## Abstract

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 |