Restrictions Search for Panel VARs

Annika Schnücker

VfS Annual Conference 2016 (Augsburg): Demographic Change from Verein für Socialpolitik / German Economic Association

Abstract: Panel vector autoregressive (PVAR) models can include several countries and variables in one system and thus are well suited for global spillover analyses. However, PVARs require restrictions to ensure the feasibility of the estimation. The present paper uses a selection prior for a data-based restriction search. It introduces the stochastic search variable selection for PVAR models (SSVSP) as an alternative estimation procedure for PVARs. This extends Koop's and Korobilis's stochastic search specification selection (S4) to a restriction search on single elements. The SSVSP allows to incorporate dynamic and static interdependencies as well as cross-country heterogeneities. It uses a hierarchical prior to search for data-supported restrictions. The prior differentiates between domestic and foreign variables, thereby allowing a less restrictive panel structure. Absent a matrix structure for restrictions, a Monte Carlo simulation shows that SSVSP outperforms S4. Furthermore, this is validated by performing a forecast exercise for G7 countries.

JEL-codes: C11 C33 C52 (search for similar items in EconPapers)
Date: 2016
New Economics Papers: this item is included in nep-ets and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:vfsc16:145566

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