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As Easy as Pie: How Retirement Savers use Prescribed Investment Disclosures

Author

Listed:
  • Hazel Bateman

    (School of Risk and Actuarial Studies, University of New South Wales)

  • Isabella Dobrescu

    (CEPAR and School of Economics, University of New South Wales)

  • Ben R. Newell

    (School of Psychology, University of New South Wales)

  • Andreas Ortmann

    (School of Economics, University of New South Wales)

  • Susan Thorp

    (University of Sydney)

Abstract

We report the results of two laboratory experiments that study how university student and staff participants chose retirement savings investment options using ‘user-friendly’ information prescribed by regulators. We demonstrate that choices of more than 20% of participants cannot be predicted using any of the prescribed information items but that 30% of participants used all, or almost all, items, frequently in unexpected ways. A pie-chart showing asset allocation had the largest marginal impact on investment choices. Participants preferred options with more segmented pies (lower concentration) and with equally sized segments (lower deviation froma 1/n allocation). This choice behavior is consistent with the application of a simple diversification heuristic. Participants cannot choose more than one investment but are guided by the extent to which a pre-mixed investment option appears evenly balanced across asset classes. This novel application of a 1/n strategy is distinct from existing findings of naïve diversification in ‘mix-it-yourself’ conditions where participants spread resources evenly across funds or categories. The results highlight that information contained in prescribed investment disclosures may not be used in the manner intended by the regulator. The results also pose interesting methodological questions about the way ‘user-friendly’ information prescribed by regulators is validated before being legislated.

Suggested Citation

  • Hazel Bateman & Isabella Dobrescu & Ben R. Newell & Andreas Ortmann & Susan Thorp, 2013. "As Easy as Pie: How Retirement Savers use Prescribed Investment Disclosures," Research Paper Series 326, Quantitative Finance Research Centre, University of Technology, Sydney.
  • Handle: RePEc:uts:rpaper:326
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    File URL: https://www.uts.edu.au/sites/default/files/qfr-archive-03/QFR-rp326.pdf
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    Cited by:

    1. is not listed on IDEAS
    2. Cardella, Eric & Kalenkoski, Charlene M. & Parent, Michael, 2018. "Less Is Not More: Information Presentation Complexity and 401(k) Planning Choices," IZA Discussion Papers 11538, Institute of Labor Economics (IZA).
    3. Newall, Philip Warren Stirling & Parker, Katie, 2017. "Improved mutual fund investment choice architecture," OSF Preprints qknjt, Center for Open Science.
    4. Isler, Ozan & Rojas, Andres & Dulleck, Uwe, 2022. "Easy to shove, difficult to show: Effect of educative and default nudges on financial self-management," Journal of Behavioral and Experimental Finance, Elsevier, vol. 34(C).
    5. Keane, M.P. & Thorp, S., 2016. "Complex Decision Making," Handbook of the Economics of Population Aging, in: Piggott, John & Woodland, Alan (ed.), Handbook of the Economics of Population Aging, edition 1, volume 1, chapter 0, pages 661-709, Elsevier.
    6. Geoffrey Kingston & Susan Thorp, 2019. "Superannuation in Australia: A Survey of the Literature," The Economic Record, The Economic Society of Australia, vol. 95(308), pages 141-160, March.
    7. Daugaard, Dan & Kent, Danielle & Servátka, Maroš & Zhang, Le, 2023. "Optimistic framing increases responsible investment of investment professionals," MPRA Paper 119677, University Library of Munich, Germany.
    8. Keller, Elena & Ortmann, Andreas & Chambers, Georgina Mary, 2024. "Exploring the demand for elective egg freezing: A laboratory experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 111(C).
    9. Antonia Settle, 2021. "'Don't play if you can't win': exploring household disengagement with the pension system through financial diaries data," Melbourne Institute Working Paper Series wp2021n29, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    10. Emawtee Bissoondoyal-Bheenick & Robert Brooks & Hung Do, 2023. "Asset allocation of Australian superannuation funds: a markov regime switching approach," Annals of Operations Research, Springer, vol. 330(1), pages 485-515, November.
    11. Thorp, S. & Bateman, H. & Dobrescu, L.I. & Newell, B.R. & Ortmann, A., 2020. "Flicking the switch: Simplifying disclosure to improve retirement plan choices," Journal of Banking & Finance, Elsevier, vol. 121(C).
    12. Michael P. Keane & Susan Thorp, 2016. "Complex Decision Making: The Roles of Cognitive Limitations, Cognitive Decline and Ageing," Economics Papers 2016-W10, Economics Group, Nuffield College, University of Oxford.
    13. Hazel Bateman & Inka Eberhardt, 2024. "How Fact Sheets affect retirement income product knowledge, perceptions and choices," Australian Journal of Management, Australian School of Business, vol. 49(2), pages 119-141, May.
    14. Chernulich, Aleksei, 2021. "Modelling reference dependence for repeated choices: A horse race between models of normalisation," Journal of Economic Psychology, Elsevier, vol. 87(C).
    15. Robert L. McDonald & Thomas A. Rietz, 2018. "Ratings and Asset Allocation: An Experimental Analysis," NBER Working Papers 25046, National Bureau of Economic Research, Inc.
    16. Rafal Chomik & John Piggott, 2016. "Australian Superannuation: The Current State of Play," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 49(4), pages 483-493, December.
    17. repec:osf:osfxxx:qknjt_v1 is not listed on IDEAS
    18. Kim, Dongwoo, 2020. "Worker retirement responses to pension incentives: Do they respond to pension wealth?," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 365-385.
    19. Wang-Ly, Nathan & Bateman, Hazel & Dobrescu, Isabella & Newell, Ben R. & Thorp, Susan, 2022. "Defaults, disclosures, advice and calculators: One size does not fit all," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).

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    Keywords

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    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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