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Alternative Estimators And Unit Root Tests For The Autoregressive Process

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  • Heon Jin Park
  • Wayne A. Fuller

Abstract

. We compare several estimators for the second‐order autoregressive process and compare the associated tests for a unit root. Monte Carlo results are reported for the ordinary least squares estimator, the simple symmetric least squares estimator and the weighted symmetric least squares estimator. The weighted symmetric least squares estimator of the autoregressive parameters generally has smaller mean square error than that of the ordinary least squares estimator, particularly when one root is close to one in absolute value. For the second‐order model with known zero intercept, the one‐sided ordinary least squares test for a unit root is more powerful than the symmetric tests. For the model with an estimated intercept, the one‐sided weighted symmetric least squares test is the most powerful test.

Suggested Citation

  • Heon Jin Park & Wayne A. Fuller, 1995. "Alternative Estimators And Unit Root Tests For The Autoregressive Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(4), pages 415-429, July.
    • Handle: RePEc:bla:jtsera:v:16:y:1995:i:4:p:415-429
    DOI: 10.1111/j.1467-9892.1995.tb00243.x
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    1. Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-174, January.
    2. Alok Bhargava, 1986. "On the Theory of Testing for Unit Roots in Observed Time Series," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(3), pages 369-384.
    3. Pantula, Sastry G & Gonzalez-Farias, Graciela & Fuller, Wayne A, 1994. "A Comparison of Unit-Root Test Criteria," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 449-459, October.
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