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Resource Allocation Models with Risk Aversion and Probabilistic Dependence: Offshore Oil and Gas Bidding

Author

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  • Donald L. Keefer

    (Department of Decision and Information Systems, College of Business, Arizona State University, Tempe, AZ 85287-4206)

Abstract

Bidding for offshore U.S. oil and gas leases is a major corporate resource allocation problem involving enormous uncertainties and very high stakes. This paper presents two new, operationally useful decision analysis models to aid in bidding for oil and gas leases. They are unique in that they consider risk aversion and probabilistic dependence among the values of the leases, with both bid levels and partnership shares as (continuous) decision variables. They are suitable for use in evaluating proposed bidding policies or as objective functions in optimization formulations. Practicality of their data requirements is evidenced by use of one of the models for several years in a major oil company. Comparison of optimal solutions to these models on a small example, using actual oil-company data, demonstrates the importance of taking risk aversion and probabilistic dependence into account, and provides insight into the adequacy of independence and conditional dependence as approximations for dependence. These results are pertinent to other real-world allocation problems that share many of the characteristics of bidding problems, such as R&D funds allocation.

Suggested Citation

  • Donald L. Keefer, 1991. "Resource Allocation Models with Risk Aversion and Probabilistic Dependence: Offshore Oil and Gas Bidding," Management Science, INFORMS, vol. 37(4), pages 377-395, April.
  • Handle: RePEc:inm:ormnsc:v:37:y:1991:i:4:p:377-395
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    File URL: http://dx.doi.org/10.1287/mnsc.37.4.377
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    Cited by:

    1. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Decision analysis in energy and environmental modeling: An update," Energy, Elsevier, vol. 31(14), pages 2604-2622.
    2. Li, Zhen & Kuo, Ching-Chung, 2011. "Revenue-maximizing Dutch auctions with discrete bid levels," European Journal of Operational Research, Elsevier, vol. 215(3), pages 721-729, December.
    3. James E. Smith & Detlof von Winterfeldt, 2004. "Anniversary Article: Decision Analysis in Management Science," Management Science, INFORMS, vol. 50(5), pages 561-574, May.

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