ECOSEL: An Auction Mechanism for Forest Ecosystem Services

Auteurs-es

  • Sándor F. Tóth The University of Washington, USA
  • Gregory J. Ettl The University of Washington, USA
  • Sergey S. Rabotyagov The University of Washington, USA

Mots-clés :

Multi-objective optimization, integer programming, public good provisions, auctions

Résumé

This paper describes the foundations of a  market mechanism that was designed to stimulate more efficient provisions of  forest ecosystem services to society. The proposed tool is a competitive  multi-unit public goods subscription game of incomplete information. A  conceptual and mathematical characterization of the game is followed by an  illustrative example where Pareto-efficient bundles of timber, carbon and  mature forest habitat services of a real forest are used in a simulated  bidding game. Attractive features of the mechanism include the use of  multi-criteria optimization to ensure only the most cost-efficient bundles  of ecosystem services are offered for bidding, and that it does not rely on  regulatory control or on complex valuation exercises that are otherwise  needed in alternative methods such as the cap-and-trade scheme.   MCFNS 2(2):99-116.

Biographies de l'auteur-e

  • Sándor F. Tóth, The University of Washington, USA
    Assistant Professor of Natural Resource Informatics at the School of Forest Resources, College of the Environment
  • Gregory J. Ettl, The University of Washington, USA
    Associate Professor/Director, Center for Sustainable Forestry at Pack Forest
    Sustainable forestry; Forest ecology; Silviculture, School of Forest Resources, College of the Environment
  • Sergey S. Rabotyagov, The University of Washington, USA
    Assitant Professor of Environmental economics; Human resources; Applied econometrics. School of Forest Resources, College of the Environment

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Publié

2010-08-28

Numéro

Rubrique

Special Section on Systems Analysis in Forest Resources

Comment citer

ECOSEL: An Auction Mechanism for Forest Ecosystem Services. (2010). Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 2(2), Pages: 99-116 (18). https://mcfns.com/index.php/Journal/article/view/2.17

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