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: [email protected]
[mailto:[email protected]] 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
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