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Durbin–Watson Test

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The Concise Encyclopedia of Statistics
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The Durbin–Watson test introduces a statistic d that is used to test the autocorrelation of the residuals obtained from a linear regression model. This is a problem that often appears during the application of a linear model to a time series, when we want to test the independence of the residuals obtained in this way.

HISTORY

Durbin, J. and Watson, G.S. invented this test in 1950.

MATHEMATICAL ASPECTS

Consider the case of a multiple linear regression model containing \( { p-1 } \) independent variables. The model is written:

$$ Y_t = \beta_0 + \sum_{j=1}^{p-1} \beta_j X_{jt} + \varepsilon_t\:,\quad t = 1,\ldots, T\:, $$

where

Y t :

is the dependent variable,

X jt ,:

with \( { j=1, \ldots, p-1 } \) are the independent variables

β j ,:

with \( { j=1, \ldots, p-1 } \) are the parameters to be estimated,

ε t :

with \( { t=1, \ldots, T } \) is an unobservable random error term.

In the matrix form, the model is written as:

$$...

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REFERENCES

  1. Bourbonnais, R.: Econométrie, manuel et exercices corrigés, 2nd edn. Dunod, Paris (1998)

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  2. Durbin, J.: Alternative method to d-test. Biometrika 56, 1–15 (1969)

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  3. Durbin, J., Watson, G.S.: Testing for serial correlation in least squares regression, I. Biometrika 37, 409–428 (1950)

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  4. Durbin, J., Watson, G.S.: Testing for serial correlation in least squares regression, II. Biometrika 38, 159–177 (1951)

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  5. Harvey, A.C.: The Econometric Analysis of Time Series. Philip Allan, Oxford (Wiley, New York) (1981)

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© 2008 Springer-Verlag

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(2008). Durbin–Watson Test. In: The Concise Encyclopedia of Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-32833-1_122

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