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

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

From |
Bond Tiger <bond0910@ymail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: st. Simultaneous Equations Model & GMM Estimation |

Date |
Sat, 17 Jul 2010 13:30:53 -0700 (PDT) |

Hello All, It would be extremely helpful if you could guide me on the following matter: I am using a simultaneous equations model and IV-GMM estimation technique (2-step GMM or continuously updated GMM) to estimate the following equations: (1) Y1=a0+a1*Y2+a2*K+E1, (2) Y2=b0+b1*Y1+b2*L+E2, L & K are other exogenous variables and E1 & E2 are independent errors. Y2 is the regressor in (1) & Y1 is the regressor in (2). (I am using a cross-section data.) I will estimate my model using both the equations simultaneously (NOT single equation estimation). However, in order to test the instruments for each of my regressor (Y1 and Y2), I am using single equation setup (one equation at a time).The set of IVs for Y1 and Y2 are different (containing different instruments) and both the sets are passing the orthogonality conditions, overidentifying restriction test and weak identification tests in the single equation setup, implying that my IVs are relevant and can very well identify the equations. In the single equation setup, I have also tested for endogeneity of my regressors (Y1 & Y2) and found neither of the regressor to be endogenous in the single equation setup. Now, my actual model is a SIMULTANEOUS EQUATION model where I am trying to estimate both the equations jointly. In the simultaneous equation model my regressors are endogenous by model specification, therefore, I am using IV-GMM estimation (i.e. instrumental variable GMM technique). Also in my model, I could detect the presence of heteroskedasticity and therefore GMM is more efficient than 2SLS. So my questions are: (A) Can I test the IVs in a single equation setup (where neither of the regressor is endogenous) and then use those instruments in jointly estimating the 2 equations in the simultaneous equations framework? (B) Is there any way I can test the IVs in a simultaneous equations setup (using both the equations)? If yes, could you advice me some references or codes in STATA or SAS or MATLAB. (C) Can I use instrumental variable GMM to estimate the simultaneous equations model in which the regressors are endogenous by model specification? It would be really helpful if anybody can provide some advice & references. I will greatly appreciate your help. Regards, Bond * * 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/

- Prev by Date:
**st: AW: Re: AW: treatment effect estimation with an ordinal 1st step and a continuous 2nd step** - Next by Date:
**st: AW: Re: AW: treatment effect estimation with an ordinal 1st step and a continuous 2nd step** - Previous by thread:
**st: kapetanois codes** - Next by thread:
**Re: st: st. Simultaneous Equations Model & GMM Estimation** - Index(es):