TY - JOUR
T1 - Partial identification of the distribution of treatment effects and its confidence sets
AU - Fan, Yanqin
AU - Park, Sang Soo
PY - 2009
Y1 - 2009
N2 - In this paper, we study partial identification of the distribution of treatment effects of a binary treatment for ideal randomized experiments, ideal randomized experiments with a known value of a dependence measure, and for data satisfying the selection-on-observables assumption, respectively. For ideal randomized experiments, (i) we propose nonparametric estimators of the sharp bounds on the distribution of treatment effects and construct asymptotically valid confidence sets for the distribution of treatment effects; (ii) we propose bias-corrected estimators of the sharp bounds on the distribution of treatment effects; and (iii) we investigate finite sample performances of the proposed confidence sets and the bias-corrected estimators via simulation.
AB - In this paper, we study partial identification of the distribution of treatment effects of a binary treatment for ideal randomized experiments, ideal randomized experiments with a known value of a dependence measure, and for data satisfying the selection-on-observables assumption, respectively. For ideal randomized experiments, (i) we propose nonparametric estimators of the sharp bounds on the distribution of treatment effects and construct asymptotically valid confidence sets for the distribution of treatment effects; (ii) we propose bias-corrected estimators of the sharp bounds on the distribution of treatment effects; and (iii) we investigate finite sample performances of the proposed confidence sets and the bias-corrected estimators via simulation.
UR - http://www.scopus.com/inward/record.url?scp=84863012200&partnerID=8YFLogxK
U2 - 10.1108/S0731-9053(2009)0000025004
DO - 10.1108/S0731-9053(2009)0000025004
M3 - Article
AN - SCOPUS:84863012200
SN - 0731-9053
VL - 25
SP - 3
EP - 70
JO - Advances in Econometrics
JF - Advances in Econometrics
ER -