format

Share Document