A Time Series Model of Multiple Structural changes in Level, Trend and Variance
AbstractWe consider a deterministically trending dynamic time series model in which multiple changes in level, trend and error variance are modeled explicitly and the number but not the timing of the changes are known. Estimation of the model is made possible by the use of the Gibbs sampler. The determination of the number of structural breaks and the form of structural change is considered as a problem of model selection and we compare the use of marginal likelihoods, posterior odds ratios and Schwarz' BIC model selection criterion to select the most appropriate model from the data. We evaluate the efficacy of the Bayesian approach using a small Monte Carlo experiment. As empirical examples, we investigate structural changes in the U.S. ex-post real interest rate and in a long time series of U.S. GDP.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 9903002.
Length: 13 pages
Date of creation: 24 Mar 1999
Date of revision: 31 Mar 1999
Note: Type of Document - Adobe Acrobat; prepared on PC using TeX; to print on Postscript; pages: 13 ; figures: included
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BIC; Gibbs sampling; multiple structural changes; posterior odds ratio;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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