Advertisement

Preference discovery

  • Jason Delaney
  • Sarah JacobsonEmail author
  • Thorsten Moenig
Original Paper
  • 5 Downloads

Abstract

Is the assumption that people automatically know their own preferences innocuous? We present an experiment studying the limits of preference discovery. If tastes must be learned through experience, preferences for some goods may never be learned because it is costly to try new things, and thus non-learned preferences may cause welfare loss. We conduct an online experiment in which finite-lived participants have an induced utility function over fictitious goods about whose marginal utilities they have initial guesses. Subjects learn most, but not all, of their preferences eventually. Choice reversals occur, but primarily in early rounds. Subjects slow their sampling of new goods over time, supporting our conjecture that incomplete learning can persist. Incomplete learning is more common for goods that are rare, have low initial value guesses, or appear in choice sets alongside goods that appear attractive. It is also more common for people with lower incomes or shorter lifetimes. More noise in initial value guesses has opposite effects for low-value and high-value goods because it affects the perceived likelihood that the good is worth trying. Over time, subjects develop a pessimistic bias in beliefs about goods’ values, since optimistic errors are more likely to be corrected. Overall, our results show that if people need to learn their preferences through consumption experience, that learning process will cause choice reversals, and even when a person has completed sampling the goods she is willing to try, she may continue to lose welfare because of suboptimal choices that arise from non-learned preferences.

Keywords

Discovered preferences Preference stability Learning 

JEL Classification

D81 D83 D01 D03 

Notes

Acknowledgements

We are grateful for helpful comments from the editor and two anonymous referees. For advice early on, we thank Yongsheng Xu, Annemie Maertens, and participants at FUR 2012, SABE/IAREP/ICABEEP 2013, and seminars at Williams College and George Mason University, and we particularly thank CeMENT 2014 participants Brit Grosskopf, Muriel Niederle, J. Aislinn Bohren, Angela de Oliveira, Jessica Hoel, and Jian Li for detailed feedback. We gratefully acknowledge funding from the Williams College Hellman Fellows Grant.

Supplementary material

10683_2019_9628_MOESM1_ESM.pdf (179 kb)
Supplementary material 1 (pdf 179 KB)
10683_2019_9628_MOESM2_ESM.pdf (904 kb)
Supplementary material 2 (pdf 904 KB)

References

  1. Aghion, P., Bolton, P., Harris, C., & Jullien, B. (1991). Optimal learning by experimentation. The Review of Economic Studies, 58(4), 621–654.CrossRefGoogle Scholar
  2. Andersen, S., Harrison, G. W., Lau, M. I., & Rutstrom, E. E. (2008). Lost in state space: Are preferences stable? International Economic Review, 49(3), 1091–1112.CrossRefGoogle Scholar
  3. Ariely, D., Loewenstein, G., & Prelec, D. (2003). “Coherent arbitrariness”: Stable demand curves without stable preferences. The Quarterly Journal of Economics, 118(1), 73–105.CrossRefGoogle Scholar
  4. Armantier, O., Lévy-Garboua, L., Owen, C., & Placido, L. (2016). Discovering preferences: A theoretical framework and an experiment.Google Scholar
  5. Becker, G. S. (1996). Accounting for tastes. Harvard: Harvard University Press.Google Scholar
  6. Braga, J., & Starmer, C. (2005). Preference anomalies, preference elicitation and the discovered preference hypothesis. Environmental and Resource Economics, 32(1), 55–89.CrossRefGoogle Scholar
  7. Brezzi, M., & Lai, T. L. (2000). Incomplete learning from endogenous data in dynamic allocation. Econometrica, 68(6), 1511–1516.  https://doi.org/10.1111/1468-0262.00170.CrossRefGoogle Scholar
  8. Chen, D. L., Schonger, M., & Wickens, C. (2016). oTree: An open-source platform for laboratory, online, and field experiments. Journal of Behavioral and Experimental Finance, 9, 88–97.CrossRefGoogle Scholar
  9. Chuang, Y., & Schechter, L. (2015). Stability of experimental and survey measures of risk, time, and social preferences: A review and some new results. Journal of Development Economics, 117, 151–170.  https://doi.org/10.1016/j.jdeveco.2015.07.008.CrossRefGoogle Scholar
  10. Cooke, K. (2017). Preference discovery and experimentation. Theoretical Economics, 12(3), 1307–1348.CrossRefGoogle Scholar
  11. Coursey, D. L., Hovis, J. L., & Schulze, W. D. (1987). The disparity between willingness to accept and willingness to pay measures of value. The Quarterly Journal of Economics, 102(3), 679–690.CrossRefGoogle Scholar
  12. Cox, J. C., & Grether, D. M. (1996). The preference reversal phenomenon: Response mode, markets and incentives. Economic Theory, 7(3), 381–405.CrossRefGoogle Scholar
  13. Dasgupta, U., Gangadharan, L., Maitra, P., & Mani, S. (2017). Searching for preference stability in a state dependent world. Journal of Economic Psychology, 62(Supplement C), 17–32.  https://doi.org/10.1016/j.joep.2017.05.001.CrossRefGoogle Scholar
  14. Delaney, J. J., Jacobson, S. A., & Moenig, T. P. (2019). A theory of preference discovery.Google Scholar
  15. Easley, D., & Kiefer, N. M. (1988). Controlling a stochastic process with unknown parameters. Econometrica, 56(5), 1045–1064.CrossRefGoogle Scholar
  16. Eckel, C. C., El-Gamal, M. A., & Wilson, R. K. (2009). Risk loving after the storm: A bayesian-network study of hurricane katrina evacuees. Journal of Economic Behavior and Organization, 69(2), 110–124.  https://doi.org/10.1016/j.jebo.2007.08.012.CrossRefGoogle Scholar
  17. Kahneman, D., & Snell, J. (1990). Predicting utility. In R. M. Hogarth (Ed.), Insights in decision making: A tribute to Hillel J (pp. 295–310). London: University of Chicago Press.Google Scholar
  18. Kahneman, D., Wakker, P. P., & Sarin, R. (1997). Back to Bentham? explorations of experienced utility. The Quarterly Journal of Economics, 112(2), 375–405.CrossRefGoogle Scholar
  19. Keller, G., & Rady, S. (1999). Optimal experimentation in a changing environment. The Review of Economic Studies, 66(3), 475–507.CrossRefGoogle Scholar
  20. Kihlstrom, R. E., Mirman, L. J., & Postlewaite, A. (1984). Experimental consumption and the ‘Rothschild Effect’., Studies in Bayesian econometrics, New York; Amsterdam and Oxford: North-Holland; distributed in U.S. and Canada by Elsevier Science, New York (vol. 5, pp. 279–302).Google Scholar
  21. Lichtenstein, S., & Slovic, P. (2006). The construction of preference. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  22. List, J. A. (2003). Does market experience eliminate market anomalies? The Quarterly Journal of Economics, 118(1), 41.CrossRefGoogle Scholar
  23. Loewenstein, G., & Adler, D. (1995). A bias in the prediction of tastes. The Economic Journal, 105(431), 929–937.CrossRefGoogle Scholar
  24. Noussair, C., Robin, S., & Ruffieux, B. (2004). Revealing consumers’ willingness-to-pay: A comparison of the BDM mechanism and the Vickrey auction. Journal of Economic Psychology, 25(6), 725–741.CrossRefGoogle Scholar
  25. Piermont, E., Takeoka, N., & Teper, R. (2016). Learning the krepsian state: Exploration through consumption. Games and Economic Behavior, 100, 69–94.  https://doi.org/10.1016/j.geb.2016.09.002.CrossRefGoogle Scholar
  26. Plott, C.R. (1996). Rational individual behaviour in markets and social choice processes: The discovered preference hypothesis. In: K.J. Arrow, et al (Eds.) The rational foundations of economic behaviour: Proceedings of the IEA Conference held in Turin, Italy, IEA Conference (vol. 114, pp. 225–250). New York: St. Martin’s Press; London: Macmillan Press in association with the International Economic Association.Google Scholar
  27. Rothschild, M. (1974). A two-armed bandit theory of market pricing. Journal of Economic Theory, 9(2), 185–202.CrossRefGoogle Scholar
  28. Scitovsky, T. (1976). The joyless economy: An inquiry into human satisfaction and consumer dissatisfaction. Oxford: Oxford University Press.Google Scholar
  29. Shogren, J. F., Cho, S., Koo, C., List, J., Park, C., Polo, P., et al. (2001). Auction mechanisms and the measurement of WTP and WTA. Resource and Energy Economics, 23(2), 97–109.CrossRefGoogle Scholar
  30. Shogren, J. F., Shin, S. Y., Hayes, D. J., & Kliebenstein, J. B. (1994). Resolving differences in willingness to pay and willingness to accept. American Economic Review, 84(1), 255–270.Google Scholar
  31. Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. London: Penguin.Google Scholar
  32. van de Kuilen, G., & Wakker, P. P. (2006). Learning in the Allais paradox. Journal of Risk and Uncertainty, 33(3), 155–164.CrossRefGoogle Scholar
  33. Weber, R. A. (2003). Learning with no feedback in a competitive guessing game. Games and Economic Behavior, 44(1), 134–144.  https://doi.org/10.1016/S0899-8256(03)00002-2.CrossRefGoogle Scholar
  34. Wilson, T. D., & Gilbert, D. T. (2005). Affective forecasting: Knowing what to want. Current Directions in Psychological Science, 14(3), 131–134.  https://doi.org/10.1111/j.0963-7214.2005.00355.x.CrossRefGoogle Scholar

Copyright information

© Economic Science Association 2019

Authors and Affiliations

  1. 1.School of BusinessGeorgia Gwinnett CollegeLawrencevilleUSA
  2. 2.Department of EconomicsWilliams CollegeWilliamstownUSA
  3. 3.Fox School of BusinessTemple UniversityPhiladelphiaUSA

Personalised recommendations