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From |
Kit Baum <baum@bc.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: re: ivreg2: No validity tests if just-identified? |

Date |
Sat, 18 Apr 2009 09:06:00 -0400 |

<> I can reproduce the results below with

use http://fmwww.bc.edu/ec-p/data/hayashi/griliches76.dta ivreg2 lw s expr (iq=med), endog(iq) liml first

Kit Baum | Boston College Economics & DIW Berlin | http://ideas.repec.org/e/pba1.html

An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html On Apr 18, 2009, at 02:33 , John wrote:

Thanks for the note. I like the endog option and I see what yourendogtest is doing--it seems to me that it is constraining the residualcovariance to zero (this is what I meant by overidentifying test--whichI see is not one in the classical sense). As for constraining the residuals I can accomplish this (and obtain a similar result to what your endog test does) using Mplus to estimate the system of equations you note below. The estimator is maximum likelihood estimation. Estimating the covariance I obtain: Estimate S.E. Est./S.E. P-Value IQ ON S 2.876 0.205 14.022 0.000 EXPR -0.239 0.207 -1.153 0.249 MED 0.482 0.164 2.935 0.003 Cons 60.467 2.913 20.759 0.000 LW ON IQ 0.022 0.012 1.815 0.070 S 0.040 0.038 1.050 0.294 EXPR 0.051 0.008 6.280 0.000 Cons 2.789 0.771 3.618 0.000 Note: I explicitly correlated the residuals of IQ and LW and obtained: LW WITH IQ -2.412 1.638 -1.472 0.141 (this residual covariance is not different from zero) Also, the model is just-identified, just as in ivreg2: TESTS OF MODEL FIT Chi-Square Test of Model Fit Value 0.000 Degrees of Freedom 0 P-Value 0.0000These estimates are pretty much the same as the ivreg2 estimatesfrom Stata.Now, when I constrain the covariance between the two error terms oftheendogenous variables to be to be zero, I have what I termed "an overidentifying restriction": TESTS OF MODEL FIT Chi-Square Test of Model Fit Value 2.914 Degrees of Freedom 1 P-Value 0.0878 This test is is about the same as your endog test: Endogeneity test of endogenous regressors: 2.909 Chi-sq(1) P-val = 0.0881 Thus, in this case, the test cannot reject the null.

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**Follow-Ups**:**Re: st: re: ivreg2: No validity tests if just-identified?***From:*John Antonakis <john.antonakis@unil.ch>

**Re: st: re: ivreg2: No validity tests if just-identified?***From:*John Antonakis <john.antonakis@unil.ch>

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