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R: st: control a variable in stata
From
<[email protected]>
To
<[email protected]>
Subject
R: st: control a variable in stata
Date
Tue, 24 Apr 2012 09:09:09 +0200
Andy may want to take a look at the following paper:
Kyle Rehnstrom. Racial Salary Discrimination in the NBA: 2008-2009.
http://business.uni.edu/economics/Themes/rehnstrom.pdf
and to this URL:
http://www.stata.com/meeting/italy11/abstracts/italy11_capelli.pdf and its
references.
Best wishes,
Carlo
-----Messaggio originale-----
Da: [email protected]
[mailto:[email protected]] Per conto di Kong, Chun
Inviato: lunedì 23 aprile 2012 21:34
A: [email protected]
Oggetto: RE: st: control a variable in stata
Thank you very much!!
I am looking at the factors in determining nba player's salary. Race and
ethnicity are two of my variables, they both turn out to be significant in
affecting the player's salary. However, I would like to compare them again -
the race variable (white players and non-white players) and ethnicity
variable (international players and US born players) after controlling the
performance.
Kind regards,
Andy
________________________________________
From: [email protected]
[[email protected]] on behalf of
[email protected] [[email protected]]
Sent: 23 April 2012 06:31
To: [email protected]
Cc: [email protected]
Subject: R: st: control a variable in stata
Dear Andy,
the result of Breusch-Pagan / Cook-Weisberg test are saying that you cannot
reject the null hypothesis of no_heteroskedasticity at 0.05 significance
level.
Hence, there is no need for robust standard error in your OLS.
Kndest Regards,
Carlo
-----Messaggio originale-----
Da: [email protected]
[mailto:[email protected]] Per conto di Kong, Chun
Inviato: domenica 22 aprile 2012 15:56
A: [email protected]
Oggetto: RE: st: control a variable in stata
Carlo, Thank you very much for your help! After I have entered the command
'estat hettest' after my regression, the following has come up:
----------------------------------------------------------------------------
--
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity
Ho: Constant variance
Variables: fitted values of lnsalary
chi2(1) = 1.62
Prob > chi2 = 0.2037
Does it mean there is heteroskedasticity in my model? After that, I have
done the same regression and added (, robust) at the end of it. However, it
seems that nothing has changed.
Should I go ahead with the OLS or white standard errors?
Thank you very much for all your help and time again! :)
Andy
________________________________________
From: [email protected]
[[email protected]] on behalf of
[email protected] [[email protected]]
Sent: 22 April 2012 13:20
To: [email protected]
Cc: Kong, Chun
Subject: R: st: control a variable in stata
Andy may want to check for heteroskedasticity after -regress- via - estat
hettest- ( from -regress postestimation- suite).
As an aside, Huber-White sandwich estimator is implemented via the -robust-
option available with most Stata commands (including -regress-), as reported
in Baum CF. An Introduction to Modern Econometrics Using Stata. College
Station, TX: Stata Press, 2006: 136-38.
Best wishes,
Carlo
-----Messaggio originale-----
Da: [email protected]
[mailto:[email protected]] Per conto di Kong, Chun
Inviato: domenica 22 aprile 2012 01:05
A: [email protected]
Oggetto: RE: st: control a variable in stata
Thank you very much for all your help!
I have run both poisson and OLS, the OLS gives a R2 of 0.6175 and Poisson
has a R2 of 0.6250, however, all the research that I have gone through is
using OLS. Therefore, I think I should go with OLS, but I really appreciate
for your suggestion and time.
Most of the reserachs stressed in desribing the variable and analyzing the
resutls, however, very few have explained the methodology. One have used
white standard corrected errors because there is a difference between the
adjusted standard errors and the normal standard errors, suggesting there is
small level of heteroskedascticity. Therefore, the model is regressed using
the white standard errors. I have google something relate to white standard
error, however, i still do not understand whether i should follow this
approach.
I am sorry for all the silly question. Once again, thank you very much for
your time and help. :)
Andy
________________________________________
From: [email protected]
[[email protected]] on behalf of Nora Reich
[[email protected]]
Sent: 21 April 2012 20:38
To: [email protected]
Subject: Re: st: control a variable in stata
Andy, by the way, what is the value of the R2? It gives you a hint on how
much of the variation in salary can be explained by your model. I would
improve the model with new variables (as proposed earlier) and see which
ones have a significant effect and which ones lead to substantial increases
in R2.
Nora
Am 21. April 2012 21:33 schrieb Nora Reich <[email protected]>:
> As far as I know, -poisson- is for skewed distributions, and salary
> distribution in general often fulfills this requirement, but salary of
> NBA players might show a different distribution. The distribution can
> be checked, e.g. with the command
>
> -histogram salary-
>
> (for more information type -help histogram-).
>
> Andy, I would compare the assumptions and requirements of different
> estimation strategies (OLS, poisson) and find out which fits better
> with the data.
>
> I would also check which estimations strategies are used by similar
> papers, and why.
>
> Apart from -poisson- and -regress-, I cannot think of any at the
> moment that have to be considered for your salary-estimations.
> However, if there was something like a "minimum wage" for NBA players,
> i.e. salary is censored, -tobit- would be an alternative.
>
> Best regards
> Nora
>
>
>
>
> --
> Nora Reich
> www.nora-reich.de
> Publications:
> http://www.nora-reich.de/publikationen.html
> http://www.hwwi.org/ueber-uns/team/forscher/nora-reich/publications.ht
> ml
--
Nora Reich
www.nora-reich.de
Publications:
http://www.nora-reich.de/publikationen.html
http://www.hwwi.org/ueber-uns/team/forscher/nora-reich/publications.html
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