Hostname: page-component-5d84bcc8dc-lvr7c Total loading time: 0 Render date: 2026-09-04T17:57:01.366Z Has data issue: false hasContentIssue false
  • English
  • Français

Payoff and presentation modulation of elicited risk preferences in MPLs

Published online by Cambridge University Press:  17 January 2025

Sameh Habib Open the ORCID record for Sameh Habib [Opens in a new window] ,
Daniel Friedman ,
Sean Crockett  and
Duncan James
Sameh Habib*
Affiliation:
Economics Department, University of California, Santa Cruz, 401 Engineering 2 Building, 1156 High Street, Santa Cruz, CA 95064, USA
Daniel Friedman
Affiliation:
Economics Department, University of California, Santa Cruz, Santa Cruz, USA
Sean Crockett
Affiliation:
Zicklin School of Business, Baruch College, New York City, USA
Duncan James
Affiliation:
Economics Department, Fordham University, New York City, USA
*
e-mail: sfhabib@ucsc.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Since Holt and Laury (Am Econ Rev 92(5):1644–1655, 2002), the multiple price list (MPL) procedure has widely been used to elicit individual risk preferences. We assess the impact of varying list order and spacing, and of presentation via text or graphs. Relative to the original MPL baseline, some non-linear transformations of lottery prices systematically increase elicited risk aversion, while some graphical displays tend to reduce it.

Keywords

Multiple price listElicitationRisk aversionExperiment

JEL classification

D89: Other C91: Laboratory, Individual Behavior D81: Criteria for Decision-Making under Risk and Uncertainty

Information

Type
Original Paper
Information
Journal of the Economic Science Association , Volume 3 , Issue 2 , December 2017 , pp. 183 - 194
Copyright
Copyright © Economic Science Association 2017

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

Footnotes

Electronic supplementary material The online version of this article (doi:10.1007/s40881-016-0032-8) contains supplementary material, which is available to authorized users.

References

Andersen, S., Harrison, G. W., Lau, M. I., Rutström, E. E. (2006). Elicitation using multiple price list formats. Experimental Economics, 9(4), 383–405. 10.1007/s10683-006-7055-6CrossRefGoogle Scholar
Benjamin, D. J., Brown, S. A., Shapiro, J. M. (2013). Who is “behavioral” cognitive ability and anomalous preferences. Journal of the European Economic Association, 11(6), 1231–1255. 10.1111/jeea.12055CrossRefGoogle ScholarPubMed
Bosch-Domènech, A., Silvestre, J. (2013). Measuring risk aversion with lists: A new bias. Theory and Decision, 75(4), 465–496. 10.1007/s11238-012-9332-5CrossRefGoogle Scholar
Camerer, C. F. (1989). An experimental test of several generalized utility theories. Journal of Risk and uncertainty, 2(1), 61–104. 10.1007/BF00055711CrossRefGoogle Scholar
Cokely, E. T., Kelley, C. M. (2009). Cognitive abilities and superior decision making under risk: A protocol analysis and process model evaluation. Judgment and Decision Making, 4(1),20.CrossRefGoogle Scholar
Cox, J. C., Smith, V. L., Walker, J. M. (1988). Theory and individual behavior of first-price auctions. Journal of Risk and Uncertainty, 1(1), 61–99. 10.1007/BF00055565CrossRefGoogle Scholar
Eichberger, J., Oechssler, J., & Schnedler, W. (2011). How do subjects cope with ambiguous situations when they become even more ambiguous?. Technical report, Mimeo, University of Heidelberg.Google Scholar
Eliaz, K., & Ortoleva, P. (2011). A variation on Ellsberg. Brown University Working Paper. doi:10.2139/ssrn.1761445CrossRefGoogle Scholar
Frederick, S. (2005). Cognitive reflection and decision making. The Journal of Economic Perspectives, 19(4), 25–42. 10.1257/089533005775196732CrossRefGoogle Scholar
Friedman, D., Isaac, R. M., James, D., Sunder, S. (2014). Risky curves: On the empirical failure of expected utility, New York: Routledge.CrossRefGoogle Scholar
Hey, J. D., Orme, C. (1994). Investigating generalizations of expected utility theory using experimental data. Econometrica: Journal of the Econometric Society, 62(6), 1291–1326. 10.2307/2951750CrossRefGoogle Scholar
Holt, C. A., Laury, S. K. (2002). Risk aversion and incentive effects. American Economic Review, 92(5), 1644–1655. 10.1257/000282802762024700CrossRefGoogle Scholar
James, D. (2007). Stability of risk preference parameter estimates within the Becker–DeGroot–Marschak procedure. Experimental Economics, 10(2), 123–141. 10.1007/s10683-006-9136-yCrossRefGoogle Scholar
Lévy-Garboua, L., Maafi, H., Masclet, D., Terracol, A. (2012). Risk aversion and framing effects. Experimental Economics, 15(1), 128–144. 10.1007/s10683-011-9293-5CrossRefGoogle Scholar
Park, J., Brannon, E. M. (2013). Training the approximate number system improves math proficiency. Psychological Science, 24(10), 2013–2019. 10.1177/0956797613482944CrossRefGoogle ScholarPubMed
Schley, D. R., Peters, E. (2014). Assessing “economic value” symbolic-number mappings predict risky and riskless valuations. Psychological Science.CrossRefGoogle Scholar
Weller, J. A., Dieckmann, N. F., Tusler, M., Mertz, C. K., Burns, W. J., Peters, E. (2013). Development and testing of an abbreviated numeracy scale: A Rasch analysis approach. Journal of Behavioral Decision Making, 26(2), 198–212. 10.1002/bdm.1751CrossRefGoogle Scholar
Supplementary material: File

Habib et al. supplementary material

Habib et al. supplementary material
Download Habib et al. supplementary material(File)
File 471.8 KB