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RE: st: strong instruments
From
Cameron McIntosh <[email protected]>
To
STATA LIST <[email protected]>
Subject
RE: st: strong instruments
Date
Mon, 7 Nov 2011 22:31:29 -0500
It shouldn't be too difficult -- those would just be instruments that have high correlations with the endogenous regressors.
Murray, M.P. (2006). Avoiding Invalid Instruments and Coping with Weak Instruments. Journal of Economic Perspectives, 20(4), 111-132.http://www.eui.eu/Personal/Guiso/Courses/Econometrics/Murray_IV_jep_06.pdf
But you say you did not get significant results with 2SLS or ivreg2... perhaps when you use the simultaneous equation approach you may be observing suppression effects. How do the the path coefficients compare to the zero-order correlations?
Shieh, G. (2006). Suppression situations in multiple linear regression. Educational and Psychological Measurement, 66(3), 435-447.
Maassen, G.H., & Bakker, A.B. (2001). Suppressor variables in path models: definitions and interpretations. Sociological Methods & Research, 30(2), 241-270.http://www.beanmanaged.eu/pdf/articles/arnoldbakker/article_arnold_bakker_64.pdf
Cam
> From: [email protected]
> To: [email protected]
> Subject: st: strong instruments
> Date: Mon, 7 Nov 2011 21:06:13 -0500
>
> I'm running a 3sls model (I tried ivreg2 or 2sls, and I didn't get
> significant results) , and I wondering if my instruments are strong. Can we
> just see it with the output results?
> as example: pdvavg4 is an instrument for j30f. we see that pdvavg4 is
> significant. It is enough to say that pdvavg4 is a strong instrument?
> thanks
>
> reg3 (emploi: emploi = j30f j30b) (j30b = taxeavg4 b5 a2 b2a b2b
> b2c a4a a7 a6a ) (j30f = pdvavg4 b5 a2
> b2a b2b b2c a4a a7 a6
> > a)
>
> Three-stage least-squares regression
> ----------------------------------------------------------------------
> Equation Obs Parms RMSE "R-sq" chi2 P
> ----------------------------------------------------------------------
> emploi 131 2 .4052919 -0.1658 3.45 0.1784
> j30b 131 8 .9394929 0.2112 37.17 0.0000
> j30f 131 8 .9930078 0.2500 45.75 0.0000
> ----------------------------------------------------------------------
>
> ----------------------------------------------------------------------------
> --
> | Coef. Std. Err. z P>|z| [95% Conf.
> Interval]
> -------------+--------------------------------------------------------------
> --
> emploi |
> j30f | -.0895928 .0645908 -1.39 0.165 -.2161883
> .0370028
> j30b | .1245075 .0755103 1.65 0.099 -.02349
> .272505
> _cons | .0341791 .2257434 0.15 0.880 -.4082698
> .4766279
> -------------+--------------------------------------------------------------
> --
> j30b |
> taxeavg4 | .9566036 .1901856 5.03 0.000 .5838467
> 1.32936
> b5 | .011787 .0073776 1.60 0.110 -.0026729
> .0262469
> a2 | -.004885 .15014 -0.03 0.974 -.299154
> .289384
> b2a | .0032782 .0052013 0.63 0.529 -.0069162
> .0134726
> b2b | .004151 .0063073 0.66 0.510 -.008211
> .016513
> b2c | -.0580875 .0315122 -1.84 0.065 -.1198504
> .0036753
> a4a | -.0025426 .0044695 -0.57 0.569 -.0113026
> .0062174
> a7 | .0132198 .2282933 0.06 0.954 -.4342267
> .4606664
> a6a | (omitted)
> _cons | -23.56414 14.58883 -1.62 0.106 -52.15771
> 5.02944
> -------------+--------------------------------------------------------------
> --
> j30f |
> pdvavg4 | .9825736 .1833886 5.36 0.000 .6231387
> 1.342009
> b5 | -.0090748 .0077313 -1.17 0.240 -.0242279
> .0060782
> a2 | -.0717486 .1705269 -0.42 0.674 -.4059751
> .2624778
> b2a | -.0106844 .0054099 -1.97 0.048 -.0212877
> -.0000812
> b2b | -.0118935 .0065061 -1.83 0.068 -.0246453
> .0008583
> b2c | -.109557 .0328635 -3.33 0.001 -.1739684
> -.0451457
> a4a | -.0003704 .004611 -0.08 0.936 -.0094079
> .0086671
> a7 | .1681194 .237539 0.71 0.479 -.2974484
> .6336873
> a6a | (omitted)
> _cons | 19.01283 15.26012 1.25 0.213 -10.89645
> 48.92212
> ----------------------------------------------------------------------------
> --
> Endogenous variables: emploi j30b j30f
> Exogenous variables: taxeavg4 b5 a2 b2a b2b b2c a4a a7 a6a pdvavg4
> ---------------------------------------
>
>
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