Flexible Fat-tailed Vector Autoregression

Sune Karlsson () and Stepan Mazur

No 2020:5, Working Papers from Örebro University, School of Business

Abstract: We propose a general class of multivariate fat-tailed distributions which includes the normal, t and Laplace distributions as special cases as well as their mixture. Full conditional posterior distributions for the Bayesian VAR-model are derived and used to construct a MCMC-sampler for the joint posterior distribution. The framework allows for selection of a specific special case as the distribution for the error terms in the VAR if the evidence in the data is strong while at the same time allowing for considerable flexibility and more general distributions than offered by any of the special cases. As fat tails can also be a sign of conditional heteroskedasticity we also extend the model to allow for stochastic volatility. The performance is evaluated using simulated data and the utility of the general model specification is demonstrated in applications to macroeconomics.

Keywords: Scale mixture of normals; Elliptically contoured distribution; Mixture distributions; Stochastic volatility; Markov Chain Monte Carlo (search for similar items in EconPapers)
JEL-codes: C11 C15 C16 C32 C52 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2020-04-27
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-gen and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:hhs:oruesi:2020_005

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