European Business Schools Librarian's Group
Department of Economics Working Papers,
Vienna University of Economics and Business, Department of Economics
Model instability in predictive exchange rate regressions
Niko Hauzenberger () and Florian Huber ()
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Niko Hauzenberger: Vienna University of Economics and Business, Department of Economics
Florian Huber: Paris Lodron University of Salzburg, Salzburg Centre of European Union Studies
Abstract: In this paper we aim to improve existing empirical exchange rate models by accounting for uncertainty with respect to the underlying structural representation. Within a flexible Bayesian non-linear time series framework, our modeling approach assumes that different regimes are characterized by commonly used structural exchange rate models, with their evolution being driven by a Markov process. We assume a time-varying transition probability matrix with transition probabilities depending on a measure of the monetary policy stance of the central bank at the home and foreign country. We apply this model to a set of eight exchange rates against the US dollar. In a forecasting exercise, we show that model evidence varies over time and a model approach that takes this empirical evidence seriously yields improvements in accuracy of density forecasts for most currency pairs considered.
Keywords: Empirical exchange rate models, exchange rate fundamentals, Markov switching
JEL-codes: C30; E32; E52; F31 December 2018
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