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From |
"Henrique Neder" <hdneder@ufu.br> |

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

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

Date |
Thu, 9 Oct 2008 21:30:15 -0300 |

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/

**Follow-Ups**:**Re: st: estimating distribution functions from Kernel densities***From:*"Ben Jann" <ben.jann@gmail.com>

**RE: st: estimating distribution functions from Kernel densities***From:*philippe van kerm <philippe.vankerm@ceps.lu>

**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>

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