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Re: st: Re: Finding initial feasible values for xtfrontier, ti cost version, please help!
From
Rogie Mercado <[email protected]>
To
[email protected]
Subject
Re: st: Re: Finding initial feasible values for xtfrontier, ti cost version, please help!
Date
Fri, 26 Mar 2010 06:37:27 -0700 (PDT)
Dear Scott,
You could try the Winbugs program and then download their ado files. The program has the option that it will generate its own initial values. However, such models follows Gibbs sampling (Bayesian). I hope this helps.
Cheers,
Rogelio
--- On Fri, 26/3/10, Scott Merryman <[email protected]> wrote:
> From: Scott Merryman <[email protected]>
> Subject: Re: st: Re: Finding initial feasible values for xtfrontier, ti cost version, please help!
> To: [email protected]
> Received: Friday, 26 March, 2010, 7:28 PM
> On Thu, Mar 25, 2010 at 4:27 PM,
> Chong, Qi Lin Andrew
> <[email protected]>
> wrote:
> > Hello all,
> >
> > I am running an xtfrontier on commercil banks, with
> the cost specification on stata. I have found David
> Drukker's guide to finding the initial value for a frontier
> eqn v. helpful, but he uses the normal specification
> (production and not cost) and also the example is not in
> panel form.
> >
> > http://www.stata.com/statalist/archive/2003-05/msg00650.html
> >
> > QUERY1) My question is how to replicate the above
> steps and find the appropriate inital values for xtfrontier,
> ti cost. I'm not sure how it changes the format above, in
> terms of running a straightforward regression, but using
> >
> > regress logexpense logsum logpdep logpop logdeppop
> logsumdep logsumpop,
> > matrix b0 = e(b), ln(e(rmse)^2) , .1
> >
> > I am left with one missing variable and get the error
> message
> >
> > initial vector: matrix must be dimension 10
> >
> <snip>
>
> With -xtfrontier , ti- there are 3 additional parameters:
> -mu-,
> -lnsigma2-, and -ilgtgamma- and value must be given for
> each of them.
>
> For example:
>
>
> . webuse xtfrontier1
>
> . qui reg lnwidgets lnmachines lnworkers
>
> . matrix b0 = e(b), 1, ln(e(rmse)^2) , .1
>
> . xtfrontier lnwidgets lnmachines lnworkers, ti
> from(b0, copy) nolog
>
> Time-invariant inefficiency model
> Number of obs
> = 948
> Group variable: id
>
> Number of groups =
> 91
>
>
>
> Obs
> per group: min = 6
>
>
>
>
> avg = 10.4
>
>
>
>
> max = 14
>
>
>
> Wald
> chi2(2) =
> 661.76
> Log likelihood = -1472.6069
> Prob >
> chi2 = 0.0000
>
> ------------------------------------------------------------------------------
> lnwidgets |
> Coef. Std. Err. z
> P>|z| [95% Conf.
> Interval]
> -------------+----------------------------------------------------------------
> lnmachines
> | .2904551 .0164219
> 17.69 0.000
> .2582688 .3226415
> lnworkers
> | .2943332 .0154352
> 19.07 0.000
> .2640807 .3245857
> _cons
> | 3.030971 .144102
> 21.03 0.000
> 2.748536 3.313406
> -------------+----------------------------------------------------------------
> /mu
> | 1.125531 .648041
> 1.74 0.082
> -.1446056 2.395668
> /lnsigma2 |
> 1.42203 .2673122
> 5.32 0.000
> .8981073 1.945952
> /ilgtgamma |
> 1.13875 .3563081
> 3.20 0.001
> .440399 1.837101
> -------------+----------------------------------------------------------------
> sigma2
> | 4.145526 1.10815
>
> 2.454952 7.000293
> gamma
> | .7574501 .0654607
>
> .6083541 .8626055
> sigma_u2
> | 3.140029 1.107447
>
> .969473 5.310585
> sigma_v2
> | 1.005497 .0484144
>
> .9106065 1.100387
> ------------------------------------------------------------------------------
>
> Scott
>
> *
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