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Pairwise Difference Estimation With Nonparametric Control Variables

Author

Listed:
  • Andres Aradillas-Lopez
  • Bo E. Honoré
  • James L. Powell

Abstract

This article extends the pairwise difference estimators for various semilinear limited dependent variable models proposed by Honoré and Powell ("Identification and Inference in Econometric Models". "Essays in Honor of Thomas Rothenberg" Cambridge: Cambridge University Press, 2005) to permit the regressor appearing in the nonparametric component to itself depend upon a conditional expectation that is nonparametrically estimated. This permits the estimation approach to be applied to nonlinear models with sample selectivity and/or endogeneity, in which a "control variable" for selectivity or endogeneity is nonparametrically estimated. We develop the relevant asymptotic theory for the proposed estimators and we illustrate the theory to derive the asymptotic distribution of the estimator for the partially linear logit model. Copyright 2007 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.

Suggested Citation

  • Andres Aradillas-Lopez & Bo E. Honoré & James L. Powell, 2007. "Pairwise Difference Estimation With Nonparametric Control Variables," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1119-1158, November.
  • Handle: RePEc:ier:iecrev:v:48:y:2007:i:4:p:1119-1158
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    Cited by:

    1. Federico Belotti & Giuseppe Ilardi, 2012. "Consistent Estimation of the “True” Fixed-effects Stochastic Frontier Model," CEIS Research Paper 231, Tor Vergata University, CEIS, revised 18 Apr 2012.
    2. Koen Jochmans, 2013. "Pairwise‐comparison estimation with non‐parametric controls," Econometrics Journal, Royal Economic Society, vol. 16(3), pages 340-372, October.
    3. Aradillas-Lopez, Andres, 2012. "Pairwise-difference estimation of incomplete information games," Journal of Econometrics, Elsevier, vol. 168(1), pages 120-140.

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