BAYESIAN APPROACH FOR INDONESIA INFLATION FORECASTING

Amry, Zul (2018) BAYESIAN APPROACH FOR INDONESIA INFLATION FORECASTING. International Journal of Economics and Financial Issues, 08 (05). pp. 96-102. ISSN 2146-4138

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Official URL: http://www.econjournals.com/index.php/ijefi/index

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.

Item Type: Article
Keywords: Bayes theorem; Inflation; Normal-gamma prior
Subjects: H Social Sciences > HC Economic History and Conditions
H Social Sciences > HJ Public Finance > HJ2240 Revenue. Taxation. Internal revenue > HJ2351 Inflation and taxation
Q Science > QA Mathematics
Divisions: Fakultas Matematika dan Ilmu Pengetahuan Alam > Matematika
Depositing User: Mrs Harly Christy Siagian
Date Deposited: 13 Sep 2018 02:08
URI: http://digilib.unimed.ac.id/id/eprint/30900

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