Testing for auto-calibration with Lorenz and Concentration curves

Michel Denuit (), Julie Huyghe, Julien Trufin () and Thomas Verdebout
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Michel Denuit: Université catholique de Louvain, LIDAM/ISBA, Belgium
Julie Huyghe: Université Libre de Bruxelles
Julien Trufin: Université Libre de Bruxelles
Thomas Verdebout: ECARES

No 2024015, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: Dominance relations and diagnostic tools based on Lorenz and Concentration curves in order to compare competing estimators of the regression function have recently been proposed. This approach turns out to be equivalent to forecast dominance when the estimators under consideration are auto-calibrated. A new characterization of auto-calibration is established, based on the graphs of Lorenz and Concentration curves. This result is exploited to propose an effective testing procedure for auto-calibration. A simulation study is conducted to evaluate its performances and its relevance for practice is demonstrated on an insurance data set.

Keywords: Concentration curve; Lorenz curve; Integrated Concentration Curve (ICC); Area Between the Curves (ABC); Gini coefficient; Auto-calibrated estimators (search for similar items in EconPapers)
JEL-codes: C12 G22 (search for similar items in EconPapers)
Pages: 10
Date: 2024-05-06
Note: In: Insurance Mathematics and Economics, 2024, vol. 117, p. 130-139
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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvar:2024015

DOI: 10.1016/j.insmatheco.2024.04.003

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