scholarly journals Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations

2021 ◽  
Author(s):  
Liang Jiang ◽  
Peter C. B. Phillips ◽  
Yubo Tao ◽  
Yichong Zhang
Keyword(s):  
Treatment Effects ◽  
Quantile Treatment Effects

scholarly journals Quantile Treatment Effects of College Quality on Earnings: Evidence from Administrative Data in Texas

2012 ◽  
Author(s):  
Rodney Andrews ◽  
Jing Li ◽  
Michael Lovenheim
Keyword(s):  
Administrative Data ◽  
Treatment Effects ◽  
College Quality ◽  
Quantile Treatment Effects

scholarly journals Unconditional Quantile Treatment Effects Under Endogeneity

2013 ◽  
Vol 31 (3) ◽  
pp. 346-357 ◽  
Author(s):  
Markus Frölich ◽  
Blaise Melly
Keyword(s):  
Treatment Effects ◽  
Quantile Treatment Effects

scholarly journals An IV Model of Quantile Treatment Effects

Econometrica ◽  
2005 ◽  
Vol 73 (1) ◽  
pp. 245-261 ◽  
Author(s):  
Victor Chernozhukov ◽  
Christian Hansen
Keyword(s):  
Treatment Effects ◽  
Quantile Treatment Effects ◽  
Iv Model

scholarly journals An IV Model of Quantile Treatment Effects

2002 ◽  
Author(s):  
Victor Chernozhukov ◽  
Christian Hansen
Keyword(s):  
Treatment Effects ◽  
Quantile Treatment Effects ◽  
Iv Model

scholarly journals Bounds on Average and Quantile Treatment Effects of Job Corps Training on Wages

2011 ◽  
Author(s):  
German Blanco ◽  
Carlos A. Flores ◽  
Alfonso Flores-Lagunes
Keyword(s):  
Treatment Effects ◽  
Job Corps ◽  
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.

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