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Simulating small-sample properties of the maximum likelihood cointegration method : estimation and testing

  • Tor Jacobson

    (Department of Statistics, Uppsala University, Sweden)

This paper analyzes - using Monte Carlo simulation - small-sample properties of the maximum likelihood cointegration method for estimation and inference in cointegrated systems. The simulations of a bivariate system concentrate on the following; the estimator of the cointegrating vector; the trace test for determining cointegrating rank, and the likelihood ratio and Wald tests for linear restrictions on the cointegrating vector: Furthermore, we introduce autoregressive conditional heteroscedasticity, as well as multivariate non-normality in the form of excess skewness and kurtosis, in the error process. All in all, the results suggest that the maximum likelihood method displays desirable features as long as the samples are of reasonable sizes.

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Article provided by Finnish Economic Association in its journal Finnish Economic Papers.

Volume (Year): 8 (1995)
Issue (Month): 2 (Autumn)
Pages: 96-107

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Handle: RePEc:fep:journl:v:8:y:1995:i:2:p:96-107
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  1. Campbell, John & Perron, Pierre, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," Scholarly Articles 3374863, Harvard University Department of Economics.
  2. Allen Fleishman, 1978. "A method for simulating non-normal distributions," Psychometrika, Springer, vol. 43(4), pages 521-532, December.
  3. Johansen, Soren, 1992. "Cointegration in partial systems and the efficiency of single-equation analysis," Journal of Econometrics, Elsevier, vol. 52(3), pages 389-402, June.
  4. Cheung, Yin-Wong & Lai, Kon S, 1993. "Finite-Sample Sizes of Johansen's Likelihood Ration Tests for Conintegration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 55(3), pages 313-28, August.
  5. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
  6. Banerjee, Anindya, et al, 1986. "Exploring Equilibrium Relationships in Econometrics through Static Models: Some Monte Carlo Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 253-77, August.
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