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From |
btgilber@weber.ucsd.edu |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Frontier estimation using truncated normal option |

Date |
Fri, 8 Feb 2008 23:50:56 -0800 (PST) |

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 * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Frontier estimation using truncated normal option***From:*"Scott Merryman" <scott.merryman@gmail.com>

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