Doubly Robust Estimation of Local Average Treatment Effects Using Inverse Probability Weighted Regression Adjustment

Tymon Słoczyński, Selver Uysal and Jeffrey Wooldridge

No 15727, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: We revisit the problem of estimating the local average treatment effect (LATE) and the local average treatment effect on the treated (LATT) when control variables are available, either to render the instrumental variable (IV) suitably exogenous or to improve precision. Unlike previous approaches, our doubly robust (DR) estimation procedures use quasi-likelihood methods weighted by the inverse of the IV propensity score – so-called inverse probability weighted regression adjustment (IPWRA) estimators. By properly choosing models for the propensity score and out-come models, fitted values are ensured to be in the logical range determined by the response variable, producing DR estimators of LATE and LATT with appealing small sample properties. Inference is relatively straightforward both analytically and using the nonparametric bootstrap. Our DR LATE and DR LATT estimators work well in simulations. We also propose a DR version of the Hausman test that can be used to assess the unconfoundedness assumption through a comparison of different estimates of the average treatment effect on the treated (ATT) under one-sided noncompliance. Unlike the usual test that compares OLS and IV estimates, this procedure is robust to treatment effect heterogeneity.

Keywords: double robustness; instrumental variables; local average treatment effects; one-sided noncompliance (search for similar items in EconPapers)
JEL-codes: C21 C26 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2022-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://docs.iza.org/dp15727.pdf (application/pdf)

Related works:
Working Paper: Doubly Robust Estimation of Local Average Treatment Effects Using Inverse Probability Weighted Regression Adjustment (2022)
Working Paper: Doubly Robust Estimation of Local Average Treatment Effects Using Inverse Probability Weighted Regression Adjustment (2022)
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: https://EconPapers.repec.org/RePEc:iza:izadps:dp15727

Ordering information: This working paper can be ordered from
IZA, Margard Ody, P.O. Box 7240, D-53072 Bonn, Germany

Access Statistics for this paper

More papers in IZA Discussion Papers from Institute of Labor Economics (IZA) IZA, P.O. Box 7240, D-53072 Bonn, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Holger Hinte ().