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On the Potential Use of Adaptive Control Methods for Improving Adaptive Natural Resource Management

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  • Bond, Craig A.

Abstract

The paradigm of adaptive natural resource management (AM), in which experiments are used to learn about uncertain aspects of natural systems, is gaining prominence as the preferred technique for administration of large-scale environmental projects. To date, however, tools consistent with economic theory have yet to be used to either evaluate AM strategies or improve decision-making in this framework. Adaptive control (AC) techniques provide such an opportunity. This paper demonstrates the conceptual link between AC methods, the alternative treatment of realized information during a planning horizon, and AM practices; shows how the different assumptions about the treatment of observational information can be represented through alternative dynamic programming model structures; and provides a means of valuing alternative treatments of information and augmenting traditional benefit-cost analysis through a decomposition of the value function. The AC approach has considerable potential to help managers prioritize experiments, plan AM programs, simulate potential AM paths, and justify decisions based on an objective valuation framework.

Suggested Citation

  • Bond, Craig A., 2008. "On the Potential Use of Adaptive Control Methods for Improving Adaptive Natural Resource Management," Working Papers 108721, Colorado State University, Department of Agricultural and Resource Economics.
  • Handle: RePEc:ags:csdawp:108721
    DOI: 10.22004/ag.econ.108721
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    File URL: http://ageconsearch.umn.edu/record/108721/files/wp002-08.pdf
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    References listed on IDEAS

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    12. Kiefer, Nicholas M & Nyarko, Yaw, 1989. "Optimal Control of an Unknown Linear Process with Learning," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 571-586, August.
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    Cited by:

    1. Craig A. Bond & John B. Loomis, 2009. "Using Numerical Dynamic Programming to Compare Passive and Active Learning in the Adaptive Management of Nutrients in Shallow Lakes," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 57(4), pages 555-573, December.

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    Resource /Energy Economics and Policy;

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