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Distilling co-movements from persistent macro and financial series

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  • Abadir, Karim
  • Talmain, Gabriel

Abstract

We provide a methodology to disentangle the long-run relation between variables from their own dynamics. Macroeconomic and aggregate financial series have a high degree of inertia. If this persistence is not properly accounted for, spurious correlations will give rise to paradoxes. Our procedure shows that the Uncovered Interest Parity (UIP) puzzle evaporates when the dynamics are properly modelled: the forward premium loses all the predictive power that it seemed to have. We also show how the stock market grows in long cycles around a trend given by GDP, in a stable relation that does not break. JEL Classification: E37

Suggested Citation

  • Abadir, Karim & Talmain, Gabriel, 2005. "Distilling co-movements from persistent macro and financial series," Working Paper Series 525, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:2005525
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    References listed on IDEAS

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    Cited by:

    1. Gianluca, MORETTI & Giulio, NICOLETTI, 2008. "Estimating DGSE models with long memory dynamics," Discussion Papers (ECON - Département des Sciences Economiques) 2008037, Université catholique de Louvain, Département des Sciences Economiques.

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    More about this item

    Keywords

    ACF-based GLS procedure; Autocorrelation Function; long memory; Nonlinearities; Uncovered Interest Parity anomaly;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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