{smcl} {* 18feb2001/27oct2004}{...} {hline} help for {hi:glcurve}{right: (SJ4-4: gr0001_1; SJ1-1: gr0001; STB-49: sg107_1; STB-48: sg107)} {hline} {title:Derivation of generalised Lorenz curve ordinates with unit record data} {p 8 17 2}{cmd:glcurve} {it:varname} [{it:weight}] [{cmd:if} {it:exp}] [{cmd:in} {it:range}] [{cmd:,} {cmdab:p:var}{cmd:(}{it:newvarname}{cmd:)} {cmdab:gl:var}{cmd:(}{it:newvarname}{cmd:)} {cmdab:so:rtvar}{cmd:(}{it:varname}{cmd:)} {cmd:by}{cmd:(}{it:varname}{cmd:)} {cmdab:sp:lit} {cmdab:nogr:aph} {cmd:replace} {cmdab:l:orenz} {cmd:atip}{cmd:(}{it:string}{cmd:)} {cmd:rtip}{cmd:(}{it:string}{cmd:)} {cmd:plot}{cmd:(}{it:plot}{cmd:)} {it:graph_options} ] {p 4 4 2}{cmd:aweight}s and {cmd:fweight}s are allowed; see help {help weights}. {title:Description} {p 4 4 2}Given a variable {it:varname}, call it x with c.d.f. F(x), {cmd:glcurve} draws its Generalised Lorenz curve and/or generates two new variables containing the Generalised Lorenz ordinates for x, i.e. GL(p) at each p = F(x). For a population ordered in ascending order of x, a graph of GL(p) against p plots the cumulative total of x divided by population size against cumulative population share GL(1) = mean(x). {cmd:glcurve} can also be used to derive many other related concepts such as Lorenz curves, concentration curves and 'Three Is of Poverty' (TIP) curves, with appropriate definition of {it:varname}, order of cumulation (set with the {cmd:sortvar} option), and normalisation (e.g. by the mean of {it:varname}). Alternatively {cmd:glcurve} with the {cmd:lorenz}, {cmd:atip} or {cmd:rtip} option can be used directly to draw the related Lorenz, concentration and TIP curves. {p 4 4 2}Comparisons of pairs of distributions (and dominance checks) can be undertaken by using the {cmd:by()} (with or without the {cmd:split}) options. It can also be made manually by 'stacking' the data (see help on {help stack}). {title:Options} {p 4 8 2}{cmd:pvar(}{it:pvarname}{cmd:)} generates the variable {it:pvarname} containing the x coordinates of the created curve. {p 4 8 2}{cmd:glvar(}{it:glvarname}{cmd:)} generates the variable {it:glvarname} containing the y coordinates of the created curve. {p 4 8 2}{cmd:sortvar(}{it:sname}{cmd:)} specifies the sort variable. By default, the data are sorted (and cumulated) in ascending order of {it:varname}. If the {cmd:sortvar} option is specified, sorting and cumulation is in ascending order of variable {it:sname}. {p 4 8 2}{cmd:by(}{it:groupvar}{cmd:)} specifies that the coordinates are to be computed separately for each subgroup defined by {it:groupvar}. {it:groupvar} must be an integer variable. {p 4 8 2}{cmd:split} specifies that a series of new variables are created containing the coordinates for each subgroup specified by {cmd:by(}{it:groupvar}{cmd:)}. {cmd:split} can not be used without {cmd:by()}. If {cmd:split} is specified, then the string {it:glname} in {cmd:glvar(}{it:glname}{cmd:)} is used as a prefix to create new variables {it:glname_X1}, {it:glname_X2},... (where X1, X2, ... are the values taken by {it:groupvar}). {p 4 8 2}{cmd:nograph} avoids the automatic display of a crude graph made out of the created variables. {cmd:nograph} is assumed if {cmd:by()} is specified without {cmd:split}. {p 4 8 2}{cmd:replace} allows the variables specified in {cmd:glvar(}{it:glvarname}{cmd:)} and {cmd:pvar(}{it:pvarname}{cmd:)} to be overwritten if they already exist. Otherwise {it:glvarname} and {it:pvarname} must be new variable names. {p 4 8 2}{cmd:lorenz} requires that the ordinates of the Lorenz curve are computed instead of generalised Lorenz ordinates. The Lorenz ordinates of variable x, L(p), are GL(p)/mean(x). {p 4 8 2}{cmd:rtip(}{it:povline}{cmd:)} and {cmd:atip(}{it:povline}{cmd:)} require that the ordinates of TIP curves are computed instead of generalised Lorenz ordinates. {it:povline} specifies the value of the poverty line: it can be either a numeric value taken as the poverty line for all observations or a variable name containing the value of the poverty line for each observation. {cmd:atip()} draws 'absolute' TIP curves (by cumulating max(z-x,0)) and {cmd:rtip()} draws 'relative' TIP curves (by cumulating max(1-(x/z),0)). {p 4 8 2}{cmd:plot(}{it:plot}{cmd:)} provides a way to add other plots to the generated graph; see {help plot option}. {p 4 8 2}{it:graph_options} are standard {help twoway scatter} options. {title:Examples} {p 4 8 2}{cmd:. glcurve x, gl(gl1) p(p1) nograph}{p_end} {p 4 8 2}{cmd:. line gl1 p1} {p 4 8 2}{cmd:. glcurve x, lorenz plot(function equality = x)} {p 4 8 2}{cmd:. glcurve x [fw=wgt] if x > 0, gl(gl2) p(p2) lorenz} {p 4 8 2}{cmd:. glcurve x, gl(gl2) p(p2) replace sort(y) by(state) split} {p 4 8 2}{cmd:. glcurve x, gl(gl3) p(p3) atip(10000)} {p 4 8 2}{cmd:. glcurve x, gl(gl3) p(p3) atip(plinevar)} {title:Acknowledgements} {p 4 4 2}Nicholas J. Cox helped with updating the code for our program from Stata 7 ({help glcurve7}) to Stata 8. {title:Authors} {p 4 4 2}Philippe Van Kerm, CEPS/INSTEAD, Differdange, G.-D. Luxembourg{break} philippe.vankerm@ceps.lu {p 4 4 2}Stephen P. Jenkins, ISER, University of Essex{break} stephenj@essex.ac.uk {title:References} {p 4 8 2}Cowell, F.A. 1995. {it:Measuring Inequality} (second edition). Hemel Hempstead: Prentice-Hall/Harvester-Wheatsheaf. {p 4 8 2}Jenkins, S.P. and Lambert, P.J. 1997. Three 'I's of poverty curves, with an analysis of UK poverty trends. {it:Oxford Economic Papers} 49: 317{c -}327. {p 4 8 2}Lambert, P.J. 2001. {it:The Distribution and Redistribution of Income} (third edition). Manchester: Manchester University Press. {p 4 8 2}Shorrocks, A.F. 1983. Ranking income distributions. {it:Economica} 197: 3{c -}17. {title:Also see} {p 4 13 2} Manual: {hi:[R] lorenz}{p_end} {p 4 13 2} STB: {hi:STB-48 sg107}, {hi:STB-49 sg107.1}, {hi:SJ 1(1) gr0001}{p_end} {p 4 13 2}On-line: help for {help sumdist} (if installed)