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Uniform convergence of weighted sums of non and semiparametric residuals for estimation and testing

Juan Carlos Escanciano (), David Jacho-Chávez () and Arthur Lewbel ()

Journal of Econometrics, 2014, vol. 178, issue P3, 426-443

Abstract: A new uniform expansion is introduced for sums of weighted kernel-based regression residuals from nonparametric or semiparametric models. This expansion is useful for deriving asymptotic properties of semiparametric estimators and test statistics with data-dependent bandwidths, random trimming, and estimated efficiency weights. Provided examples include a new estimator for a binary choice model with selection and an associated directional test for specification of this model’s average structural function. An appendix contains new results on uniform rates for kernel estimators and primitive sufficient conditions for high level assumptions commonly used in semiparametric estimation.

Keywords: Semiparametric regression; Semiparametric residuals; Nonparametric residuals; Uniform-in-bandwidth; Sample selection models; Empirical process theory; Limited dependent variables (search for similar items in EconPapers)
JEL-codes: C13 C14 C21 D24 (search for similar items in EconPapers)
Date: 2014
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Working Paper: Uniform Convergence of Weighted Sums of Non- and Semi-parametric Residuals for Estimation and Testing (2012) Downloads
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DOI: 10.1016/j.jeconom.2013.06.004

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