Mean Location and Gini-like Inequality measures for Multivariate Ordinal Variates: Examining the Progress of Health Outcomes in Pre Covid United Kingdom

Gordon Anderson

Working Papers from University of Toronto, Department of Economics

Abstract: The ever-expanding use of ordinal data is usually facilitated by artificial attribution of cardinal scale to ordered categories. Such practices have been shown to lead to ambiguous and equivocal results. Here a probabilistic distance construct is employed to develop unambiguous level and inequality measures for ordinal situations analogous to the Mean and Gini coefficient used in cardinally measurable paradigms. The commonality of the probabilistic distance measure across dimensions means that the measures are readily extended to multidimensional situations. The measures are exemplified in an analysis of the progress of health outcomes in pre-covid 21st century United Kingdom

Keywords: Ordered Categorical Data; Level and Inequality measurement; Health Outcomes (search for similar items in EconPapers)
JEL-codes: C13 C43 H11 I14 (search for similar items in EconPapers)
Pages: Unknown pages
Date: 2025-09-25
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