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Re: st: RE: SUR correction for autocorrelation


From   "Dalhia Mani" <dalhia.mani@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: SUR correction for autocorrelation
Date   Sun, 5 Oct 2008 10:41:34 -0500

Benjamin,
Yes. Thanks. This is very helpful.

best
dalhia

On Sun, Oct 5, 2008 at 12:31 AM, Benjamin Villena Roldan
<bvillena@troi.cc.rochester.edu> wrote:
> Hi Dalhia,
> I reread my answers. I'm sorry I wasn't that clear. You could implement
> robust cluster variance estimators in simple regressions
> -regress y x1 x2, robust cluster(gr)-
> The option -cluster- is available in most estimations commands in Stata. The
> cluster variable -gr- defines groups of firms of a similar characteristic.
> The errors are correlated among the cluster, but they are independent across
> clusters. See Wooldridge "Econometric Analysis of Cross-Sectional and Panel
> Data" page 134 for further details.
> Prais-Weinstein is not a good idea because you have to define that some
> firms are "closer"to other in some sense. The correlation among errors
> decays in the "distance" among firms. Unless you have a good reason your
> observations need to be ordered in a very specific way, this procedure
> doesn't make sense. In time series for instance, the time order among
> observations is obvious, so in that case it will work.
> Regarding to the second point, your system is clearly a simultaneous
> equation model, since you have endogenous variables on the right-hand side
> of equations 2 and 3. You need to check your equations are identified before
> running any procedure. This is very important. Any introductory textbook in
> econometrics such as Gujarati or Maddala, could help you to address this
> question.
> After you have done this, you'll need instrumental variables to estimate the
> structural form. Then you have several estimators you could choose from
> two-stage least square (2SLS), three-stage least square (3SLS), and even the
> Limited-information-Max-Likelihood (LIML) which is preferable when you have
> "weak instruments". You could implement these estimators using the Stata
> commands -ivreg- or -ivreg2-.
>
> I hope I was clearer than I was before.
>
> Best,
>
> Benjamin
>
> -----Mensaje original-----
> De: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] En nombre de Dalhia Mani
> Enviado el: Saturday, October 04, 2008 11:43 PM
> Para: statalist@hsphsun2.harvard.edu
> Asunto: Re: st: RE: SUR correction for autocorrelation
>
> Benjamin,
>
> Thanks. This is useful but I'd like to clarify and make sure I
> understand your comments.  I apologize if these are really elementary
> questions. I'm still trying to figure this stuff out.
>
> 1) The data is not time series.  I have data about firms for a single
> time period, and I also have data indicating which firms belong to
> which cluster of firms.  From what I understand, you are suggesting
> that I should use the Prais-Winston command in stata, with a "cluster"
> option?? Did I understand you correctly?
>
> 2) I am a bit confused about whether I should be using SUR or
> simultaneous equations.
> My three equations look something like this:
>  y1=f(X+Z)+e_1
>  y2=g(X+Z)+y1+e_2
> y3=g(X+Z)+y1+y2+e_3
> This set of equations looks like simultaneous equations since
> independent variables in one equation become dependent variables in
> another.  However, I also seem to remember that in cases where all
> equations use the same exogenous variables (X and Z), I should be
> using SUR.
>
> Thanks for your suggestions and help. I appreciate it.
> dalhia
>
>
> On Sat, Oct 4, 2008 at 4:41 PM, Benjamin Villena Roldan
> <bvillena@troi.cc.rochester.edu> wrote:
>> Hi
>> You don't mention whether your data is a cross-section or a panel. That's
>> quite important.
>> Regarding (1) you have clusters of firms, so you can estimate your
> variance
>> matrix using the option cluster. Cochrane-Orcutt works for time
>> autocorrelation, so you need a measure of "proximity"among the firms
> within
>> a cluster. I think you don't have that. In time-series, that measure is
>> given by the time dimension.
>> Regarding (2), I think you need to think carefully about the relationship
>> among your equations. Are you estimating structural or reduced forms
>> equations? For instance, is accounting performance included as a regressor
>> in your stock-market valuation?. If it is you have a simultaneous equation
>> model. If it's not, you're estimating a reduced form, but you have to be
>> very careful about the interpretation of your marginal effects.
>>
>> I hope it helps
>>
>> Benjamin
>>
>> -----Mensaje original-----
>> De: owner-statalist@hsphsun2.harvard.edu
>> [mailto:owner-statalist@hsphsun2.harvard.edu] En nombre de Dalhia Mani
>> Enviado el: Saturday, October 04, 2008 4:48 PM
>> Para: statalist@hsphsun2.harvard.edu
>> Asunto: st: SUR correction for autocorrelation
>>
>> hi,
>>
>> I have a set of equations that specify the relationship between a set
>> of independent variables and outcome variables - survival, stockmarket
>> and accounting performance.  I have two questions that I would
>> appreciate your help with.
>>
>> 1) The data is at the firm level.  Some of the firms belong to
>> clusters of firms, and hence I expect autocorrelation in the residuals
>> when I run each equation separately.  Therefore, I plan to use the the
>> Prais-Winston command, specifying the Cochran-Orcutt option in stata
>> to correct for autocorrelation when running each equation separately.
>> I think this approach is correct, however I am not a 100% sure, and
>> will appreciate it if you think otherwise and can correct me.
>>
>> 2) I also need to use a simultaneous unrelated regression (SUR) model
>> since it is possible that the set of equations are related (e.g.
>> survival might be related to performance).  How do I correct for
>> autocorrelation for the SUR model in stata?
>>
>> Any suggestions and advice will be much appreciated.
>>
>> thanks
>> dalhia
>> *
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>
>
>
> --
> Dalhia Mani
> Department of Sociology
> University of Minnesota
> Office: 1052 Social Sciences
> 267 19th Avenue South, Minneapolis
> MN 55455
> *
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>



-- 
Dalhia Mani
Department of Sociology
University of Minnesota
Office: 1052 Social Sciences
267 19th Avenue South, Minneapolis
MN 55455
*
*   For searches and help try:
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*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/



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