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From |
Rachel <academicgirl@gmail.com> |

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

Subject |
st: Why Heckprob's estimate of rho is off? |

Date |
Mon, 13 Aug 2007 14:34:57 -0400 |

I am trying to simulate data for a censored probit model and then use heckprob to check how close its estimates are to the true values. It turns out the estimates of the coefficients are very close and highly significant, but the estimates of rho (whose true value is -0.5) is off and highly insignificant. Here is my code: matrix Csample = (1, -.5\-0.5, 1) drop eps11 eps22 drawnorm eps11 eps22, n(2000) corr(Csample) drawnorm x1 x2 x3, means(10 -9 11) sd (1 1 1) //defined all beta parameters here--will not list this part// replace yselectstar=beta00+beta11*x1+beta22*x2+eps11 regress yselectstar x1 x2 gen yselect=0 replace yselect=1 if ystar>0 gen yhat=alpha+beta33*x3 gen ystar=yhat+eps22 gen y=0 replace y=1 if ystar>0 heckprob y x3, sel(yselect=x1 x2) I get estimates for the parameters that are very close to the true values, with p-values of 0.000. But the estimated rho value is -.2056815 with a p value of 0.69. Can anyone spot the problem with the way I am simulating the data for the censored probit? (I realize that I have values of y for all observations, regardless of the value of yselect, but this doesn't seem to make a difference in Heckprob's estimates.) Or is the problem with heckprob? I understand that heckprob estimates atanhrho and then transforms the parameter and estimates the standard errors using the delta method. But I don't understand why it would land at a value that is so far off. Thanks, Rachel * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Why Heckprob's estimate of rho is off?***From:*Partha Deb <partha.deb@hunter.cuny.edu>

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