Re: st: ml maximize works if ml check is run first but hits a discontinuous region otherwise Poi TSP

[Alex Olssen <alex.olssen@gmail.com>]

Hi Brian,

In fact the ml program converges after   ml check   but NOT after   ml search.

I am really unsure why.  I haven't tried specifying initial values - I
will do this though.

I am aware of your 2008 article.  I feel that   nlsur   is overly
restrictive in terms of identification.

Kind regards,

Alex

On 7 May 2011 12:47, Brian P. Poi <brian@poiholdings.com> wrote:
>
>
> On 05/05/2011 11:58 PM, Alex Olssen wrote:
>>
>> Dear Statlisters,
>>
>> I am in the process of reproducing the results from Berndt and Savin's
>> 1975 Econometrica estimation of a singular system of equations with
>> autoregressive errors in Stata using manual maximum likelihood.
>>
>> Poi's stata help desk articles have been of invaluable assistance.
>>
>> I have noticed something odd.
>>
>> For my estimation of model 7 in table 1
>>
>> If I run the sequence
>>
>> ml model d0 ...
>> ml check
>> ml maximize
>>
>> everything runs fine and the results are similar to those in Berndt and
>> Savin.
>>
>> If I run the sequence
>>
>> ml model d0 ...
>> ml maximize
>>
>> Stata hits a discontinuous region.
>>
>> Any ideas what is going on here?
>
> -ml- might be making use of random numbers in its search for initial values
> when checking and maximizing your likelihood function.  When you run -ml
> check- before -ml maximize-, the first random number that -ml maximize-
> would therefore be different than when you call -ml maximize- without having
> called -ml check-.
>
> Have you tried using -ml search- before -ml maximize-?  -ml search- does a
> more thorough search for initial values than -ml maximize- does by itself.
>  Also, did -ml check- issue some kind of message indicating it was going to
> call -ml search-?
>
>>
>> Also, for model 8, my maximum likelihood procedure in Stata reproduces
>> Berndt and Savin's coefficients to only 2 decimal places - at the 3rd
>> decimal place there are often differences.
>> Standard errors are reproduced more accurately.
>>
>> Does anyone have any ideas what is happening here either?  I have seen
>> somebody reproduce one part of Berndt and Savin in TSP and their
>> results were much closer - the paper was originally done in TSP.
>>
>> Kind regards,
>>
>> Alex
>
> Have you tried specifying initial values?  Getting different packages to
> produce the same estimates with difficult problems can itself be a difficult
> problem.  You could try playing with different optimization techniques,
> convergence criteria, etc., though that is no guarantee. I've found that
> sometimes having a small dataset makes matching results even more difficult
> than if the dataset were larger.
>
> One final thought: for estimating a system of nonlinear equations, even
> singular systems, you might try using -nlsur- instead.  It's much faster on
> these problems.  The reference manual entry for -nlsur- shows how to fit an
> AIDS model, and my article from 2008 in the Stata Journal (v. 8 number 4)
> shows how to replicate the results in my old helpdesk article using -nlsur-.
>
>   -- Brian Poi
>   -- brian@poiholdings.com
> *
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>

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