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A Gaussian Test for Cointegration

Author

Listed:
  • Gulasekaran Rajaguru

    (School of Business, Bond University, Australia)

  • Tilak Abeysinghe

    () (Department of Economics, National University of Singapore)

Abstract

We use a mixed-frequency regression technique to develop a test for cointegration under the null of stationarity of the deviations from a long-run relationship. What is noteworthy about this MA unit root test, based on a variance-difference, is that, instead of having to deal with non-standard distributions, it takes the testing back to the normal distribution and offers a way to increase power without having to increase the sample size substantially. Monte Carlo simulations show minimal size distortions even when the AR root is close to unity and that the test offers substantial gains in power against near-null alternatives in moderate size samples. An empirical exercise illustrates the relative usefulness of the test further.

Suggested Citation

  • Gulasekaran Rajaguru & Tilak Abeysinghe, 2009. "A Gaussian Test for Cointegration," SCAPE Policy Research Working Paper Series 0905, National University of Singapore, Department of Economics, SCAPE.
  • Handle: RePEc:sca:scaewp:0905
    as

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    File URL: http://www.fas.nus.edu.sg/ecs/pub/wp-scape/0905.pdf
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    References listed on IDEAS

    as
    1. Markku Lanne & Helmut Lutkepohl & Pentti Saikkonen, 2003. "Test Procedures for Unit Roots in Time Series with Level Shifts at Unknown Time," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(1), pages 91-115, February.
    2. Rajaguru GULASEKARAN & Tilak ABEYSINGHE, 2002. "The Distortionary Effects Of Temporal Aggregation On Granger Causality," Departmental Working Papers wp0204, National University of Singapore, Department of Economics.
    3. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots," NBER Chapters,in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220 National Bureau of Economic Research, Inc.
    4. Lo, Andrew W. & MacKinlay, A. Craig, 1989. "The size and power of the variance ratio test in finite samples : A Monte Carlo investigation," Journal of Econometrics, Elsevier, vol. 40(2), pages 203-238, February.
    5. 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.
    6. Lanne, Markku & Lutkepohl, Helmut, 2002. "Unit root tests for time series with level shifts: a comparison of different proposals," Economics Letters, Elsevier, vol. 75(1), pages 109-114, March.
    7. Phillips, Peter C. B., 2002. "New unit root asymptotics in the presence of deterministic trends," Journal of Econometrics, Elsevier, vol. 111(2), pages 323-353, December.
    8. Perron, Pierre & Rodriguez, Gabriel, 2003. "GLS detrending, efficient unit root tests and structural change," Journal of Econometrics, Elsevier, vol. 115(1), pages 1-27, July.
    9. Abeysinghe, Tilak, 2000. "Modeling variables of different frequencies," International Journal of Forecasting, Elsevier, vol. 16(1), pages 117-119.
    10. Choi, In, 1994. "Residual-Based Tests for the Null of Stationarity with Applications to U.S. Macroeconomic Time Series," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 720-746, August.
    11. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-144, January.
    12. Hwang, Jaeyoun & Schmidt, Peter, 1996. "Alternative methods of detrending and the power of unit root tests," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 227-248.
    13. Pantula, Sastry G. & Hall, Alastair, 1991. "Testing for unit roots in autoregressive moving average models : An instrumental variable approach," Journal of Econometrics, Elsevier, vol. 48(3), pages 325-353, June.
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    More about this item

    Keywords

    Null of stationarity; MA unit root; mixed-frequency regression; variance difference; normal distribution; power.;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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