Stochastic dominance criteria are commonly used to draw welfare-theoretic inferences about comparisons of income distribution as well as ranking probability distributions in the analysis of choice under uncertainty. However, just as some measures of location and dispersion can be catastrophically sensitive to extreme values in the data it is also possible that conclusions drawn from empirical implementations of dominance criteria are unduly influenced by data contamination. We show the conditions under which this may occur for a number of standard dominance tools used in welfare analysis.

Frank A. Cowell, Maria-Pia Victoria-Feser (2002). Welfare Rankings in the Presence of Contaminated Data. ECONOMETRICA, 70(3), 1221-1233 [10.1111/1468-0262.00324].

Welfare Rankings in the Presence of Contaminated Data

Maria-Pia Victoria-Feser
2002

Abstract

Stochastic dominance criteria are commonly used to draw welfare-theoretic inferences about comparisons of income distribution as well as ranking probability distributions in the analysis of choice under uncertainty. However, just as some measures of location and dispersion can be catastrophically sensitive to extreme values in the data it is also possible that conclusions drawn from empirical implementations of dominance criteria are unduly influenced by data contamination. We show the conditions under which this may occur for a number of standard dominance tools used in welfare analysis.
2002
Frank A. Cowell, Maria-Pia Victoria-Feser (2002). Welfare Rankings in the Presence of Contaminated Data. ECONOMETRICA, 70(3), 1221-1233 [10.1111/1468-0262.00324].
Frank A. Cowell; Maria-Pia Victoria-Feser
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/952914
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