Drichoutis, Andreas and Lusk, Jayson (2012): What can multiple price lists really tell us about risk preferences?
This is the latest version of this item.
Preview |
PDF
MPRA_paper_42128.pdf Download (591kB) | Preview |
Abstract
Multiple price lists have emerged as a simple and popular method for eliciting risk preferences. Despite their popularity, a key downside of multiple price lists has not been widely recognized - namely that the approach is unlikely to generate sufficient information to accurately identify different dimensions of risk preferences. The most popular theories of decision making under risk posit that preference for risk are driven by a combination of two factors: the curvature of the utility function and the extent to which probabilities are weighted non-linearly. In this paper, we show that the widely used multiple price list introduced by Holt and Laury (2002) is likely more accurate at eliciting the latter, and we introduce a different multiple price list that is likely more accurate at eliciting the former. We show that by combining information from different multiple price lists, greater predictive performance can be achieved.
Item Type: | MPRA Paper |
---|---|
Original Title: | What can multiple price lists really tell us about risk preferences? |
Language: | English |
Keywords: | expected utility theory; experiment; multiple price list; probability weighting; rank dependent utility; risk |
Subjects: | D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D81 - Criteria for Decision-Making under Risk and Uncertainty C - Mathematical and Quantitative Methods > C9 - Design of Experiments > C91 - Laboratory, Individual Behavior |
Item ID: | 42128 |
Depositing User: | Andreas Drichoutis |
Date Deposited: | 22 Oct 2012 13:16 |
Last Modified: | 26 Sep 2019 10:53 |
References: | Andersen, S., G. W. Harrison, M. I. Lau, and E. E. Rutstrom (2006). Elicitation using multiple price list formats. Experimental Economics 9 (4), 383-405. Andersen, S., G. W. Harrison, M. I. Lau, and E. E. Rutstrom (2008). Eliciting risk and time preferences. Econometrica 76 (3), 583-618. Andersen, S., G. W. Harrison, M. I. Lau, and E. E. Rutstrom (2011). Discounting behavior: A reconsideration. Center for the Economic Analysis of Risk, Working Paper 2011-03 . Becker, G. M., M. H. Degroot, and J. Marschak (1964). Measuring utility by a single-response sequential method. Behavioral Science 9 (3), 226-232. Bellemare, C. and B. Shearer (2010). Sorting, incentives and risk preferences: Evidence from a field experiment. Economics Letters 108 (3), 345-348. Binswanger, H. P. (1980). Attitudes toward risk: Experimental measurement in rural india. American Journal of Agricultural Economics 62 (3), 395-407. Binswanger, H. P. (1981). Attitudes toward risk: Theoretical implications of an experiment in rural india. Economic Journal 91 (364), 867-890. Bleichrodt, H. (2002). A new explanation for the dierence between time trade-o utilities and standard gamble utilities. Health Economics 11 (5), 447-456. Bruner, D., M. McKee, and R. Santore (2008). Hand in the cookie jar: An experimental investigation of equity-based compensation and managerial fraud. Southern Economic Journal 75 (1), 261-278. Camerer, C. F. and T.-H. Ho (1994). Violations of the betweenness axiom and nonlinearity in probability. Journal of Risk and Uncertainty 8 (2), 167-196. Cohen, M., J.-Y. Jaray, and T. Said (1987). Experimental comparison of individual behavior under risk and under uncertainty for gains and for losses. Organizational Behavior and Human Decision Processes 39 (1), 1-22. Eckel, C. C. and R. K. Wilson (2004). Is trust a risky decision? Journal of Economic Behavior & Organization 55 (4), 447-465. Erdem, T. (1996). A dynamic analysis of market structure based on panel data. Marketing Science 15 (4), 359-378. Fischbacher, U. (2007). z-tree: Zurich toolbox for ready-made economic experiments. Experimental Economics 10 (2), 171-178. Glockner, A. and G. Hochman (2011). The interplay of experience-based aective and probabilistic cues in decision making. Experimental Psychology 58 (2), 132-141. Greiner, B. (2004). An online recruitment system for economic experiments. In K. Kremer and V. Macho (Eds.), Forschung Und Wissenschaftliches Rechnen. Gwdg Bericht 63. Ges. Fr Wiss, pp. 79-93. Datenverarbeitung, Gttingen. Harrison, G. W., E. Johnson, M. M. McInnes, and E. E. Rutstrom (2005). Risk aversion and incentive eects: Comment. American Economic Review 95 (3), 897-901. Harrison, G. W., M. I. Lau, and E. E. Rutstrom (2009). Risk attitudes, randomization to treatment, and self-selection into experiments. Journal of Economic Behavior & Organization 70 (3), 498-507. Harrison, G. W. and E. E. Rutstrom (2008). Risk aversion in the laboratory. In J. C. Cox and G. W. Harrison (Eds.), Research in Experimental Economics Vol 12: Risk Aversion in Experiments, Volume 12, pp. 41-196. Bingley, UK: Emerald Group Publishing Limited. Holt, C. A. and S. K. Laury (2002). Risk aversion and incentive eects. American Economic Review 92 (5), 1644-1655. Holt, C. A. and S. K. Laury (2005). Risk aversion and incentive eects: New data without order eects. American Economic Review 95 (3), 902-904. Lusk, J. L. and K. H. Coble (2005). Risk perceptions, risk preference, and acceptance of risky food. American Journal of Agricultural Economics 87 (2), 393-405. Miller, L., D. E. Meyer, and J. T. Lanzetta (1969). Choice among equal expected value alternatives: Sequential eects of winning probability level on risk preferences. Journal of Experimental Psychology 79 (3), 419-423. Norwood, B. F., J. L. Lusk, and B. W. Brorsen (2004). Model selection for discrete dependent variables: Better statistics for better steaks. Journal of Agricultural and Resource Economics 29 (3), 404-419. Norwood, B. F., M. C. Roberts, and J. L. Lusk (2004). Ranking crop yield models using out-of-sample likelihood functions. American Journal of Agricultural Economics 86 (4), 1032-1043. Prelec, D. (1998). The probability weighting function. Econometrica 66 (3), 497-528. Quiggin, J. (1982). A theory of anticipated utility. Journal of Economic Behavior & Organization 3 (4), 323-343. Roy, R., P. K. Chintagunta, and S. Haldar (1996). A framework for investigating habits, "the hand of the past," and heterogeneity in dynamic brand choice. Marketing Science 15 (3), 280-299. Saha, A. (1993). Expo-power utility: A exible form for absolute and relative risk aversion. American Journal of Agricultural Economics 75 (4), 905-913. Selten, R., A. Sadrieh, and K. Abbink (1999). Money does not induce risk neutral behavior, but binary lotteries do even worse. Theory and Decision 46 (3), 213-252. Tversky, A. and D. Kahneman (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty 5 (4), 297-323. Wakker, P. and D. Denee (1996). Eliciting von neumann-morgenstern utilities when probabilities are distorted or unknown. Management Science 42 (8), 1131-1150. Wakker, P. P. (2010). Prospect theory for risk and ambiguity. Cambridge, UK: Cambridge University Press. Wu, G. and R. Gonzalez (1996). Curvature of the probability weighting function. Management Science 42 (12), 1676-1690. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/42128 |
Available Versions of this Item
-
Risk preference elicitation without the confounding effect of probability weighting. (deposited 30 Mar 2012 20:32)
-
Risk preference elicitation without the confounding effect of probability weighting. (deposited 31 Mar 2012 22:30)
- What Can Multiple Price Lists Really Tell Us about Risk Preferences? (deposited 04 Jan 2014 18:31)
- What can multiple price lists really tell us about risk preferences? (deposited 22 Oct 2012 13:16) [Currently Displayed]
-
Risk preference elicitation without the confounding effect of probability weighting. (deposited 31 Mar 2012 22:30)