Abstract / Description of output
Standard measures of inequality have been criticized for a long
time on the grounds that they are snap shot measures which do not
take into account the process generating the observed distribution.
Rather than focusing on outcomes, it is argued, we should be interested
in whether the underlying process is “fair”. Following this line
of argument, this paper develops statistical tests for fairness within a
well defined income distribution generating process and a well speci-
fied notion of “fairness”. We find that standard test procedures, such
as LR, LM and Wald, lead to test statistics which are closely related
to standard measures of inequality. The answer to the “process versus
outcomes” critique is thus not to stop calculating inequality measures,
but to interpret their values differently–to compare them to critical
values for a test of the null hypothesis of fairness.
time on the grounds that they are snap shot measures which do not
take into account the process generating the observed distribution.
Rather than focusing on outcomes, it is argued, we should be interested
in whether the underlying process is “fair”. Following this line
of argument, this paper develops statistical tests for fairness within a
well defined income distribution generating process and a well speci-
fied notion of “fairness”. We find that standard test procedures, such
as LR, LM and Wald, lead to test statistics which are closely related
to standard measures of inequality. The answer to the “process versus
outcomes” critique is thus not to stop calculating inequality measures,
but to interpret their values differently–to compare them to critical
values for a test of the null hypothesis of fairness.
Original language | English |
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Publisher | Edinburgh School of Economics Discussion Paper Series |
Number of pages | 16 |
Publication status | Published - Aug 2007 |
Publication series
Name | ESE Discussion Papers |
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No. | 174 |