WALS Prediction

CentER Discussion Paper Series No. 2012-043

38 Pages Posted: 1 Jun 2012

See all articles by J.R. Magnus

J.R. Magnus

Vrije Universiteit Amsterdam, School of Business and Economics

Wendun Wang

Erasmus University Rotterdam (EUR) - Department of Econometrics

Xinyu Zhang

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

Date Written: May 31, 2012

Abstract

Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty from the selection procedure. This paper proposes a weighted average least squares (WALS) prediction procedure that is not conditional on the selected model. Taking both model and error uncertainty into account, we also propose an appropriate estimate of the variance of the WALS predictor. Correlations among the random errors are explicitly allowed. Compared to other prediction averaging methods, the WALS predictor has important advantages both theoretically and computationally. Simulation studies show that the WALS predictor generally produces lower mean squared prediction errors than its competitors, and that the proposed estimator for the prediction variance performs particularly well when model uncertainty increases.

Keywords: Model averaging, Model uncertainty, Bayesian analysis, Prediction

JEL Classification: C11, C52, C53

Suggested Citation

Magnus, Jan R. and Wang, Wendun and Zhang, Xinyu, WALS Prediction (May 31, 2012). CentER Discussion Paper Series No. 2012-043. Available at SSRN: https://ssrn.com/abstract=2071146 or http://dx.doi.org/10.2139/ssrn.2071146

Jan R. Magnus (Contact Author)

Vrije Universiteit Amsterdam, School of Business and Economics ( email )

De Boelelaan 1105
Amsterdam, 1081HV
Netherlands

Wendun Wang

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

P.O. Box 1738
3000 DR Rotterdam
Netherlands

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

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