Bootstrapped Durbin– Watson Test of Autocorrelation for Small Samples

Authors

  • Jesmin Akter ASA University Bangladesh

DOI:

https://doi.org/10.18034/abcjar.v3i2.39

Keywords:

Bootstrap, Durbin-Watson test, Autocorrelation, Recursive Bootstrap

Abstract

The Durbin-Watson (DW) test is the most widely used test for autocorrelation of a first order in regression analysis. The critical value of DW test depends on X matrix. As a result, the DW test statistic falls sometime in the inconclusive region. For large sample, the DW test can be used for normal distribution. In this paper, we proposed a bootstrap critical value for small sample and compared the power properties with other procedures. Monte-Carlo study shows that the bootstrapped DW test performs better than the usual DW test with the help of power.

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Author Biography

  • Jesmin Akter, ASA University Bangladesh

    Assistant Professor, Faculty of Business, ASA University Bangladesh, BANGLADESH

     

References

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Published

2014-12-31

How to Cite

Akter, J. . (2014). Bootstrapped Durbin– Watson Test of Autocorrelation for Small Samples. ABC Journal of Advanced Research, 3(2), 137-142. https://doi.org/10.18034/abcjar.v3i2.39

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