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Critical values for the Durbin-Watson test in large samples

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  • Paul Turner

Abstract

This paper estimates functional relationships between the Durbin-Watson critical bounds and the sample size. The functions estimated provide a quick and easy way to calculate critical values for sample sizes not reported as standard in books of statistical tables. They also allow estimation of the sample sizes necessary for the convergence of the Durbin-Watson lower and upper bounds to those derived from the normal distribution and each other. Our results indicate that what constitutes a ‘large’ sample is highly sensitive to the number of independent variables in the regression equation.

Suggested Citation

  • Paul Turner, 2020. "Critical values for the Durbin-Watson test in large samples," Applied Economics Letters, Taylor & Francis Journals, vol. 27(18), pages 1495-1499, October.
    • Handle: RePEc:taf:apeclt:v:27:y:2020:i:18:p:1495-1499
    DOI: 10.1080/13504851.2019.1691711
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    Cited by:

    1. Sergio Luis Náñez Alonso & Javier Jorge-Vázquez & Miguel Ángel Echarte Fernández & Ricardo Francisco Reier Forradellas, 2021. "Cryptocurrency Mining from an Economic and Environmental Perspective. Analysis of the Most and Least Sustainable Countries," Energies, MDPI, vol. 14(14), pages 1-22, July.
    2. Haq, Mahin & Moazzam, Muhammad & Khan, Abdul Salam & Ahmed, Waqas, 2023. "The impact of reverse logistics process coordination on third party relationship quality: A moderated mediation model for multichannel retailers in the fashion industry," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).

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