Prospect theory: A parametric analysis of functional forms in Brazil
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Abstract
This study aims to analyze risk preferences in Brazil based on prospect theory by estimating the risk aversion parameter of the expected utility theory (EUT) for a select sample, in addition to the value and probability function parameter, assuming various functional forms, and a newly proposed value function, the modified log. This is the first such study in Brazil, and the parameter results are slightly different from studies in other countries, indicating that subjects are more risk averse and exhibit a smaller loss aversion. Probability distortion is the only common factor. As expected, the study finds that behavioral models are superior to EUT, and models based on prospect theory, the TK and Prelec weighting function, and the value power function show superior performance to others. Finally, the modified log function proposed in the study fits the data well, and can thus be used for future studies in Brazil.
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References
Abdellaoui, M. (2000). Parameter-free elicitation of utility and probability weighting functions. Management Science, 46(11), 1497- 1512.
Abdellaoui, M., Bleichrodt, H., & L’Haridon, O. (2008). A tractable method to measure utility and loss aversion under prospect theory. Journal of Risk and Uncertainty, 36(3), 245-266. doi:10.1007/s11166- 008-9039-8
Abdellaoui, M., Bleichrodt, H., & L’Haridon, O. (2013). Sign-dependence in intertemporal choice. Journal of Risk and Uncertainty, 47(3), 225- 253. doi:10.1007/s11166-013-9181-9
Abdellaoui, M., Bleichrodt, H., & Paraschiv, C. (2007). Loss aversion under prospect theory: A parameter-free measurement. Management Science, 53(10), 1659-1674.
Abdellaoui, M., Vossmann, F., & Weber, M. (2005). Choice-based elicitation and decomposition of decision weights for gains and losses under uncertainty. Management Science, 51(9), 1384-1399.
Allais, M. (1953). Le comportement de l’homme rationnel devant le risque: Critique des postulats et axiomes de l’ecole americaine. Econometrica, 21(4), 503-546. doi:10.2307/1907921
Attema, A. E., Brouwer, W. B. F., & L’Haridon, O. (2013). Prospect theory in the health domain: A quantitative assessment. Journal of Health Economics, 32(6), 1057-1065. doi:10.1016/j.jhealeco.2013.08.006
Barberis, N., & Huang, M. (2008). Stocks as lotteries: The implications of probability weighting for security prices. American Economic Review, 98(5), 2066-2100.
Barberis, N., Huang, M., & Santos, T. (2001). Prospect theory and asset prices. The Quarterly Journal of Economics, 116(1), 1-53. doi:10.1162/003355301556310
Bernoulli, D. (1954). Exposition of a new theory on the measurement of risk. Econometrica, 22(1), 23-36. doi:10.2307/1909829
Booij, A., van Praag, B., & van de Kuilen, G. (2010). A parametric analysis of prospect theory’s functionals for the general population. Theory and Decision, 68(1-2), 115-148. doi:10.1007/s11238-009-9144-4
Bui, T. (2009). Prospect Theory and Functional Choice. A Dissertation Submitted to the Graduate School in Partial Fulfillment of the Requirements for the Degree Erasmus Mundus Master: Models and Methods of Quantitative Economics (QEM), Bielefeld University and The University of Paris 1 Panthéon-Sorbonne.
Camerer, C. F., & Ho, T.-H. (1994). Violations of the betweenness axiom and nonlinearity in probability. Journal of Risk and Uncertainty, 8(2), 167-196. doi:10.1007/BF01065371
Ellsberg, D. (1961). Risk, ambiguity, and the savage axioms. The Quarterly Journal of Economics, 75(4), 643-669.
Fishburn, P. C., & Kochenberger, G. A. (1979). Two-piece Von NeumannMorgenstern utility functions. Decision Sciences, 10(4), 503-518. doi:10.1111/j.1540-5915.1979.tb00043.x
Gerber, H. U., & Pafum, G. (1998). Utility functions: From risk theory to finance. North American Actuarial Journal, 2(3), 92-94. doi:10.1080/ 10920277.1998.10595731
Goldstein, W. M., & Einhorn, H. J. (1987). Expression theory and the preference reversal phenomena. Psychological Review, 94(2), 236- 254. doi:10.1037/0033-295X.94.2.236
Gomes, F. J. (2005). Portfolio choice and trading volume with loss‐averse investors. The Journal of Business, 78(2), 675-706. doi:10.1086/427643
Gonzalez, R., & Wu, G. (1999). On the shape of the probability weighting function. Cognitive Psychology, 38(1), 129-166. doi:10.1006/ cogp.1998.0710
Harrison, G., & Rutström, E. (2009). Expected utility theory and prospect theory: One wedding and a decent funeral. Experimental Economics, 12(2), 133-158. doi:10.1007/s10683-008-9203-7
Harrison, G. W., Humphrey, S. J., & Verschoor, A. (2010). Choice under uncertainty: Evidence from Ethiopia, India and Uganda. The Economic Journal, 120(543), 80-104. doi:10.1111/j.1468-0297.2009.02303.x
Holt, C. A., & Laury, S. K. (2002). Risk aversion and incentive effects. American Economic Review, 92(5), 1644-1655.
Instituto Brasileiro de Geografia e Estatística (IBGE). (2014). Pesquisa Nacional por Amostra de Domicílios (Pnad) Contínua. Brasilia, DF.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-292. doi:10.2307/1914185
Karmarkar, U. S. (1978). Subjectively weighted utility: A descriptive extension of the expected utility model. Organizational Behavior and Human Performance, 21(1), 61-72. doi:10.1016/0030-5073(78)90039-9
Karmarkar, U. S.. (1979). Subjectively weighted utility and the Allais Paradox. Organizational Behavior and Human Performance, 24(1), 67-72. doi:10.1016/0030-5073(79)90016-3
Köbberling, V., & Wakker, P. P. (2005). An index of loss aversion. Journal of Economic Theory, 122(1), 119-131. doi:10.1016/j.jet.2004.03.009
Liebenehm, S., & Waibel, H. (2014). Simultaneous estimation of risk and time preferences among small-scale cattle farmers in West Africa. American Journal of Agricultural Economics, 96(5), 1420-1438. doi:10.1093/ajae/aau056
Liu, E. M. (2012). Time to change what to sow: Risk Preferences and technology adoption decisions of cotton farmers in China. Review of Economics and Statistics, 95(4), 1386-1403. doi:10.1162/REST_a_00295
Machina, M. J. (2008). Non-expected utility theory. In S. N. Durlauf & L. E. Blume (Eds.), The New Palgrave Dictionary of Economics, 2nd Edition. London, UK: Palgrave Macmillan.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77- 91. doi:10.1111/j.1540-6261.1952.tb01525.x
Nguyen, Q., & Leung, P. (2009). Do Fishermen have Different Attitudes Toward Risk? An Application of Prospect Theory to the Study of Vietnamese Fishermen. Journal of Agricultural and Resource Economics, 34(3), 518-538.
Nguyen, Q., & Leung, P. (2010). How nurture can shape preferences: An experimental study on risk preferences of Vietnamese fishers. Environment and Development Economics, 15(5), 609-631. doi:10.1017/S1355770X10000203
Palacios-Huerta, I., & Serrano, R. (2006). Rejecting small gambles under expected utility. Economics Letters, 91(2), 250-259. doi:10.1016/j. econlet.2005.09.017
Prelec, D. (1998). The probability weighting function. Econometrica, 66(3), 497-527. doi:10.2307/2998573
Rieger, M. O., Wang, M., & Hens, T. (2011). Prospect theory around the world (October 31, 2011). NHH Dept. of Finance & Management Science Discussion Paper No. 2011/19.
Rieger, M., & Wang, M. (2008). Prospect theory for continuous distributions. Journal of Risk and Uncertainty, 36(1), 83-102. doi:10.1007/s11166-007-9029-2
Rieger, M. O., & Bui, T. (2011). Too risk-averse for prospect theory? Modern Economy, 2(4), 691-670. doi:10.4236/me.2011.24077
Rieger, M. O., Wang, M., & Hens, T. (2017). Estimating cumulative prospect theory parameters from an international survey. Theory and Decision, 82(4), 567-596. doi:10.1007/s11238-016-9582-8
Schmidt, U., & Traub, S. (2002). An experimental test of loss aversion. Journal of Risk and Uncertainty, 25(3), 233-249. doi:10.1023/A:1020923921649
Scholten, M., & Read, D. (2014). Prospect theory and the “forgotten” fourfold pattern of risk preferences. Journal of Risk and Uncertainty, 48(1), 67-83. doi:10.1007/s11166-014-9183-2
Stott, H. P. (2006). Cumulative prospect theory’s functional menagerie. Journal of Risk and Uncertainty, 32(2), 101-130. doi:10.1007/s11166-006-8289-6
Tanaka, T., Camerer, C. F., & Nguyen, Q. (2010). Risk and time preferences: Linking experimental and household survey data from Vietnam. American Economic Review, 100(1), 557-571. doi:10.1257/ aer.100.1.557
Tu, Q. (2005). Empirical analysis of time preferences and risk aversion. Tilburg University: CentER, Center for Economic Research.
Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297-323.
Tversky, A., & Wakker, P. (1995). Risk attitudes and decision weights. Econometrica, 63(6), 1255-1280. doi:10.2307/2171769
von Neumann, J., & Morgenstern, O. (1944). Theory of Games and Economic Behavior. Princeton, USA: Princeton University Press.
Wakker, P. P. (2008). Explaining the characteristics of the power (CRRA) utility family. Health Economics, 17(12), 1329-1344. doi:10.1002/hec.1331
Wu, G., & Gonzalez, R. (1996). Curvature of the probability weighting function. Management Science, 42(12), 1676-1690.
Zeisberger, S., Vrecko, D., & Langer, T. (2012). Measuring the time stability of Prospect Theory preferences. Theory and Decision, 72(3), 359-386. doi:10.1007/s11238-010-9234-3
