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Investigating the performance of market-based instruments for resource conservation: the contribution of agent-based modelling

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  • Hailu, Atakelty
  • Schilizzi, Steven

Abstract

Auctions are increasingly being considered as a mechanism for allocating conservation contracts to private landowners. This interest is based on the widely held belief that competitive bidding helps minimize information rents. This study constructs an agent-based model to evaluate the long term performance of conservation auctions under settings where bidders are allowed to learn from previous outcomes. The results clearly indicate that the efficiency benefits of one-shot auctions are quickly eroded under dynamic settings. Furthermore, the auction mechanism is found to be inferior to fixed payment schemes except when the latter involve the use of high reserve prices.

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Bibliographic Info

Paper provided by Australian Agricultural and Resource Economics Society in its series 2003 Conference (47th), February 12-14, 2003, Fremantle, Australia with number 57883.

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Date of creation: Feb 2003
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Handle: RePEc:ags:aare03:57883

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Keywords: Environmental Economics and Policy; Land Economics/Use;

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  13. Tesfatsion, Leigh, 1997. "A Trade Network Game with Endogenous Partner Selection," Staff General Research Papers 1680, Iowa State University, Department of Economics.
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  17. Isaac, R. Mark & Walker, James M., 1985. "Information and conspiracy in sealed bid auctions," Journal of Economic Behavior & Organization, Elsevier, vol. 6(2), pages 139-159, June.
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  19. Ashenfelter, Orley, 1989. "How Auctions Work for Wine and Art," Journal of Economic Perspectives, American Economic Association, vol. 3(3), pages 23-36, Summer.
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  22. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, Blackwell, vol. 25(2-3), pages 245-260, September.
  23. Donald B. Hausch, 1986. "Multi-Object Auctions: Sequential vs. Simultaneous Sales," Management Science, INFORMS, INFORMS, vol. 32(12), pages 1599-1610, December.
  24. A. Roth & I. Er’ev, 2010. "Learning in Extensive Form Games: Experimental Data and Simple Dynamic Models in the Intermediate Run," Levine's Working Paper Archive 387, David K. Levine.
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