Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.


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

Re: st: control a variable in stata


From   Prakash Singh <[email protected]>
To   [email protected]
Subject   Re: st: control a variable in stata
Date   Sun, 22 Apr 2012 21:44:52 +0530

Your Null is Constant Variance and the calculated chi2 test statistics
with 1 degree of freedom is not significant at even 10 percent level
of significance. This means that there is no problem of
heteroskedasticity in your estimation.
You can go ahead with OLS and I think white standard errors would also do good.

On Sun, Apr 22, 2012 at 7:26 PM, Kong, Chun <[email protected]> wrote:
> 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
>         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
>
> *
> *   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/

*
*   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 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index