Model instability in predictive exchange rate regressions

Hauzenberger, Niko and Huber, Florian ORCID: (2020) Model instability in predictive exchange rate regressions. Journal of Forecasting, 39 (2). pp. 168-186. ISSN 02776693

Available under License Creative Commons: Attribution 4.0 International (CC BY 4.0).

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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 framework, our modeling approach assumes that different regimes are characterized by commonly used structural exchange rate models, with transitions across regimes 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 home and in the USA. 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 more accurate density forecasts for most currency pairs considered.

Item Type: Article
Additional Information: Oesterreichische Nationalbank, Grant/ Award Number: Jubilaeumsfond grant no. 17650; Austrian Science Fund (FWF); Austrian Academy of Sciences (ÖAW), Grant/Award Number: Zukunftskolleg ZK 35
Keywords: empirical exchange rate models, exchange rate fundamentals, Markov switching
Divisions: Departments > Volkswirtschaft > Makroökonomie
Version of the Document: Published
Depositing User: Gertraud Novotny
Date Deposited: 28 Aug 2020 14:03
Last Modified: 02 Sep 2020 15:07
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