Mei-Yu LEE

The Effect of Nonzero Autocorrelation Coefficients on the Distributions of Durbin-Watson Test Estimator: Three Autoregressive Models

This paper investigates the effect of the nonzero autocorrelation coefficients on the sampling distributions of the Durbin-Watson test estimator in three time-series models that have different variance-covariance matrix assumption, separately. We show that the expected values and variances of the Durbin-Watson test estimator are slightly different, but the skewed and kurtosis coefficients are considerably different among three models. The shapes of four coefficients are similar between the Durbin-Watson model and our benchmark model, but are not the same with the autoregressive model cut by one-lagged period. Second, the large sample case shows that the three models have the same expected values, however, the autoregressive model cut by one-lagged period explores different shapes of variance, skewed and kurtosis coefficients from the other two models. This implies that the large samples lead to the same expected values, 2(1 – ρ0), whatever the variance-covariance matrix of the errors is assumed. Finally, comparing with the two sample cases, the shape of each coefficient is almost the same, moreover, the autocorrelation coefficients are negatively related with expected values, are inverted-U related with variances, are cubic related with skewed coefficients, and are U related with kurtosis coefficients.
JEL ClassificationC32, C15, C52

References

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Author(s)

Mei-Yu LEE
Yuanpei University, Taiwan

Correspondence

Mei-Yu Lee, Yuanpei University, Department of Applied Finance, Taiwan

Article History

Received: October 19, 2014
Accepted: November 5, 2014
Available Online: November 24, 2014

Cite Reference

Lee, M-Y., 2014. The Effect of Nonzero Autocorrelation Coefficients on the Distributions of Durbin-Watson Test Estimator: Three Autoregressive Models. Expert Journal of Economics, 2(3), pp.85-99

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© 2014 The Author. Published by Sprint Investify. ISSN 2359-7704

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