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Nonparametric IV Estimation of Local Average Treatment Effects with Covariates

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  • Frölich, Markus

    ()
    (University of Mannheim)

Abstract

In this paper nonparametric instrumental variable estimation of local average treatment effects (LATE) is extended to incorporate confounding covariates. Estimation of local average treatment effects is appealing since their identification relies on much weaker assumptions than the identification of average treatment effects in other nonparametric instrumental variable models. Including covariates in the estimation of LATE is necessary when the instrumental variable itself is endogenous (e.g. when the instrument is self-selected). However, all previous approaches to handle covariates in the estimation of LATE rely on parametric or semiparametric methods. In this paper, a nonparametric estimator for the estimation of LATE with covariates is suggested that is root-n asymptotically normal and efficient.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 588.

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Length: 41 pages
Date of creation: Sep 2002
Date of revision:
Publication status: published in: Journal of Econometrics, 2007, 139 (1), 35-75
Handle: RePEc:iza:izadps:dp588

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Related research

Keywords: treatment effect; evaluation; matching; unobserved heterogeneity; instrumental variables; LATE;

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References

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  1. Whitney Newey & James Powell & Francis Vella, 1998. "Nonparametric Estimation of Triangular Simultaneous Equations Models," Working papers, Massachusetts Institute of Technology (MIT), Department of Economics 98-16, Massachusetts Institute of Technology (MIT), Department of Economics.
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  3. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, Econometric Society, vol. 71(4), pages 1161-1189, 07.
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  5. Angrist, Joshua D & Graddy, Kathryn & Imbens, Guido W, 2000. "The Interpretation of Instrumental Variables Estimators in Simultaneous Equations Models with an Application to the Demand for Fish," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 67(3), pages 499-527, July.
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  12. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, Econometric Society, vol. 74(1), pages 235-267, 01.
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  17. Imbens, Guido W & Rubin, Donald B, 1997. "Estimating Outcome Distributions for Compliers in Instrumental Variables Models," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 64(4), pages 555-74, October.
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  20. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, Econometric Society, vol. 66(2), pages 315-332, March.
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  22. Yau L.H.Y. & Little R.J., 2001. "Inference for the Complier-Average Causal Effect From Longitudinal Data Subject to Noncompliance and Missing Data, With Application to a Job Training Assessment for the Unemployed," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 96, pages 1232-1244, December.
  23. Guido W. Imbens & Donald B. Rubin & Bruce I. Sacerdote, 2001. "Estimating the Effect of Unearned Income on Labor Earnings, Savings, and Consumption: Evidence from a Survey of Lottery Players," American Economic Review, American Economic Association, American Economic Association, vol. 91(4), pages 778-794, September.
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