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From |
Christopher F Baum <baum@bc.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Re: Goldfeld-Quandt vs hettest |

Date |
Thu, 5 Feb 2004 07:38:55 -0500 |

On Feb 5, 2004, at 2:33 AM, Stas wrote:

So if heteroskedasticity is related to groups of observations, GQ test isBut the GQ test does not involve defining groups of obs: it merely sorts the data on the basis of a SINGLE variable (which may or may not be in the model) and then compares the residual variances for large values and small values of that variable (usually leaving out middle-sized values). When teaching this subject, I argue that the GQ test is dominated by the Breusch--Pagan test (findit bpagan), which allows you to specify a SET of variables that you might expect to have some relation to the error variances across observations. In other words, you don't have to "get the groups right"; maybe it's not net sales, it's total assets, but if you put both in the B-P test, it will pick up the relationship if it exists.

likely to be the most powerful once you guessed the groups correctly. If

it is related to a certain variable, then approaches like Cook-Weisberg

(Stata's -hettest-) would be likely to be the most powerful.

Also note that the common "White's general test" is a special case of B-P. It has its own strengths and weaknesses, but I would think that the two of them would clearly dominate the GQ test for any diagnosis of H.

Kit

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