Pairwise-comparison estimation with nonparametric controls

Koen Jochmans

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Abstract: 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.

Keywords: control function; discontinuous criterion function; distribution theory; empirical process; Euclidean class; pairwise comparisons; two-step estimation (search for similar items in EconPapers)
Date: 2013-04
Note: View the original document on HAL open archive server: https://sciencespo.hal.science/hal-00973068
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Related works:
Journal Article: Pairwise‐comparison estimation with non‐parametric controls (2013)
Working Paper: Pairwise-comparison estimation with non-parametric controls (2013)
Working Paper: Pairwise-comparison estimation with nonparametric controls (2013)
Working Paper: Pairwise-comparison estimation with non-parametric controls (2013)
Working Paper: Pairwise-comparison estimation with nonparametric controls (2013)
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