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From |
"Ben Jann" <ben.jann@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: estimating distribution functions from Kernel densities |

Date |
Fri, 10 Oct 2008 12:51:51 +0200 |

mm_kint() provides analytic integrals for a number of specific kernel functions. It cannot be used to integrate over an empirical density function. ben On Fri, Oct 10, 2008 at 2:30 AM, Henrique Neder <hdneder@ufu.br> wrote: > I think that programs svylorenz, inequal, calculate inequality measures > directly from the data, for example, a sequence of observations of income. I > want to use the DFL method to decompose the effects of the minimum wage and > the characteristics of workers. For this, obtained through this method is a > counterfactual Kernel density function. After obtaining this function, I > desire from the same function (and not directly from my observed income > data) to obtain some measures of inequality, as the difference between the > ninth decile and the first decile, the Theil index and the Gini index, as is > done in the Dinardo, J., NM Fortin, and T. Lemieux (1996) article. For the > first measure (difference between deciles) and I think also for the other > two, is necessary to obtain the cumulative distribution function related to > the Kernel density function. For this I need a procedure in Stata to > integrate the kernel density function. I discovered that in the set of > commands named moremata there is a code (mm_kint()) that apparently > integrates Kernel density functions. This is the right path? > > Regards > > Henrique Neder > > -----Mensagem original----- > De: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] Em nome de Austin Nichols > Enviada em: quinta-feira, 9 de outubro de 2008 18:05 > Para: statalist@hsphsun2.harvard.edu > Assunto: Re: st: estimating distribution functions from Kernel densities > > Henrique Neder <hdneder@ufu.br> : > I think you need to be more clear about what you mean to do. The DFL > approach reweights the data to obtain the counterfactual density. If > you are interested in an inequality measure for the reweighted > distribution, can't you just compute the measure using your new > weights, using e.g. a program by Stephen Jenkins et al. (findit > svygei, findit ineqdeco)? > > DiNardo, J., N.M. Fortin, and T.Lemieux (1996) "Labour Market > Insitutions and the Distribution of Wages, 1973-1992: A Semiparametric > Approach," Econometrica, 64(5): 1001-1044. > > > On Thu, Oct 9, 2008 at 4:52 PM, Henrique Neder <hdneder@ufu.br> wrote: >> Dear Stata listers >> >> >> I am studying the methodology of decomposition of Dinardo, Fortin and >> Lemieux, known as Dfl. I need to estimate the inter-quantile deviation, > the >> Gini index and the Theil index for Kernel density functions. There would > be >> some method (for example, numerical integration) to do this using Stata? >> >> Henrique Neder > * > * 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/ > > * > * 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/ > * * 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/

**Follow-Ups**:**RE: st: estimating distribution functions from Kernel densities***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**References**:**st: estimating distribution functions from Kernel densities***From:*"Henrique Neder" <hdneder@ufu.br>

**Re: st: estimating distribution functions from Kernel densities***From:*"Austin Nichols" <austinnichols@gmail.com>

**RES: st: estimating distribution functions from Kernel densities***From:*"Henrique Neder" <hdneder@ufu.br>

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