I am glad Ray posted this since I was going to as well and wanted to go on to
ask a more general question about how we formulate our understanding of
inequality in general. As a summary we use Gini coefficients and as a
distributional description we use relative proportions of income (and
expenditure) defined in various ways - pre-tax, post-tax, with cash benefits,
with cash benefits and estimates of in kind income - received by deciles or
quintiles with some recent attention to the top 1%. I always think this is
unsatisfactory. If I was chopping up a distribution of a continuous variable
like income into ordered categories I would actually do a visual inspection of
the distribution (now I use the visual bander in SPSS) and try to see how the
pattern actually worked. If I had more than one measure I would do a cluster
analysis and generate ordered types. Any views? And by the way the use of
deciles and quintiles enables government grossly to overestimate actual income
mobility.
David Byrne
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