Economics at your fingertips  

Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance

Liang Jiang, Oliver Linton (), Haihan Tang and Yichong Zhang

Papers from

Abstract: We study how to improve efficiency via regression adjustments with additional covariates under covariate-adaptive randomizations (CARs) when subject compliance is imperfect. We first establish the semiparametric efficiency bound for the local average treatment effect (LATE) under CARs. Second, we develop a general regression-adjusted LATE estimator which allows for parametric, nonparametric, and regularized adjustments. Even when the adjustments are misspecified, our proposed estimator is still consistent and asymptotically normal, and their inference method still achieves the exact asymptotic size under the null. When the adjustments are correctly specified, our estimator achieves the semiparametric efficiency bound. Third, we derive the optimal linear adjustment that leads to the smallest asymptotic variance among all linear adjustments. We then show the commonly used two stage least squares estimator is not optimal in the class of LATE estimators with linear adjustments while Ansel, Hong, and Li's (2018) estimator is. Fourth, we show how to construct a LATE estimator with nonlinear adjustments which is more efficient than those with the optimal linear adjustment. Fifth, we give conditions under which LATE estimators with nonparametric and regularized adjustments achieve the semiparametric efficiency bound. Last, simulation evidence and empirical application confirm efficiency gains achieved by regression adjustments relative to both the estimator without adjustment and the standard two-stage least squares estimator.

Date: 2022-01, Revised 2022-09
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Papers from
Bibliographic data for series maintained by arXiv administrators ().

Page updated 2022-09-07
Handle: RePEc:arx:papers:2201.13004