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Re: st: RE: ivreg2 and xtoverid error


From   John Antonakis <[email protected]>
To   [email protected]
Subject   Re: st: RE: ivreg2 and xtoverid error
Date   Sat, 03 Apr 2010 15:46:35 +0200

Hi Mark

Thanks for the note.

I get exactly the same estimates and standard errors with -ivreg- and -ivregress-, with the cluster robust variance estimator. When using -ivreg2- with the -noid- option it works and I get the same estimates; more importantly, I also get the Hansen J-test, which is what interests me most (the -ivregress- estimator does not report an overid for cluster-robust vce's):

Hansen J statistic (overidentification test of all instruments): 402.476, Chi-sq(404) P-val = 0.5121

Note, my estimates make sense and the regressors I expected to be significant are mostly significant. I guess I can assume that my estimates are consistent--and this because the endogeneity test is significant (from -ivregres-), right?

. estat endogenous

 Tests of endogeneity
 Ho: variables are exogenous

 Robust regression F(13,417)     =  119.753  (p = 0.0000)
   (Adjusted for 418 clusters in lead_number)

Best,
J.

____________________________________________________

Prof. John Antonakis, Associate Dean Faculty of Business and Economics
Department of Organizational Behavior
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland

Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305

Faculty page:
http://www.hec.unil.ch/people/jantonakis

Personal page:
http://www.hec.unil.ch/jantonakis
____________________________________________________



On 03.04.2010 15:16, Schaffer, Mark E wrote:
John,

You've got a very large number of instruments (almost 500), but also 13
endogenous regressors.  The under- and weak-id statistics are calculated
by -ranktest-, and it's running of memory because it works with the
reduced form in matrix form (13 first-stage regressions, each with
almost 500 regressors).

If you use the -noid- option, it might address that problem problem (but
you won't get the weak id stats).

The
invsym(): matrix has missing values

is different.  -ivreg2- is having problems inverting this huge Z'Z
matrix  and -ivregress- isn't (I think possibly because the latter uses
a different Mata matrix inversion function).  I do wonder whether the
results you're getting actually make sense.

Have you tried using the old -ivreg-, which uses -regress-?  It is
numerically very stable and accurate.  Does it give the same results as
-ivregress-?

Cheers,
Mark

-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of John Antonakis
Sent: 03 April 2010 01:20
To: [email protected]
Subject: st: ivreg2 and xtoverid error
Hi:

I am running Stata version 11 and have everything up to date.

When running a two-stage model with ivreg2, I get the following error:

. xi: ivreg2 sat (x1-x13=i.lead_n) , cluster(lead_n)
i.lead_number _Ilead_numb_1-484 (naturally coded; _Ilead_numb_1 omitted) quadcross(): 3900 unable to allocate real <tmp>[5421,5421]
                rkstat():     -  function returned error
                 <istmt>:     -  function returned error
r(3900);

If I remove the vce cluster command I get another error:

. xi: ivreg2 y (x1-x13=i.lead_n) ,
i.lead_number _Ilead_numb_1-484 (naturally coded; _Ilead_numb_1 omitted)

invsym(): matrix has missing values

This model is estimated fine with the official -ivregress- command, whether I use a cluster-robust or normal variance estimator, e.g.,

. xi: ivregress 2sls y (x1-x13=i.lead_n) ,cluster(lead_n)
i.lead_number _Ilead_numb_1-484 (naturally coded; _Ilead_numb_1 omitted)

Instrumental variables (2SLS) regression Number of obs = 832
                                                       Wald chi2(13) =
1020.01
Prob > chi2 = 0.0000 R-squared = 0.7020 Root MSE = .2955

                          (Std. Err. adjusted for 418 clusters in
lead_number)
--------------------------------------------------------------
----------------
             |               Robust
y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+------------------------------------------------
----------
-------------+------
x1 | .3849406 .0509433 7.56 0.000 .2850935 .4847877 x2 | -.0452167 .0541093 -0.84 0.403 -.1512689 .0608355 x3 | -.0214062 .0392473 -0.55 0.585 -.0983295 .0555171 x4 | .0743079 .0528296 1.41 0.160 -.0292363 .177852 x5 | .1559398 .056997 2.74 0.006 .0442276 .2676519 x6 | .168241 .0577832 2.91 0.004 .0549879 .281494 x7 | -.1359489 .0290323 -4.68 0.000 -.1928512 -.0790465 x8 | .0485811 .0358857 1.35 0.176 -.0217535 .1189157 x9 | -.1772587 .0512706 -3.46 0.001 -.2777472 -.0767701 x10 | .1785753 .0570718 3.13 0.002 .0667166 .2904339 x11 | .0309138 .0533183 0.58 0.562 -.0735883 .1354158 x12 | .2282491 .0554658 4.12 0.000 .1195381 .33696 x13 | -.0723148 .0486346 -1.49 0.137 -.1676369 .0230072 _cons | .4183937 .1616004 2.59 0.010 .1016627 .7351247
--------------------------------------------------------------
----------------
Instrumented:  x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13
Instruments:   _Ilead_numb_2 _Ilead_numb_3 _Ilead_numb_4 _Ilead_numb_5
[output snipped]


Interestingly, when I run it with -xtivreg-, the model is estimated fine; however, -xtoverid- gives me the following error:

. xtoverid
invsym(): matrix has missing values
r(504);

This is the same error that follows ivreg2 estimation.

I suspect it might have something to do with the fact that I have a large number of instruments (fixed-effects, with 483 dummies) and clustering on those fixed-effects.

Best,
John.

--
____________________________________________________

Prof. John Antonakis, Associate Dean
Faculty of Business and Economics
Department of Organizational Behavior
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland

Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305

Faculty page:
http://www.hec.unil.ch/people/jantonakis

Personal page:
http://www.hec.unil.ch/jantonakis
____________________________________________________


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