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Re: st: Frontier estimation using truncated normal option

Subject   Re: st: Frontier estimation using truncated normal option
Date   Sun, 10 Feb 2008 20:22:17 +0100

Why not moving to Frontier 4.1 (somewhere near )? It's free, and _UNFORTUNATELY_ it does stochastic frontier estimation much better than Stata (at least up to version 9.2)

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)
>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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