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Expert systems and economic policy analysis: An application to OCS auction leasing

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Abstract

In this paper we argue that expert systems can be powerful tools for modelling microeconomic systems, including both individual decision making and the coordination of individual agents in a resource allocation mechanism. Using the fact that expert systems are essentially computerized versions of decision processes, we illustrate how they can be viewed as generalized process models of decision-making. We argue that the expert system approach is beneficial because it allows a policy analyst to explore the implication of policy alternatives without having to incur the generally prohibitive cost of field implementation studies. Further, enables the incorporation and updating of decision strategies and qualitative information, which human experts typically use but which is not amenable to pure mathematical modelling.

One particular microeconomic system we suggest could be modelled as an expert system is the OCS offshore oil lease auction process. Moreover, we argue that constructing such an expert system model would require the development of two integrated expert systems: one for the auction process and subsequent resource allocation and the other to model the individual bidding behavior of the auction participants. We set out the structure of the auction expert system in some detail and discuss rules of thumb used by bidders inferred from our empirical research on past OCS auctions.

Such an expert system of an auction leasing process could provide benefits to both bidders (e.g., oil companies) and the auctioneer (e.g., the Department of the Interior) as well. Bidders, by trying different strategies against different hypothesized strategies by their opponents could use such an integrated expert system to improve their bidding performances. The auctioneer, on the other hand, could test the efficiency of various proposed auction institutions under different assumptions about bidding behavior. In some circumstances, it might be desirable to even automate the auction process with a network coordinating the expert systems used by the individual firms and a computerized auctioneer.

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References

  • Battalio, R.C., Kogut, J., and Meyer, J., 1988, Individual and Market Bidding in a Vickrey First Price Auction: Varying Market Size and Information, in L. Green and J.H. Kagel (eds.), Advances and Behavioral Economics, vol. 2, Norwood, NJ Ablex Publishing.

    Google Scholar 

  • Belovicz, M.W., 1979, Sealed-Bid Auctions: Experimental Results and Applications, in V.L. Smith (ed.), Research in Experimental Economics, vol. 1, JAI Press, Greenwich, CT, pp. 279–338.

    Google Scholar 

  • Bever, R.C., Marsden, J.R., Salas-Fumas, V. and Whinston, A., 1982, Verifying the usefulness of process models applied to forecasting, Final Report EA-2441, Electric Power Research Institute, Palo Alto, CA.

    Google Scholar 

  • Coppinger, V., Smith, V.L., and Titus, J., 1980, Incentives and behavior in English, Dutch, and sealed-bid auctions, Economic Inquiry 18, 1–22.

    Google Scholar 

  • Cox, J.C., Isaac, R.M., and Smith, V.L., 1983, OCS auctions: incentives and the performance of alternative bidding institutions, Supreme Court Economic Review 2, 43–87.

    Google Scholar 

  • Cox, J.C., Robertson, B., and Smith, V., 1982, Theory and behavior in single object auctions, in V. Smith (ed.), Research in Experimental Economics, Vol. 2, JAI Press, Greenwich, CT.

    Google Scholar 

  • Cox, J.C., Smith, V.L., and Walker, J.M., 1985, Experimental development of sealed bid auction theory: calibrating controls for risk aversion, American Economic Review (Papers and Proceedings) 75, 160–165.

    Google Scholar 

  • Cox, J.C., Smith, V.L., and Walker, J.M., 1986, Theory and behavior of first price auctions, Unpublished manuscript, University of Arizona.

  • Davis, R., et al. 1981, The Dipmeter Advisor: interpretation of geological signals, Seventh Joint Conference on Artificial Intelligence, Vancouver, British Columbia, Canada.

  • Duda et al., 1979, Model design in the prospector consultant system for mineral exploration, in Donald Michie (ed.), Expert Systems in the Micro-Electronic Age, Edinburgh University Press, Edinburgh.

    Google Scholar 

  • Einhorn, J. Hillel, and Hogarth, R. M., 1981, behavioral decision theory: processes of judgement and choice, Annual Review of Psychology 32, 53–88.

    Google Scholar 

  • Engelbrecht-Wiggans, R., 1980, Auctions and bidding models: a survey, Management Science 26, 119–142.

    Google Scholar 

  • Gershman, A., 1982, Building a geological expert system for dipmeter interpretation, Proc. European Conference on Artificial Intelligence.

  • Griffin, J.M., 1972, The process analysis alternative to statistical cost functions: an application to petroleum refining, American Economic Review 62, 46–56.

    Google Scholar 

  • Hoffman, E., Jacob, V.S., Marsden, J.R., and Whinston, A., 1986, Artificial intelligence in economics — expert systems modelling microeconomic systems, in L.F. Pau (ed.), Artificial Intelligence in Economics and Management, North-Holland, Amsterdam.

    Google Scholar 

  • Hoffman, E., Jacob, V.S., Marsden, J.R., and Whinston, A., 1987, Development, use, and verification of expert systems in modelling microeconomic systems, in Clyde W. Holsapple and Andrew B. Whinston (ed.), Decision Support Systems: Theory and Application, Springer-Verlag, Heidelberg.

    Google Scholar 

  • Hoffman, E., and Marsden, J.R., 1986a, Empirical evidence on competitive bidding: some surprising results, Economics Letters 22, 15–21.

    Google Scholar 

  • Hoffman, E., and Marsden, J.R., 1986b, Testing informational assumptions in common value bidding models, Scandanavian Journal of Economics 88(4), 627–641.

    Google Scholar 

  • Hoffman, R., Marsden, J.R., and Saidibaghgandomi, R., 1987a, A note on the analysis of OCS oil lease auctions — some empirical results and their implications for the design of laboratory experiments, unpublished manuscript, University of Arizona.

  • Hoffman, E., Marsden, J.R., and Saidibaghgandomi, R., 1987b, Joint bidding in common value auctions: evidence from offshore oil lease auctions, unpublished manuscript, University of Arizona.

  • Hoffman, E., Marsden, J.R., and Saidibaghgandomi, R., 1987c, Sequential simultaneous multiobject auctions: some evidence from OCS leasing data, Unpublished manuscript, University of Arizona.

  • Hoffman, E., Marsden, J.R., and Saidibaghgandomi, R., 1987d, Testing the continuity of individual bid density functions — some further results, Economics Letters 24, 388–402.

    Google Scholar 

  • Hoffman, E., Marsden, J.R., and Whinston, A., (forthcoming a), Laboratory experiments and computer simulation: an introduction to the use of experiments and process models in economic analysis, in L. Green and J. H. Kagel (eds.), Advances in Behavioral Economics, Vol. 2, Ablex Publishing, Norwood, NJ.

  • Hoffman, E., Marsden, J.R., and Whinston, A., 1986, Using different economic data forms, Journal of Behavioral Economics 15, 67–84.

    Google Scholar 

  • Hoffman, E., and Spitzer, M.L., 1985, Experimental law and economics: an introduction, Columbia Law Review 85(5), 991–1036.

    Google Scholar 

  • Holsapple, C.W., and Whinston, A.B., 1987, Business Expert Systems Irwin, Homewood, IL.

    Google Scholar 

  • Holt, C.A., 1980, Competitive bidding for contracts under alternative auction procedures, Journal of Political Economy 88, 433–445.

    Google Scholar 

  • Kagel, J.H., Harstad, R.M., and Levin, D., 1987, Son of winner's curse: bidder behavior and public information in second price common value auctions, Economic Science Association Annual Meetings, Tucson, Arizona, March.

  • McAfee, R.P., and McMillan, J., 1987, Auctions and bidding, Journal of Economic Literature 25.

  • Marsden, J.R., Pingry, D.E., and Whinston, A., 1972, Production function theory and the optimal design of waste treatment facilities, Applied Economics, 279–290.

  • Marsden, J.R., Pingry, D.E., and Whinston, A., 1974a, Engineering foundations of the production function, Journal of Economic Theory 9, 124–140.

    Google Scholar 

  • Marsden, J.R., Pingry, D.E., and Whinston, A., 1974b, The process analysis alternative to statistical cost functions: comment, American Economic Review 64, 773–776.

    Google Scholar 

  • Milgrom, P., and Weber, R., 1982, A theory of auctions and competitive bidding, Econometrica 50, 1089–1122.

    Google Scholar 

  • Riley, J.C., and Samuelson, W.F., 1981, Optimal auctions, American Economic Review 71, 381–392.

    Google Scholar 

  • Smith, V.L., 1962, An experimental study of competitive market behavior, Journal of Political Economy 70, 111–137.

    Google Scholar 

  • Smith, V.L., 1982, Microeconomic systems as an experimental science, American Economic Review 72, 923–955.

    Google Scholar 

  • Tsao, C.S., and Day, R.H., 1971, A process analysis model of the U.S. steel industry, Management Science 17(10), B588-B608.

    Google Scholar 

  • Vickrey, W., 1961, Counterspeculation, auctions, and competitive sealed tenders, Journal of Finance 16, 8–37.

    Google Scholar 

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Hoffman, E., Jacob, V.S., Marsden, J.R. et al. Expert systems and economic policy analysis: An application to OCS auction leasing. Computer Science in Economics and Management 1, 113–135 (1988). https://doi.org/10.1007/BF00427159

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