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Model instability in predictive exchange rate regressions

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  • Hauzenberger, Niko

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  • Huber, Florian

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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.

Suggested Citation

  • Hauzenberger, Niko & Huber, Florian, 2018. "Model instability in predictive exchange rate regressions," Department of Economics Working Paper Series 6770, WU Vienna University of Economics and Business.
  • Handle: RePEc:wiw:wus005:6770
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    More about this item

    Keywords

    Empirical exchange rate models; exchange rate fundamentals; Markov switching;

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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