Model instability in predictive exchange rate regressions

Niko Hauzenberger, Florian Huber

Publication: Working/Discussion PaperWU Working Paper

40 Downloads (Pure)

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.
Original languageEnglish
Place of PublicationVienna
PublisherWU Vienna University of Economics and Business
DOIs
Publication statusPublished - 1 Dec 2018

Publication series

SeriesDepartment of Economics Working Paper Series
Number276

WU Working Paper Series

  • Department of Economics Working Paper Series

Cite this