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Pairwise‐comparison estimation with non‐parametric controls

  • Koen Jochmans

The purpose of this paper is the presentation of distribution theory for generic estimators based on the pairwise comparison of observations in problems where identification is achieved through the use of control functions. The controls can be specified semi- or non-parametrically. The criterion function may be non-smooth. The theory is applied to the estimation of the coefficients in a monotone linear-index model and to inference on the link function in a partially-linear transformation model. A number of simulation exercises serve to assess the small-sample performance of these techniques.

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File URL: http://hdl.handle.net/10.1111/ectj.2013.16.issue-3
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Article provided by Royal Economic Society in its journal Econometrics Journal.

Volume (Year): 16 (2013)
Issue (Month): 3 (October)
Pages: 340-372

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Handle: RePEc:wly:emjrnl:v:16:y:2013:i:3:p:340-372
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  1. 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.
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  15. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January.
  16. Honore, Bo E. & Powell, James L., 1994. "Pairwise difference estimators of censored and truncated regression models," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 241-278.
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