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From |
Ernest Berkhout <ernestb@seo.fee.uva.nl> |

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

Subject |
Re: st: RE: Goldfeldt-Quant versus -hettest- |

Date |
Wed, 04 Feb 2004 12:09:23 +0100 |

At 04:54 04/02/2004, Richard Williams wrote:

Also, some of the examples did show how to use Stata to do the calculations for you, but I think this is one of those cases where it may be easier just to do it on a calculator.Effectively, I find it not so difficult to let Stata do the calculations. Advantage is that it does it for several groups and several variables within a foreach-loop. The trick is to refer directly to the scalars e(rss) and e(df_r). A possible setup to perform the GQ-test for a variable named "ophoogf2" would be:

*************************************************************************

egen group = cut(ophoogf2), group(3)

tabstat ophoogf2 , s(mean min max) by(group)

foreach group of num 0 2 {

quiet xi: reg lnloon $rhsvars_xi if group==`group'

scalar ee_oph_`group' = e(rss)

scalar df_oph_`group' = e(df_r)

}

scalar GQ_oph = max(ee_oph_0,ee_oph_2)/min(ee_oph_0,ee_oph_2)

scalar dir GQ*

*************************************************************************

But then, I still have to agree with Nick Cox' earlier argument that only looking at the p-value is not enough, one might first take a look at residuals & outliers.

Ernest Berkhout

SEO Amsterdam Economics

University of Amsterdam

Room 3.08

Roetersstraat 29

1018 WB Amsterdam

The Netherlands

tel.:+ 31 20 525 1657

fax:+ 31 20 525 1686

http://www.seo.nl

===========================

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**Follow-Ups**:**st: problem with -estimates table- command***From:*"Alexander Tsai" <act2@case.edu>

**References**:**Re: st: RE: Goldfeldt-Quant versus -hettest-***From:*Richard Williams <Richard.A.Williams.5@nd.edu>

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