Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
"Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: 2nd Step GMM estimation with nonlinear endogenous regressors is biased? |

Date |
Thu, 16 Dec 2010 17:35:27 -0000 |

Jordana, > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of > Jordana Rodrigues Cunha > Sent: 14 December 2010 15:24 > To: statalist@hsphsun2.harvard.edu > Subject: st: 2nd Step GMM estimation with nonlinear > endogenous regressors is biased? > > Dear all, > I need to test the endogeneity of two regressors (a > dichotomous and an ordinal ranked in five levels ) in a > single equation model with a continuous dependent variable. I > would like to confirm if I could do this using the amazing > GMM option of ivreg2. Thanks for the kind words. Or did you mean a new kind of GMM estimator? 2-step efficient GMM, continuously updated GMM, amazing GMM.... > As I am not interested in estimating > the full system of equations (fitting in the first stage, in > this case a probit and an ordinal probit and in the 2nd stage > an OLS), I don't need to give the correct functional form of > my regressors in the first stage, do I? Correct. ivreg2 estimates single-equation ("limited information") models only. Adding functional form assumptions for the first stage is akin to estimation a system of two equations (a "full information" setup) where you have to specify both equations correctly. > I explain: > > All the tests for underidentification (I am using clustered > robust errors) and the J Hansen shows that if I need to > instrumentalize my regressors I would be able to do it, even > if my endog results confirms that my regressors are not > endogenous and in this way, seems that my OLS results are > more efficient. I had to read this a couple of times but I think I understand: the equation isn't underidentified; the overidentifying restrictions are apparently valid; and an endogeneity test fails to reject the hypothesis that your endogeneous regressors are actually exogenous. > My point, than, is: > > The parameters estimated in the 2nd stage GMM are not > significative for the tested regressors, but those in the OLS > are... This is quite possible. OLS is more efficient than 2-step GMM, so the standard errors are smaller and the estimates are more precise. > While the assumption of a linear relationship between > the dependents and independents variables in my 2 first stage > models is violated, Not true. There is no such linearity assumption. You're using a single-equation, limited-information setup precisely so that you don't have to make such assumptions. The tradeoff is that your results are more robust but not as efficient vs. using a system estimator. This is basically what you yourself say above. > they recover correct standard errors that > will be applied in the second stage, when I need to good > estimates. Am I right? The parameters estimated with the 2nd > step GMM could be biased after the assumption of linear form > in my first stage "Bias" is the wrong word - you mean "inconsistent". And no, your second-stage estimates are consistent, because there is no linear functional form assumption for the first stage - see above. Best wishes, Mark > and I can believe in the results in my OLS, > or the parameters estimated with ivreg2 GMM are better? > Any help will be appreciate, thank you very much, > > jordana > > > Jordana Rodrigues Cunha > PhD. Candidate > University of Bologna > Department of Management > Via Capo di Lucca, 34, 1st floor > 40126 - Bologna, ITALY > Fixed line: 0039 (051) 20 98 073 > Fax: 0039 (051) 20 98 074 > jordana.rodrigues@unibo.it > www.sa.unibo.it > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > -- Heriot-Watt University is a Scottish charity registered under charity number SC000278. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**st: R: 2nd Step GMM estimation with nonlinear endogenous regressors is biased?***From:*Jordana Rodrigues Cunha <jordana.rodrigues@unibo.it>

**References**:**st: 2nd Step GMM estimation with nonlinear endogenous regressors is biased?***From:*Jordana Rodrigues Cunha <jordana.rodrigues@unibo.it>

- Prev by Date:
**Re: st: xtnbreg, nbreg, and tests of assumptions** - Next by Date:
**st: RE: comparing different means using ttest** - Previous by thread:
**st: 2nd Step GMM estimation with nonlinear endogenous regressors is biased?** - Next by thread:
**st: R: 2nd Step GMM estimation with nonlinear endogenous regressors is biased?** - Index(es):