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RE: st: frontier models
Dear George,
One of the reasons for choosing alternate error distributions is to check
how robust your results are. Also, if you flip through Lovell and
Kumbhakar's book (2000) "Stochastic Frontier Analysis" you will read that
they state that qualititative estimates are not sensitive to the type of
distributional assumptions made, however quantitative estimates are but the
rankings do not change.
Half normal is widely used in the literature. When I used frontier, I had
problems of convergence when using the exponential form. Half normal behaved
better.
Hope this helps.
Regards,
(Ms) Gauri
PhD Candidate
Dept. of Economics
Graduate Institute of International Studies
Geneva
From: george owuor <[email protected]>
Reply-To: [email protected]
To: statalist <[email protected]>
Subject: st: frontier models
Date: Tue, 28 Nov 2006 00:06:26 -0800 (PST)
Dear all,
I am new with frontier. Yet I can see there are three oprions. My model
is a production function. What are the key salient reasons for using
noemal, exponential or truncated. Please assist.
I am interested to measure inefficiency covariates too.
george
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