Arbeitspapier

Sharing the cost of cleaning up a polluted river

Consider a group of agents located along a polluted river where every agent must pay a certain cost for cleaning up the polluted river. Following the model of Ni and Wang (2007), we propose the class of alpha-Local Responsibility Sharing methods, which generalizes the Local Responsibility Sharing (LRS) method and the Upstream Equal Sharing (UES) method. We fi rst show that the UES method is characterized by relaxing independence of upstream costs appearing in Ni and Wang (2007). Then we provide two axiomatizations with endogenous responsibility of the alpha-Local Responsibility Sharing method, one using this weak independence axiom (taken from the UES method) and one using a weak version of the no blind cost axiom (taken from the LRS method). Moreover, we also provide an axiomatization with exogenous responsibility by introducing alpha-responsibility balance. Finally, we defi ne a pollution cost-sharing game, and show that, interestingly, the Half Local Responsibility Sharing (HLRS) method coincides with the Shapley value, the nucleolus and the tau-value of the corresponding pollution cost-sharing game. This HLRS method can be seen as some kind of middle compromise of the LRS and UES methods.

Sprache
Englisch

Erschienen in
Series: Tinbergen Institute Discussion Paper ; No. TI 2021-028/II

Klassifikation
Wirtschaft
Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
Cooperative Games
Renewable Resources and Conservation: Water
Thema
pollution cost-sharing problems
alpha-Local Responsibility Sharing method
axiomatization
cooperative games

Ereignis
Geistige Schöpfung
(wer)
Li, Wenzhong
Xu, Genjiu
van den Brink, Rene
Ereignis
Veröffentlichung
(wer)
Tinbergen Institute
(wo)
Amsterdam and Rotterdam
(wann)
2021

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Li, Wenzhong
  • Xu, Genjiu
  • van den Brink, Rene
  • Tinbergen Institute

Entstanden

  • 2021

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