Quotation Feldkircher, Martin, Huber, Florian, Kastner, Gregor. 2017. Sophisticated and Small Versus Simple and Sizeable: When Does it Pay Off to Introduce Drifting Coefficients in Bayesian VARs?


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Abstract

We assess the relationship between model size and complexity in the time-varying parameter VAR framework via thorough predictive exercises for the Euro Area, the United Kingdom and the United States. It turns out that sophisticated dynamics through drifting coefficients are important in small data sets while simpler models tend to perform better in sizeable data sets. To combine best of both worlds, novel shrinkage priors help to mitigate the curse of dimensionality, resulting in competitive forecasts for all scenarios considered. Furthermore, we discuss dynamic model selection to improve upon the best performing individual model for each point in time.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Working/discussion paper, preprint
Language English
Title Sophisticated and Small Versus Simple and Sizeable: When Does it Pay Off to Introduce Drifting Coefficients in Bayesian VARs?
Year 2017
URL https://arxiv.org/abs/1711.00564
JEL C11, C30, C53, E52

Associations

People
Huber, Florian (Details)
Kastner, Gregor (Details)
External
Feldkircher, Martin (OeNB, Austria)
Organization
Institute for Statistics and Mathematics IN (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
1105 Computer software (Details)
1162 Statistics (Details)
5323 Econometrics (Details)
5701 Applied statistics (Details)
5707 Time series analysis (Details)
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