Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging

Econometrics

关键词: model selection;    model averaging;    focused information criterion;    generalized empirical likelihood;   

DOI  :  10.3390/econometrics1020141

来源: mdpi

【 摘 要 】

This paper develops model selection and averaging methods for moment restriction models. We first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rather than a correct model, for estimating a specific parameter of interest. Then, this study investigates a generalized empirical likelihood-based model averaging estimator that minimizes the asymptotic mean squared error. A simulation study suggests that our averaging estimator can be a useful alternative to existing post-selection estimators.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.