# RE: st: fixed effects estimation with time invariant variables

 From "ALICE DOBSON" <[email protected]> To [email protected] Subject RE: st: fixed effects estimation with time invariant variables Date Wed, 27 Jul 2005 07:03:32 -0400

I have two obseervations. First, xthtaylor is more suitable for endogenous time-invariant variables. Hence, it relaxes the assumption of orthogonality. It is a bigger gun that Jona may proably require. Hence, conducting the Hausman test first is a better option.
Second, I often face a similar problem like Jona. For instance, I reporduce a Hausman test (fixed vs. random effect) result. How do I interpret this result?

hausman fixed random

---- Coefficients ----
| (b) (B) (b-B) sqrt(diag(V_b-V_B))
| fixed random Difference S.E.
-------------+----------------------------------------------------------------
beta | .0227671 .0407022 -.0179352 .023357
------------------------------------------------------------------------------
b = consistent under Ho and Ha; obtained from xtreg
B = inconsistent under Ha, efficient under Ho; obtained from xtreg

Test: Ho: difference in coefficients not systematic

chi2(1) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 0.59
Prob>chi2 = 0.4426

From: Christopher Baum <[email protected]>
To: [email protected]
Subject: st: fixed effects estimation with time invariant variables
Date: Tue, 26 Jul 2005 13:49:55 -0400

Martha said .............................

Chris replied: This is quite incorrect. The standard random effects model, xtreg, re, does NOT involve anything beyond a random intercept. She is correct is noting that to use RE there is a maintained assumption of orthogonality between regressors and the random intercept for each unit. As Mark S. said, xthtaylor is a way around the oft-violated orthogonality assumption. Mark is right on in suggesting that you should do the Hausman test.

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You do not need Some Alternative Software nor GLLAMM to estimate a mixed model in Stata. These models (which indeed combine random and fixed effects) are available with command xtmixed.

Kit
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