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

Author

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  • Antonio Villar

    (Universidad Pablo de Olavide)

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.

Suggested Citation

  • Antonio Villar, 2022. "An elementary algorithm to make quantitative assessments from multidimensional, unstructured, categorical data," Working Papers 22.14, Universidad Pablo de Olavide, Department of Economics.
    • Handle: RePEc:pab:wpaper:22.14
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    More about this item

    Keywords

    multidimensional evaluation; categorical data; non-transitive and incomplete preferences; pairwise comparisons.;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General

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