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Title:Large sample theory in a semiparametric partially linear errors-in-variables models PDF Logo
Authors:Liang, Hua
Härdle, Wolfgang
Carroll, Raymond J.
Issue Date:1997
Series/Report no.:Discussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 1997,27
Abstract:We consider the partially linear model relating a response Y to predictors (X,T) with mean function XT ß + g (T) when the X's are measured with additive error. The semiparametric likelihood estimate of Severini and Staniswalis (1994) leads to biased estimates of both the parameter ß and the function g(·) when measurement error is ignored. We derive a simple modification of their estimator which is a semiparametric version of the usual parametric correction for attenuation. The resulting estimator of ß is shown to be consistent and its asymptotic distribution theory is derived. Consistent standard error estimates using sandwich-type ideas are also developed.
Subjects:Measurement Error
Errors-in-Variables
Functional Relations
Non-parametric Likelihood
Orthogonal Regression
Partially Linear Model
Semiparametric Models
Structural Relations
Persistent Identifier of the first edition:urn:nbn:de:kobv:11-10064133
Document Type:Working Paper
Appears in Collections:Discussion Papers, SFB 373, HU Berlin

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