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Equilibrium real exchange rate estimates across time and space

Author

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  • Christoph Fischer

    (Deutsche Bundesbank)

Abstract

Equilibrium real exchange rate and corresponding misalignment estimates differ tremendously depending on the panel estimation method used to derive them. Essentially, these methods differ in their treatment of the time-series (time) and the cross-section (space) variation in the panel. The study shows that conventional panel estimation methods (pooled OLS, fixed, random, and between effects) can be interpreted as restricted versions of a correlated random effects (CRE) model. It formally derives the distortion that arises if these restrictions are violated and uses two empirical applications from the literature to show that the distortion is generally very large. This suggests the use of the CRE model for the panel estimation of equilibrium real exchange rates and misalignments.

Suggested Citation

  • Christoph Fischer, 2019. "Equilibrium real exchange rate estimates across time and space," GRU Working Paper Series GRU_2019_008, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    • Handle: RePEc:cth:wpaper:gru_2019_008
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    File URL: https://www.cb.cityu.edu.hk/ef/doc/GRU/WPS/GRU%232019-008%20Fischer.pdf
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    Cited by:

    1. is not listed on IDEAS
    2. Claire Giordano, 2021. "How frequent a BEER? Assessing the impact of data frequency on real exchange rate misalignment estimation," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 365-404, July.
    3. Rui Mano & Ms. Carolina Osorio-Buitron & Mr. Luca A Ricci & Mr. Mauricio Vargas, 2019. "The Level REER model in the External Balance Assessment (EBA) Methodology," IMF Working Papers 2019/192, International Monetary Fund.

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    Keywords

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    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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