@techreport{a5211b15b18b40568580f22ebe3d1685,
title = "Model instability in predictive exchange rate regressions",
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.",
author = "Niko Hauzenberger and Florian Huber",
year = "2018",
month = dec,
day = "1",
doi = "10.57938/a5211b15-b18b-4056-8580-f22ebe3d1685",
language = "English",
series = "Department of Economics Working Paper Series",
number = "276",
publisher = "WU Vienna University of Economics and Business",
address = "Austria",
type = "WorkingPaper",
institution = "WU Vienna University of Economics and Business",
}