IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/119743.html
   My bibliography  Save this paper

A Note on an Alternative Approach to Experimental Design of Lottery Prospects

Author

Listed:
  • Balcombe, Kelvin
  • Fraser, Iain

Abstract

e introduce an alternative approach to lottery prospects experimental design aimed at collecting experimental data for parametric estimation of the cumulative form of Prospect Theory (PT). Our approach incorporates two fundamental principles: ensuring that all tasks provide valuable information and avoiding redundancy among tasks. These principles mean that we avoid the construction of lottery prospects that duplicate information within the set of tasks generated. The methodological approach that we have designed ensures that each lottery pair is non-redundant in an informational sense. This means that the set of lottery tasks generated can help to improve the effectiveness of data collection when estimation of preference parameters is the main research objective. In this note, we describe our approach to experimental design in detail.

Suggested Citation

  • Balcombe, Kelvin & Fraser, Iain, 2024. "A Note on an Alternative Approach to Experimental Design of Lottery Prospects," MPRA Paper 119743, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:119743
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/119743/1/MPRA_paper_119743.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Catherine C. Eckel & Philip J. Grossman, 2002. "Sex Differences and Statistical Stereotyping in Attitudes Toward Financial Risk," Monash Economics Working Papers archive-03, Monash University, Department of Economics.
    2. Loomes, Graham & Sugden, Robert, 1998. "Testing Different Stochastic Specifications of Risky Choice," Economica, London School of Economics and Political Science, vol. 65(260), pages 581-598, November.
    3. David J. Freeman & Guy Mayraz, 2019. "Why choice lists increase risk taking," Experimental Economics, Springer;Economic Science Association, vol. 22(1), pages 131-154, March.
    4. Hans P. Binswanger, 1980. "Attitudes Toward Risk: Experimental Measurement in Rural India," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 62(3), pages 395-407.
    5. Adam Booij & Bernard Praag & Gijs Kuilen, 2010. "A parametric analysis of prospect theory’s functionals for the general population," Theory and Decision, Springer, vol. 68(1), pages 115-148, February.
    6. Glenn W. Harrison & Jia Min Ng, 2016. "Evaluating The Expected Welfare Gain From Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(1), pages 91-120, January.
    7. Kelvin Balcombe & Iain Fraser, 2015. "Parametric preference functionals under risk in the gain domain: A Bayesian analysis," Journal of Risk and Uncertainty, Springer, vol. 50(2), pages 161-187, April.
    8. Douadia Bougherara & Xavier Gassmann & Laurent Piet & Arnaud Reynaud, 2017. "Corrigendum: Structural estimation of farmers’ risk and ambiguity preferences: a field experiment," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 44(5), pages 809-809.
    9. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    10. Daniel R. Cavagnaro & Richard Gonzalez & Jay I. Myung & Mark A. Pitt, 2013. "Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach," Management Science, INFORMS, vol. 59(2), pages 358-375, February.
    11. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    12. John D. Hey, 2018. "Does Repetition Improve Consistency?," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 2, pages 13-62, World Scientific Publishing Co. Pte. Ltd..
    13. Michal Bauer & Julie Chytilova & Jonathan Morduch, 2012. "Behavioral Foundations of Microcredit: Experimental and Survey Evidence from Rural India," American Economic Review, American Economic Association, vol. 102(2), pages 1118-1139, April.
    14. Glenn W. Harrison & J. Todd Swarthout, 2016. "Cumulative Prospect Theory in the Laboratory: A Reconsideration," Experimental Economics Center Working Paper Series 2016-04, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University.
    15. Balcombe, Kelvin & Bardsley, Nicholas & Dadzie, Sam & Fraser, Iain, 2019. "Estimating parametric loss aversion with prospect theory: Recognising and dealing with size dependence," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 106-119.
    16. Felix Holzmeister & Matthias Stefan, 2021. "The risk elicitation puzzle revisited: Across-methods (in)consistency?," Experimental Economics, Springer;Economic Science Association, vol. 24(2), pages 593-616, June.
    17. Andreas C. Drichoutis & Jayson L. Lusk, 2016. "What can multiple price lists really tell us about risk preferences?," Journal of Risk and Uncertainty, Springer, vol. 53(2), pages 89-106, December.
    18. David Buschena & David Zilberman, 1999. "Testing the Effects of Similarity on Risky Choice: Implications for Violations of Expected Utility," Theory and Decision, Springer, vol. 46(3), pages 253-280, June.
    19. Patrick S. Ward & Vartika Singh, 2015. "Using Field Experiments to Elicit Risk and Ambiguity Preferences: Behavioural Factors and the Adoption of New Agricultural Technologies in Rural India," Journal of Development Studies, Taylor & Francis Journals, vol. 51(6), pages 707-724, June.
    20. Grether, David M & Plott, Charles R, 1979. "Economic Theory of Choice and the Preference Reversal Phenomenon," American Economic Review, American Economic Association, vol. 69(4), pages 623-638, September.
    21. Steffen Andersen & James C. Cox & Glenn W. Harrison & Morten I. Lau & E. Elisabet Rutström & Vjollca Sadiraj, 2018. "Asset Integration and Attitudes toward Risk: Theory and Evidence," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 816-830, December.
    22. Armin Falk & Anke Becker & Thomas Dohmen & Benjamin Enke & David B. Huffman & Uwe Sunde, 2017. "Global Evidence on Economic Preferences," NBER Working Papers 23943, National Bureau of Economic Research, Inc.
    23. Armin Falk & Anke Becker & Thomas Dohmen & Benjamin Enke & David Huffman & Uwe Sunde, 2018. "Global Evidence on Economic Preferences," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(4), pages 1645-1692.
    24. Ola Andersson & Håkan J. Holm & Jean-Robert Tyran & Erik Wengström, 2016. "Risk Aversion Relates To Cognitive Ability: Preferences Or Noise?," Journal of the European Economic Association, European Economic Association, vol. 14(5), pages 1129-1154, October.
    25. Graham Loomes & Ganna Pogrebna, 2017. "Do Preference Reversals Disappear When We Allow for Probabilistic Choice?," Management Science, INFORMS, vol. 63(1), pages 166-184, January.
    26. Daniel Cavagnaro & Mark Pitt & Richard Gonzalez & Jay Myung, 2013. "Discriminating among probability weighting functions using adaptive design optimization," Journal of Risk and Uncertainty, Springer, vol. 47(3), pages 255-289, December.
    27. Paolo Crosetto & Antonio Filippin, 2016. "A theoretical and experimental appraisal of four risk elicitation methods," Experimental Economics, Springer;Economic Science Association, vol. 19(3), pages 613-641, September.
    28. John D. Hey & Chris Orme, 2018. "Investigating Generalizations Of Expected Utility Theory Using Experimental Data," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 3, pages 63-98, World Scientific Publishing Co. Pte. Ltd..
    29. Henry Stott, 2006. "Cumulative prospect theory's functional menagerie," Journal of Risk and Uncertainty, Springer, vol. 32(2), pages 101-130, March.
    30. Tomomi Tanaka & Colin F. Camerer & Quang Nguyen, 2010. "Risk and Time Preferences: Linking Experimental and Household Survey Data from Vietnam," American Economic Review, American Economic Association, vol. 100(1), pages 557-571, March.
    31. Ryan O. Murphy & Robert H. W. ten Brincke, 2018. "Hierarchical Maximum Likelihood Parameter Estimation for Cumulative Prospect Theory: Improving the Reliability of Individual Risk Parameter Estimates," Management Science, INFORMS, vol. 64(1), pages 308-328, January.
    32. Regier, Dean A. & Watson, Verity & Burnett, Heather & Ungar, Wendy J., 2014. "Task complexity and response certainty in discrete choice experiments: An application to drug treatments for juvenile idiopathic arthritis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 50(C), pages 40-49.
    33. Graham Loomes & Robert Sugden, 1998. "Testing Different Stochastic Specificationsof Risky Choice," Economica, London School of Economics and Political Science, vol. 65(260), pages 581-598, November.
    34. Douadia Bougherara & Xavier Gassmann & Laurent Piet & Arnaud Reynaud, 2017. "Structural estimation of farmers’ risk and ambiguity preferences: a field experiment," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 44(5), pages 782-808.
    35. Andreas Pedroni & Renato Frey & Adrian Bruhin & Gilles Dutilh & Ralph Hertwig & Jörg Rieskamp, 2017. "The risk elicitation puzzle," Nature Human Behaviour, Nature, vol. 1(11), pages 803-809, November.
    36. Robert J. Johnston & Kevin J. Boyle & Wiktor (Vic) Adamowicz & Jeff Bennett & Roy Brouwer & Trudy Ann Cameron & W. Michael Hanemann & Nick Hanley & Mandy Ryan & Riccardo Scarpa & Roger Tourangeau & Ch, 2017. "Contemporary Guidance for Stated Preference Studies," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(2), pages 319-405.
    37. Muller, Werner G & Ponce de Leon, Antonio C M, 1996. "Optimal Design of an Experiment in Economics," Economic Journal, Royal Economic Society, vol. 106(434), pages 122-127, January.
    38. Adrian Bruhin & Helga Fehr-Duda & Thomas Epper, 2010. "Risk and Rationality: Uncovering Heterogeneity in Probability Distortion," Econometrica, Econometric Society, vol. 78(4), pages 1375-1412, July.
    39. Buschena, David E. & Atwood, Joseph A., 2011. "Evaluation of similarity models for expected utility violations," Journal of Econometrics, Elsevier, vol. 162(1), pages 105-113, May.
    40. Shyamal Chowdhury & Matthias Sutter & Klaus F. Zimmermann, 2022. "Economic Preferences across Generations and Family Clusters: A Large-Scale Experiment in a Developing Country," Journal of Political Economy, University of Chicago Press, vol. 130(9), pages 2361-2410.
    41. B. Douglas Bernheim & Rebecca Royer & Charles Sprenger, 2022. "Robustness of Rank Independence in Risky Choice," AEA Papers and Proceedings, American Economic Association, vol. 112, pages 415-420, May.
    42. Tversky, Amos & Kahneman, Daniel, 1986. "Rational Choice and the Framing of Decisions," The Journal of Business, University of Chicago Press, vol. 59(4), pages 251-278, October.
    43. Liu, Elaine M. & Huang, JiKun, 2013. "Risk preferences and pesticide use by cotton farmers in China," Journal of Development Economics, Elsevier, vol. 103(C), pages 202-215.
    44. Cary Frydman & Lawrence J Jin, 2022. "Efficient Coding and Risky Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(1), pages 161-213.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fidanoski, Filip & Johnson, Timothy, 2023. "A z-Tree implementation of the Dynamic Experiments for Estimating Preferences [DEEP] method," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    2. Jonathan Chapman & Erik Snowberg & Stephanie Wang & Colin Camerer, 2018. "Loss Attitudes in the U.S. Population: Evidence from Dynamically Optimized Sequential Experimentation (DOSE)," NBER Working Papers 25072, National Bureau of Economic Research, Inc.
    3. Kpegli, Yao Thibaut & Corgnet, Brice & Zylbersztejn, Adam, 2023. "All at once! A comprehensive and tractable semi-parametric method to elicit prospect theory components," Journal of Mathematical Economics, Elsevier, vol. 104(C).
    4. Gary Charness & Thomas Garcia & Theo Offerman & Marie Claire Villeval, 2020. "Do measures of risk attitude in the laboratory predict behavior under risk in and outside of the laboratory?," Journal of Risk and Uncertainty, Springer, vol. 60(2), pages 99-123, April.
    5. Ferdinand M. Vieider & Peter Martinsson & Pham Khanh Nam & Nghi Truong, 2019. "Risk preferences and development revisited," Theory and Decision, Springer, vol. 86(1), pages 1-21, February.
    6. Toritseju Begho & Kelvin Balcombe, 2023. "Attitudes to Risk and Uncertainty: New Insights From an Experiment Using Interval Prospects," SAGE Open, , vol. 13(3), pages 21582440231, July.
    7. Tamás Csermely & Alexander Rabas, 2016. "How to reveal people’s preferences: Comparing time consistency and predictive power of multiple price list risk elicitation methods," Journal of Risk and Uncertainty, Springer, vol. 53(2), pages 107-136, December.
    8. Menkhoff, Lukas & Sakha, Sahra, 2017. "Estimating risky behavior with multiple-item risk measures," Journal of Economic Psychology, Elsevier, vol. 59(C), pages 59-86.
    9. Balcombe, Kelvin & Bardsley, Nicholas & Dadzie, Sam & Fraser, Iain, 2019. "Estimating parametric loss aversion with prospect theory: Recognising and dealing with size dependence," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 106-119.
    10. Julia Ihli, Hanna & Chiputwa, Brian & Winter, Etti & Gassner, Anja, 2022. "Risk and time preferences for participating in forest landscape restoration: The case of coffee farmers in Uganda," World Development, Elsevier, vol. 150(C).
    11. Villacis, Alexis H., 2023. "Inconsistent choices over prospect theory lottery games: Evidence from field experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 103(C).
    12. Golo-Friedrich Bauermeister & Daniel Hermann & Oliver Musshoff, 2018. "Consistency of determined risk attitudes and probability weightings across different elicitation methods," Theory and Decision, Springer, vol. 84(4), pages 627-644, June.
    13. Ryan O. Murphy & Robert H. W. ten Brincke, 2018. "Hierarchical Maximum Likelihood Parameter Estimation for Cumulative Prospect Theory: Improving the Reliability of Individual Risk Parameter Estimates," Management Science, INFORMS, vol. 64(1), pages 308-328, January.
    14. Holzmeister, Felix & Stefan, Matthias, 2019. "The Risk Elicitation Puzzle Revisited: Across-Methods (In)consistency?," OSF Preprints pj9u2, Center for Open Science.
    15. Eriksen, Kristoffer W. & Kvaløy, Ola & Luzuriaga, Miguel, 2020. "Risk-taking on behalf of others," Journal of Behavioral and Experimental Finance, Elsevier, vol. 26(C).
    16. Barrafrem, Kinga & Hausfeld, Jan, 2020. "Tracing risky decisions for oneself and others: The role of intuition and deliberation," Journal of Economic Psychology, Elsevier, vol. 77(C).
    17. Ola Andersson & Håkan J. Holm & Jean-Robert Tyran & Erik Wengström, 2020. "Robust inference in risk elicitation tasks," Journal of Risk and Uncertainty, Springer, vol. 61(3), pages 195-209, December.
    18. Pavlo Blavatskyy, 2018. "A second-generation disappointment aversion theory of decision making under risk," Theory and Decision, Springer, vol. 84(1), pages 29-60, January.
    19. Felix Holzmeister & Matthias Stefan, 2021. "The risk elicitation puzzle revisited: Across-methods (in)consistency?," Experimental Economics, Springer;Economic Science Association, vol. 24(2), pages 593-616, June.
    20. Felix Holzmeister & Matthias Stefan, 2019. "The risk elicitation puzzle revisited: Across-methods (in)consistency?," Working Papers 2019-19, Faculty of Economics and Statistics, Universität Innsbruck.

    More about this item

    Keywords

    Experimental Design; Lotteries; Risk and Uncertainty; Prospect Theory.;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:119743. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.