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# Re: st: RE: Frontier code- r(1400) error

 From Nick Cox <[email protected]> To [email protected] Subject Re: st: RE: Frontier code- r(1400) error Date Wed, 6 Apr 2011 09:16:20 +0100

```I have no specialist knowledge here, and others may have much better
answers. But I think your question answers itself. The evidence is
that with your model and data Stata is straining very hard to use a
normal, and an exponential is a much better idea. How else can anyone
interpret this information? Have you tried independent diagnostics,
e.g. plotting observed vs predicted or residual vs predicted, if that
makes sense?

2011/4/6  <[email protected]>:
> Dear Nick,
>
> I tried the Cobb Douglas function at first then I include the other
> variables to the model one by one. The results are much more better.
> Another thing I want you to ask is about the distribution assumption. When
> I use the exponential distribution, the results are significant even if
> the iteration number is small (for instance: 1000). However, when I use
> the half normal distribution with 1000 iteration, some of the parameters
> appear as dots in the results. Sometimes increasing the iteration number
> works in such cases. Is it logical to increase the iteration number? Or if
> the results appear as dots even with the 1000 iteration, then it is not
> needed to be continued?
>
> Thanks
> Hande
>
>
>
>> Your original posting was
>>
>> http://www.stata.com/statalist/archive/2011-03/msg01715.html
>>
>> Evidently, that guess of 29 observations was wrong. You are still left
>> with the suggestion that your model appears too complicated and that
>> one strategy is to simplify it radically. When you get a model that
>> does not produce estimates, you can complicate it step by step to see
>> where the problem lies.
>>
>> Nick
>>
>> 2011/4/2  <[email protected]>:
>>>
>>> Dear Nick and Gordon
>>>
>>> Thank you for your advices. But Gordon says that "you have only 29
>>> observations". I might have expressed myself in an incorrect way. I have
>>> 4
>>> output variables, 3 input price variables for the 29 firms. Actually I
>>> have 208 observations. It seems enough to estimate the frontier, isn't
>>> it
>>> ?
>>>
>>> Thank you
>>> Hande
>>>
>>>> Nick's answer is correct.  You have 27 parameters plus the additional
>>>> parameters for the efficiency error distribution and only 29
>>>> observations.  This will never produce a satisfactory result.
>>>>
>>>> Translog frontier models can be difficult to estimate under the best
>>>> of circumstances without trying to over-determine the frontier.  You
>>>> should start by estimating the basic log-linear Cobb-Douglas form
>>>> (dropping all of the interaction terms) and then introduce
>>>> interactions individually and very carefully.  Even then it is
>>>> unlikely that you will get any convincing results with such a small
>>>> sample.

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