Eliciting Parameters of Cumulative Prospect Theory in an Iranian Sample

Document Type : Research Paper

Author

Assistant Professor, Faculty of Social Sciences & Economics, Alzahra University, Tehran, Iran

Abstract

 Among decision theories under risk and uncertainty, cumulative prospect theory has become very popular because of its explanatory and predictive power, which is evident in more than 50,000 citations. In applied studies or for scenario making and explaining many phenomena, most researchers use the initial parameters estimated by Kahnemann and Torsky (1979). Given the impact of environment and culture on risky behavior and parameters ofprospect theory, the present paper elicits the utility and probability weighting functions in both gain and loss domains and estimates parameters of their functional forms. By estimating all parameters of cumulative prospect theory, this paper tries to provide an integrated picture of people's attitude towards risk from an Iranian sample. In addition, the superiority of this theory over expected utility is indirectly tested.
Findings confirm many predictions of cumulative prospect theory such as the fourfold pattern of risk attitude and concavity of value function over gains and its convexity over losses. The findings of this experiment show the superiority of cumulative prospect theory over expected utility theory.
The findings show that people's perceptions of probabilities are not linear and their degree of risk aversion depends on probabilities. More specifically, most subjects behaved according to the pattern of reducing risk aversion by increasing the probability of loss and increasing risk aversion by increasing the probability of gain. These findings are consistent with the fourfold pattern of risk attitude and indicate that the behavior of the sample is not different from previous samples. 

Keywords

References

  • Abdellaoui, M. (2000). Parameter-free elicitation of utility and probability weighting functions. Management Science, 46(11), 1497-1512.
  • Abdellaoui, M., Bleichrodt, H., & Paraschiv, C. (2007). Loss aversion under prospect theory: A parameter-free measurement. Management Science,53(10), 1659-74.
  • Barberis, N. C., Jin, L. J., & Wang, B. (2020). Prospect theory and stock market anomalies (No. w27155). National Bureau of Economic Research.
  • Bruhin, A.; Fehr‐Duda, H., & Epper, T. (2010). Risk and rationality: Uncovering heterogeneity in probability distortion. Econometrica, 78(4), 1375-1412.
  • Camerer, C. F., & Hogarth, R. M. (1999). The effects of financial incentives in experiments: A review and capital-labor-production framework. Journal of Risk and Uncertainty,19(1-3), 7-42.
  • Camerer, C., Babcock, L., Loewenstein, G., & Thaler, R. (1997). Labor supply of New York City cabdrivers: One day at a time. The Quarterly Journal of Economics,112(2), 407-441.
  • Chapman, J., Snowberg, E., Wang, S., & Camerer, C. (2019). Loss attitudes in the US population: Evidence from dynamically optimized sequential experimentation (DOSE) (No. w25072). National Bureau of Economic Research.
  • Charness, G., Gneezy, U., & Imas, A. (2013). Experimental methods: Eliciting risk preferences. Journal of Economic Behavior & Organization, 87, 43-51.
  • Dhami, S. (2016). The Foundations of Behavioral Economic Analysis. Oxford University Press.
  • Du, X., Li, J., & Du, X. (2014). Testing risk-taking behavior in Chinese undergraduate students. PLoS one, 9(5), e97989. https://doi.org/10.1371/journal.pone.0097989
  • Einav, L., Finkelstein, A., Pascu, I., & Cullen, M. R. (2012). How general are risk preferences? Choices under uncertainty in different domains. American Economic Review, 102(6), 2606-38.
  • Etchart-Vincent, N. (2004). Is probability weighting sensitive to the magnitude of consequences? An experimental investigation on losses. Journal of Risk and Uncertainty, 28(3), 217-235.
  • Etchart-Vincent, N. (2009). Probability weighting and the ‘level’ and ‘spacing’ of outcomes: An experimental study over losses. Journal of Risk and Uncertainty, 39(1), 45-63.
  • Fehr, E., & Goette, L. (2007). Do workers work more if wages are high? Evidence from a randomized field experiment. American Economic Review, 97(1), 298-317.
  • Fehr-Duda, H., & Epper, T. (2011). Probability and risk: Foundations and economic implications of probability-dependent risk preferences.  Rev. Econ., 4(1), 567-593.
  • Fennema, H., & Van Assen, M. (1998). Measuring the utility of losses by means of the trade-off method. Journal of Risk and Uncertainty, 17(3), 277-296.
  • Fischbacher, U. (2007). Z-Tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10(2), 171-178.
  • Genesove, D., & Mayer, C. (2001). Loss aversion and seller behavior: Evidence from the housing market. The Quarterly Journal of Economics, 116(4), 1233-60.
  • Gonzalez, R., & Wu, G. (1999). On the shape of the probability weighting function. Cognitive Psychology, 38(1), 129-166.
  • Hajimoladarvish, N. (2017). Very low probabilities in the loss domain. The Geneva Risk and Insurance Review, 42(1), 41-58.
  • Hajimoladarvish, N. (2018). How do people reduce compound lotteries?. Journal of Behavioral and Experimental Economics, 75, 126-133.
  • Halpern, S. D., French, B., Small, D. S., Saulsgiver, K., Harhay, M. O., Audrain-McGovern, J., & Volpp, K. G. (2015). Randomized trial of four financial-incentive programs for smoking cessation. N Engl J Med, 372, 2108-2117.
  • Harbaugh, R. (2020). Prospect theory or skill signaling?. Available at SSRN 311409, https://ssrn.com/abstract=311409.
  • Helson, H. (1964). Adaptation-level theory: An experimental and systematic approach to behaviour, Harper and Row: New York.
  • Kahneman, D., & Tversky, A. (2000). Choices, values, and frames. New York; Cambridge, UK: Russell Sage Foundation.
  • Kahneman, D., & Tversky. A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263-291.
  • Kpegli, Y., Corgnet, B., & Zylbersztejn, A. (2020). All at Once! A Comprehensive and Tractable Semi-Parametric Method to Elicit Prospect Theory Components, Article in press.
  • Mas, A. (2006). Pay, reference points, and police performance. The Quarterly Journal of Economics, 121(3), 783-821.
  • Nelder, J. A., & Mead, R. (1965). A simplex method for function minimization. The Computer Journal, 7(4), 308-313.
  • Page, L., Savage, D. A., & Torgler, B. (2012). Variation in risk seeking behavior in a natural experiment on large losses induced by a natural disaster. CESifo Working Paper Series 3878.
  • Prelec, D. (1998). The probability weighting function. Econometrica, 66(3), 497-527.
  • Quiggin, J. (1982). A theory of anticipated utility. Journal of Economic Behavior & Organization, 3(4), 323-343.
  • Rieger, M. O., Wang, M., & Hens, T. (2015). Risk preferences around the world. Management Science, 61(3), 637-648.             
  • Sheeran, P. (2002). Intention-behavior relations: a conceptual and empirical review. European Review of Social Psychology, 12(1), 1-36.
  • Starmer, C. (2000). Developments in Non-Expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk. Journal of Economic Literature, 38, 332-382.
  • Thaler, R. (1980). Toward a positive theory of consumer choice. Journal of Economic Behavior & Organization, 1(1), 39-
  • Thaler, R. H., Tversky, A., Kahneman, D., & Schwartz, A. (1997). The effect of myopia and loss aversion on risk taking: An experimental test. The Quarterly Journal of Economics, 112(2), 647-661.
  • Tversky, A., & Fox, C. R. (1995). Weighing risk and uncertainty. Psychological Review, 102(2), 269-283
  • Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297-323.
  • Von Neumann, J. and Morgenstern, O. (1944). Theory of Games and Economic Behaviour. Princeton, NJ: Princeton University Press.
  • Wakker, P., & Deneffe, D. (1996). Eliciting von Neumann-Morgenstern utilities when probabilities are distorted or  Management Science, 42(8), 1131-50.                      
  • Walasek, L., & Stewart, N. (2015). How to make loss aversion disappear and reverse: Tests of the decision by sampling origin of loss aversion. Journal of Experimental Psychology: General, 144(1), 7-11.

 

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