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From |
Woolton Lee <finished07@gmail.com> |

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

Subject |
st: question concerning generalized hausman test for clustered std errs using SUEST, regress and ivregress |

Date |
Wed, 17 Mar 2010 21:22:58 -0400 |

Hello, I am trying to compute a Hausman test between two models both adjusted for clustering for patient zip codes. One model is simple OLS, the other is IV where one variable has been instrumented. I have tried to obtain this using the SUEST procedure, but I am finding a problem with the patient zip code clustered standard errors for the IV estimates obtained from the SUEST procedure (which are clearly wrong). I estimate the first and second stage regression both via OLS because SUEST will not accept the variance covariance matrix from IVREGRESS (I keep getting an error indicating the model ..."was estimated with a non-standard vce (unadjusted)" - this is even when I set the VCE option in IVREGRESS to unadjusted). The instrumented variable (in the IV regression) is sl_change_end. This variable has the following coefficient and standard error estimates (in parentheses) from clustered IV regression: -1.16 (1.607) Using OLS with clustered standard errors I get the following coefficient (std err): -0.125 (0.169) When I run SUEST with zip code clustered standard errors I get for the IV model: -1.16 (6.54) and for the OLS model I get -0.125 (0.169) The problem is that the standard errors I get from SUEST for the IV estimate is clearly wrong so the result I get from the generalized HAUSMAN test is that I can't reject the null that the coefficients between the two models are the same. It seems strange to me that SUEST will not accept the covariance matrix from IVREGRESS. Is there no way to implement this test or am I just missing something? Many thanks for your help, Woolton * * 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/

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