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On the Specification of Local Models in a Global Vector Autoregression: A Comparison of Markov-Switching Alternatives
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In this paper, focus is on the global vector autoregressive (GVAR) model. Its attractiveness

stems from an ability to incorporate global interdependencies when modeling local

economies. The model is based on a collection of local models, which in general are estimated as regular VAR models. This paper examines alternative specifications of the local

models by estimating them as regime-switching VAR models, where transition probabilities

between different states are studied using both constant and time-varying settings. The

results show that regime-switching models are appealing as they yield inferences about the

states of the economy, but these inferences are not guaranteed to be reasonable from an

economic point of view. Furthermore, the global solution of the model is in some cases

non-stationary when local models are regime-switching. The conclusion is that the regime-switching alternatives, while theoretically reasonable, are sensitive to the exact specification

used. At the same time, the issue of specifying the regime-switching models in such

a way that they perform adequately speaks in favor of the simpler, yet functional, basic

GVAR model.

Place, publisher, year, edition, pages
2014. , 30 p.
Keyword [en]
GVAR, VAR, time-varying, regime switching, macroeconometrics, global
National Category
Probability Theory and Statistics
URN: urn:nbn:se:uu:diva-226918OAI: diva2:727669
Subject / course
Educational program
Master Programme in Statistics
Available from: 2014-06-24 Created: 2014-06-23 Last updated: 2014-06-24Bibliographically approved

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