Estimation of the directions for unknown parameters in semiparametric models

Jinyue Han, Jun Wang, Wei Gao and Man-Lai Tang

MPRA Paper from University Library of Munich, Germany

Abstract: Semiparametric models are useful in econometrics, social sciences and medicine application. In this paper, a new estimator based on least square methods is proposed to estimate the direction of unknown parameters in semi-parametric models. The proposed estimator is consistent and has asymptotic distribution under mild conditions without the knowledge of the form of link function. simulations show that the proposed estimator is significantly superior to maximum score estimator given by Manski (1975) for binary response variables. When the error term is long-tailed distributions or distribution with no moments, the proposed estimator perform well. Its application is illustrated with data of exportibg participation of manufactures in Guangdong

Keywords: Binary model; direction; least squares estimator; maximum score; semi-parametric models; single index model. (search for similar items in EconPapers)
JEL-codes: C2 C25 C4 C51 (search for similar items in EconPapers)
Date: 2023-02-13
New Economics Papers: this item is included in nep-ecm
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