Statalist


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

R: st: R: linear regression question


From   "Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it>
To   <statalist@hsphsun2.harvard.edu>
Subject   R: st: R: linear regression question
Date   Tue, 17 Mar 2009 09:24:21 +0100

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 to
avoid 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: martedì 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 such 
models works out as antilog(beta) on the appropriate base. in this case, 
because galina explicitly mentioned natural log, and using carlo's 
example, it is exp(.2) = 1.2214, a 22.14% increase. try with base-10 and 
you will get something completely different.

the approximation 100*beta% works better and better as beta approaches 
zero (and as the log-transformation base approaches 1, but that's not 
typical in practice). in the stata journal article referred to below, 
beta=.0741516 and exp(beta)=1.07697, arguably close to 1.07415. in other 
cases, 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 independent
>> variable X (i.e., DeltaX=1)is associated with a 100*Beta% 
>> change in Y.
>>     
>
> This is one possible way of interpreting such a model. An 
> alternative way is discussed in: Roger Newson (2003) "Stata
> Tip 1: The eform() option with regress" The Stata Journal,
> 3(4): 445. 
> http://www.stata-journal.com/article.html?article=st0054
>
> Both 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/



*
*   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/



© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index