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Stochastic model specification in Markov switching vector error correction models

Florian Huber, Michael Pfarrhofer () and Thomas O. Zörner
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Thomas O. Zörner: WU Wirtschaftsuniversität Wien

Authors registered in the RePEc Author Service: Thomas O. Zoerner

No 2018-3, Working Papers in Economics from University of Salzburg

Abstract: This paper proposes a hierarchical modeling approach to perform stochastic model specification in Markov switching vector error correction models. We assume that a common distribution gives rise to the regime-specific regression coefficients. The mean as well as the variances of this distribution are treated as fully stochastic and suitable shrinkage priors are used. These shrinkage priors enable to assess which coefficients differ across regimes in a flexible manner. In the case of similar coefficients, our model pushes the respective regions of the parameter space towards the common distribution. This allows for selecting a parsimonious model while still maintaining sufficient flexibility to control for sudden shifts in the parameters, if necessary. In the empirical application, we apply our modeling approach to Euro area data and assume that transition probabilities between expansion and recession regimes are driven by the cointegration errors. Our findings suggest that lagged cointegration errors have predictive power for regime shifts and these movements between business cycle stages are mostly driven by differences in error variances.

Keywords: Non-linear vector error correction model; Markov switching; hierarchical modeling; variable selection; equilibrium credit level; Euro area (search for similar items in EconPapers)
JEL-codes: C11 C32 E32 E44 E51 (search for similar items in EconPapers)
Pages: 17 pages
Date: 2018-11-01
New Economics Papers: this item is included in nep-mac and nep-ore
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Working Paper: Stochastic model specification in Markov switching vector error correction models (2019) Downloads
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