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Evolutionary Analysis of Risk Attitudes in Competitive Bidding Environments Using Simulation

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Book cover Uncertainty and Risk

Part of the book series: Theory and Decision Library C ((TDLC,volume 41))

Abstract

Exactly how risk-averse a person should be is an elusive question that may be answerable only through evolutionary analysis. The literature on the evolution of risk attitudes is quite diffuse. Researchers have taken widely varying approaches. A survey of these approaches is presented. One approach to study the evolution is to simulate a small society of individuals whose risk taking behaviors are interrelated according to simple rules. The aim of this paper is to introduce a few different ways to conduct such simulations and visualize the results. These approaches can be extended in diverse ways. While this type of simulation is unlikely to produce normative or prescriptive results for an individual, it may reveal some facts about the collective fate of a society. Simulation codes written in Mathematica are included.

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References

  • Abreu, D., Rubinstein, A. (1988), “The structure of nash equilibrium in repeated games with finite automata.” Econometrica, Vol. 56, No. 6, pp. 1259–1281.

    Article  Google Scholar 

  • Ben-Porath, E. (1993), “Repeated games with finite automata.” Journal of Economic Theory. Vol. 59, pp. 17–32.

    Article  Google Scholar 

  • Bell, D.E. (1988), “One-switch utility functions and a measure of risk.” Management Science, Vol. 34, pp. 1416–1424.

    Google Scholar 

  • Bell, D.E. (1995), “A contextual uncertainty condition for behavior under risk.” Management Science. Vol. 41, pp. 1145–1150.

    Google Scholar 

  • Bell, D.E., Fishburn, P.C. (2000), “Utility functions for wealth.” Journal of Risk and Uncertainty. Vol. 20, pp. 5–44.

    Article  Google Scholar 

  • Bernoulli, D. (1738), “Specimen theoriae novae de mensura sortis.” Commentarii Academiae Scientiarum Imperialis Petropolitanae. Vol. 5, pp. 175–192. Translated in L. Sommer (1954), “Exposition of a new theory on the measurement of risk.” Econometrica, Vol. 22, pp. 23–36.

    Google Scholar 

  • Binmore, K., Samuelson, L. (1999), “Evolutionary drift and equilibrium selection.” Review of Economic Studies, Vol. 66, pp. 363–393.

    Article  Google Scholar 

  • Borch, K. (1968), “Decision rules depending on the probabilty of ruin.” Oxford Economic Papers, Vol. 20, No. 1, pp. 1–10.

    Google Scholar 

  • Bordley, R., Calzi, L.M. (2000), “Decision analysis using targets instead of utility functions.” Decisions in Economics and Finance Vol. 23, pp. 53–74.

    Article  Google Scholar 

  • Cooper, W.S. (1987), “Decision theory as a branch of evolutionary theory: A biological derivation of the Savage axioms”. Psychological Review, Vol. 94, No. 4, pp. 395–411.

    Article  Google Scholar 

  • Degeorge, F., Moselle, B., Zeckhauser, R. (2004), “The ecology of risk taking.” The Journal of Risk and Uncertainty. Vol. 28, No. 3, pp. 195–215.

    Article  Google Scholar 

  • Dekel, E., Scotchmer, S. (1999), “On the evolution of attitudes towards risk in winner-take-all games.” Journal of Economic Theory, Vol. 87, pp. 125–143.

    Article  Google Scholar 

  • Ellison, G. (2000), “Basins of attraction, long-run stochastic stability, and the speed of step-by-step evolution.” Review of Economic Studies, Vol. 67, pp. 17–45.

    Article  Google Scholar 

  • Friedman, D. (1996), “Equilibrium in evolutionary games: Some experimental results.” The Economic Journal, Vol. 106, pp. 1–25.

    Article  Google Scholar 

  • Gaylord, R.J., D’Andria, L.J. (1998), Simulating Society: A Mathematica Toolkit for Modeling Socioeconomic Behavior. Springer, Berlin Heidelberg New York.

    Google Scholar 

  • Hagen, O. (1992), “Survival through the Allais paradox.” Theory and Decision, Vol. 32, pp. 209–217.

    Article  Google Scholar 

  • Harsanyi, J. (1967), “Games with incomplete information played by Bayesian players, Part I: The basic model,” Management Science, Vol. 14, pp. 159–82.

    Google Scholar 

  • Hodgson, G.M. (1993a), “The Mecca of Alfred Marshall,” The Economic Journal, Vol. 103, No. 417, pp. 406–415.

    Article  Google Scholar 

  • Hodgson, G.M. (1993b), Economics and Evolution: Bringing Life Back into Economics. Polity Press, Cambridge, MA.

    Google Scholar 

  • Kandori, M., Mailath, G.J., Rob, R. (1993), “Learning, mutation, and long run equilibria in games.” Econometrica, Vol. 61, No. 1, pp. 29–56.

    Article  Google Scholar 

  • Karni, E., Schmeidler, D. (1986), “Self-preservation as a foundation of rational behavior under risk.” Journal of Economic Behavior and Organization, Vol. 7, pp. 71–81.

    Article  Google Scholar 

  • Keenan, D.C., O’Brien, M.J. (1993), “Competition, collusion and chaos.” Journal of Economic Dynamics and Control, Vol. 17, pp. 327–353.

    Article  Google Scholar 

  • Kelly Jr., J.L. (1956), “A new interpretation of information rate.” The Bell System Technical Journal, Vol. 35, pp. 917–926.

    Google Scholar 

  • Kreps, D.M. (1990), A Course in Microeconomic Theory. Princeton University Press, Princeton, NJ.

    Google Scholar 

  • Levy, M. (2003), “Are rich people smarter?” Journal of Economic Theory. Vol. 11, pp. 42–64.

    Article  Google Scholar 

  • Lippman, S.A., Mamer, J.W. (1988), “When many wrongs make a right: An asymptotic analysis of risk aversion and additive risks.” Probability in the Engineering and Information Sciences, Vol. 2, pp. 115–127.

    Article  Google Scholar 

  • Marshall, A. (1961), The Principles of Economics. 9th edition, Macmillan, London.

    Google Scholar 

  • Maynard Smith, J. (1982), Evolution and the Theory of Games. Cambridge University Press, New York.

    Google Scholar 

  • McCardle, K.F., Winkler, R.L. (1992), “Repeated gambles, learning and risk aversion.” Management Science, Vol. 38, No. 6, pp. 807–818.

    Google Scholar 

  • Morris, S. (2000), “Contagion.” Review of Economic Studies, Vol. 67, pp. 57–78.

    Article  Google Scholar 

  • Oechssler, J., Riedel, F. (2002), “On the dynamic foundation of evolutionary stability in continuous models.” Journal of Economic Theory. Vol. 107, pp. 223–252.

    Article  Google Scholar 

  • Pollock, G.B., Lewis, K. (1993), “Gambling in a Malthusian universe.” Rationality and Society, Vol. 5, No. 1, pp. 85–106.

    Article  Google Scholar 

  • Pratt, J.W., Zeckhauser, R.J. (1987), “Proper risk aversion.” Econometrica, Vol. 55, No. 1, pp. 143–154.

    Article  Google Scholar 

  • Robson, A.J. (1996), “A biological basis for expected and non-expected utility.” Journal of Economic Theory, Vol. 68, pp. 397–424.

    Article  Google Scholar 

  • Rothkopf, M.H., Harstad, R.M. (1994), “Modeling competitive bidding: A critical essay.” Management Science, Vol. 40, No. 3, pp. 364–384.

    Article  Google Scholar 

  • Savage, L.J. (1972), The Foundations of Statistics. Dover, New York.

    Google Scholar 

  • Sinn, H.-W. (2003), “Weber’s law and the biological evolution of risk preferences: The selection dominance of the logarithmic utility function”, 2002 Geneva Risk Lecture. The Geneva Papers on Risk and Insurance Theory, Vol. 28, No. 2, pp. 87–100.

    Article  Google Scholar 

  • Spencer, H. (1890), First Principles, 5th edition, Williams and Norgate, London.

    Google Scholar 

  • Spencer, H. (1892), Essays Scientific, Political and Speculative. Appleton, New York.

    Google Scholar 

  • Taylor, P., Jonker, L. (1978), “Evolutionarily stable strategies and game dynamics.” Mathematical Biosciences, Vol. 40, pp. 145–156.

    Article  Google Scholar 

  • Weibull, J.W. (1997), Evolutionary Game Theory. MIT Press, Cambridge, MA.

    Google Scholar 

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Sounderpandian, J. (2007). Evolutionary Analysis of Risk Attitudes in Competitive Bidding Environments Using Simulation. In: Abdellaoui, M., Luce, R.D., Machina, M.J., Munier, B. (eds) Uncertainty and Risk. Theory and Decision Library C, vol 41. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48935-1_16

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