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RE: st: RE: panel data fixed vs random


From   pietro masci <pete888888@msn.com>
To   statalist <statalist@hsphsun2.harvard.edu>
Subject   RE: st: RE: panel data fixed vs random
Date   Mon, 4 Feb 2013 10:13:06 -0500

thanks!!

I ran the hausman after log transformation, 

 hausman fix6 random6

                 ---- Coefficients ----
             |      (b)          (B)            (b-B)     sqrt(diag(V_b-V_B))
             |      fix6       random6       Difference          S.E.
-------------+----------------------------------------------------------------
logPenetra~2 |    .0867588    -.4900428        .5768016        .0213524
logGastosS~a |      .00316    -.0937751         .096935               .
logMortHom~b |    .0033615     .0204816         -.01712               .
loginterin~a |   -.0596365     .5041358       -.5637723        .0428176
------------------------------------------------------------------------------
                           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(4) = (b-B)'[(V_b-V_B)^(-1)](b-B)
                          =      158.35
                Prob>chi2 =      0.0000
                (V_b-V_B is not positive definite)

and from the output it looks like i should stay with the fixed effects.
As Kit suggest i am  reviewing the fixed effects model. What i am trying to test is the role of insurance (penetration) on entrepreneurship (depvar) The variable loginterins is interaction between insurance and finance and there is endogeneity. 
thanks
Pietro


----------------------------------------
> From: kit.baum@bc.edu
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: panel data fixed vs random
> Date: Mon, 4 Feb 2013 12:21:46 +0000
>
> <>
> On Feb 4, 2013, at 2:33 AM, Pietro said:
>
> > If i run the hausman test in the reverse order:
> >
> > hausman random fix
> >
> > i get the following output:
> >
> > Note: the rank of the differenced variance matrix (2) does not equal the number of coefficients
> > being tested (4); be sure this is what you expect, or there may be problems computing
> > the test. Examine the output of your estimators for anything unexpected and possibly
> > consider scaling your variables so that the coefficients are on a similar scale.
> >
> > ---- Coefficients ----
> > | (b) (B) (b-B) sqrt(diag(V_b-V_B))
> > | random fix Difference S.E.
> > - -------------+----------------------------------------------------------------
> > Penetratio~2 | -29177.79 -83456.95 54279.16 56513.77
> > GastosSaud~a | -4.087394 .6067533 -4.694147 2.920822
> > MortHomicp~b | 65.12774 4.54167 60.58607 31.10263
> > interinsfi~a | .3677846 .238441 .1293436 .0192787
> > - ------------------------------------------------------------------------------
> > 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
>
> Garbage in, garbage out. You cannot arbitrarily reverse the order of arguments to -hausman-. As the footer says, you
> have specified that the first set of estimates is always consistent, i.e. FE, not RE. You have to use fixed as the first argument.
>
> The huge difference in point estimates suggests to me that RE is not acceptable. Furthermore, when you run the
> test properly, you get a negative Chi2 value, and the command tells you that you are not meeting the underlying assumptions.
> In my experience this often signals that you are comparing two inconsistent estimators, i.e., that your FE model is
> seriously misspecified, and is itself junk. I would work with the FE model, analyze its residuals, and consider whether
> there are obvious problems of omitted variables, endogeneity, etc.
>
> Kit
>
> Kit Baum | Boston College Economics & DIW Berlin | http://ideas.repec.org/e/pba1.html
> An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html
> An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html
>
>
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