Journal of Risk and Uncertainty

, Volume 46, Issue 2, pp 191–213 | Cite as

Heterogeneity in life-duration preferences: Are risky recreationists really more risk loving?

Article

Abstract

We conduct multiple price list experiments that elicit life duration risk preferences from amateur auto racers, technical rock climbers, SCUBA divers, and a student control group. We posit a preference function that allows for risk aversion and probability weighting. We are particularly interested in whether the behavior of risk takers, such as risky recreationists or smokers, is best explained by a risk-tolerant utility function or if immunity to possibility bias arising from overweighting of low probabilities is a more important motivator of the choice to engage in risky activities. We find that amateur auto racers are more rational than either students or other risky recreationists because they are less likely to overemphasize low-probability events. Women, older subjects, and rock climbers are more susceptible to possibility bias than others, making them likely to overinvest in disease treatments that have a low probability of success.

Keywords

Life duration preferences CRRA Cumulative prospect theory Medical decision analysis 

JEL Classification

D800 D890 I100 

References

  1. Allais, M. (1988). The general theory of random choices in relation to the invariant cardinal utility function and the specific probability function. In B. R. Munier (Ed.), Risk, decision and rationality. Dordrecht: Reidel.Google Scholar
  2. Anderson, L. R., & Mellor, J. M. (2008). Predicting health behaviors with an experimental measure of risk preference. Journal of Health Economics, 27, 1260–1274.CrossRefGoogle Scholar
  3. Ball, S., Eckel, C. C., & Heracleous, M. (2010). Risk aversion and physical prowess: prediction, choice and bias. Journal of Risk and Uncertainty, 41, 167–193.CrossRefGoogle Scholar
  4. Baltagi, B. H., & Griffin, J. M. (2001). The econometrics of rational addiction: the case of cigarettes. Journal of Business & Economic Statistics, 19, 449–454.CrossRefGoogle Scholar
  5. Barsky, R. B., Juster, F. T., Kimball, M. S., & Shapiro, M. D. (1997). Preference parameters and behavioral heterogeneity: an experimental approach in the Health and Retirement Study. Quarterly Journal of Economics, 112, 537–579.CrossRefGoogle Scholar
  6. Becker, G. S., & Murphy, K. S. (1988). A theory of rational addiction. Journal of Political Economy, 96, 675–700.CrossRefGoogle Scholar
  7. Becker, G. S., Grossman, M., & Murphy, K. M. (1994). An empirical analysis of cigarette addiction. The American Economic Review, 84, 396–418.Google Scholar
  8. Bleichrodt, H., & Pinto, J. L. (2000). A parameter-free elicitation of the probability-weighting function in medical decision analysis. Management Science, 46, 1485–1496.CrossRefGoogle Scholar
  9. Camerer, C., & Hogarth, R. M. (1999). The effects of financial incentives in experiments: a review and capital-labor-production framework. Journal of Risk and Uncertainty, 19, 7–42.CrossRefGoogle Scholar
  10. Creyer, E., Ross, W., & Evers, D. (2010). Risky recreation: an exploration of factors influencing the likelihood of participation and the effects of experience. Leisure Studies, 22, 239–253.CrossRefGoogle Scholar
  11. Croson, R., & Gneezy, U. (2009). Gender differences in preferences. Journal of Economic Literature, 47, 1–27.CrossRefGoogle Scholar
  12. Daneshvary, N., & Clauretie, M. (2007). Gender difference in the valuation of employer-provided health insurance. Economics Inquiry, 45, 800–816.CrossRefGoogle Scholar
  13. Diecidue, E., & Wakker, P. P. (2001). On the intuition of rank-dependent utility. Journal of Risk and Uncertainty, 23, 281–298.CrossRefGoogle Scholar
  14. Dohmen, T., Falk, A., Huffman, D., Sunde, U., Schupp, J., & Wagner, G. G. (2011). Individual risk attitudes: measurement, determinants and behavioral consequences. Journal of the European Economic Association, 9, 522–550.CrossRefGoogle Scholar
  15. Edwards, R. D. (2010). Optimal portfolio choice when utility depends on health. International Journal of Economic Theory, 6, 205–225.CrossRefGoogle Scholar
  16. Harrison, G. W., List, J. A., & Towe, C. (2007a). Naturally occurring preferences and exogenous laboratory experiments: a case study of risk aversion. Econometrica, 75, 433–458.CrossRefGoogle Scholar
  17. Harrison, G. W., Lau, M. I., & Rutstrom, E. (2007b). Estimating risk attitudes in Denmark: a field experiment. The Scandinavian Journal of Economics, 109, 341–368.CrossRefGoogle Scholar
  18. Health and Safety Executive. (2012). http://www.hse.gov.uk/education/statistics.htm. Accessed January 12, 2012.
  19. Hersch, J., & Pickton, T. S. (1995). Risk-taking activities and heterogeneity of job-risk tradeoffs. Journal of Risk and Uncertainty, 11, 205–217.CrossRefGoogle Scholar
  20. Hirshleifer, J., & Riley, J. G. (1992). The analytics of uncertainty and information. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  21. Holt, C., & Laury, S. (2002). Risk aversion and incentive effects. American Economic Review, 95, 1644–1655.CrossRefGoogle Scholar
  22. Jakus, P., & Shaw, W. D. (1996). An empirical analysis of rock climbers’ response to hazard warnings. Risk Analysis, 16, 581–586.CrossRefGoogle Scholar
  23. Jianakoplos, N., & Bernasek, A. (1998). Are women more risk averse? Economic Inquiry, 36, 620–630.CrossRefGoogle Scholar
  24. Jones, A. M. (1989). A systems approach to the demand for alcohol and tobacco. Bulletin of Economic Research, 41, 85–105.CrossRefGoogle Scholar
  25. Kaplow, L. (2005). The value of a statistical life and the coefficient of relative risk aversion. Journal of Risk and Uncertainty, 31, 23–34.CrossRefGoogle Scholar
  26. Kniesner, T. J., Viscusi, W. K., & Ziliak, J. P. (2010). Policy relevant heterogeneity in the value of statistical life: new evidence from panel data quantile regressions. Journal of Risk and Uncertainty, 40, 15–31.CrossRefGoogle Scholar
  27. Morin, R. A., & Suarez, A. F. (1983). Risk aversion revisited. Journal of Finance, 38(4), 1201–1216.CrossRefGoogle Scholar
  28. Prelec, P. (1998). The probability weighting function. Econometrica, 6, 497–527.CrossRefGoogle Scholar
  29. Riley Jr., W. B., & Chow, K. V. (1992). Asset allocation and individual risk aversion. Financial Analysts Journal, 32–37.Google Scholar
  30. Rodgers, G. (1991). Bicyclist risks and helmet usage patterns: an analysis of compensatory behavior in a risky recreational activity. Managerial and Decision Economics, 17, 493–507.CrossRefGoogle Scholar
  31. Savage, L. J. (1972). The Foundations of Statistics. New York: Wiley, 1954. Revised and Enlarged Edition, New York: Dover.Google Scholar
  32. Sports Car Club of America. (2012). http://www.sccaforums.com/forums/forumid/30/postid/6903/scope/posts. Accessed January 12, 2012.
  33. Stigglebout, A. M., Kiebert, G. M., Kievit, J., Leer, J. W. H., Stoter, G., & de Haes, J. M. (1994). Utility assessment in cancer patients: adjustment of time tradeoff scores for the utility of life years and comparison with standard gamble scores. Medical Decision Making, 14, 82–90.CrossRefGoogle Scholar
  34. Sundén, A. E., & Surette, B. J. (1998). Gender differences in the allocation of assets in retirement savings plans. American Economic Review, Papers & Proceedings, 88, 207–211.Google Scholar
  35. Tanaka, T., Camerer, C. F., & Nguyen, Q. (2010). Risk and time preferences: linking experimental and household survey data from Vietnam. American Economic Review, 100, 557–571.CrossRefGoogle Scholar
  36. Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5, 297–323.CrossRefGoogle Scholar
  37. Tversky, A., & Wakker, P. (1995). Risk attitudes and decision weights. Econometrica, 63, 1255–1280.CrossRefGoogle Scholar
  38. Viscusi, W. K., & Hersch, J. (2001). Cigarette smokers as job risk takers. The Review of Economics and Statistics, 83, 269–280.CrossRefGoogle Scholar
  39. Wakker, P., & Deneffe, D. (1996). Eliciting von Neumann-Morgenstern utilities when probabilities are distorted or unknown. Management Science, 42, 1131–1150.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Economics DepartmentUniversity of Nevada, Las VegasLas VegasUSA
  2. 2.Department of EconomicsUniversity of OregonEugeneUSA

Personalised recommendations