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Bayesian Model Averaging and Identification of Structural Breaks in Time Series

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Author Info
Fraser, Iain
Balcombe, Kelvin
Sharma, Abhijit

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Abstract

Bayesian model averaging is used for testing for multiple break points in uni- variate 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 speciÖcations including: station- ary; stationary around trend; and, unit root models, each containing di§ erent types and numbers of breaks and di§ erent 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 al l of the natural resource series and most of the macroeconomic series. Many of the series had multiple breaks. Our Öndings regarding the existence of unit roots, having al lowed for structural breaks in the data, are largely consistent with previous work.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 8676.

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Date of creation: Oct 2007
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Handle: RePEc:pra:mprapa:8676

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Related research
Keywords: Bayesian Model Averaging Structural Breaks Unit Root Macro- economic Data Natural Resource data

Find related papers by JEL classification:
C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis

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