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Re: st: intreg cluster vs tobit cluster (one reports some missing std errors,
From
[email protected] (Jeff Pitblado, StataCorp LP)
To
[email protected]
Subject
Re: st: intreg cluster vs tobit cluster (one reports some missing std errors,
Date
Fri, 05 Nov 2010 10:52:23 -0500
Leandro Brufman <[email protected]> is getting a missing standard error
from -intreg- with -cluster()- using a dataset that is roughly 98% censored:
> I was running a Tobit model with clustered errors using -intreg
> varlist, clustered(clustervar)- as detailed in here
> (http://www.stata.com/support/faqs/stat/tobit.html). Sometimes the
> standard errors of a couple of coefficients appeared as missing. After
> reading a lot of useful things here in Statalist I couldn't find the
> problem behind those results (for example, I never had 1 observation
> per cluster, which was pointed out as a possible problem by Mark
> Schaefer, I fixed a scale problem in one variable that was driving a
> couple of missing std errors, but not all of them, etc.).
>
> Just by chance I found one article of Woolridge (2006)
> (https://www.msu.edu/~ec/faculty/wooldridge/current%20research/clus1aea.pdf)
> At the end it says that you can run tobit with clustered errors by
> typing -tobit varlist, ll(0) cluster(clustervar)-
> I was just curious about that (I thought that tobit didn't allow
> cluster option). I run it and guess what.... the missing std errors
> dissapeared!
>
> Below you'll see the results. Any ideas of why is this happening????
Leandro's output follows my signature.
We are having trouble reproducing this result. If Leandro will contact me
privately with a copy of the dataset we can look into this more closely.
--Jeff
[email protected]
> *********** BEGIN EXAMPLE **************************
>
> . intreg amt_mt2 amt_mt3 ip_vsam_ipolate_w cridum ccc*, cluster(cricode)
>
> Fitting constant-only model:
>
> Iteration 0: log pseudolikelihood = -8848.0525
> Iteration 1: log pseudolikelihood = -1547.301
> Iteration 2: log pseudolikelihood = -1425.1908
> Iteration 3: log pseudolikelihood = -1407.5083
> Iteration 4: log pseudolikelihood = -1407.1085
> Iteration 5: log pseudolikelihood = -1407.1083
> Iteration 6: log pseudolikelihood = -1407.1083
>
> Fitting full model:
>
> Iteration 0: log pseudolikelihood = -8834.4116
> Iteration 1: log pseudolikelihood = -1526.3341
> Iteration 2: log pseudolikelihood = -1366.9358
> Iteration 3: log pseudolikelihood = -1332.2446
> Iteration 4: log pseudolikelihood = -1331.6778
> Iteration 5: log pseudolikelihood = -1331.6745
> Iteration 6: log pseudolikelihood = -1331.6745
>
> Interval regression Number of obs = 6757
> Wald chi2(11) = 996.00
> Log pseudolikelihood = -1331.6745 Prob > chi2 = 0.0000
>
> (Std. Err. adjusted for 21 clusters in cricode)
> ------------------------------------------------------------------------------
> | Robust
> | Coef. Std. Err. z P>|z| [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> ip_vsam_ip~w | -.0263045 . . . . .
> cridum | -156.2131 50.9088 -3.07 0.002 -255.9925 -56.43371
> ccc1 | 219.9064 70.44264 3.12 0.002 81.84139 357.9715
> ccc2 | 442.6939 147.2167 3.01 0.003 154.1545 731.2333
> ccc3 | 97.37137 32.76476 2.97 0.003 33.15362 161.5891
> ccc4 | 555.3243 185.262 3.00 0.003 192.2175 918.4311
> ccc5 | 421.7124 142.3647 2.96 0.003 142.6827 700.7422
> ccc6 | 269.146 87.67189 3.07 0.002 97.31224 440.9797
> ccc8 | 96.5494 37.97573 2.54 0.011 22.11834 170.9804
> ccc9 | 36.67169 13.64486 2.69 0.007 9.928247 63.41513
> ccc10 | 179.9544 60.99526 2.95 0.003 60.40586 299.5029
> ccc11 | 58.70021 28.58481 2.05 0.040 2.67502 114.7254
> _cons | -300.8123 94.71781 -3.18 0.001 -486.4558 -115.1688
> -------------+----------------------------------------------------------------
> /lnsigma | 4.989588 .3018269 16.53 0.000 4.398018 5.581157
> -------------+----------------------------------------------------------------
> sigma | 146.8758 44.33108 81.28957 265.3786
> ------------------------------------------------------------------------------
>
> Observation summary: 6613 left-censored observations
> 144 uncensored observations
> 0 right-censored observations
> 0 interval observations
>
> . tobit amt_mt3 ip_vsam_ipolate_w cridum ccc*, ll(0) cluster(cricode)
> note: ccc7 dropped because of collinearity
>
> Tobit regression Number of obs = 6757
> F( 12, 6745) = 287.30
> Prob > F = 0.0000
> Log pseudolikelihood = -1331.6745 Pseudo R2 = 0.0536
>
> (Std. Err. adjusted for 21 clusters in cricode)
> ------------------------------------------------------------------------------
> | Robust
> amt_mt3 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> ip_vsam_ip~w | -.0263045 .0088692 -2.97 0.003 -.043691 -.008918
> cridum | -156.2131 50.9064 -3.07 0.002 -256.0057 -56.42051
> ccc1 | 219.9064 70.44073 3.12 0.002 81.82035 357.9925
> ccc2 | 442.6939 147.2129 3.01 0.003 154.1102 731.2777
> ccc3 | 97.37137 32.76389 2.97 0.003 33.1438 161.5989
> ccc4 | 555.3243 185.2573 3.00 0.003 192.1616 918.487
> ccc5 | 421.7124 142.3617 2.96 0.003 142.6385 700.7864
> ccc6 | 269.146 87.66958 3.07 0.002 97.28593 441.006
> ccc8 | 96.5494 37.97516 2.54 0.011 22.10609 170.9927
> ccc9 | 36.67169 13.64448 2.69 0.007 9.924197 63.41918
> ccc10 | 179.9544 60.99367 2.95 0.003 60.38752 299.5212
> ccc11 | 58.70021 28.58445 2.05 0.040 2.665667 114.7348
> _cons | -300.8123 94.71551 -3.18 0.002 -486.4846 -115.14
> -------------+----------------------------------------------------------------
> /sigma | 146.8758 44.33002 59.97501 233.7767
> ------------------------------------------------------------------------------
> Obs. summary: 6613 left-censored observations at amt_mt3<=0
> 144 uncensored observations
> 0 right-censored observations
>
>
> . compare amt_mt2 amt_mt3 // just to show you that the vars are ok,
> amt_mt2 is missing whenever amt_mt3==0, and both are equal otherwise.
>
> ---------- difference ----------
> count minimum average maximum
> ------------------------------------------------------------------------
> amt_mt2=amt_mt3 152
> ----------
> jointly defined 152 0 0 0
> amt_mt2 missing only 6639
> ----------
> total 6791
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