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Endogenous Shared Punishment Model in Threshold Public Goods Games

Author

Listed:
  • Gabriela Koľveková

    (Technical University of Košice)

  • Manuela Raisová

    (Technical University of Košice)

  • Martin Zoričak

    (Technical University of Košice)

  • Vladimír Gazda

    (Technical University of Košice)

Abstract

Population growth and greater human well-being imply increased use of scarce resources, which makes innovative proposals for fair redistribution policies necessary. The utilisation of common-pool resources (CPRs) offers an economising solution to this problem; however, addressing the complex issue of harmonising the participants’ interests is challenging. The use of CPRs has been theoretically discussed for decades and is addressed by theory of public goods (PGs) provision. Surprisingly, experimental tests of this theory have observed systematic deviations from the theoretical conclusions. Economists have applied agent-based methods to resolve this puzzle. We follow this approach and propose an agent-based model that innovatively employs voting on the punishment of free/cheap riders. The voting participants simultaneously determine the strictness of the punishment meted out to free/cheap riders and the cost burden of this punishment system. The proposed endogenous shared punishment model works within the threshold public goods game framework. Simulation results show that the presented method is more efficient than models with full or no punishment. Furthermore, the involvement of activists increases the likelihood of PGs provision. Introducing voting into PGs provision increases its efficiency and thus extends the set of available solutions to increase the efficiency of PGs provision.

Suggested Citation

  • Gabriela Koľveková & Manuela Raisová & Martin Zoričak & Vladimír Gazda, 2021. "Endogenous Shared Punishment Model in Threshold Public Goods Games," Computational Economics, Springer;Society for Computational Economics, vol. 58(1), pages 57-81, June.
    • Handle: RePEc:kap:compec:v:58:y:2021:i:1:d:10.1007_s10614-020-10017-1
    DOI: 10.1007/s10614-020-10017-1
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