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From |
"Alfonso Miranda Caso Luengo" <Alfonso.Miranda-Caso-Luengo@warwick.ac.uk> |

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

Subject |
Re: st: A question about bootstrap |

Date |
Tue, 10 Aug 2004 16:42:27 +0100 |

You could also see 3rd edition, Chap. 4. In particular you are interested on Theorem 4.19 - discussed in section 4.6. Best wishes, Alfonso. ===================================== Alfonso Miranda PhD Student Economics Department University of Warwick Coventry CV4 7AL E-mail:ecrgw@warwick.ac.uk WebPage: http://www.warwick.ac.uk/go/amiranda ===================================== >>> Alfonso Miranda Caso Luengo 08/10/04 16:03 PM >>> Dear Tak-wai Chau, The first question I would ask is whether bootstrapping standard errors from your ml rutine will be practical. Notice that bootstrapping needs running your ml code many times. With large data sets and slow ml routines this could be an important issue. Since you have cross section data it seems that you can use the lf method and that helps speed a lot. Besides your ml code you will need to write a small program to perform the bootstrapping. This is a minor problem as it is fairly easy if you know the basics of Stata programming. Have a look in the manuals. If I remember well you can adjust the covariance matrix for the first stage estimation and it should be simple. Have a look on chap. 16 and 17 in Greene's Econometric Analysis. Best, Alfonso. ===================================== Alfonso Miranda PhD Student Economics Department University of Warwick Coventry CV4 7AL E-mail:ecrgw@warwick.ac.uk WebPage: http://www.warwick.ac.uk/go/amiranda ===================================== >>> tchau@troi.cc.rochester.edu 08/10/04 15:18 PM >>> Dear all, I have some questions in using bootstrap in my task. I would like to estimate labor supply equations of husbands and wives. (One for husbands, one for wives) I am going to use a two-step procedure. First, I estimate the husband's and wife's wage equations on instruments by OLS. Second, I estimate jointly the husband's and wife's labor supply equations with Maximum Likelihood (using the predicted wages in the first step). For this step, I am going to use the ml commands. I would like to use bootstrap to obtain the standard errors or confidence interval of parameters of the labor supply equation (reduced form) and some non-linear functions of these parameters. I want to do this because I don't know how to adjust standard error for the first stage estimation, and also approximation for standard errors may be poor for non-linear functions of parameters. The data is from a cross-sectional data so IID can be assumed. I have the following questions in actually carrying out the above estimation. 1. Is my understanding of the use of bootstrap correct? Any special thing I should take care in my case? 2. I know there is a bootstrap command in Stata. Can it be used to do bootstrap in a two-stage process? 3. How can I obtain the standard error/confidence interval estimates from bootstrap of a non-linear function of parameter in Stata? Thank you very much in advance! Regards, Tak-wai Chau * * 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/ * * 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/

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