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Asymptotic Properties of the Estimator of the Long-run Coefficient in a Dynamic Model with Integrated Regressors and Serially Correlated Errors

Author

Listed:
  • Koichi Maekawa
  • Michael McAleer
  • Zonglu He

Abstract

In this paper we examine the asymptotic properties of the estimator of the long-run coefficient (LRC) in a dynamic regression model with integrated regressors and serially correlated errors. We show that the OLS estimators of the regression coefficients are inconsistent but the OLS-based estimator of the LRC is superconsistent. Furthermore, we propose an alternative consistent estimator of the LRC, compare the two estimators through a Monte Carlo experiment, and find that the proposed estimator is MSE-superior to the OLS-based estimator.

Suggested Citation

  • Koichi Maekawa & Michael McAleer & Zonglu He, 2001. "Asymptotic Properties of the Estimator of the Long-run Coefficient in a Dynamic Model with Integrated Regressors and Serially Correlated Errors," ISER Discussion Paper 0538, Institute of Social and Economic Research, The University of Osaka.
    • Handle: RePEc:dpr:wpaper:0538
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    References listed on IDEAS

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    1. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
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