An elementary algorithm to make quantitative assessments from multidimensional, unstructured, categorical data

Antonio Villar

No 22.14, Working Papers from Universidad Pablo de Olavide, Department of Economics

Abstract: This paper proposes and characterizes an elementary algorithm to solve multicriteria evaluation problems when individual judgements are categorical and may fail to satisfy both transitivity and completeness. The evaluation function consists of a weighted sum of the average number of times that each alternative precedes some other, in all pairwise comparisons. It provides, therefore, a quantitative assessment which is well-grounded, immediate to compute, and easy to understand. An application to the evaluation of human development illustrates how this evaluation protocol works.

Keywords: multidimensional evaluation; categorical data; non-transitive and incomplete preferences; pairwise comparisons. (search for similar items in EconPapers)
JEL-codes: C60 D70 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2022
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