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A Ranking Method Based on Handicaps

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  • Gabrielle Demange

Abstract

Ranking methods are fundamental tools in many areas. Popular methods aggregate the statements of ‘experts’ in different ways. As such, there are various reasonable ranking methods, each one of them more or less adapted to the environment under consideration. This paper introduces a new method, called the handicap-based method, and characterizes it through appealing properties. This method assigns not only scores to the items but also weights to the experts. Scores and weights form an equilibrium for a relationship based on the notion of handicaps. The method is, in a sense made precise in the paper, the counterpart to the counting method in environments that require intensity-invariance. Intensity-invariance is a desirable property when the intensity of the experts' statements has to be controlled. Otherwise, both the counting and handicap-based methods satisfy a property called homogeneity, which is a desirable property when cardinal statements matter, as is the case in many applications. The method is illustrated for ranking economic journals.

Suggested Citation

  • Gabrielle Demange, 2014. "A Ranking Method Based on Handicaps," CESifo Working Paper Series 4636, CESifo.
  • Handle: RePEc:ces:ceswps:_4636
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    References listed on IDEAS

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    Cited by:

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    2. Antonin Macé, 2023. "The Limits of Citation Counts," Working Papers halshs-01630095, HAL.
    3. Angus, Simon D. & Atalay, Kadir & Newton, Jonathan & Ubilava, David, 2021. "Geographic diversity in economic publishing," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 255-262.
    4. Eric Danan & Thibault Gajdos & Jean-Marc Tallon, 2023. "Tailored recommendations," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 60(1), pages 15-34, January.
    5. Gabrielle Demange, 2021. "On the resolution of cross-liabilities," Working Papers halshs-03151128, HAL.
    6. Dequiedt, Vianney & Zenou, Yves, 2017. "Local and consistent centrality measures in parameterized networks," Mathematical Social Sciences, Elsevier, vol. 88(C), pages 28-36.
    7. L'aszl'o Csat'o, 2019. "Journal ranking should depend on the level of aggregation," Papers 1904.06300, arXiv.org, revised Sep 2019.
    8. Demange, Gabrielle, 2017. "Mutual rankings," Mathematical Social Sciences, Elsevier, vol. 90(C), pages 35-42.
    9. Kim‐Sau Chung & Meng‐Yu Liang & Melody Lo, 2022. "On the information contents of indirect citations," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(1), pages 156-173, February.
    10. Cho, Wonki Jo, 2022. "How to add apples and oranges: Aggregating performances of different nature," Games and Economic Behavior, Elsevier, vol. 131(C), pages 222-244.
    11. Flores-Szwagrzak, Karol & Treibich, Rafael, 2015. "Co-authorship and the Measurement of Individual Productivity," Discussion Papers on Economics 17/2015, University of Southern Denmark, Department of Economics.
    12. Karol Flores-Szwagrzak & Rafael Treibich, 2020. "Teamwork and Individual Productivity," Management Science, INFORMS, vol. 66(6), pages 2523-2544, June.
    13. Johannes König & David I. Stern & Richard S.J. Tol, 2022. "Confidence Intervals for Recursive Journal Impact Factors," Tinbergen Institute Discussion Papers 22-038/III, Tinbergen Institute.
    14. van den Brink, René & Rusinowska, Agnieszka, 2022. "The degree measure as utility function over positions in graphs and digraphs," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1033-1044.
    15. Rene (J.R.) van den Brink & Agnieszka Rusinowska, 2017. "The Degree Measure as Utility Function over Positions in Networks," Tinbergen Institute Discussion Papers 17-065/II, Tinbergen Institute.
    16. Germano, Fabrizio & Sobbrio, Francesco, 2020. "Opinion dynamics via search engines (and other algorithmic gatekeepers)," Journal of Public Economics, Elsevier, vol. 187(C).
    17. Csató, László, 2019. "Journal ranking should depend on the level of aggregation," Journal of Informetrics, Elsevier, vol. 13(4).
    18. Sprumont, Yves, 2018. "Ranking by rating," Theoretical Economics, Econometric Society, vol. 13(1), January.
    19. Nicolas CARAYOL & Agenor LAHATTE, 2014. "Dominance relations and ranking when quantity and quality both matter: Applications to US universities and econ. departments worldwide," Cahiers du GREThA (2007-2019) 2014-14, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    20. Brink, René van den & Rusinowska, Agnieszka, 2021. "The degree ratio ranking method for directed graphs," European Journal of Operational Research, Elsevier, vol. 288(2), pages 563-575.
    21. Ham, John C. & Wright, Julian & Ye, Ziqiu, 2023. "Documenting and Explaining the Dramatic Rise of the New Society Journals in Economics," IZA Discussion Papers 16337, Institute of Labor Economics (IZA).
    22. Bouyssou, Denis & Marchant, Thierry, 2016. "Ranking authors using fractional counting of citations: An axiomatic approach," Journal of Informetrics, Elsevier, vol. 10(1), pages 183-199.
    23. Lutz Bornmann & Alexander Butz & Klaus Wohlrabe, 2018. "What are the top five journals in economics? A new meta-ranking," Applied Economics, Taylor & Francis Journals, vol. 50(6), pages 659-675, February.
    24. Palacios-Huerta, Ignacio & Volij, Oscar, 2014. "Axiomatic measures of intellectual influence," International Journal of Industrial Organization, Elsevier, vol. 34(C), pages 85-90.

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    More about this item

    Keywords

    ranking; scores; invariant method; peers' method; handicap; scaling matrix;
    All these keywords.

    JEL classification:

    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D89 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Other

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