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Re: st: RE: Results of overidentification and underidentification test missing
From
Sutirtha Bagchi <[email protected]>
To
[email protected]
Subject
Re: st: RE: Results of overidentification and underidentification test missing
Date
Mon, 23 Sep 2013 09:53:46 -0400
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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>>> * For searches and help try:
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>>
>>
>>
>> --
>> PhD Candidate, Business Economics,
>> Stephen M. Ross School of Business,
>> University of Michigan, Ann Arbor.
>> http://sitemaker.umich.edu/sbagchi/home
>
>
>
> --
> PhD Candidate, Business Economics,
> Stephen M. Ross School of Business,
> University of Michigan, Ann Arbor.
> http://sitemaker.umich.edu/sbagchi/home
--
PhD Candidate, Business Economics,
Stephen M. Ross School of Business,
University of Michigan, Ann Arbor.
http://sitemaker.umich.edu/sbagchi/home
*
* 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/