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The power of the KPSS-test for cointegration when residuals are fractionally integrated

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  • Sibbertsen, Philipp
  • Kramer, Walter

Abstract

We show that the power of the KPSS-test against integration, as measured by divergence rates of the test statistic under the alternative, remains the same when residuals from an OLS-regression rather than true observations are used. The divergence rate is independent of the order of integration of the cointegrating regressors which are allowed to be I(1 + dX) in our set up.
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Suggested Citation

  • Sibbertsen, Philipp & Kramer, Walter, 2006. "The power of the KPSS-test for cointegration when residuals are fractionally integrated," Economics Letters, Elsevier, vol. 91(3), pages 321-324, June.
  • Handle: RePEc:eee:ecolet:v:91:y:2006:i:3:p:321-324
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    1. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
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    3. Kramer, Walter & Marmol, Francesc, 2004. "The power of residual-based tests for cointegration when residuals are fractionally integrated," Economics Letters, Elsevier, vol. 82(1), pages 63-69, January.
    4. Lee, Dongin & Schmidt, Peter, 1996. "On the power of the KPSS test of stationarity against fractionally-integrated alternatives," Journal of Econometrics, Elsevier, vol. 73(1), pages 285-302, July.
    5. Marmol, Francesc, 1998. "Searching for fractional evidence using combined unit root tests," DES - Working Papers. Statistics and Econometrics. WS 10613, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    7. Marinucci, D. & Robinson, P. M., 2000. "Weak convergence of multivariate fractional processes," Stochastic Processes and their Applications, Elsevier, vol. 86(1), pages 103-120, March.
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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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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