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Tests for the order of integration against higher order integration

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Abstract

Locally best invariant tests for the null hypothesis of I(p) against the alternative hypothesis of I(q), < q, are developed for models with independent normal errors. The tests are semiparametrically extended for models with autocorrelated errors. The method is illustrated by two real data sets in terms of double unit roots. The proposed tests can be used for determining integration orders of nonstationary time series.

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References

  1. Andrews, D. W. K. (1991) Heteroskedasricity and autocorrelation consistent covariance matrix estimation, Econometrica, 59, 817–858.

    Article  MATH  MathSciNet  Google Scholar 

  2. Billingsley, P. (1968). Convergence of Probability Measures. John Wiley, New York.

    MATH  Google Scholar 

  3. Chang, Y. and Phillips, P.C.B. (1995). Time series regression with mixtures of integrated processes, Econometric Theory, 11, 1033–1094.

    Article  MathSciNet  Google Scholar 

  4. Dickey, D. A. and Pantula, S. G. (1987). Determining the order of differencing in autoregressive processes, J. Bus. Econ. Statist., 5, 455–461.

    Article  Google Scholar 

  5. Durlauf, S. N. and Phillips, P. C. B. (1988). Trends versus random walks in time series analysis, Econometrica, 56, 1333–54.

    Article  MATH  MathSciNet  Google Scholar 

  6. Ferguson, T. S. (1967). Mathmatical Statistics: A Decision Theoretic Approach. Academic, New York.

    Google Scholar 

  7. Haldrup, N. (1994a). Semiparametric tests for double unit roots, J. Bus. Econ. Statist., 12, 109–122.

    Article  MathSciNet  Google Scholar 

  8. — (1994b). The asymptotics of single-equation cointegration regressions with I(1) and I(2) variables, J. Econometrics, 63, 153–181.

    Article  MATH  MathSciNet  Google Scholar 

  9. Hasza, D. P. and Fuller, W. A.(1979). Estimation for autoregressive processes with unit roots, Annal, Statist., 7, 1106–1120.

    Article  MATH  MathSciNet  Google Scholar 

  10. Imhof, J. P. (1961). Computing the distribution of quadratic forms in normal variables, Biometrika, 48, 419–426.

    MATH  MathSciNet  Google Scholar 

  11. IMSL (1989). User’s manual. IMSL, Houston, Texas.

    Google Scholar 

  12. Johansen, S. (1995). A Statistical analysis of cointegration for I(2) variables, Econometric Theory, 11, 25–59.

    Article  MathSciNet  Google Scholar 

  13. Herrndorf, N. (1984). A functional central limit theorem for weakly dependent sequence of random variables, Ann. Probab., 12, 141–53.

    Article  MATH  MathSciNet  Google Scholar 

  14. King, M. L. (1980). Robust tests for spherical symmetry and their application to least squares regression, Ann. Statist, 8, 1265–1271.

    Article  MATH  MathSciNet  Google Scholar 

  15. King, R. G., Plosser, C. I., Stock, J. H., and Watson, M. W. (1991). Stochastic trends and economic fluctuations, Amer. Econ.c Rev., 81, 819–840.

    Google Scholar 

  16. Kitamura, Y. (1995). Estimation of cointegrated systems with I(2) processes. Econometric Theory, 11, 1–24.

    Article  MathSciNet  Google Scholar 

  17. Kwiatkowski, D., Phillips, P. C. B., Schmidt, P. and Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. J. Econometrics, 54, 159–178.

    Article  MATH  Google Scholar 

  18. LaMotte, L. Y. and McWhorterm A. Jr. (1978). An exact test for the presence of random walk coefficients in a linear regression model, J. Amer. Statist. Assoc., 73, 816–820.

    Article  MATH  Google Scholar 

  19. Nabeya, S. and Tanaka, K. (1988). Asymptotic theory of a test for the constancy of regression coefficients against the random walk alternative, Ann. Statist. 16, 218–235.

    Article  MATH  MathSciNet  Google Scholar 

  20. Nelson, C. R. and Plosser, C. I. (1982). Trends versus random walks in macroeconomic time series: Some evidence and implications, J. Monetary Econ., 10, 139–162.

    Article  Google Scholar 

  21. Nyblom, J. and Makelainen (1983). Comparisons of tests of the presence of random walk coefficients in a simple linear model, J. Amer. Statist. Assoc., 78, 856–864.

    Article  MATH  MathSciNet  Google Scholar 

  22. Phillips, P. C. B. (1987). Time series regression with a unit root. Econometrica, 55, 277–301.

    Article  MATH  MathSciNet  Google Scholar 

  23. Phillips, P. C. B. (1991). Spectral regression for cointegrated time series in W. Barnett, ed. Parametric and semiparametric methods in economics and statistics, Cambridge University press, Cambridge.

    Google Scholar 

  24. Phillips, P. C. B. and Solo, V. (1992), Asymptotics for linear processes, Ann. Statist., 20, 971–1001.

    Article  MATH  MathSciNet  Google Scholar 

  25. Saikkonen, P. and Luukkonen, R. (1993). Testing for a moving average unit root in autoregressive integrated moving average models, J. Amer. Statist. Assoc., 88, 596–601.

    Article  MATH  MathSciNet  Google Scholar 

  26. Schwert, G. W. (1989). Tests for unit roots: A Monte Carlo investigation, J. Bus. Econ. Statist., 7, 147–159.

    Article  Google Scholar 

  27. Sen, D. L. and Dickey, D. A. (1987). Symmetric test for second differencing in univariate time series, J. Bus. Econ. Statist., 5, 463–473.

    Article  Google Scholar 

  28. Shin, D. W. and Kim, H. J. (1999). Semiparametric tests for double unit roots based on symmetric estimators, J. Bus. Econ. Statist, 17, 67–73.

    Article  MathSciNet  Google Scholar 

  29. Tanaka, K. (1983). Non-normality of the Lagrangian multiplier statistic for testing the constancy of regression coefficients, Econometrica, 51, 1577–1582.

    Article  MATH  MathSciNet  Google Scholar 

  30. Tanaka, K. (1990). Testing for a moving average unit root, Econmetric Theory, 6, 433–444.

    Article  Google Scholar 

  31. Tanaka, K. (1996). Time Series Analysis: Nonstationary and Noninvertible Distribution Theory. J. Wiley: New York.

    Google Scholar 

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Shin, D.W., Oh, MS. Tests for the order of integration against higher order integration. Statistical Papers 44, 383–396 (2003). https://doi.org/10.1007/s00362-003-0162-y

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  • DOI: https://doi.org/10.1007/s00362-003-0162-y

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