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Regime-Sensitive Cointegration With An Application To Interest-Rate Parity

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  • SIKLOS, PIERRE L.
  • GRANGER, CLIVE W.J.

Abstract

There exist a variety of reasons for the failure to find a unique cointegrating relationship between economic time series where one would normally be expected on the basis of economic theory. Among these are the testing procedure, the span of the data set, the choice of lag length in generating the test statistic, the presence of structural breaks, and the presence of cointegration only beyond some threshold. We propose the concept of regime-sensitive cointegration whereby the underlying series need not be cointegrated at all times. We show that cointegration can be switched off when a common stochastic trend is added. Alternatively, cointegration can be switched on or off because series normally believed to contain a unit actually do not. This implies that a linear combination of such variables need not be cointegrated. To illustrate the concept empirically, we test the hypothesis of interest-rate parity, and related hypotheses, using daily Eurorates for the United States and Canada.

Suggested Citation

  • Siklos, Pierre L. & Granger, Clive W.J., 1997. "Regime-Sensitive Cointegration With An Application To Interest-Rate Parity," Macroeconomic Dynamics, Cambridge University Press, vol. 1(3), pages 640-657, September.
    • Handle: RePEc:cup:macdyn:v:1:y:1997:i:03:p:640-657_00
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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