Quotation Hauzenberger, Niko, Huber, Florian. 2018. Model instability in predictive exchange rate regressions.


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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.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Working/discussion paper, preprint
Language English
Title Model instability in predictive exchange rate regressions
Year 2018
URL https://arxiv.org/abs/1811.08818
JEL C30, E32, E52, F31

Associations

Projects
Modeling and forecasting exchange rates in an unified econometric framework
People
Hauzenberger, Niko (Details)
Huber, Florian (Details)
Organization
Institute for Macroeconomics IN (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
5323 Econometrics (Details)
5371 Macroeconomics (Details)
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