Okay. Thanks though!
- Amber
On Tue, 24 Feb 2004 16:08:43 +0000, "Alfonso Miranda Caso Luengo" wrote:
> Ignore my last post. In this case there is no such transformation.
>
> ===========================================
> Alfonso Miranda
> PhD Student
>
> Economics Department
> University of Warwick
> Coventry CV4 7AL
> E-mail: [email protected]
> ===========================================
> >>> [email protected] 02/24/04 16:03 PM >>>
> I guess sigma_u = log(sigma). In many cases Stata estimates a function of an
auxiliary parameter instead of the parameter itself. This thick helps to keep
estimates whithin a set of admissible values and ease ML maximisation. In any
case, you could always recover the value of the parameter in the original scale
applying the inverse function. Standard errors may be obtained using the delta
method.
>
> ===========================================
> Alfonso Miranda
> PhD Student
>
> Economics Department
> University of Warwick
> Coventry CV4 7AL
> E-mail: [email protected]
> ===========================================
> >>> [email protected] 02/24/04 15:39 PM >>>
> I'm very confused about why the sigma_u listed in the output from a random
> effects model reports a value of zero, despite the fact that I have unit
> variance in my dataset (I promise). I'm attaching the output below. Could
> someone please tell me what this means? Thanks!
>
>
>
>
> xtreg dppct educpct repubpct fundpct whitepct, re;
>
> Random-effects GLS regression Number of obs = 220
> Group variable (i) : cohort Number of groups = 10
>
> R-sq: within = 0.0577 Obs per group: min = 22
> between = 0.6344 avg = 22.0
> overall = 0.0622 max = 22
>
> Random effects u_i ~ Gaussian Wald chi2(4) = 14.27
> corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0065
>
> ------------------------------------------------------------------------------
> dppct | Coef. Std. Err. z P>|z| [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> educpct | .0596706 .0526787 1.13 0.257 -.0435777 .1629189
> repubpct | .2223392 .1046384 2.12 0.034 .0172516 .4274267
> fundpct | .2698267 .1397987 1.93 0.054 -.0041737 .543827
> whitepct | .2623254 .1236531 2.12 0.034 .0199697 .5046811
> _cons | .2656249 .1358642 1.96 0.051 -.000664 .5319138
> -------------+----------------------------------------------------------------
> sigma_u | 0
> sigma_e | .09882399
> rho | 0 (fraction of variance due to u_i)
> ------------------------------------------------------------------------------
> Amber E. Boydstun
> Graduate Student
> Department of Political Science
> Penn State University
> University Park, PA 16802-6200
> [email protected]
> *
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> * http://www.ats.ucla.edu/stat/stata/
>
>
> *
> * For searches and help try:
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> * http://www.ats.ucla.edu/stat/stata/
>
>
> *
> * For searches and help try:
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> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
>
Amber E. Boydstun
Graduate Student
Department of Political Science
Penn State University
University Park, PA 16802-6200
[email protected]
*
* For searches and help try:
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* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
