Random Walk Smooth Transition Autoregressive Models
AbstractThis paper extends the family of smooth transition autoregressive (STAR) models by proposing a specification in which the autoregressive parameters follow random walks. The random walks in the parameters can capture structural change within a regime switching framework, but in contrast to the time varying STAR (TV-STAR) speciifcation recently introduced by Lundbergh et al (2003), structural change in our random walk STAR (RW-STAR) setting follows a stochastic process rather than a deterministic function of time. We suggest tests for RW-STAR behaviour and study the performance of RW-STARmodels in an empirical setting. The out-of sample forecasting performance of our RW-STAR models is encouraging - better than AR, LSTAR and TV-STAR specifications with respect to point forecasts and on a par with TV-STAR speciÞcations with respect to forecast density evaluations.
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Bibliographic InfoPaper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 22/04.
Length: 40 pages
Date of creation: Nov 2004
Date of revision: May 2005
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Web page: http://www.buseco.monash.edu.au/depts/ebs/
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Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-12-02 (All new papers)
- NEP-ECM-2004-12-02 (Econometrics)
- NEP-ETS-2004-12-02 (Econometric Time Series)
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