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Re: st: RE: intreg with fixed effects and clustered standard errors


From   Pamela Campa <pamela.campa@iies.su.se>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: intreg with fixed effects and clustered standard errors
Date   Wed, 29 Feb 2012 20:21:45 +0100

Thanks for your reply

If I use intreg it does not estimate some standard errors. The data are on log emissions; for most of the plants I have point data, but for plants that release substances below a certain level I have interval-coded data. This is how the output looks like:

. xi: intreg llnemissions ulnemissions L1lndistance_year lidensity_bu5 industry_id1-industry_id20 industry_id22-industry_id64 i.countyid if year>=2001, vce(cluster firm_code) i.countyid _Icountyid_1-1568 (_Icountyid_1 for coun~id==01001 omitted)
note: industry_id35 omitted because of collinearity
note: industry_id36 omitted because of collinearity
note: industry_id38 omitted because of collinearity
note: industry_id39 omitted because of collinearity
note: industry_id41 omitted because of collinearity
note: industry_id42 omitted because of collinearity
note: industry_id46 omitted because of collinearity
note: industry_id49 omitted because of collinearity
note: industry_id54 omitted because of collinearity
note: industry_id55 omitted because of collinearity
note: industry_id56 omitted because of collinearity
note: industry_id61 omitted because of collinearity
note: _Icountyid_1232 omitted because of collinearity
note: _Icountyid_1373 omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -421061.15
Iteration 1:   log pseudolikelihood = -420990.91
Iteration 2:   log pseudolikelihood = -420990.91

Fitting full model:

Iteration 0:   log pseudolikelihood = -407783.52
Iteration 1:   log pseudolikelihood = -407606.27
Iteration 2:   log pseudolikelihood = -407606.26

Interval regression                         Number of obs   =   134769
                                            Wald chi2(1574) =       0.00
Log pseudolikelihood = -407606.26           Prob > chi2     =     1.0000

(Std. Err. adjusted for 24839 clusters in firm_code)
------------------------------------------------------------------------------
             |               Robust
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
L1lndistan~r | -.0103242 . . . . . lidensity_~5 | -.4127465 . . . . . and the standard errors are also not estimated for some industry and county fixed effects

Thanks
Pamela





On 2/29/2012 6:36 PM, Nick Cox wrote:
-intreg2- qualifies as user-written; you are asked to specify this.

However, in this particular case hasn't the functionality been folded into -intreg-?

That aside, you are asking for guidance on a key issue without telling us anything precise about the data or showing any output.

Nick
n.j.cox@durham.ac.uk

Pamela Campa

I'm trying to estimate a regression model with an interval-coded
dependent variable. I have plant-level data for several years, and I
regress an interval coded dependent variable on some continuous  X's,
industry and county fixed effects, and state by year shocks.

I cluster the standard errors by plant. I use the command intreg2. The
Stata output gives standard errors for all the variables I put in, but
it does not show the Wald chi(2) statistic. I did try to remove plants
that appear only once in the dataset, counties for which there is only
one plant and industries for which there is only one plant, but that
does not fix the problem.

Could anyone please suggest a way to deal with this?I'm not necessarily
interested in the Wald chi(2) , but I'm afraid that the fact that it is
missing signals some misspecification in my model.

Moreover, my pseudo likelihood is as low as -590000. Is that worrisome?


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