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From |
"Verkuilen, Jay" <JVerkuilen@gc.cuny.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: RE : Heteroskedasticity and fixed effects (was: st: RE: Re: Weak instruments) |

Date |
Thu, 17 Jul 2008 16:21:34 -0400 |

Richard Williams wrote: >>I might have a slightly different take: If a test for hetero comes up positive, don't just assume that means that you should use wls or robust standard errors or whatever. [snip]<< I agree. Heteroscedasticity can be a sign of a lot of things. This is why I recall a nice warning about on "White-washing" your VCE mentioned in Peter Kennedy's excellent A Guide to Econometrics. I recall a case in some multinomial discrete choice data from a linguistics experiment I analyzed where there was clear heteroscedasticity. It turned out that it went away once a very large outlier was removed from the dataset. When we checked, the outlier was explainable in terms of the stimulus in that cell of the experiment. The stimulus word was "thanks", which is ambiguous about whether it's singular or plural due to the -s ending. Finding outliers in complex models can be very tricky. Of course, heteroscedastiticy also often arises due to a misspecification of the error term. For instance, if you use OLS in the presence of a ceiling or floor effect, you often "need" either an interaction term or suffer from heteroscedasticity or both. In fact, you simply have the wrong model and need to get one that can accommodate the ceiling or floor effect, of which there are several. Nonetheless, robust standard errors and related methods such as bootstrapping and jackknifing can be quite useful. A lot of times there's just some "crud" in your data for which you won't ever find a model. The variables you would need to measure are unavailable, either because nobody gathered them or because they simply can't be gathered. A model-based solution such as random effects isn't going to work---maybe you simply don't have the information on the clustering. It would be a shame for analysis to stop because someone decides to go unreasonably purist. (I'm invoking the spirit of Tukey here.) Robust VCE and the like can let you get more reasonable standard errors in the presence of crud. But you should be honest about what you did, most importantly with yourself. JV * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**RE : Heteroskedasticity and fixed effects (was: st: RE: Re: Weakinstruments)***From:*Gaulé Patrick <patrick.gaule@epfl.ch>

**Re: RE : Heteroskedasticity and fixed effects (was: st: RE: Re: Weak instruments)***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: RE : Heteroskedasticity and fixed effects (was: st: RE: Re: Weak instruments)***From:*Richard Williams <Richard.A.Williams.5@ND.edu>

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