Semiparametric Estimation of Nonseparable Models: A Minimum Distance from Independence Approach

Ivana Komunjer and Andres Santos

University of California at San Diego, Economics Working Paper Series from Department of Economics, UC San Diego

Abstract: This paper focuses on nonseparable structural models of the form Y = m(X, U, α0) with U X and in which the structural parameter α0 contains both finite dimensional (θ0) and infinite dimensional (h0) unknown components. Our proposal is to estimate α0 by a minimum distance from independence (MDI) criterion. We show that: (i) our estimator of h0 is consistent and obtain rates of convergence; (ii) the estimator of θ0 is square root n consistent and asymptotically normally distributed.

Keywords: Nonparametric methods; Identification; estimation (search for similar items in EconPapers)
Date: 2009-03-01
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Related works:
Journal Article: Semi-parametric estimation of non-separable models: a minimum distance from independence approach (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:cdl:ucsdec:qt32k957bp

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