Experimental Economics

, Volume 9, Issue 3, pp 281–295 | Cite as

Misperceiving the value of information in predicting the performance of others

  • George LoewensteinEmail author
  • Don A. Moore
  • Roberto A. Weber


Economic models typically allow for “free disposal” or “reversibility” of information, which implies non-negative value. Building on previous research on the “curse of knowledge” we explore situations where this might not be so. In three experiments, we document situations in which participants place positive value on information in attempting to predict the performance of uninformed others, even when acquiring that information diminishes their earnings. In the first experiment, a majority of participants choose to hire informed—rather than uninformed—agents, leading to lower earnings. In the second experiment, a significant number of participants pay for information—the solution to a puzzle—that hurts their ability to predict how many others will solve the puzzle. In the third experiment, we find that the effect is reduced with experience and feedback on the actual performance to be predicted. We discuss implications of our results for the role of information and informed decision making in economic situations.


Experiments Information Bias 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Supplementary material

10683_2006_Article_9128.pdf (23 kb)
Supplementary material (23.1 KB)


  1. Stigler, G. (1961). The economics of information. Journal of Political Economy, 69(3), 213–225CrossRefGoogle Scholar
  2. Akerlof, G. A., & Kranton, R. E. (2000). Economics and identity. Quarterly Journal of Economics, 115, 713–753CrossRefGoogle Scholar
  3. Babcock, L., & Loewenstein, G. (1997). Explaining bargaining impasse: the role of self-serving biases. Journal of Economic Perspectives, 11, 109–126Google Scholar
  4. Banerjee, A. V. (1992). A simple model of herd behavior. Quarterly Journal of Economics, 107, 797–817CrossRefGoogle Scholar
  5. Bar-Hillel, M. (1990). Back to base rates. In Hogarth, R. M. (Ed.), Insights in decision making: A tribute to Hillel J. Einhorn (pp. 200–216). Chicago, IL: The University of Chicago PressGoogle Scholar
  6. Camerer, C. F. (1992). The rationality of prices and volume in experimental markets. Organizational Behavior and Human Decision Processes, 51, 237–272CrossRefGoogle Scholar
  7. Camerer, C., Loewenstein, G., & Weber, M. (1989). The curse of knowledge in economic settings: an experimental analysis. The Journal of Political Economy, 97, 1232–1254CrossRefGoogle Scholar
  8. Caplin, A., & Leahy, J. (2001). Psychological expected utility theory and anticipatory feelings. Quarterly Journal of Economics, 116, 55–79CrossRefGoogle Scholar
  9. Charness, G., & Gneezy, U. (2003). Portfolio choice and risk attitudes: An experimental study. Working paperGoogle Scholar
  10. Earl, P. E. (1990). Economics and psychology: a survey. The Economic Journal, 100(402), 718–755CrossRefGoogle Scholar
  11. Engelmann, D., & Strobel, M. (2004). The false consensus effect: Deconstruction and reconstruction of an anomaly, Working paperGoogle Scholar
  12. Fischhoff, B. (1975). Hindsight ≠ foresight: The effect of outcome knowledge on judgment under uncertainty. Journal of Experimental Psychology: Human Perception and Performance, 104, 288–299CrossRefGoogle Scholar
  13. Gneezy, U., & Potters, J. (1997). An experiment on risk-taking and evaluation periods. Quarterly Journal of Economics, 112, 631–645CrossRefGoogle Scholar
  14. Goldstein, D. G., & Gigerenzer, G. (1999). The recognition heuristic: how ignorance makes us smart. In G. Gigerenzer, P. M. Todd, & the ABC Research Group (Eds.), Simple heuristics that make us smart(pp. 37–58). New York: Oxford University PressGoogle Scholar
  15. Goldstein, D. G., & Gigerenzer, G. (2005). The recognition heuristic and the less-is-more effect. In C. R. Plott and V. L. Smith (Eds.), Handbook of experimental results, volume 1. Amsterdam: North Holland/Elsevier PressGoogle Scholar
  16. Hinds, P. J. (1999). The curse of expertise: The effects of expertise and debiasing methods on prediction of novice performance. Journal of Experimental Psychology: Applied, 5(2), 205–221CrossRefGoogle Scholar
  17. Hoch, S., & Loewenstein, G. (1989). Outcome feedback: Hindsight and information. Journal of Experimental Psychology: Learning, Memory and Cognition, 15, 605–619CrossRefGoogle Scholar
  18. Koszegi, B. (2001). Who has anticipatory feelings. Working Paper. University of California, BerkeleyGoogle Scholar
  19. Lewis, T. R., & Sappington, D. E. M. (1997). Information management in incentive problems. The Journal of Political Economy, 105(4), 796–821CrossRefGoogle Scholar
  20. Loewenstein, G. (1987). Anticipation and the valuation of delayed consumption. Economic Journal, 97, 666–684CrossRefGoogle Scholar
  21. Loewenstein, G. (1999). Because it is there: The challenge of mountaineering⋯for utility theory. Kyklos, 52, 315–344Google Scholar
  22. Lord, C., Lepper, M. R., & Ross, L. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37, 2098–2110CrossRefGoogle Scholar
  23. Newton, L. (1990). Overconfidence in the communication of intent: Heard and unheard melodies. Unpublished doctoral dissertation. Stanford. CA: Stanford University.Google Scholar
  24. Osband, K. (1989). Optimal forecasting incentives. The Journal of Political Economy, 97(5), 1091–1112CrossRefGoogle Scholar
  25. Ouden, P. H. den (2006). Development of a design analysis model for consumer complaints: Revealing a new class of quality failures. Eindhoven, the Netherlands: Technische Universiteit Eindhoven. Unpublished doctoral dissertationGoogle Scholar
  26. Porter, R. H. (1995). The role of information in U.S. offshore oil and gas lease auctions. Econometrica, 63(1), 1–27CrossRefGoogle Scholar
  27. Rabin, M. (1993). Incorporating fairness into game theory and economics. American Economic Review, 83(5), 1281–1302Google Scholar
  28. Rabin, M., & Schrag, J. (1999). First impressions matter: a model of confirmatory bias. Quarterly Journal of Economics, 114(1), 37–82CrossRefGoogle Scholar
  29. Rensink, R. A., O’Regan, J. K., & Clark, J. J. (1997). To see or not to see: the need for attention to perceive changes in Scenes. Psychological Science, 8, 368–373CrossRefGoogle Scholar
  30. Ross, L., Lepper, M. R., & Hubbard, M. (1975). Perseverance in self perception and social perception: biased attributional processes in the debriefing paradigm. Journal of Personality and Social Psychology, 32, 880–892CrossRefGoogle Scholar
  31. Ross, L., Greene, D., & House, P. (1977). The ‘false consensus effect’: an egocentric bias in social perception and attribution processes. Journal of Experimental Social Psychology, 13, 279–301CrossRefGoogle Scholar
  32. Ross, L., & Ward, A. (1996). Naive realism in everyday life: Implications for social conflict and misunderstanding. In E. Reed, E. Turiel, and T. Brown (Eds.), Social cognition: The Ontario Symposium(pp. 305–321). Hillsdale. NJ: ErlbaumGoogle Scholar
  33. Siegel, S., & Castellan, N. J. Jr. (1988). Nonparametric statistics for the behavioral sciences. Boston. MA: McGraw-HillGoogle Scholar
  34. Simons, D. J., & Levin, D. T. (1997). Change blindness. Trends in Cognitive Science, 1, 261–267CrossRefGoogle Scholar

Copyright information

© Economic Science Association 2006

Authors and Affiliations

  • George Loewenstein
    • 1
    Email author
  • Don A. Moore
    • 2
  • Roberto A. Weber
    • 1
  1. 1.Department of Social and Decision SciencesCarnegie Mellon UniversityPittsburgh
  2. 2.Tepper School of BusinessCarnegie Mellon UniversityPittsburgh

Personalised recommendations