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Defaults and Attention: The Drop Out Effect

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  • Andrew Caplin
  • Daniel Martin

Abstract

Policy makers may try to reduce decision making errors by making a high quality option the default option. The positive effect of this policy can be undermined by “drop out” behavior in which the default is accepted hastily and with little regard for personal suitability. We measure the drop out effect in an experimental setting using response time as a proxy for attention. We find that this effect can completely offset the benefits of a high quality default. We use a model of costly attention to indicate conditions under which this drop out effect is rational and find moderate evidence that these conditions are satisfied.

Suggested Citation

  • Andrew Caplin & Daniel Martin, 2017. "Defaults and Attention: The Drop Out Effect," Revue économique, Presses de Sciences-Po, vol. 68(5), pages 747-755.
    • Handle: RePEc:cai:recosp:reco_pr3_0094
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    References listed on IDEAS

    as
    1. Gabriel D. Carroll & James J. Choi & David Laibson & Brigitte C. Madrian & Andrew Metrick, 2009. "Optimal Defaults and Active Decisions," The Quarterly Journal of Economics, Oxford University Press, vol. 124(4), pages 1639-1674.
    2. Patrick Bolton & Antoine Faure-Grimaud, 2009. "Thinking Ahead: The Decision Problem," Review of Economic Studies, Oxford University Press, vol. 76(4), pages 1205-1238.
    3. Ariel Rubinstein, 2007. "Instinctive and Cognitive Reasoning: Response Times Study," Levine's Bibliography 321307000000001011, UCLA Department of Economics.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Altmann, Steffen & Falk, Armin & Grunewald, Andreas, 2013. "Incentives and Information as Driving Forces of Default Effects," IZA Discussion Papers 7610, Institute of Labor Economics (IZA).
    2. Altmann, Steffen & Falk, Armin & Heidhues, Paul & Jayaraman, Rajshri, 2014. "Defaults and Donations: Evidence from a Field Experiment," IZA Discussion Papers 8680, Institute of Labor Economics (IZA).
    3. Kenan Kalaycı & Marta Serra-Garcia, 2016. "Complexity and biases," Experimental Economics, Springer;Economic Science Association, vol. 19(1), pages 31-50, March.
    4. Tse, Alan & Friesen, Lana & Kalaycı, Kenan, 2016. "Complexity and asset legitimacy in retirement investment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 60(C), pages 35-48.
    5. repec:eee:joecag:v:1-2:y:2013:i::p:83-89 is not listed on IDEAS
    6. Steffen Altmann & Armin Falk & Paul Heidhues & Rajshri Jayaraman, 2014. "Defaults and Donations: Evidence from a Field Experiment," CESifo Working Paper Series 5118, CESifo Group Munich.
    7. Blumenstock, Joshua & Callen, Michael & Ghani, Tarek, 2016. "Mobile-izing Savings with Automatic Contributions: Experimental Evidence on Present Bias and Default Effects in Afghanistan," CEPR Discussion Papers 11400, C.E.P.R. Discussion Papers.

    More about this item

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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