Bayesian Approach for Indonesia Inflation Forecasting

Zul - Amry
Additional contact information
Zul - Amry: Department of Mathematics, State University of Medan, Indonesia

International Journal of Economics and Financial Issues, 2018, vol. 8, issue 5, 96-102

Abstract: This paper presents a Bayesian approach to find the Bayesian model for the point forecast of ARMA model under normal-gamma prior assumption with quadratic loss function in the form of mathematical expression. The conditional posterior predictive density is obtained from the combination of the posterior under normal-gamma prior with the conditional predictive density. The marginal conditional posterior predictive density is obtained by integrating the conditional posterior predictive density, whereas the point forecast is derived from the marginal conditional posterior predictive density. Furthermore, the forecasting model is applied to inflation data and compare to traditional method. The results show that the Bayesian forecasting is better than the traditional forecasting.

Keywords: ARMA model; Bayes theorem; Inflation; Normal-gamma prior (search for similar items in EconPapers)
JEL-codes: C13 C15 C22 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.econjournals.com/index.php/ijefi/article/download/6870/pdf (application/pdf)
https://www.econjournals.com/index.php/ijefi/article/view/6870/pdf (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eco:journ1:2018-05-15

Access Statistics for this article

International Journal of Economics and Financial Issues is currently edited by Ilhan Ozturk

More articles in International Journal of Economics and Financial Issues from Econjournals
Bibliographic data for series maintained by Ilhan Ozturk ().