IDEAS home Printed from https://ideas.repec.org/p/vnm/wpaper/138.html
   My bibliography  Save this paper

Selection matters

Author

Listed:
  • Paolo Pin

    (Department of Applied Mathematics, University of Venice)

Abstract

To test for the adaptive optimization of risk attitudes, we use a simple model of preferences among lotteries, where agents evolve with a Genetic Algorithm. We find that the genetic selection operator are fundamental in determining the outcomes of the simulations, along with the possibility of iterate choices in a single generation and an eventual factor of heritage across generations (all innocuous technical parameters at a first sight). Different choices of these mechanisms may easily lead to opposite behaviors, from risk aversion to even risk love. The simulations give a hint on the possible implications of the different selection operators, when trying to model the evolution of risk attitudes in different social and economic settings.

Suggested Citation

  • Paolo Pin, 2006. "Selection matters," Working Papers 138, Department of Applied Mathematics, Università Ca' Foscari Venezia.
  • Handle: RePEc:vnm:wpaper:138
    as

    Download full text from publisher

    File URL: http://virgo.unive.it/wpideas/storage/2006wp138.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lettau, Martin, 1997. "Explaining the facts with adaptive agents: The case of mutual fund flows," Journal of Economic Dynamics and Control, Elsevier, vol. 21(7), pages 1117-1147, June.
    2. Green, Jerry R & Stokey, Nancy L, 1983. "A Comparison of Tournaments and Contracts," Journal of Political Economy, University of Chicago Press, vol. 91(3), pages 349-364, June.
    3. Arthur J. Robson, 2002. "Evolution and Human Nature," Journal of Economic Perspectives, American Economic Association, vol. 16(2), pages 89-106, Spring.
    4. Grossman, Sanford J & Hart, Oliver D, 1983. "An Analysis of the Principal-Agent Problem," Econometrica, Econometric Society, vol. 51(1), pages 7-45, January.
    5. M. Keith Chen & Venkat Lakshminarayanan & Laurie R. Santos, 2006. "How Basic Are Behavioral Biases? Evidence from Capuchin Monkey Trading Behavior," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 517-537, June.
    6. Joost M. E. Pennings & Ale Smidts, 2003. "The Shape of Utility Functions and Organizational Behavior," Management Science, INFORMS, vol. 49(9), pages 1251-1263, September.
    7. Robson, Arthur J., 1996. "A Biological Basis for Expected and Non-expected Utility," Journal of Economic Theory, Elsevier, vol. 68(2), pages 397-424, February.
    8. Matthew Rabin, 2002. "Inference by Believers in the Law of Small Numbers," The Quarterly Journal of Economics, Oxford University Press, vol. 117(3), pages 775-816.
    9. Thomas Riechmann, 1999. "Learning and behavioral stability An economic interpretation of genetic algorithms," Journal of Evolutionary Economics, Springer, vol. 9(2), pages 225-242.
    10. Chris Starmer, 2000. "Developments in Non-expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk," Journal of Economic Literature, American Economic Association, vol. 38(2), pages 332-382, June.
    11. John A. List, 2004. "Neoclassical Theory Versus Prospect Theory: Evidence from the Marketplace," Econometrica, Econometric Society, vol. 72(2), pages 615-625, March.
    12. Levy, Moshe, 2005. "Is risk-aversion hereditary?," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 157-168, February.
    13. Arthur J. Robson, 2001. "The Biological Basis of Economic Behavior," Journal of Economic Literature, American Economic Association, vol. 39(1), pages 11-33, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Avi Waksberg & Andrew Smith & Martin Burd, 2012. "A model of decision making in an ecologically realistic environment: Relative comparison and the Independence of Irrelevant Alternatives," Journal of Bioeconomics, Springer, vol. 14(3), pages 197-215, October.
    2. Graham, Liam & Oswald, Andrew J., 2006. "Hedonic Capital," The Warwick Economics Research Paper Series (TWERPS) 745, University of Warwick, Department of Economics.
    3. Robatto, Roberto & Szentes, Balázs, 2017. "On the biological foundation of risk preferences," Journal of Economic Theory, Elsevier, vol. 172(C), pages 410-422.
    4. Neyse, Levent & Vieider, Ferdinand M. & Ring, Patrick & Probst, Catharina & Kaernbach, Christian & Eimeren, Thilo van & Schmidt, Ulrich, 2020. "Risk attitudes and digit ratio (2D:4D): Evidence from prospect theory," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue 60, pages 29-51.
    5. Anton Suvorov & Jeroen van de Ven, 2008. "Goal Setting as a Self-Regulation Mechanism," Working Papers w0122, Center for Economic and Financial Research (CEFIR).
    6. Marco Castillo & Ragan Petrie & Maximo Torero, 2008. "Rationality and the Nature of the Market," Experimental Economics Center Working Paper Series 2008-12, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University.
    7. Songjia Fan & Yi Tao & Cong Li, 2022. "Evolutionary rationality of risk preference," Papers 2206.09813, arXiv.org.
    8. Mattos, Fabio & Garcia, Philip & Pennings, Joost M.E., 2008. "Probability weighting and loss aversion in futures hedging," Journal of Financial Markets, Elsevier, vol. 11(4), pages 433-452, November.
    9. Alger, Ingela, 2021. "On the evolution of male competitiveness," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 228-254.
    10. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    11. Maarten Voors & Eleonora Nillesen & Philip Verwimp & Erwin Bulte & Robert Lensink & Daan van Soest, 2010. "Does Conflict affect Preferences? Results from Field Experiments in Burundi," HiCN Working Papers 71, Households in Conflict Network.
    12. Ewerhart, Christian, 2016. "An envelope approach to tournament design," Journal of Mathematical Economics, Elsevier, vol. 63(C), pages 1-9.
    13. Thomas J. Brennan & Andrew W. Lo & Ruixun Zhang, 2018. "Variety Is the Spice of Life: Irrational Behavior as Adaptation to Stochastic Environments," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 8(03), pages 1-39, September.
    14. Julius Pahlke & Sebastian Strasser & Ferdinand Vieider, 2015. "Responsibility effects in decision making under risk," Journal of Risk and Uncertainty, Springer, vol. 51(2), pages 125-146, October.
    15. Günther Rehme, 2011. "Endogenous Policy And Cross‐Country Growth Empirics," Scottish Journal of Political Economy, Scottish Economic Society, vol. 58(2), pages 262-296, May.
    16. Dubey, Pradeep & Wu, Chien-wei, 2001. "Competitive prizes: when less scrutiny induces more effort," Journal of Mathematical Economics, Elsevier, vol. 36(4), pages 311-336, December.
    17. Galarza, Francisco, 2009. "Choices under Risk in Rural Peru," MPRA Paper 17708, University Library of Munich, Germany.
    18. Nick Netzer, 2009. "Evolution of Time Preferences and Attitudes toward Risk," American Economic Review, American Economic Association, vol. 99(3), pages 937-955, June.
    19. Perez Truglia, Ricardo Nicolas, 2009. "On the genesis of Hedonic Adaptation," MPRA Paper 19929, University Library of Munich, Germany.
    20. Guido Baltussen & G. Post & Martijn Assem & Peter Wakker, 2012. "Random incentive systems in a dynamic choice experiment," Experimental Economics, Springer;Economic Science Association, vol. 15(3), pages 418-443, September.

    More about this item

    Keywords

    Risk preferences; genetic algorithm;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vnm:wpaper:138. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Marco LiCalzi (email available below). General contact details of provider: https://edirc.repec.org/data/dmvenit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.