[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

From |
Mark Schaffer <M.E.Schaffer@hw.ac.uk> |

To |
anirban basu <abasu@midway.uchicago.edu>, statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Cross-Sectional Time Series |

Date |
Tue, 25 Jun 2002 22:34:12 +0100 (BST) |

Anirban, Quoting anirban basu <abasu@midway.uchicago.edu>: > > Hi Mark, > > Thanks for the clarifications. I knew that the cluster option > does the > Huber-White correction for the standard errors but realized > that the > empirical var-cov estimate used by this command is different > from the > parameterized exchageable corr model. > However, the coefficient estimates with regress are the same > as the xtreg, > fe or xtreg, re command which assumes an exchangeable > correlation. I > think, and please fell free to correct me, these will be > different if we > use a different correlation structure model. Not quite sure what you mean, so apologies if I'm off target. The coefficient estimates with -regress- won't be the same as with -xtreg, fe- (unless the former is estimating the same model by explicitly including the fixed effects as dummy vars). Both sets of coefficients will be different again from those produced by -xtreg, re-. --Mark > > > Anirban > > ______________________________________ > ANIRBAN BASU > Doctoral Student > Harris School of Public Policy Studies > University of Chicago > (312) 563 0907 (H) > ________________________________________________________________ > > > On Tue, 25 Jun 2002, Mark Schaffer wrote: > > > Hi everybody. > > > > Just a couple of clarifying details on -cluster- vs. -xtreg- > and > > Anirban's response to John. > > > > The -cluster- option for -regress- doesn't really impose a > particular > > within-cluster correlation structure on the data. If I > understand it > > correctly, what -cluster- does instead is loosen the usual > assumption > > of independence of observations to independence of clusters. > The > > correlation between observations within clusters can be > arbitrary. > > The way this works is basically by treating all the > observations in a > > cluster as a kind of "super-observation" and then applying > the robust > > ("sandwich") formula to these super-observations in order to > > > calculate the standard errors of the coefficients produced > by - > > regress-. See the manual entry for -regress-, p. 87. > > > > The estimated coefficients (the betas) produced by -regress- > are the > > same whether or not the -cluster- option is used; the only > thing that > > is different is the standard errors. > > > > With fixed effects, you _do_ impose a particular correlation > > > structure, namely all the observations within a cluster > share U(k) in > > Anirban's notation. If you use -xtreg- with -fe- to > estimate, Stata > > does not, however, use a first-difference estimator - it > uses a fixed > > effects estimator. In other words, it doesn't > first-difference to > > get rid of the fixed effects, it uses the mean-deviation > > transformation to get rid of them. > > > > Hope this helps. > > > > --Mark > > > > Quoting anirban basu <abasu@midway.uchicago.edu>: > > > > > Hi John, > > > > > > > > > With reg command and cluster option, one basically imposes > an > > > exchangeable > > > correlation structure on the data. i.e assume corr (y(i), > > > y(j)) = rho, > > > where i ne j and i,j are any two observation from the > same > > > cluster. Rho > > > is constant for every pair of observation within a > cluster. > > > So, one can > > > visuaize it in terms of a random effects model where : > > > > > > Y(k) = Xb + U(k) + e, where k represents clusters and U(k) > is > > > a > > > cluster-specific random effect that is common to all > > > observation in that > > > cluster. However, -reg- does not give estimates of this > random > > > effect. It > > > just estimates -betas- assuming this structure. > > > > > > However, this estimation is correct only if U(k) are > > > uncorrelated with > > > Xs. i.e. the unobserved characteristics of a cluster over > time > > > is > > > uncorrelated with the X over time. If not then fixed > effects > > > is useful. > > > > > > > > > With fixed effects, one evades the correlation problem by > > > taking > > > differences. i.e for any cluster k: > > > > > > Y(ik) - Y(1k) = [X(ik) - X(1k)]b + [e(ik) - e(1k)] > > > > > > Note that by taking the difference, the unobserved U(k) is > > > eliminated. > > > However, fixed effects assume the U(k) is fixed over time > for > > > any cluster > > > k. i.e. the unobserved characteristics of a cluster is not > > > changing over > > > time. Also, since we are taking a difference, fixed > effects > > > model cannot > > > estimate the betas for baseline covariates since they > cancel > > > out in the > > > difference. > > > > > > Hope this helps, > > > > > > Anirban > > > > > > > > > > > > ______________________________________ > > > ANIRBAN BASU > > > Doctoral Student > > > Harris School of Public Policy Studies > > > University of Chicago > > > (312) 563 0907 (H) > > > > ________________________________________________________________ > > > > > > > > > On Tue, 25 Jun 2002, John Neumann wrote: > > > > > > > Hello all, > > > > > > > > Since I frequently see panel data questions flying > around > > > the > > > > list, I'm thinking that some of you can provide me with > a > > > > very succinct answer to the following question, and in > so > > > > doing clarify conceptually for me the data-related > issue: > > > > > > > > I have data on investment products, by year. Not all > > > > products have data in each year. The dependent > > > > variable is scaled in such a way as to make time series > > > > variation in its levels of no concern. Here's the > question: > > > > > > > > What is the difference between using the reg command, > > > > with the robust and cluster option, vs. the xtreg > command > > > > fixed effects model? The cluster variable using reg > would > > > > naturally be the i( ) parameter for xtreg ... > > > > > > > > Thanks! > > > > > > > > John Neumann > > > > Boston University Prof. Mark Schaffer Director, CERT Department of Economics, School of Management Heriot-Watt University, Edinburgh EH14 4AS tel +44-131-451-3494 / fax +44-131-451-3008 email: m.e.schaffer@hw.ac.uk web: http://www.som.hw.ac.uk/ecomes ________________________________________________________________ DISCLAIMER: This e-mail and any files transmitted with it are confidential and intended solely for the use of the individual or entity to whom it is addressed. If you are not the intended recipient you are prohibited from using any of the information contained in this e-mail. In such a case, please destroy all copies in your possession and notify the sender by reply e-mail. Heriot Watt University does not accept liability or responsibility for changes made to this e-mail after it was sent, or for viruses transmitted through this e-mail. Opinions, comments, conclusions and other information in this e-mail that do not relate to the official business of Heriot Watt University are not endorsed by it. ________________________________________________________________ * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Cross-Sectional Time Series***From:*anirban basu <abasu@midway.uchicago.edu>

**References**:**Re: st: Cross-Sectional Time Series***From:*anirban basu <abasu@midway.uchicago.edu>

- Prev by Date:
**st: contract command** - Next by Date:
**Re: st: Cross-Sectional Time Series** - Previous by thread:
**Re: st: Cross-Sectional Time Series** - Next by thread:
**Re: st: Cross-Sectional Time Series** - Index(es):

© Copyright 1996–2017 StataCorp LLC | Terms of use | Privacy | Contact us | What's new | Site index |