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Model instability in predictive exchange rate regressions

Niko Hauzenberger () and Florian Huber
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Niko Hauzenberger: WU Wirtschaftsuniversität Wien

No 2018-8, Working Papers in Economics from University of Salzburg

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 (search for similar items in EconPapers)
JEL-codes: C30 E32 E52 F31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-for, nep-mac and nep-mon
Date: 2018-11-21
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Working Paper: Model instability in predictive exchange rate regressions (2018) Downloads
Working Paper: Model instability in predictive exchange rate regressions (2018) Downloads
Working Paper: Model instability in predictive exchange rate regressions (2018) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:ris:sbgwpe:2018_008

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