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From |
"Jacob, Jeffry Ankur" <jajacob@mail.smu.edu> |

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

Subject |
st: RE: Fixed effects decomposition (was xthtaylor) |

Date |
Wed, 11 Feb 2004 00:30:20 -0600 |

Hi Alex, There is a discussion of the Hausman Taylor method in Wooldridge's book, "Econometric Analysis of Cross Section and Panel Data" in pps 325-328, and the estimation is coded in stata 8. From a fe regression, one can not obtain a(i) as they are cleared off through time demeaning ( and so are z(i)). You can estimate a(i) by using individual dummies and running an OLS, but may loose several degrees of freedom. The advantage of H-T estimation is that you can obtain consistent and efficient estimates of g. This is done in two basic steps. A fe regression is run to obtain within group errors. From these one obtains consistent, though inefficient, parameter estimates. From this intermediate step, one can obtain standard errors of the individual and idiosyncratic error components and run a re model to obtain consistent and efficient parameter estimates. In comparison to this approach, I do not think that the two- step procedure that you have outlined may work. Hope this helps, Best, Jeffry Jacob -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu on behalf of ACavallo@lexecon.com Sent: Tue 10-Feb-04 2:35 PM To: statalist@hsphsun2.harvard.edu Cc: Subject: st: Fixed effects decomposition (was xthtaylor) Mario, Thanks for your tips - I forgot that these characteristics can be estimated using a random effects model. My question about the decomposition still stands though, how do I estimate g in the model below when using fixed effects. y(it)=b*x(it) + g*z(i) + a(i) + e(it) where x(it) are time varying characteristics, z(i) are time invariant characteristics, and a(i) are the fixed effects. My proposal is to estimate fixed effects model, predict a(i), then regress a(i) on z. I would bootstrap to get the standard errors right on the auxilliary regression xtreg y x, fe predict a, u by id : keep if _n==1 regress a z I looked in Greene's "Econometric Analysis" and Baltagi's "Econometric Analysis of Panel Data" but did not see any explanation. Does anyone have references or comments on my proposal? Regards, --Alex Cavallo Lexecon (312) 322-0208 voice (312) 322-0218 fax >Can I use XTHTAYLOR assuming no variables are correlated with a(i)? In >other words, is the endog(varlist_endog) option required? I don't yet have >Stata 8 so I can't just try this. The online help for -xthtaylor- states that the endog() option is required, http://www.stata.com/help.cgi?xthtaylor However, the Hausman-Taylor estimator of a model where every variable in X and Z is assumed to be uncorrelated with the random effect [a(i), or u(i) in stata's notation] is simply a random-effects model (-xtreg, re- y on X and Z varlists). I don't have the paper here, but I think this is stated in Hausman and Taylor (1981) econometrica paper. >If not, does anyone have a reaction to this proposed method: > 1. estimate y(it)=b*x(it) + a(i) + e(it) > 2. regress ahat(i) on z(i) to estimate ghat, using bootstrap to get >standard errors right Don't trust me much in this, but I think that depending on the procedures used in steps (1) and (2) (and possibly on the (un)balanced nature of your panel data set) you could get a "ghat" estimator that would be consistent but not efficient. If all variables in X and Z are really exogenous, -xtreg, fe- is both consistent and efficient. Hope this helps, Mario F. Rueda Narváez Departamento de Estadística y Econometría Facultad de Ciencias Económicas Universidad de Málaga El Ejido s/n 29013 Málaga (España) <http://www.estyeco.uma.es/>http://www.estyeco.uma.es/ Tlf: +34 952 13 71 90 Fax: +34 952 13 72 62 * * 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/

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