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Diagnostic Uncertainty and Insurance Coverage in Credence Goods Markets

Author

Listed:
  • Loukas Balafoutas
  • Helena Fornwagner
  • Rudolf Kerschbamer
  • Matthias Sutter
  • Maryna Tverdostup
Abstract
Credence goods markets – like for health care or repair services – with their informational asymmetries between sellers and customers are prone to fraudulent behavior of sellers and resulting market inefficiencies. We present the first model that considers both diagnostic uncertainty of sellers and the effects of insurance coverage of consumers in a unified framework. We test the model’s predictions in a laboratory experiment. Both in theory and in the experiment diagnostic uncertainty decreases the rate of efficient service provision and leads to less trade. In theory, insurance also decreases the rate of efficient service provision, but at the same time it also increases the volume of trade, leading to an ambiguous net effect on welfare. In the experiment, the net effect of insurance coverage on efficiency turns out to be positive. We also uncover an important interaction effect: if consumers are insured, experts invest less in diagnostic precision. We discuss policy implications of our results.

Suggested Citation

  • Loukas Balafoutas & Helena Fornwagner & Rudolf Kerschbamer & Matthias Sutter & Maryna Tverdostup, 2020. "Diagnostic Uncertainty and Insurance Coverage in Credence Goods Markets," CESifo Working Paper Series 8681, CESifo.
    • Handle: RePEc:ces:ceswps:_8681
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Balafoutas, Loukas & Kerschbamer, Rudolf, 2020. "Credence goods in the literature: What the past fifteen years have taught us about fraud, incentives, and the role of institutions," Journal of Behavioral and Experimental Finance, Elsevier, vol. 26(C).
    2. Mehdi Ayouni & Thomas Lanzi, 2022. "Credence goods, consumer feedback and (in)efficiency," Working Papers of BETA 2022-27, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    3. Minyan Zhu, 2021. "Evidence-Based Medicine and Healthcare Quality in the Context of Information Failure: The Case of the UK Fertility Sector," PharmacoEconomics - Open, Springer, vol. 5(4), pages 561-576, December.
    4. Lagarde, Mylène & Blaauw, Duane, 2022. "Overtreatment and benevolent provider moral hazard: Evidence from South African doctors," Journal of Development Economics, Elsevier, vol. 158(C).
    5. Lagarde, Mylène & Blaauw, Duane, 2022. "Overtreatment and benevolent provider moral hazard: evidence from South African doctors," LSE Research Online Documents on Economics 115383, London School of Economics and Political Science, LSE Library.
    6. Evert Reins, 2021. "Seductive subsidies? An analysis of second-degree moral hazard in the context of photovoltaic solar systems," IRENE Working Papers 21-03, IRENE Institute of Economic Research.
    7. Alexander Erlei & Lukas Meub, 2024. "Technological Shocks and Algorithmic Decision Aids in Credence Goods Markets," Papers 2401.17929, arXiv.org, revised Apr 2024.
    8. Fang Liu & Alexander Rasch & Marco Alexander Schwarz & Christian Waibel, 2020. "The Role of Diagnostic Ability in Markets for Expert Services," CESifo Working Paper Series 8704, CESifo.

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    More about this item

    Keywords

    credence goods; diagnostic uncertainty; insurance coverage; welfare; model; experiment;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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