Optimal Model Averaging Estimation for Partially Linear Models

32 Pages Posted: 8 Apr 2017

See all articles by Xinyu Zhang

Xinyu Zhang

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Sciences

Wendun Wang

Erasmus University Rotterdam (EUR) - Department of Econometrics

Date Written: November 5, 2015

Abstract

This article studies optimal model averaging for partially linear models with heteroscedasticity. A Mallows-type criterion is proposed to choose the weight. The resulting model averaging estimator is proved to be asymptotically optimal under some regularity conditions. Simulation experiments show that the proposed model averaging method is superior to commonly-used model selection and averaging methods. The proposed procedure is further applied to study Japan’s sovereign credit default swap spreads.

Keywords: Asymptotic optimality, Heteroscedasticity, Model averaging, Partially linear model

JEL Classification: C52, C14, H63

Suggested Citation

Zhang, Xinyu and Wang, Wendun, Optimal Model Averaging Estimation for Partially Linear Models (November 5, 2015). Available at SSRN: https://ssrn.com/abstract=2948380 or http://dx.doi.org/10.2139/ssrn.2948380

Xinyu Zhang

Chinese Academy of Sciences (CAS) - Academy of Mathematics and Systems Sciences ( email )

Zhong-Guan-Cun-Dong-Lu 55, Haidian District
Beijing, 100190, P.R., Beijing 100190
China

Wendun Wang (Contact Author)

Erasmus University Rotterdam (EUR) - Department of Econometrics ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

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