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st: RE: re: overidentification test and endogeneity test with -ivreg2-


From   "Kelvin Tan" <j.tan@business.uq.edu.au>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: re: overidentification test and endogeneity test with -ivreg2-
Date   Tue, 3 Nov 2009 12:20:20 +1000

Thanks Kit for your helpful insight about the endog test.  

One more question, 

Kit said: "You get different results for the overid test and endog test
in (2)  
because you're using a different VCE. If you use the same VCE they  
agree exactly."

I am sorry for the typo. I meant to have clustered standard errors
"cl(idcode)" in both -ivregress- and -ivreg2- command lines. I get
different results for the overid test and endog test when I used
clustered standard errors in both -ivregress- and -ivreg2-.

************************************************************************
*************
webuse nlswork, clear
ivregress 2sls wks_ue ( tenure = hours c_city  union)  grade, cl(idcode)
estat overid
estat endog
ivreg2  wks_ue ( tenure = hours c_city  union)  grade, endog(tenure)
cl(idcode)
************************************************************************
**************

***************************************************************
Results from -ivregress-
. estat overid
  Test of overidentifying restrictions:
  Score chi2(2)          =  4.32413  (p = 0.1151)

. estat endog
  Tests of endogeneity
  Ho: variables are exogenous
  Robust regression F(1,4007)     =  .195661  (p = 0.6583)
    (Adjusted for 4008 clusters in idcode)
****************************************************************

************************************************************************
*****
Results from -ivreg2- 
------------------------------------------------------------------------
------
Hansen J statistic (overidentification test of all instruments):
3.519
                                                   Chi-sq(2) P-val =
0.1722
-endog- option:
Endogeneity test of endogenous regressors:
0.567
                                                   Chi-sq(1) P-val =
0.4513
Regressors tested:    tenure
------------------------------------------------------------------------
------
************************************************************************
******

Thanks

Regards,
Kelvin

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Kit Baum
Sent: Tuesday, 3 November 2009 11:58 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: re: overidentification test and endogeneity test with
-ivreg2-

<>

You get different results for the overid test and endog test in (2)  
because you're using a different VCE. If you use the same VCE they  
agree exactly.

webuse nlswork, clear
ivregress 2sls wks_ue ( tenure = hours c_city  union)  grade
estat overid
estat endog
ivreg2  wks_ue ( tenure = hours c_city  union)  grade, endog(tenure)

Re (1), ivreg2 without the gmm2s option (that is, 2SLS) bases its  
overid test on the Hansen J statistic from the two-step GMM VCE. The  
endog test is the difference between two Hansen J statistics. Thus it  
does not matter, for the overid test and the endog test, whether you  
estimate the equation with 2SLS or GMM. The coefficient vector and its  
VCE change, of course, but the tests are based on the optimal two-step  
VCE in either case.

Kit Baum   |   Boston College Economics & DIW Berlin   |
http://ideas.repec.org/e/pba1.html
                               An Introduction to Stata Programming   
|   http://www.stata-press.com/books/isp.html
    An Introduction to Modern Econometrics Using Stata  |
http://www.stata-press.com/books/imeus.html

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