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From |
huyen le <cbt_fx@yahoo.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Problem with cross sectional regression, different results from xtreg, xi |

Date |
Tue, 19 Jul 2011 09:56:14 +0100 (BST) |

Dear Stata Friends, I'm facing a serious problem with the cross sectional regression. Even I've searched around but couldn't solve it yet. Therefore, I'd be deeply grateful for your help. I'm doing a cross-sectional regression for about 2000 funds to examize the relationship between funds returns and age, expense, size. Each fund includes data about returns, age, etc. for 10 years, from 2000 to 2010. Since I want to do a yearly cross-sectional regression, I regress 2000 funds controlled for the time variable. Well, I do it according to the following 3 ways. Sadly, I get 3 different results. And I'm not sure, which one is correct. 1st way: seperate regression . regress returns age expense size if year==2000, robust . regress returns age expense size if year==2001, robust ... . regress returns age expense size if year==2010, robust Hence, I get 10 coefficients for each independent variable from 2000 to 2010. Then I calculate the average of them, and check the statistical significance by ttest. E.g. coeff_age = (coeff_age2000+coeff_age2001+ ... + coeff_age2010) / 10 ttest coeff_age==0 /*check for statistical significance*/ 2nd way: Using dummy variables . xi: regress returns age expense size i.year, robust 3rd way: Using xtreg . xtreg: regress returns age expense size, fe i(year) robust If I don't use the robust option, the 2nd way and 3rd way deliver the same result in p_values. But because of heteroskedasticity I have to use robust regression and get totally different p_values between the two ways. Could you please tell me, which way is the correct one and how I can solve this problem. Thank you very much! * * 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/

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