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st: endogeneity and overidentification results differ clustered standard errors are used with -ivregress 2SLS- vs -ivreg 2SLS-


From   "Kelvin Tan" <j.tan@business.uq.edu.au>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: endogeneity and overidentification results differ clustered standard errors are used with -ivregress 2SLS- vs -ivreg 2SLS-
Date   Mon, 19 Oct 2009 12:42:18 +1000

Hi, 

I would like to know the reasons why the endogeneity test and
overidentification test results differ after 2SLS estimation with
-ivreg2- and -ivregress-. When GMM estimators are used, both commands
give the same endogeneity and overidentification results.

Here are the codes that I used:

webuse nlswork
sort idcode year
tsset idcode year

ivreg2  wks_ue ( tenure = hours c_city), cl(idcode) endog(tenure)

ivregress 2sls  wks_ue ( tenure = hours c_city), cl(idcode) 
estat endog
estat overid


Results from -ivreg2-
------------------------------------------------------------------------
------
Underidentification test (Kleibergen-Paap rk LM statistic):
201.142
                                                   Chi-sq(2) P-val =
0.0000
------------------------------------------------------------------------
------
Weak identification test (Kleibergen-Paap rk Wald F statistic):
101.210
Stock-Yogo weak ID test critical values: 10% maximal IV size
19.93
                                         15% maximal IV size
11.59
                                         20% maximal IV size
8.75
                                         25% maximal IV size
7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------
------
Hansen J statistic (overidentification test of all instruments):
4.057
                                                   Chi-sq(1) P-val =
0.0440
-endog- option:
Endogeneity test of endogenous regressors:
2.825
                                                   Chi-sq(1) P-val =
0.0928
Regressors tested:    tenure

------------------------------------------------------------------------
------


Results from -ivregress-
. estat endog

  Tests of endogeneity
  Ho: variables are exogenous

  Robust regression F(1,4629)     =  3.59988  (p = 0.0578)
    (Adjusted for 4630 clusters in idcode)

. 
. estat overid

  Test of overidentifying restrictions:

  Score chi2(1)          =  5.30928  (p = 0.0212)



When GMM estimators are used, both commands give the same results. 

ivreg2  wks_ue ( tenure = hours c_city), cl(idcode) endog(tenure) gmm

ivregress gmm wks_ue ( tenure = hours c_city), cl(idcode) 
estat endog
estat overid

Thanks. Please advise me which command to use when clustered standard
errors are used. 


Regards,
Kelvin


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