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An Approximation to the Null Distribution of the Durbin-Watson Statistic in Models Containing Lagged Dependent Variables

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  • Inder, Brett

Abstract

We consider testing for autoregressive disturbances in the linear regression model with a lagged dependent variable. An approximation to the null distribution of the Durbin—Watson statistic is developed using small-disturbance asymptotics, and is used to obtain test critical values. We also obtain nonsimilar critical values for the Durbin—Watson and Durbin's h and t tests. Monte Carlo results are reported comparing the performances of the tests under the null and alternative hypotheses. The Durbin–Watson test is found to be more powerful and to perform more consistently than either of Durbin's tests under H o .

Suggested Citation

  • Inder, Brett, 1986. "An Approximation to the Null Distribution of the Durbin-Watson Statistic in Models Containing Lagged Dependent Variables," Econometric Theory, Cambridge University Press, vol. 2(03), pages 413-428, December.
  • Handle: RePEc:cup:etheor:v:2:y:1986:i:03:p:413-428_01
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    1. Atukorala, Ranjani & Sriananthakumar, Sivagowry, 2015. "A comparison of the accuracy of asymptotic approximations in the dynamic regression model using Kullback-Leibler information," Economic Modelling, Elsevier, vol. 45(C), pages 169-174.
    2. Mohamed Nagy Eltony, 2012. "On Fuel Subsidies for Transportation Sector in Kuwait," Working Papers 687, Economic Research Forum, revised 2012.
    3. Robert Brooks & Edwyna Harris, 2005. "An Analysis of Watermove Water Markets," Monash Econometrics and Business Statistics Working Papers 10/05, Monash University, Department of Econometrics and Business Statistics.
    4. Sriananthakumar, Sivagowry, 2013. "Testing linear regression model with AR(1) errors against a first-order dynamic linear regression model with white noise errors: A point optimal testing approach," Economic Modelling, Elsevier, vol. 33(C), pages 126-136.
    5. Sriananthakumar, Sivagowry, 2015. "Approximate Non-Similar critical values based tests vs Maximized Monte Carlo tests," Economic Modelling, Elsevier, vol. 49(C), pages 387-394.
    6. Proïa, Frédéric, 2013. "Further results on the h-test of Durbin for stable autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 118(C), pages 77-101.
    7. Munir Mahmood & Maxwell L. King, 2016. "On solving bias-corrected non-linear estimation equations with an application to the dynamic linear model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 332-355, November.

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