Thanks for your feedback. In fact, I think there are two problems. The first one is to find a way to estimate the coefficient for TI variables when xtreg, re is not an option (the Hausman test is rejected) and when I do not think xthtaylor is an option either (no endogenous variables). I like the idea of xtfevd, but there is a problem with the standard errors and so far, I am not sure where the problem comes from.
The second problem is whether the fact that it is an unbalanced panel creates a potential bias vs if it were a balanced panel.
I guess the other issue is that I am new to Stata. I tried to run your example, but could not manage T2+T3 as when I get to "predict aux1, r", I get the error message "option r not allowed".
Last, if I may, would xtgee be an option as well? Thanks.
Barbara.
________________________________
From: [email protected] on behalf of Rodrigo A. Alfaro
Sent: Tue 10/17/2006 6:11 PM
To: [email protected]
Subject: st: Re: RE: Fixed-effects, unbalanced panel and time-invariant variable
Dear Mark,
RE estimation is more restrictive than the current FE+BE. For RE we need
that time variant (TV) and time invariant (TI) variables have to be
uncorrelated with the cross sectional unobservable (u_i)), if the assumption
if false the TV and TI estimates are inconsistent. But for this procedure
(FE+BE) only TI estimates will be inconsistent (Hsiao 2003, page 52-53). Of
course under not correlation RE is more efficient. The following example
show you the 3 methods: FE+BE, RE and LS.
In T1 we have the xtfevd output, T2+T3 the FE+BE without any adjustment (the
constant is added to T3 therefore the constant in T2 is irrelevant). T4 is
GLS RE, T5 is the LS and T6 is MLE RE. It seems that std errors fot TI in T1
are too much small in compare with other methods, maybe there is a typo in
the ado-file. T2+T3 give us a more reliable result that we can compare with
T4, T5 and T6. Look fem estimate (gender dummy), GLS RE is similar to LS
even that 75% of the total variance is explained by u_i. For T6 the results
are close to FE in the case of coef but very different in the std error of
TI... any idea?
Best, Rodrigo.
/******************** Example **************************************/
qui {
webuse psidextract
tsset id t
xtfevd lwage wks south smsa ms exp exp2 occ ind union fem blk ed,
invariant(fem blk ed)
est store T1
xtreg lwage wks south smsa ms exp exp2 occ ind union, fe
est store T2
predict aux1, r
bysort id: egen aux2=mean(aux1)
replace aux2=aux2+_b[_cons]
reg aux2 fem blk ed
est store T3
xtreg lwage wks south smsa ms exp exp2 occ ind union fem blk ed, re
est store T4
reg lwage wks south smsa ms exp exp2 occ ind union fem blk ed, re
est store T5
xtreg lwage wks south smsa ms exp exp2 occ ind union fem blk ed, mle
est store T6
}
est table T*, se
/******************** Example **************************************/
----- Original Message -----
From: "Schaffer, Mark E" <[email protected]>
To: <[email protected]>
Sent: Tuesday, October 17, 2006 11:12 AM
Subject: st: RE: Fixed-effects, unbalanced panel and time-invariant variable
Barbara,
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of
> PETITT Barbara
> Sent: 17 October 2006 14:47
> To: [email protected]
> Subject: st: Fixed-effects, unbalanced panel and
> time-invariant variable
>
> Hello,
>
> I have an unbalanced panel (for some firms, I have three
> years of data, for others, two years or even only one year).
> One of my independent variables is a time-invariant variable
> and with fixed-effects models, its gets dropped. I
> contemplated using the fixed effects vector decomposition
> (xtfevd), but does it work for unbalanced panel?
> Otherwise, is there any alternative?
Maybe I am missing something obvious, but why won't the standard random
effects estimator work for you? -xtreg,re- etc.
--Mark
Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3296
email: [email protected]
web: http://www.sml.hw.ac.uk/ecomes
> Thank you.
>
> Barbara.
>
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