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From |
Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: bootstrap test for ineqdeco comparison |

Date |
Fri, 8 May 2009 14:27:43 +0100 |

Here is my code which does essentially the same as Maarten's (for a different data setup) but I would strongly suggest standardizing your differences with standard errors for the _differences_ calculated using an inner bootstrap - a double bootstrap (I have not done this) - as you do not know if your statistic is pivotal or not. See the relevant discussion for Hausman statistics in Cameron and Trivedi, pg. 374 & pg. 378. /* Bootstrap the difference of two statistics */ clear // ssc install ineqdeco, replace webuse nlswork, clear keep idcode year ttl_exp reshape wide ttl_exp, i(idcode) j(year) cap prog drop ineqdeco_bs program define ineqdeco_bs, rclass version 10 syntax varlist(max=2 min=2) [if] [in] marksample touse tokenize `varlist' local first `1' macro shift local second `*' ineqdeco `first' if `touse' scalar ge68 = r(ge1) ineqdeco `second' if `touse' scalar ge69 = r(ge1) return scalar ge = ge68-ge69 ereturn post, esample(`touse') end bootstrap Dge = r(ge), reps(2000) dots: ineqdeco_bs ttl_exp68 ttl_exp69 /* End */ ---References --- @book{cameron2005mma, title={{Microeconometrics: methods and applications}}, author={Cameron, A.C. and Trivedi, P.K.}, year={2005}, publisher={Cambridge University Press} } On Fri, May 8, 2009 at 1:44 PM, Maarten buis <maartenbuis@yahoo.co.uk> wrote: > > --- On Fri, 8/5/09, Gianluca Cafiso wrote: >> I need to test if the concentration index (CI) for a sample >> of geo-units has changed over time trough a bootstrap >> procedure. <snip> (as done in Brulhart+Traeger 2005). >> >> To compute the index, I have used the "ineqdeco" >> routine separately on the Employment variable for t1 and then >> on the one for t2. >> >> However, I do not know how to implement the bootstrap test. > <snip> > > Please give full references, and not just a author/year reference. > This is discussed in the Statalist FAQ. > > I don't know if this makes sense, I am no expert on these inequality measures, but the general strategy is to collect the different > models in one program and return the statistic of interest: > > *---------- begin example ---------------- > sysuse auto, clear > capture program drop bootdiff > program define bootdiff, rclass > tempname for > sum mpg if foreign == 1, meanonly > scalar `for' = r(mean) > sum mpg if foreign == 0, meanonly > return scalar diff = `for' - r(mean) > end > bootstrap diff=r(diff), reps(100):bootdiff > *---------- end example -------------------- > > ----------------------------------------- > Maarten L. Buis > Institut fuer Soziologie > Universitaet Tuebingen > Wilhelmstrasse 36 > 72074 Tuebingen > Germany > > http://home.fsw.vu.nl/m.buis/ > ----------------------------------------- > > > > > * > * 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/ > -- To every ω-consistent recursive class κ of formulae there correspond recursive class signs r, such that neither v Gen r nor Neg(v Gen r) belongs to Flg(κ) (where v is the free variable of r). * * 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/

**References**:**st: bootstrap test for ineqdeco comparison***From:*Gianluca Cafiso <gcafiso@unict.it>

**Re: st: bootstrap test for ineqdeco comparison***From:*Maarten buis <maartenbuis@yahoo.co.uk>

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