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Re: st: frontier models


From   george owuor <gowuor2001@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: frontier models
Date   Tue, 28 Nov 2006 00:55:04 -0800 (PST)

Thanks Gauri. 

George

----- Original Message ----
From: Gauri Khanna <gwkhanna@hotmail.com>
To: statalist@hsphsun2.harvard.edu
Sent: Tuesday, November 28, 2006 11:29:19 AM
Subject: 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 <gowuor2001@yahoo.com>
>Reply-To: statalist@hsphsun2.harvard.edu
>To: statalist <statalist@hsphsun2.harvard.edu>
>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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