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Robust partial least squares regression for the evaluation of justice court delay

Author

Listed:
  • Ida Cammnitiello

    (Second University of Naples)

  • Rosaria Lombardo

    (Second University of Naples)

  • Jean-François Durand

    (Laboratoire de Probabilités et Statistique Montpellier II University)

Abstract

Justice court delay is found to be consistently related to pending workload per judge, as well, output per judge (productivity) is found to be strongly related to demand pressure (total available workload) and size of court. The aim of this paper is to investigate among the causes of different performances in courts, highlighting possible anomalies (outliers) among the judges’ behaviour of a court due to the distribution of the workload among court sections and judges. The statistical methods considered are classical and robust variants of Partial Least Squares regression.

Suggested Citation

  • Ida Cammnitiello & Rosaria Lombardo & Jean-François Durand, 2017. "Robust partial least squares regression for the evaluation of justice court delay," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 813-827, March.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:2:d:10.1007_s11135-016-0441-z
    DOI: 10.1007/s11135-016-0441-z
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    References listed on IDEAS

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    1. Andrew Torre, 2003. "The Impact of Court Delays on the Prosecutor and the Defendant: An Economic Analysis," European Journal of Law and Economics, Springer, vol. 16(1), pages 91-111, July.
    2. Lode Vereeck & Manuela Mühl, 2000. "An Economic Theory of Court Delay," European Journal of Law and Economics, Springer, vol. 10(3), pages 243-268, November.
    3. Martin Schneider, 2005. "Judicial Career Incentives and Court Performance: An Empirical Study of the German Labour Courts of Appeal," European Journal of Law and Economics, Springer, vol. 20(2), pages 127-144, September.
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    Cited by:

    1. Monika Stachowiak-Kudła & Janusz Kudła, 2023. "Measuring the prestige of administrative courts," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3637-3662, August.
    2. Lombardo, Rosaria & Camminatiello, Ida & D'Ambra, Antonello & Beh, Eric J., 2021. "Assessing the Italian tax courts system by weighted three-way log-ratio analysis," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).

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