Bayesian model averaging and identification of structural breaks in time series

Kelvin G. Balcombe, Iain Fraser, Abhijit Sharma

Research output: Contribution to journalArticle

Abstract

Bayesian Model Averaging (BMA) is used for testing for multiple break points in univariate series using conjugate normal-gamma priors. This approach can test for the number of structural breaks and produce posterior probabilities for a break at each point in time. Results are averaged over specifications including: stationary; stationary around trend and unit root models, each containing different types and number of breaks and different lag lengths. The procedures are used to test for structural breaks on 14 annual macroeconomic series and 11 natural resource price series. The results indicate that there are structural breaks in all of the natural resource series and most of the macroeconomic series. Many of the series had multiple breaks. Our findings regarding the existence of unit roots, having allowed for structural breaks in the data, are largely consistent with previous work.

Original languageEnglish
Pages (from-to)3805-3818
Number of pages14
JournalApplied Economics
Volume43
Issue number26
Early online date18 Nov 2010
DOIs
Publication statusPublished - 1 Oct 2011
Externally publishedYes

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