Estimation of the Directions for Unknown Parameters in Semiparametric Models

Kavli Affiliate: Wei Gao

| First 5 Authors: Jinyue Han, Jun Wang, Wei Gao, Man-Lai Tang,

| Summary:

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 infinity moments, the proposed estimator perform well. Its application is
illustrated with data of exporting participation of manufactures in Guangdong.

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