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From |
Stas Kolenikov <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Wed, 29 Feb 2012 19:28:16 -0500 |

In all likelihood, you still have confounded effects of industry, county and firm that effectively eliminate a firm effect. To find yet another dummy to drop, you can try something like foreach x of varlist industry_id* { qui regress `x' i.county*firm_code if e(r2) == 1 d `x' } to find out where you have perfect prediction. On Wed, Feb 29, 2012 at 2:21 PM, Pamela Campa <pamela.campa@iies.su.se> wrote: > 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? >> >> >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ > > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: intreg with fixed effects and clustered standard errors***From:*Pamela Campa <pamela.campa@iies.su.se>

**st: RE: intreg with fixed effects and clustered standard errors***From:*Nick Cox <n.j.cox@durham.ac.uk>

**Re: st: RE: intreg with fixed effects and clustered standard errors***From:*Pamela Campa <pamela.campa@iies.su.se>

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