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Regime Sensitive Cointegration with an Application to Interest rate Parity

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  • Siklos, P.L.
  • Granger, C.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 economic theory grounds. Among these are the testing procedure (e.g., Engle and Granger (1987) or Johansen (1991), the span of the data set (Hendry (1995), Perron (1989)), the choice of the lag length in generating the test statistic (Banerjee et al. (1993)), the presence of structural breaks (Gregory and Hansen (1996)), and the presence of cointegration only beyond some threshold (Balke and Fomby (1996)). In this paper 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 US and Canada.

Suggested Citation

  • Siklos, P.L. & Granger, C.W.J., 1997. "Regime Sensitive Cointegration with an Application to Interest rate Parity," Working Papers 97-5, Wilfrid Laurier University, Department of Economics.
    • Handle: RePEc:wlu:wpaper:97-5
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    References listed on IDEAS

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    More about this item

    Keywords

    COINTEGRATION ; INTEREST RATE;

    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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