The application of Bayesian Model Averaging in Macroeconomy
Bayesian Model Averaging is a weighted averaging method based on posterior distribution. It considers comprehensively the prior and sample information of model and parameter, reduces the model uncertainty. Bayesian Model Averaging improves statistical inference accuracy and provides improved out-of-sample predictive performance. In this paper, we outline the details of the Bayesian model averaging principle, introduce the application of Bayesian Model Averaging in macroeconomy and give an example about the application of Bayesian Model Averaging in GDP research.
Key words: Bayesian Model Averaging; Model uncertainty; Macroeconomy
- There are currently no refbacks.
If you have already registered in Journal A and plan to submit article(s) to Journal B, please click the CATEGORIES, or JOURNALS A-Z on the right side of the "HOME".
We only use the following emails to deal with issues about paper acceptance, payment and submission of electronic versions of our journals to databases:
email@example.com; firstname.lastname@example.org; email@example.com
Copyright © Canadian Research & Development Centre of Sciences and Cultures (CRDCSC)
Address:758, 77e AV, Laval, Quebec, H7V 4A8, Canada
Telephone: 1-514-558 6138