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Do Forecasters use Monetary Models? An Empirical Analysis of Exchange Rate Expectations

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  • Schröder, Michael
  • Dornau, Robert

Abstract

Do financial market analysts use structural economic models when forecasting exchange rates? This is the leading question analysed in this apper. In contrast to other studies we use expectations instead of realised data. Therefore we analyse the implicit structural models forecasters have in mind when forming their exchange rate expectations. Using expected short- and long-term interest rates and business expectations as explanatory variables we estimate latent structural models to explain expected exchange rates. A special hypothesis is whether exchange rate expectations are formed according to monetary models. The currencies included in the study are US dollar, British pound, Japanese yen, French franc and Italian lire, each defined against the German mark. A major finding of the analysis is that expected GDP is the most important variable (from the set of our variables) for the determination of exchange rate expectations. For the DM/US dollar expectations a Mundell-Fleming type model is compatible with the data. This means, that increasing interest rates will led to an appreciation of the corresponding currency. The opposite result have been found for French franc and Italian lire where high expected interest rates indicate a weak currency.

Suggested Citation

  • Schröder, Michael & Dornau, Robert, 2000. "Do Forecasters use Monetary Models? An Empirical Analysis of Exchange Rate Expectations," CoFE Discussion Papers 00/14, University of Konstanz, Center of Finance and Econometrics (CoFE).
  • Handle: RePEc:zbw:cofedp:0014
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    Cited by:

    1. Cuestas, Juan Carlos & Filipozzi, Fabio & Staehr, Karsten, 2015. "Do foreign exchange forecasters believe in Uncovered Interest Parity?," Economics Letters, Elsevier, vol. 133(C), pages 92-95.
    2. Brückbauer Frank & Schröder Michael, 2023. "The ZEW Financial Market Survey Panel," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 243(3-4), pages 451-469, June.
    3. Yu Hsing, 2006. "Analysis of Short-term Exchange Rate Movements in Korea: Application of an Extended Mundell-Fleming Model," Global Economic Review, Taylor & Francis Journals, vol. 35(2), pages 145-151.
    4. Hess, Dieter, 2001. "Surprises in U.S. macroeconomic releases: Determinants of their relative impact on T-Bond futures," CoFE Discussion Papers 01/01, University of Konstanz, Center of Finance and Econometrics (CoFE).
    5. Hess, Dieter E., 2003. "Determinants of the relative price impact of unanticipated information in US macroeconomic releases," Frankfurt School - Working Paper Series 46, Frankfurt School of Finance and Management.
    6. Brückbauer, Frank & Schröder, Michael, 2021. "Data resource profile: The ZEW FMS dataset," ZEW Discussion Papers 21-100, ZEW - Leibniz Centre for European Economic Research.
    7. Muhammad Arshad Khan & Saima Nawaz, 2018. "Does Pak-Rupee Exchange Rate Respond to Monetary Fundamentals? A Structural Analysis," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 57(2), pages 175-202.
    8. HSING, Yu, 2006. "Determinants Of Exchange Rate Fluctuations For Venezuela: Application Of An Extended Mundell-Fleming Model," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 6(1).

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