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From |
"Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it> |

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

Subject |
st: R: linear regression question |

Date |
Sun, 15 Mar 2009 09:17:50 +0100 |

Dear Galina, 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 independent variable X (i.e., DeltaX=1)is associated with a 100*Beta% change in Y. For instance, a coefficient = 0.2 in your log-linear model means that the dependent variable Y increases by [(0.2*100)%]=20% for each additional unit of X. You can find a lot more on this topic (and other related issues) in an introductory econometric textbook (please, find some references below): Koop G. Introduction to Econometrics. Wiley, 2007. Stock JH, Watson MW. Introduction to Econometrics. Second Edition.Pearson International Edition, 2007. For Stata Users, the reference textbook is: Baum K. An Introduction to Modern Econometrics Using Stata. http://www.stata-press.com/books/imeus.html. HTH and Kind Regards, Carlo -----Messaggio originale----- Da: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Galina Hayes Inviato: domenica 15 marzo 2009 2.52 A: statalist Oggetto: st: linear regression question Hello everyone, In a linear regression model, if I have had to perform a natural log transformation of outcome to meet the homoscedasticity assumption, can someone tell me how to interpret the coefficents? Do I simply exponentiate them? Thanks, Galina * * 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/

**Follow-Ups**:**Re: st: R: linear regression question***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**References**:**st: linear regression question***From:*Galina Hayes <galina@uoguelph.ca>

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