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Asymptotic theory for partly linear models

By Jiti Gao

Abstract

This paper considers a partially linear model of the form y = x beta + g(t) + e, where beta is an unknown parameter vector, g(.) is an unknown function, and e is an error term. Based on a nonparametric estimate of g(.), the parameter beta is estimated by a semiparametric weighted least squares estimator. An asymptotic theory is established for the consistency of the estimators.

Topics: C14 - Semiparametric and Nonparametric Methods: General, C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
Year: 1994
DOI identifier: 10.1080/03610929508831598
OAI identifier: oai:mpra.ub.uni-muenchen.de:40452

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