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From |
dr kardos laszlo <l_kardos@chello.hu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: R: st: R: linear regression question |

Date |
Tue, 17 Mar 2009 11:52:54 +0100 |

dear carlo,

best regards, laszlo Carlo Lazzaro wrote:

Dear Laszlo, thanks for your remark. The potential misleading arises because the use of natural log is the reference in econometrics textbook. However, as you suggested, a thorough check of this requirement should be made, in order toavoid bewildering results.Kind Regards, Carlo -----Messaggio originale----- Da: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di dr kardos laszlo Inviato: martedi` 17 marzo 2009 8.34 A: statalist@hsphsun2.harvard.edu Oggetto: Re: st: R: linear regression question unless i got something wrong,the relative change in y associated with a unit change in x in suchmodels works out as antilog(beta) on the appropriate base. in this case,because galina explicitly mentioned natural log, and using carlo'sexample, it is exp(.2) = 1.2214, a 22.14% increase. try with base-10 andyou will get something completely different.the approximation 100*beta% works better and better as beta approacheszero (and as the log-transformation base approaches 1, but that's nottypical in practice). in the stata journal article referred to below,beta=.0741516 and exp(beta)=1.07697, arguably close to 1.07415. in othercases, the difference might be to an extent you do not want to ignore.laszlo Galina Hayes wrote:Thanks very much everyone, very helpful. Galina ----- Original Message ----- From: "Maarten buis" <maartenbuis@yahoo.co.uk> To: statalist@hsphsun2.harvard.edu Sent: Sunday, March 15, 2009 11:48:52 AM GMT -05:00 US/Canada Eastern Subject: Re: st: R: linear regression question --- On Sun, 15/3/09, Carlo Lazzaro wrote:your thread seems to refer to a log-linear model, where only the dependent variable (i.e., Y) is log-transformed. In a log-linear model, a unit-change in the independentvariable X (i.e., DeltaX=1)is associated with a 100*Beta%change in Y.This is one possible way of interpreting such a model. Analternative way is discussed in: Roger Newson (2003) "StataTip 1: The eform() option with regress" The Stata Journal,3(4): 445.http://www.stata-journal.com/article.html?article=st0054Both interpretations are correct, they are just different ways of looking at the same model. Hope this helps, Maarten ----------------------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://home.fsw.vu.nl/m.buis/ -----------------------------------------* * 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/ * * 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/* * 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/

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**Follow-Ups**:**Re: R: st: R: linear regression question***From:*Austin Nichols <austinnichols@gmail.com>

**References**:**R: st: R: linear regression question***From:*"Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it>

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