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RE: st: RE: Results of overidentification and underidentification test missing


From   "Schaffer, Mark E" <[email protected]>
To   "[email protected]" <[email protected]>
Subject   RE: st: RE: Results of overidentification and underidentification test missing
Date   Mon, 23 Sep 2013 17:46:51 +0000

Sutirtha,

There's something fishy about your installation of xtivreg2/ivreg2.  The output you supplied includes this:

Summary results for first-stage regressions
-------------------------------------------
Variable    | Shea Partial R2 |   Partial R2    |  F(  2,    64)    P-value
average_shar|     0.0327      |     0.0327      |        5.50       0.0062

but the most up-to-date versions of xtivreg2/ivreg2 would have output that looks like this:

Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  3,    70)  P-val | AP Chi-sq(  3) P-val | AP F(  3,    70)
mpg          |      44.47    0.0000 |      141.03   0.0000 |       44.47

I suspect you have more than one version of ivreg2/xtivreg2 installed on your machine, and Stata is making use of the wrong (=older) version(s).

Try doing this:

which ivreg2, all
which xtivreg2, all
which ranktest, all

and see if this is the problem.  If it is, uninstall the older versions and see if this solves the problem.

--Mark

> -----Original Message-----
> From: [email protected] [mailto:owner-
> [email protected]] On Behalf Of Sutirtha Bagchi
> Sent: 23 September 2013 14:54
> To: [email protected]
> Subject: Re: st: RE: Results of overidentification and underidentification test
> missing
> 
> For ivreg2, this is what I have:
> 
> ivreg2 3.1.07  28Jul2013
> 
> Sutirtha
> 
> On Sun, Sep 22, 2013 at 7:26 PM, Sutirtha Bagchi <[email protected]>
> wrote:
> > I did have a chance to update xtivreg2 and ranktest to the most
> > current version and that solved the problem. The versions I now have
> > are:
> >
> > . which xtivreg2, all
> >
> > c:\ado\plus\x\xtivreg2.ado
> > *! xtivreg2 1.0.13 28Aug2011
> > *! author mes
> >
> > . which ranktest, all
> >
> > c:\ado\plus\r\ranktest.ado
> > *! ranktest 1.3.02  27Feb2012
> > *! author mes, based on code by fk
> > *! see end of file for version comments
> >
> > Thanks,
> > Sutirtha
> >
> > On Sun, Sep 22, 2013 at 5:19 PM, Sutirtha Bagchi <[email protected]>
> wrote:
> >> Hello Mark,
> >>
> >> Thanks for responding. This is what I have:
> >>
> >> xtivreg2: xtivreg2 1.0.13 28Aug2011
> >>
> >> ranktest: ranktest 1.1.02  15oct2007
> >>
> >> Thanks,
> >> Sutirtha
> >>
> >> On Sun, Sep 22, 2013 at 1:55 PM, Schaffer, Mark E
> <[email protected]> wrote:
> >>> Sutirtha,
> >>>
> >>> Can you also tell us what versions of ivreg2 and ranktest you have
> installed?  xtivreg2 uses these programs.
> >>>
> >>> --Mark
> >>>
> >>>> -----Original Message-----
> >>>> From: [email protected] [mailto:owner-
> >>>> [email protected]] On Behalf Of Sutirtha Bagchi
> >>>> Sent: 21 September 2013 22:56
> >>>> To: [email protected]
> >>>> Subject: st: Results of overidentification and underidentification
> >>>> test missing
> >>>>
> >>>> Hello,
> >>>>
> >>>> I am using the user-written command -xtivreg2- in Stata11 (Stata/SE
> >>>> 11.2 for Windows (32-bit)).
> >>>>
> >>>> (*! xtivreg2 1.0.13 28Aug2011 *! author mes)
> >>>>
> >>>> The issue I am facing is that in the Stata output, I find the
> >>>> results of the Under identification and Weak Identification test
> >>>> missing. In particular, the Kleibergen-Paap rk LM statistic and
> >>>> associated p-value and the Kleibergen-Paap rk Wald F statistic are
> >>>> missing. Other test statistics such as the Hansen J statistic for
> overidentification and the Shea partial R2 are present in the output.
> >>>> I can verify that I have updated Stata and so that alone is
> >>>> unlikely to fix this issue for me.
> >>>>
> >>>>  Here are details of my data set on municipal pension plans where
> >>>> this comes up.
> >>>>
> >>>> I have one observation per pension plan per municipality per time
> >>>> period (decade). For simplicity, let us say, I have 2 pension plans
> >>>> per municipality for ~
> >>>> 1,000 municipalities for 3 decades - a total of
> >>>> 2 X 1,000 X 3 or ~ 6,000 observations. I am looking at the effect
> >>>> of political orientation of the municipality (more specifically,
> >>>> the independent variable is average Democratic vote share in
> >>>> mayoral elections held in the last decade) on a measure of funding for
> the pension plans offered by that municipality.
> >>>> However, I am concerned about the possible endogeneity of the
> >>>> independent variable and I therefore use demographic
> >>>> characteristics (percent of the population that is self-employed
> >>>> and percent of the population that has a
> >>>> disability) as instruments for the independent variable. As it
> >>>> turns out, Democratic vote share goes up when the  percent of the
> >>>> population that is self- employed goes down or when the percent of
> >>>> the population that has a disability goes up.
> >>>>
> >>>> The Stata command I use is:
> >>>>
> >>>> xi: xtivreg2 wmeanactfundratio_emplgrp2
> (average_share_dems_votes7
> >>>> = pctslfemplydownbiznotincp pctpop16to64wdisability)
> >>>> i.currentdecade, fe gmm2s first cluster(county)
> >>>>
> >>>> where wmeanactfundratio_emplgrp2 = Mean funding ratio of pension
> >>>> plan offered by a municipality for a particular employee group
> >>>> (with the mean being taken over a decade);
> >>>> average_share_dems_votes7 = Average Democratic vote share for
> >>>> mayoral races held in the last decade; pctslfemployedownbiznotincp
> >>>> = Percent of the population that is self-employed;
> >>>> pctpop16to64wdisability = Percent of the population between 16 to
> >>>> 64 that has a disability; i.currentdecade is a set of dummy
> >>>> variables for the decade; and finally, county - These 1,000
> >>>> municipalities can belong to one of ~ 65 counties. Clustering standard
> errors at the county level is the most conservative and so I go with that.
> >>>>
> >>>>
> >>>> Here is the output:
> >>>>
> >>>> Warning - singleton groups detected.  117 observation(s) not used.
> >>>> FIXED EFFECTS ESTIMATION
> >>>>
> >>>> ------------------------
> >>>>
> >>>> Number of groups =      1135               Obs per group: min =         2
> >>>>
> >>>>                                                             avg =       4.6
> >>>>
> >>>>                                                             max =         9
> >>>>
> >>>>  First-stage regressions
> >>>>
> >>>> -----------------------
> >>>>
> >>>>  First-stage regression of average_share_dems_votes7:
> >>>>
> >>>>  FIXED EFFECTS ESTIMATION
> >>>>
> >>>> ------------------------
> >>>>
> >>>> Number of groups =      1135              Obs per group: min =         2
> >>>>
> >>>>                                                            avg =       4.6
> >>>>
> >>>>                                                            max =         9
> >>>>
> >>>>  OLS estimation
> >>>>
> >>>> --------------
> >>>>
> >>>>  Estimates efficient for homoskedasticity only
> >>>>
> >>>> Statistics robust to heteroskedasticity and clustering on county
> >>>>
> >>>>  Number of clusters (county) = 65                      Number of obs =     5253
> >>>>
> >>>>
> >>>>     F(  4,    64) =     8.95
> >>>>
> >>>>
> >>>>     Prob > F      =   0.0000
> >>>>
> >>>> Total (centered) SS     =  9.605866911             Centered R2   =   0.2599
> >>>> Total (uncentered) SS   =  9.605866911           Uncentered R2 =   0.2599
> >>>> Residual SS             =  7.109186342                 Root MSE      =   .04157
> >>>>
> >>>>
> >>>> -------------------------------------------------------------------
> >>>> -----------
> >>>>
> >>>>              |               Robust
> >>>>
> >>>> average_s~s7 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
> >>>>
> >>>> -------------+-----------------------------------------------------
> >>>> -------------+-----
> >>>> -------------+------
> >>>>
> >>>> _Icurre~1990 |   .0355722   .0077302     4.60   0.000     .0201294     .051015
> >>>>
> >>>> _Icurre~2000 |   .0432069   .0122536     3.53   0.001     .0187274    .0676864
> >>>>
> >>>> pctslfempl~p |  -.0001385   .0007944    -0.17   0.862    -.0017255    .0014485
> >>>>
> >>>> pctpop16to~y |   .0040835   .0013014     3.14   0.003     .0014837    .0066832
> >>>>
> >>>> -------------------------------------------------------------------
> >>>> -----------
> >>>>
> >>>> Included instruments: _Icurrentde_1990 _Icurrentde_2000
> >>>>
> >>>> pctslfemplydownbiznotincp pctpop16to64wdisability
> >>>>
> >>>> ------------------------------------------------------------------------------
> >>>> Partial R-squared of excluded instruments:   0.0327
> >>>> Test of excluded instruments:
> >>>> F(  2,    64) =     5.50
> >>>> Prob > F      =   0.0062
> >>>>
> >>>> Summary results for first-stage regressions
> >>>> -------------------------------------------
> >>>>
> >>>> Variable    | Shea Partial R2 |   Partial R2    |  F(  2,    64)    P-value
> >>>>
> >>>> average_shar|     0.0327      |     0.0327      |        5.50       0.0062
> >>>>
> >>>> NB: first-stage F-stat cluster-robust
> >>>>
> >>>> Underidentification tests
> >>>>
> >>>> Ho: matrix of reduced form coefficients has rank=K1-1
> >>>> (underidentified)
> >>>>
> >>>> Ha: matrix has rank=K1 (identified)
> >>>>
> >>>> Kleibergen-Paap rk LM statistic             Chi-sq(2)=.        P-val=     .
> >>>>
> >>>> Kleibergen-Paap rk Wald statistic          Chi-sq(2)=.        P-val=     .
> >>>>
> >>>>  Weak identification test
> >>>>
> >>>> Ho: equation is weakly identified
> >>>>
> >>>> Kleibergen-Paap Wald rk F statistic                    .
> >>>>
> >>>> See main output for Cragg-Donald weak id test critical values
> >>>>
> >>>>  Weak-instrument-robust inference
> >>>>
> >>>> Tests of joint significance of endogenous regressors B1 in main
> >>>> equation
> >>>>
> >>>> Ho: B1=0 and overidentifying restrictions are valid
> >>>>
> >>>> Anderson-Rubin Wald test     F(2,64)=  0.92      P-val=0.4038
> >>>>
> >>>> Anderson-Rubin Wald test     Chi-sq(2)=1.87     P-val=0.3927
> >>>>
> >>>> Stock-Wright LM S statistic  Chi-sq(2)=1.87       P-val=0.3927
> >>>>
> >>>> NB: Underidentification, weak identification and
> >>>> weak-identification-robust test statistics cluster-robust
> >>>>
> >>>> Number of clusters                      N_clust  =         65
> >>>>
> >>>> Number of observations              N           =       5253
> >>>>
> >>>> Number of regressors                 K           =          3
> >>>>
> >>>> Number of instruments                L           =          4
> >>>>
> >>>> Number of excluded instruments  L1        =          2
> >>>>
> >>>>  2-Step GMM estimation
> >>>>
> >>>> ---------------------
> >>>>
> >>>>  Estimates efficient for arbitrary heteroskedasticity and
> >>>> clustering on county
> >>>>
> >>>> Statistics robust to heteroskedasticity and clustering on county
> >>>>
> >>>>  Number of clusters (county) = 65   Number of obs =     5253
> >>>>
> >>>>                                                        F(  3,    64) =    14.86
> >>>>
> >>>>                                                        Prob > F      =   0.0000
> >>>>
> >>>> Total (centered) SS     =  29430177.08            Centered R2   =   0.0334
> >>>>
> >>>> Total (uncentered) SS   =  29430177.08          Uncentered R2 =   0.0334
> >>>>
> >>>> Residual SS             =  28447688.07                Root MSE      =    83.12
> >>>>
> >>>>
> >>>> -------------------------------------------------------------------
> >>>> -----------
> >>>>
> >>>>              |               Robust
> >>>>
> >>>> wmeanactfu~2 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
> >>>>
> >>>> -------------+-----------------------------------------------------
> >>>> -------------+-----
> >>>> -------------+------
> >>>>
> >>>> average_s~s7 |   209.2071   159.7796     1.31   0.190    -103.9552    522.3693
> >>>>
> >>>> _Icurre~1990 |  -30.10698   9.738608    -3.09   0.002    -49.19431   -
> 11.01966
> >>>>
> >>>> _Icurre~2000 |   -47.3599   11.90716    -3.98   0.000     -70.6975    -24.0223
> >>>>
> >>>> -------------------------------------------------------------------
> >>>> -----------
> >>>>
> >>>> Underidentification test (Kleibergen-Paap rk LM statistic):                  .
> >>>>
> >>>>                                                    Chi-sq(2) P-val =         .
> >>>>
> >>>> -------------------------------------------------------------------
> >>>> -----------
> >>>>
> >>>> Weak identification test (Kleibergen-Paap rk Wald F statistic):              .
> >>>>
> >>>> 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):         0.017
> >>>>
> >>>>
> >>>> Chi-sq(1) P-val =    0.8959
> >>>>
> >>>> -------------------------------------------------------------------
> >>>> -----------
> >>>>
> >>>> Instrumented:         average_share_dems_votes7
> >>>>
> >>>> Included instruments: _Icurrentde_1990 _Icurrentde_2000
> >>>>
> >>>> Excluded instruments: pctslfemplydownbiznotincp
> >>>> pctpop16to64wdisability
> >>>>
> >>>> -------------------------------------------------------------------
> >>>> -----------
> >>>>
> >>>> Please let me know if you need any further details. Thanks for any
> >>>> and all suggestions,
> >>>>
> >>>> Sutirtha Bagchi
> >>>>
> >>>> *
> >>>> *   For searches and help try:
> >>>> *   http://www.stata.com/help.cgi?search
> >>>> *   http://www.stata.com/support/faqs/resources/statalist-faq/
> >>>> *   http://www.ats.ucla.edu/stat/stata/
> >>>



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