Maheu, John and Song, Yong (2012): A new structural break model with application to Canadian inflation forecasting.
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This paper develops an efficient approach to model and forecast time-series data with an unknown number of change-points. Using a conjugate prior and conditional on time-invariant parameters, the predictive density and the posterior distribution of the change-points have closed forms. The conjugate prior is further modeled as hierarchical to exploit the information across regimes. This framework allows breaks in the variance, the regression coefficients or both. Regime duration can be modelled as a Poisson distribution. An new efficient Markov Chain Monte Carlo sampler draws the parameters as one block from the posterior distribution. An application to Canada inflation time series shows the gains in forecasting precision that our model provides.
|Item Type:||MPRA Paper|
|Original Title:||A new structural break model with application to Canadian inflation forecasting|
|Keywords:||multiple change-points; regime duration; inflation targeting; predictive density; MCMC|
|Subjects:||C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation
C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General
|Depositing User:||Yong Song|
|Date Deposited:||24. Feb 2012 14:19|
|Last Modified:||11. Feb 2013 19:02|
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