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# Re: st: RE: Getting Started with ineqdeco

 From Austin Nichols <[email protected]> To [email protected] Subject Re: st: RE: Getting Started with ineqdeco Date Fri, 13 Jul 2012 10:11:04 -0400

```One can also fit a distribution via ML using e.g.
http://fmwww.bc.edu/repec/bocode/d/dagfit.html
using the five quantiles (10th, 30th, 50th, 70th, 90th %iles) available.

On Fri, Jul 13, 2012 at 8:33 AM,  <[email protected]> wrote:
> The Pedant did of course mean to say that there 9 deciles (not 99);
> there are 99 percentiles.
>
> More constructively, on the substantive question of "what to do given
> the data to hand?":
>
> The median of the poorest fifth is the 10th percentile (p10) and the
> median of the richest fifth is the 90th percentile (p90).  The ratio
> p90/p10 is commonly used, at least by many labo(u)r economists, to
> summarise inequality.  So you could calculate that measure for each
> community, and plug that rather than Gini coefficients into whatever
> subsequent analysis you are doing.
>
>
> Stephen
> ------------------
> Professor Stephen P. Jenkins <[email protected]>
> 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
>
>
> -----Original Message-----
> From: Jenkins,S
> Sent: 13 July 2012 09:53
> To: '[email protected]'
> Subject: st: Getting Started with ineqdeco
>
> ------------------------------
> Date: Thu, 12 Jul 2012 17:06:36 +0000 (UTC)
> From: [email protected]
> Subject: st: Getting Started with ineqdeco
>
> Hi,
>
> I'm a newbie and statistics is not my long suit to say the least. I have
> approximately 250 communities and I want to give each one a gini
> coefficient that indicates the degree of income inequality prevailing
> there. For each community I have median income for each quintile. It
> appears that I have to use ineqdeco, which I have installed on my
> computer. After looking at the material on line, I'm not even sure where
> to start. I'm guessing that I have to create a single variable for each
> community that includes this data, but I'm not sure. Can anybody provide
> a "ineqdeco for dummies" description of exactly what I need to do?
>
> Marty
> ========================
>
> For each community, you have "grouped" data, not unit-record data
> (observations on each and every unit within a community), and appear to
> have the median for each quintile group*, not the mean.
>
> Grouped data should not be used with -ineqdeco- (or other inequality
> measure programs on SSC) because they all assume that you have
> unit-record data. Put differently, if you do apply them to grouped data,
> as is, you will end up under-estimating inequality -- because you are in
> effect assuming equality within each quintile group.
>
> There are methods for estimating inequality indices from grouped data. A
> good reference is FA Cowell and F Mehta, (1982). "The estimation and
> interpolation of inequality measures", Review of Economic Studies,
> Measuring Inequality (several editions).
>
> Note that these methods typically assume that you have the _mean_ income
> within each group, not the _median_.
>
> In sum, I think your issues are not to do with -ineqdeco- or related
> programs. Rather, the fundamental issues concern the (lack of)
> information in the data at your disposal. You as researcher have to
> decide how to address those. One crude way might be to assume that the
> median within each quintile group is the same as the group mean, and
> apply one of the grouped data methods. Whatever, with only 5 pieces of
> information per community, summarising inequality accurately within each
> community is a difficult task
>
>
> Stephen
>
> * [Pedant's corner]  The term "quintile" refers to an income value;
> there are 4 quintiles, not 5 (and 99 deciles, not 100, etc.). Talk about
> "quintile groups", not "quintiles", or -- more simply -- refer to the
> "poorest fifth", ..., "richest fifth".
*
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```

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