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Re: st: Frontier estimation using truncated normal option


From   ahmed al-darwish <dar_ahmed@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Frontier estimation using truncated normal option
Date   Sun, 10 Feb 2008 14:22:41 -0800 (PST)

I think Nicola suggestion is a good one. and I can add
to her suggestion that you use Limdep 8.0 or 7 might
to do it too. You can always forward your questions to
Prof. William Greene who won't take a long time to
reply to you regarding Frontier Analysis.
Hope this helps;
Ahmed Al-Darwish
University of Essex
 
--- nicola.baldini2@unibo.it wrote:

> Why not moving to Frontier 4.1 (somewhere near
> http://www.une.edu.au/econometrics/cepa.htm )? It's
> free, and _UNFORTUNATELY_ it does stochastic
> frontier estimation much better than Stata (at least
> up to version 9.2)
> Nicola
> 
> At 02.33 10/02/2008 -0500, you wrote:
> >Dear Statalisters,
> >
> >My question is fairly simple but I have struggled
> to
> >find a good answer. I am estimating a stochastic
> >production frontier and I want to properly test
> >whether technical inefficiency is present (and thus
> >whether frontier estimation is appropriate). The
> >stata routine does this for you when the default
> >half-normal model is used, but I am using the
> >truncated normal model with explanatory variables
> for
> >inefficiency (u = d*Z + w) through the
> cm(variables)
> >option.
> >
> >If I want to do a likelihood ratio test of
> >H_o: sigma_u = 0
> >With a test statistic of LR = -2*(L(H_o)-L(H_a),
> >what is the appropriate value for L(H_o)?
> >
> >Is it the e(ll_c) value saved in the frontier
> results
> >(in which case e(chi2_c) is my test statistic) or
> is
> >it the implied log-likelihood from an OLS version
> of
> >the production function (assuming normal errors),
> >including Z directly as a set of controls on the
> >right hand side?
> >
> >I thought they would be numerically equivalent (if
> >sigma_u = 0, the frontier collapses to a simple
> >linear regression - and the likelihoods for normal
> >errors should be the same). In my data, e(ll) from
> >the OLS and e(ll_c) from the frontier are only the
> >same when Z is empty (no cm(variables) option
> >specified). Does anyone know why they are not
> >generally equivalent and which one is correct to
> use
> >when Z is included? What is this "ll_c" value stata
> >is calculating?
> >
> >Thank you!
> >Ben Gilbert 
> 
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