USAGE OF DIFFERENT PRIOR DISTRIBUTIONS IN BAYESIAN VECTOR AUTOREGRESSIVE MODELS

Sevinc V., Erguen G.

HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, cilt.38, sa.1, ss.85-93, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38 Sayı: 1
  • Basım Tarihi: 2009
  • Dergi Adı: HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.85-93
  • Hacettepe Üniversitesi Adresli: Evet

Özet

In Bayesian vector autoregressive models, the Litterman or Minnesota Prior is widely used. However, in some cases, the Minnesota prior is not the best prior distribution that can be used. Thus, other prior distributions can also be applied. In this paper, as well as the Minnesota prior, four other prior distributions have been studied. Based on these prior distributions, five different Bayesian vector autoregressive models have been built to forecast the Turkish unemployment rate and the industrial production index for the two periods of the year 2008. Finally, the five priors have been compared with each other according to the forecasting performances of the models that they are used in.