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Stata Technical Bulletin

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gp(gpname) creates a new categorical variable, gpname, containing categories summarizing group membership.

Example

To produce output mimicking the UK official low income statistics, we use the mean income as the cut-off value input into
xfrac:

. summarize eybhc [fw=wgt]

Variable ∣ Obs        Mean Std. Dev.       Min        Max

---------₊-----------------------------------------------------

eybhc I 5.6e÷07    233.0179   199.0178 -123.9898   7740.044

. local mean = .result(3)
. xfrac eybhc [fw=wgt], cut('mean^z) gp(fracgp)

Warning: eybhc has 20 values < 0. Used in calculations
Proportions of the sample in subgroups defined
by values of eybhc between specified fractions
of a cut-off value = 233.01790

There is no official poverty line in Britain, but half of the average income is used by many commentators as such a threshold.
The xfrac output shows that about one fifth of the UK population in 1991 had incomes below one half of contemporary mean
income (and 62.6% had incomes below the mean). But observe too that 38% of the population have incomes between 40%
and 60% of mean income. Thus relatively small changes in the threshold defining the poverty line can have a large impact on
estimates of the proportion who are “poor”.

The command above also created a new variable summarizing income group membership. If we were now to type
. table fracgp tenure [fw=wgt], row col

we could compare the shape of the income distribution across housing tenure groups.

ineqdeco, ineqdec0: inequality indices, with decompositions by population subgroup

ineqdeco and ineqdecθ estimate a range of inequality and related indices commonly used by economists, plus decom-
positions of a subset of these indices by population subgroup into within- and between-group inequality components. Inequality
decompositions by subgroup are useful for providing inequality profiles at a point in time, and for analyzing secular trends using
shift-share analysis. Unit record (micro level) data are required. For a non-technical introduction to the topic, see Jenkins (1991).
Standard textbook treatments are provided by Cowell (1995) and Lambert (1993).

Inequality indices estimated by ineqdeco are: members of the single parameter Generalized Entropy class GE(α) for
a = -1,0,1,2; the Atkinson class A(e) for e = 0.5,1,2; the Gini coefficient, and percentile ratios such as p90∕p10 and
p75∕p25. Also presented are related summary statistics such as subgroup means and population shares. Optionally presented are

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