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From |
"Martin Weiss" <martin.weiss1@gmx.de> |

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

Subject |
st: RE: 3 Problems in Panel Data Analysis |

Date |
Tue, 7 Oct 2008 14:54:54 +0200 |

Concerning 1): FE, because of the way it is constructed, cannot provide estimates for time-invariant covariates, so that might be the reason for dropped regressors. Concerning 2), -xtreg- has a -clustered robust- VCE which seems appropriate given your observation of stark differences between between groups vs. within group variance. Note that you can check for these two variance components with -xtsum-. Concerning 3), the lack of instruments can sometimes be overcome with -xthtaylor- which can remedy correlation between covariates and the individual effect u_i and at the same time provide estimates for time-invariant regressors. HTH Martin -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Fardad Zand Sent: Tuesday, October 07, 2008 2:45 PM To: statalist@hsphsun2.harvard.edu Subject: st: 3 Problems in Panel Data Analysis Hello All, I'm using a panel dataset to investigate the effect of R&D collaboration diversity on innovation performance at the firm level. The nature of my data is such that there is not that much variation over time with respect to the number and type of one company's set of partners, while there is substantial variation among different companies. In other words, the composition of one firm's partners usually doesn't change considerably over time, while comparing different companies with each other reveals considerable differences. I'm using Stata to run panel data regression models. Depending on the type of my dependent variable (censored or not), I use -xtreg- or -xttobit-. Here it comes the problem: 1) FE, RE, or BE? When using -xtreg- I can go for FE, RE, or BE (or is there any other versions?). As expected, the FE results in very poor, disappointing and unexpected results, with many variables dropped from the regression, or showing insignificant estimates. I believe, this is mainly due to the nature of the data explained above. Am I right? Alternatively, RE and BE result in better and more understandable results. However, when I run the Hausman test, two things could happen: either a) the null hypothesis is usually rejected, stating that FE is the preferred method and that RE results in biased estimations, or b) I get an error stating that the fitted model on the data fails to meet the asymptotic assumptions of the Hausman test. ***What should I do? What is the valid approach to pursue? How should I justify using RE or BE? Is there any alternative tests or methods that can be used? What specific conditions should I check (and how?) to be sure about using RE for my estimations? 2) Robust standard errors? There is a lot of heterogeneity in my data with respect to firm-specific or industry-specific characteristics. The results show that heteroskedasticity is inevitable. To correct for that, I can use the "robust" option when using -xtreg-. Am I right? But how about when using -xttobit- as there is no "robust" option available for -xttobit-? ***What would you suggest? How would you correct for heteroskedasticity? Is there any other important characteristics that I need to check before I can be sure about the validity and reliability of my results? What pre- or post-tests do you suggest? 3) SYS-GMM method? I know that SYS-GMM is a good way to deal with the problems of omitted variables bias and simultaneity (endogenous variables). ***How can I successfully implement this method in Stata? Is there any alternatives that you would suggest? In general, how would you correct for simultaneity problem, if you don't have access to good instruments? I know I asked too much but I decided to post my questions all in one email rather than bothering you with multiples. I hope you have time and willingness to support me and in any case, I thank you for reading and possibly responding to this post. Thank you so much all. Good luck All, Fardad * * 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/

**References**:**st: 3 Problems in Panel Data Analysis***From:*"Fardad Zand" <fardad.zand@gmail.com>

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