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From |
"laura serlenga" <lserlenga@hotmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
RE: Re[2]: st: Heckman ordered probit |

Date |
Sun, 07 Aug 2005 22:20:44 +0200 |

Dear Ian,

thanks a lot again for your very helpful suggestions. I guess now the picture is completed in my mind and very clear.

thanks again

laura

From: Ian Watson <i.watson@econ.usyd.edu.au>

Reply-To: statalist@hsphsun2.harvard.edu

To: statalist@hsphsun2.harvard.edu

Subject: Re[2]: st: Heckman ordered probit

Date: Fri, 5 Aug 2005 18:02:08 +1000

Dear Laura,

I'm more familiar with linear regression in the second stage, than

ordered probit. For OLS in the second stage you can calculate rho by

dividing lamdba (which is provided by the coefficient on your inverse

mills term) by sigma (the standard error of the residual, which Stata

can provide with: predict mysigma, stdr). When it comes to ordered

probit, I am not sure what the equivalent for sigma would be. Also,

the entries for both -heckman- and -heckprob- in the Stata manuals

note that Stata calculates atanh rho, rather than rho directly. Others

on the list will no doubt have an answer to this.

As for the standard errors, you might consider bootstrapping the whole

procedure.

Kind regards

Ian

Friday, August 5, 2005, 7:14:59 AM, you wrote:

ls> Dear Ian,

ls> Thanks a lot for your help and sorry for my late replay (was out of town).

ls> I tried to compute the two-step procedure you suggested for a binary probit

ls> and then compare results with heckprob command. Estimations seem reasonable

ls> although with the two-step procedure I am loosing some observations with

ls> respect to the ml estimation. At this stage I don’t think I fully

ls> understand how the heckprob command works and how the missing observations

ls> of the latent probit equation are treated (?)

ls> However, in this two step procedure I guess I also need to compute new

ls> standard error and rho once I introduce the inverse mills ratio. Do you

ls> think this is correct?

ls> Many thanks again for your precious help.

ls> Best wishes

ls> Laura

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**References**:**Re[2]: st: Heckman ordered probit***From:*Ian Watson <i.watson@econ.usyd.edu.au>

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