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st: ineqdeco Theil
muhammed abdul khalid <firstname.lastname@example.org>
st: ineqdeco Theil
Fri, 12 Mar 2010 21:27:36 +0100
Dear Stata list
How do we decompose the inequality (Theil Index) using the command
I tried to decompose the income by race AND strata, but it wont work. This
is what i wrote at the command
ineqdeco income , by (race strata)
If I do just by race , it works. same with strata or any other grouping. Is
it possible to decompose by more than one group?
Thank you so much in advance
2010/3/12 Kit Baum <email@example.com>
> Sergio wrote
> > Let me clarify the context. I am evaluating certain treatment that is
> > available only at some hospitals, but my data is at the patient level.
> > There are unobservables in the selection process, therefore the need for
> > an IV strategy. I am concerned about whether to adjust SE by this
> > clustering issue. Fixed effects at the hospital level is not possible,
> > "xtivreg, re" is possible with "xtset hospital". So I am exploring
> > a hausman test is possible in this context, as a way to test whether a RE
> > model is a better specification than my IV estimation.
> > I just read in the xtivreg documentation that "If the nosa option is
> > specified, the consistent estimators described in Baltagi and Chang
> > are used." (Page 213, xtivreg, re). Does that mean that a hausman test is
> > possible?
> No. The discussion in the manual is only speaking of consistent estimation
> of the variance components, that for the
> unit-specific error and that for the idiosyncratic error. But the RE
> estimator will not yield consistent estimates of anything if
> you violate the maintained hypothesis that the random effect is orthogonal
> to the regressors.
> As I said before, a Hausman test contrasts the estimates from two models
> under two states of the world:
> i) name-consistent: consistent estimates under both states
> ii) name-efficient: consistent and relatively efficient in state A, but
> inconsistent in state B
> For OLS vs IV, IV is name-consistent, OLS is name-efficient, with state A:
> E(u|X)=0, state B, not so.
> For RE vs FE, FE is name-consistent, RE is name-efficient, with state A:
> E(v|X)=0, state B, not so, with v the random component.
> In a panel setting, FE is consistent in the presence of unobserved
> heterogeneity, and OLS is inconsistent in that case. But there is no Hausman
> test in this regard; you just do the F-test for all fixed effect
> coefficients = 0. To apply a RE model, you have to be able to establish that
> E(v|X)=0. We usually do that via the above Hausman test, which you say can't
> be implemented because your variable of interest is subsumed in the
> individual (hospital) fixed effect.
> If there are unobservables in the selection of patients into hospitals,
> then why aren't you doing something like a selection model?
> This is not a 'clustering issue'. Ignoring clustering might mess up your
> VCE, but it would not make the estimates inconsistent. Ignoring the
> unobservables, or ignoring unobserved heterogeneity, would make the
> estimates inconsistent.
> Kit Baum | Boston College Economics & DIW Berlin |
> An Introduction to Stata Programming |
> An Introduction to Modern Econometrics Using Stata |
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