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Complex Decision Making

In: Handbook of the Economics of Population Aging

Author

Listed:
  • Keane, M.P.
  • Thorp, S.

Abstract

We review the evidence on decision making in complex choice situations—i.e., situations where there are many alternatives and/or where attributes of alternatives are difficult to understand. We focus on choices about health insurance, health care, and retirement planning, all of which are very important for the well-being of the elderly. Our review suggests that consumers in general, and the elderly in particular, have great difficulty making optimal choices in these areas. They often behave in ways that imply a high degree of “confusion,” such as (i) failure to understand key attributes of alternatives or (ii) inadequate cognitive capacity to process payoff relevant information. We go on to discuss extensions to standard rational choice models that account for consumer confusion. These include allowing perceived attributes to depart from true attributes, the use of heuristics, and inattention or procrastination. Such departures from rationality can be moderated by cognitive ability, age, etc. We hope that these new models may be useful in designing paternalistic interventions.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:hapoch:v1_661
    DOI: 10.1016/bs.hespa.2016.09.001
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    Cited by:

    1. Jonathan D. Ketcham & Nicolai V. Kuminoff & Christopher A. Powers, 2016. "Estimating the Heterogeneous Welfare Effects of Choice Architecture: An Application to the Medicare Prescription Drug Insurance Market," NBER Working Papers 22732, National Bureau of Economic Research, Inc.
    2. Kuti, Mónika & Schepp, Zoltán, 2020. "Aging Society and Attitude to Risk," Public Finance Quarterly, Corvinus University of Budapest, vol. 65(4), pages 457-471.
    3. Paula Cristina Albuquerque, 2017. "Information intermediaries in the social care market for the older population," Working Papers Department of Economics 2017/17, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    4. Chen, Xi, 2018. "Smog, Cognition and Real-World Decision Making," GLO Discussion Paper Series 266, Global Labor Organization (GLO).
    5. Keane, Michael & Ketcham, Jonathan & Kuminoff, Nicolai & Neal, Timothy, 2021. "Evaluating consumers’ choices of Medicare Part D plans: A study in behavioral welfare economics," Journal of Econometrics, Elsevier, vol. 222(1), pages 107-140.
    6. Amitabh Chandra & Courtney Coile & Corina Mommaerts, 2023. "What Can Economics Say about Alzheimer's Disease?," Journal of Economic Literature, American Economic Association, vol. 61(2), pages 428-470, June.
    7. Sulka, Tomasz, 2022. "Planning and saving for retirement," DICE Discussion Papers 384, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    8. Keane, Michael P. & Wasi, Nada, 2016. "How to model consumer heterogeneity? Lessons from three case studies on SP and RP data," Research in Economics, Elsevier, vol. 70(2), pages 197-231.
    9. Chakrabarti, Sandip, 2022. "Passively wait for gridlock, or proactively invest in service? Strategies to promote car-to-transit switches among aspirational urbanites in rapidly developing contexts," Transport Policy, Elsevier, vol. 115(C), pages 251-261.
    10. M. Kate Bundorf & Maria Polyakova & Ming Tai-Seale, 2019. "How do Humans Interact with Algorithms? Experimental Evidence from Health Insurance," NBER Working Papers 25976, National Bureau of Economic Research, Inc.
    11. Fabrizio Mazzonna & Franco Peracchi, 2018. "Self-assessed cognitive ability and financial wealth: Are people aware of their cognitive decline?," EIEF Working Papers Series 1808, Einaudi Institute for Economics and Finance (EIEF), revised Sep 2018.

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    More about this item

    Keywords

    Aging; Life cycle; Health insurance; Health care; Pensions; Retirement plans; Discrete choice models; I13; I11; J14; J32; H55; D14; D83; D84; D91; C35;
    All these keywords.

    JEL classification:

    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
    • J32 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Nonwage Labor Costs and Benefits; Retirement Plans; Private Pensions
    • H55 - Public Economics - - National Government Expenditures and Related Policies - - - Social Security and Public Pensions
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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