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From |
<S.Jenkins@lse.ac.uk> |

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

Subject |
st: Calculating p20/p80 indicator with weights |

Date |
Tue, 19 Jun 2012 09:34:33 +0100 |

------------------------------ Date: Mon, 18 Jun 2012 15:35:10 +0200 From: Anke Weber <anke.weber@jrc.ec.europa.eu> Subject: st: Calculating p20/p80 indicator with weights This is a multi-part message in MIME format. - --Boundary_(ID_igLNjvdU/u4kFxt69BxbMA) Content-type: text/plain; CHARSET=US-ASCII; format=flowed Content-transfer-encoding: 7BIT Dear all, I am using Stata 11, and trying to take into account pweights when constructing the p20/p80 inequality measure, i.e. the ratio of the average income of the richest 20 percent of the population divided by the average income of the bottom 20 percent (using data from the SOEP, USS, and EUSILC databases). Would anyone have a suggestion on how to account for the sampling weight (of the person) in the data? So far, I explored the ineqdeco command, which let's you use aweights but unfortunately there is only an p75/p25 or p90/p10 measure. Then, I tried to use the svy command to calculate separately the 20-percentile and the 80 percentile, using my equivalised income variable (equivincome) but this did not work either: svyset pidp [pweight=a_psnenus_xw] pweight: a_psnenus_xw VCE: linearized Single unit: missing Strata 1: <one> SU 1: pidp FPC 1: <zero> svy: egen p20= pctile(equivincome), p(20) egen is not supported by svy with vce(linearized); see help svy estimation for a list of Stata estimation commands that are supported by svy I would be very happy if some one has an idea of how to calculate the p20/p80 indicator with weights! Many thanks in advance, Anke ++++++++++++++++++++++++++++++++++++++ There are many solutions. Perhaps the easiest is to use -sumdist- (from SSC). See also -svylorenz- (SSC). Example below. . sysuse auto (1978 Automobile Data) . sumdist price [w=weight], n(5) (analytic weights assumed) Distributional summary statistics, 5 quantile groups ------------------------------------------------------------------------ --- Quantile | group | Quantile % of median Share, % L(p), % GL(p) ----------+------------------------------------------------------------- --- 1 | 4181.000 80.574 12.162 12.162 798.896 2 | 4749.000 91.521 13.632 25.794 1694.304 3 | 5798.000 111.736 16.461 42.255 2775.571 4 | 9690.000 186.741 21.242 63.497 4170.884 5 | 36.503 100.000 6568.637 ------------------------------------------------------------------------ --- Share = quantile group share of total price; L(p)=cumulative group share; GL(p)=L(p)*mean(price) . ret list scalars: r(gl5) = 6568.636904761905 r(cush5) = 1 r(sh5) = .3650305213361488 r(qrel4) = 1.867411832723068 r(q4) = 9690 r(gl4) = 4170.883950948801 r(cush4) = .6349694786638513 r(sh4) = .2124204338931906 r(qrel3) = 1.117363653883215 r(q3) = 5798 r(gl3) = 2775.571249552452 r(cush3) = .4225490447706607 r(sh3) = .164610561137709 r(qrel2) = .9152052418577761 r(q2) = 4749 r(gl2) = 1694.304242749731 r(cush2) = .2579384836329517 r(sh2) = .1363156666281005 r(qrel1) = .8057429177105415 r(q1) = 4181 r(gl1) = 798.8961242391694 r(cush1) = .1216228170048512 r(sh1) = .1216228170048512 r(ngps) = 5 r(p95) = 13594 r(p90) = 11995 r(p75) = 7827 r(p50) = 5189 r(p25) = 4424 r(p10) = 3955 r(p5) = 3798 r(median) = 5189 r(N) = 74 r(sum_w) = 223440 r(mean) = 6568.636904761905 matrices: r(relquantiles) : 1 x 4 r(shares) : 1 x 5 r(quantiles) : 1 x 4 . di "Ratio of income share of richest 20% to poorest 20% = " r(sh5)/r(sh1) Ratio of income share of richest 20% to poorest 20% = 3.0013326 ++++++++++++++++++++++++++++++++++++++ NB Anke: please ensure that your email software sends plain text (ASCII) messages to Statalist. Stephen ------------------ Professor Stephen P. Jenkins <s.jenkins@lse.ac.uk> Department of Social Policy and STICERD London School of Economics and Political Science Houghton Street, London WC2A 2AE, UK Tel: +44(0)20 7955 6527 Changing Fortunes: Income Mobility and Poverty Dynamics in Britain, OUP 2011, http://ukcatalogue.oup.com/product/9780199226436.do Survival Analysis Using Stata: http://www.iser.essex.ac.uk/survival-analysis Downloadable papers and software: http://ideas.repec.org/e/pje7.html Please access the attached hyperlink for an important electronic communications disclaimer: http://lse.ac.uk/emailDisclaimer * * 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/

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