Estimation of inequality indices with decomposition by subgroup
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Speaker |
Stephen P. Jenkins, University of Essex
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Inequality indices which are decomposable by population subgroup are
increasingly used to analyze the anatomy of (income) inequality and also
for analysis of secular trends. Examples of subgroup partitions include:
age group of household head; work attachment; family type. Particularly
useful are the class of additively decomposable indices, for which total
inequality can be written as the weighted sum of inequality within each
subgroup, plus inequality between groups. It is now well known that the
only indices with this property belong to the so-called Generalized
Entropy (GE) class, which includes the two Theil indices and the
coefficient of variation. The so-called Atkinson class of indices is
decomposable but not additively (and the Gini coefficient is neither).
This talk introduces the author's program ineqdeco for calculating
GE, Atkinson, and Gini inequality indices with options for weighted data
and decompositions by population subgroup, and gives an empirical
illustration and mentions several Stata programming issues. Time
permitting, the talk will also introduce the following related programs:
geivars which calculates sampling variances for GE inequality
measures with (f)weighted data; povdeco which calculates three
Foster, Greer and Thorbecke poverty indices with options for weighted
data and decompositions by population subgroup; sumdist, a utility
for summarising quantiles and (generalized) Lorenz ordinates of a
distribution; and smfit and dagumfit which fit the
Singh–Maddala (Burr Type 12) and Dagum (Burr Type 3) 3-parameter
distributions to unit-record data by ML with options to calculate the
predicted income quantiles and inequality indices.
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