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RE: st: control a variable in stata


From   "Jacobs, David" <[email protected]>
To   "'[email protected]'" <[email protected]>
Subject   RE: st: control a variable in stata
Date   Mon, 23 Apr 2012 21:03:23 +0000

If you haven't seen it already you might be interested in an older article on your subject.  See:

Racial Differences in Professional Basketball Player's Compensation," L. Kahn and P. Scherer 1988:40-61  Journal of Labor Economics.

For another article on sports that might be helpful, see:

Jacobs, David, and Larry Singell. 1993. "Leadership and Organizational Performance: Isolating Links between Managers and Collective Success." Social Science Research, Summer 22:165-189. 

-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Kong, Chun
Sent: Monday, April 23, 2012 3:36 PM
To: [email protected]
Subject: 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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