Distributional Dominance with Dirty Data
Distributional dominance criteria are commonly applied to draw welfare inferences about comparisons, but conclusions drawn from empirical implementations of dominance criteria may be influenced by data contamination. We examine a non-parametric approach to refining Lorenz-type comparisons and apply the technique to two important examples from the LIS data-base.
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