Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

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

From |
<carlo.lazzaro@tiscalinet.it> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
R: st: control a variable in stata |

Date |
Mon, 23 Apr 2012 07:31:40 +0200 |

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: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Kong, Chun Inviato: domenica 22 aprile 2012 15:56 A: statalist@hsphsun2.harvard.edu 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: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of carlo.lazzaro@tiscalinet.it [carlo.lazzaro@tiscalinet.it] Sent: 22 April 2012 13:20 To: statalist@hsphsun2.harvard.edu 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: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Kong, Chun Inviato: domenica 22 aprile 2012 01:05 A: statalist@hsphsun2.harvard.edu 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: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Nora Reich [nhmreich@googlemail.com] Sent: 21 April 2012 20:38 To: statalist@hsphsun2.harvard.edu 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 <nhmreich@googlemail.com>: > 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/

**Follow-Ups**:**RE: st: control a variable in stata***From:*"Kong, Chun" <C.Y.Kong@warwick.ac.uk>

**References**:**st: control a variable in stata***From:*"Kong, Chun" <C.Y.Kong@warwick.ac.uk>

**Re: st: control a variable in stata***From:*Nora Reich <nhmreich@googlemail.com>

**RE: st: control a variable in stata***From:*"Kong, Chun" <C.Y.Kong@warwick.ac.uk>

**R: st: control a variable in stata***From:*<carlo.lazzaro@tiscalinet.it>

**RE: st: control a variable in stata***From:*"Kong, Chun" <C.Y.Kong@warwick.ac.uk>

- Prev by Date:
**st: nl nonlinear regression** - Next by Date:
**Re: st: mlogit coefs** - Previous by thread:
**Re: st: control a variable in stata** - Next by thread:
**RE: st: control a variable in stata** - Index(es):