On Mon, 2015-05-04 at 18:34 +0300, Alecos Papadopoulos wrote:
> Graham,
> I verified using your data set that Gretl calculates correctly the
> Breusch-Pagan LM test for heteroskedasticity, as described in the
> original paper,
>
>
> A Simple Test for Heteroscedasticity and Random Coefficient Variation
> Author(s): T. S. Breusch and A. R. Pagan
> Source: Econometrica, Vol. 47, No. 5 (Sep., 1979), pp. 1287-1294
> Published by: The Econometric Society
> Stable URL:
http://www.jstor.org/stable/1911963
>
> The auxiliary regression is performed using the scaled squared
> residuals as Dependent variable (as indicated in the Gretl's output),
> and the statistic is 0.5*R^2*(Total Sum of Squares of the Dependent
> Variable), the R^2 from this auxiliary regression, where I used the
> exact same regression matrix of the main regression (constant + the
> three regressors)
>
> The scaling of the squared residual series is by the maximum
> likelihood estimator for the variance from the original model, ie. sum
> of squared residuals divided by nobs (not nobs-1).
>
> Maddala's Econometrics textbook (2001, 3d ed. pp 205-207) explains
> the relation of the above statistic with the approach you implemented
> (correctly) by hand, which is the "usual" way to obtain an LM
> statistic.
> But these are only asymptotically equivalent, and in practice the
> estimated sigma^4 is involved, whose estimation is seriously biased in
> any case for samples much larger than yours.
>
> So I do not think there is any bug or computational mistake involved,
> just an (educative) case of asymptotic equivalence not materializing
> at finite-sample level.
> Personally I would go with the original Breusch-Pagan test statistic.
OK, thanks everybody. I think I get it, and sorry for not going back to
the source.
What brought this up was a student using both the White and
Breusch-Pagan tests and seeing (as you do) completely different P-
values for each (0.485 vs 0.000360) So, how can I explain that to him? I
initially thought there had to be a mistake since in my mind the
Breusch-Pagan test was just the White test with some interaction terms
taken out, but I see now that's not the case.
The original B-P test assumes the error is normal, albeit possibly
heteroskedastic. You get much less of a divergence of results between
White and B-P if you use the robust variant of BP. This actually
reflects the fact that you have some substantial outliers.
Allin Cottrell