Modeling and forecasting exchange rates in an unified econometric framework


Type Research Project

Funding Bodies
  • Oesterreichische Nationalbank (Jubiläumsfonds)

Duration Jan. 1, 2018 - Dec. 31, 2020

  • Institute for Macroeconomics IN (Details)

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Abstract (German)

Dieses Projekt beschäftigt sich mit der Verbesserung empirischer Wechselkursmodelle unter Berücksichtigung von Modellunsicherheit innerhalb eines flexiblen nicht-linearen Bayesianischen Rahmens der Zeitreihenökonometrie.
Dies ermöglicht uns eine gemeinsame Darstellung von Wechselkursen und anderen latenten Komponenten, wie beispielsweise des Output Gaps oder der Trendinflation. Diese Größen werden üblicherweise durch andere beobachtbare Größen, wie zum Beispiel der Arbeitslosenrate, approximiert.
Anschließend werden wir diverse Prognosestrategien erarbeiten und untersuchen, inwiefern eine Berücksichtigung der Bewegungen von Fundamentaldaten die Prognosegüte positiv gegenüber konventionellen Modellen, wie u.a. dem Random Walk, zu bewerten ist.
Des Weiteren analysieren wir, inwiefern aktuelle Entwicklungen von dynamischen Prognosepools in der Bayesianischen Ökonometrie helfen können, robustere Vorhersagen im Vergleich zu Einzelmodellen zu erhalten.


Abstract (English)

In this project 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. This model approach provides a joint representation of the exchange rate as well as other latent components like the output gap or trend inflation, quantities that are typically approximated through different observed
measures like the unemployment rate. In a series of well designed forecasting exercises
we investigate whether allowing for movements in the underlying set of exchange rate
fundamentals significantly improves upon predictions stemming from traditionally used
models and the random walk benchmark. Moreover, we apply and assess whether recent
Bayesian techniques based on dynamic prediction pools help to obtain more robust
predictions relative to the forecast densities obtained from the best performing single
model.

Publications

Journal article

2019 Zörner, Thomas, Huber, Florian. 2019. Threshold cointegration in international exchange rates: A Bayesian approach. International Journal of Forecasting. 35 (2), 458-473. (Details)

Paper presented at an academic conference or symposium

2019 Zörner, Thomas. 2019. Stochastic model specification in Markov switching vector error correction models. 24th Spring Meeting of Young Economists (SMYE), Brüssel, Belgien, 11.04.-13.04. (Details)
  Zörner, Thomas. 2019. Stochastic model specification in Markov switching vector error correction models. Annual Meeting of the Austrian Economic Association (NOeG), Graz, Österreich, 25.04.-26.04. (Details)

Working/discussion paper, preprint

2018 Hauzenberger, Niko, Böck, Maximilian, Pfarrhofer, Michael, Stelzer, Anna, Zens, Gregor. 2018. Implications of macroeconomic volatility in the Euro area. (Details)
  Hauzenberger, Niko, Huber, Florian. 2018. Model instability in predictive exchange rate regressions. (Details)
  Huber, Florian, Pfarrhofer, Michael, Zörner, Thomas. 2018. Stochastic model specification in Markov switching vector error correction models. (Details)
  Fischer, Manfred M., Huber, Florian, Pfarrhofer, Michael, Staufer-Steinnocher, Petra. 2018. The dynamic impact of monetary policy on regional housing prices in the United States. open access (Details)
  Fischer, Manfred M., Huber, Florian, Pfarrhofer, Michael, Staufer-Steinnocher, Petra. 2018. The dynamic impact of monetary policy on regional housing prices in the US: Evidence based on factor-augmented vector autoregressions. open access (Details)
  Fischer, Manfred M., Huber, Florian, Pfarrhofer, Michael. 2018. The transmission of uncertainty shocks on income inequality: State-level evidence from the United States. open access (Details)

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