Nonparametric inference for counterfactual means: Bias-correction, confidence sets, and weak IV

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초록

This paper supplements Manski (1990) and Manski and Pepper (2000) and contributes to the literature by introducing the concept of weak IV for the partially identified mean counterfactual outcomes when an instrumental variable (IV) or a monotone instrumental variable (MIV) is available (IV or MIV assumption respectively); developing asymptotically uniformly valid confidence sets for the counterfactual mean outcomes and average treatment effects under the assumptions; correcting biases of estimates of bounds on the counterfactual mean outcomes under the assumptions. We apply the confidence sets to further examining the effect of family intactness on a child's high school graduation originally studied in Manski et al. (1992). Published by Elsevier B.V.

키워드

Average treatment effect; Counterfactual mean outcome; Kernel estimation; Partial identification; MODEL-SPECIFICATION TESTS; PARAMETERS; VARIABLES; INTERVALS; BOUNDS
제목
Nonparametric inference for counterfactual means: Bias-correction, confidence sets, and weak IV
저자
Fan, Yanqin; Park, Sang Soo
DOI
10.1016/j.jeconom.2013.08.005
발행일
2014-01
유형
Article
저널명
Journal of Econometrics
권
178
페이지
45 ~ 56