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The big picture of corruption: Five lessons from Behavioral Economics

Author

Listed:
  • Roberta Muramatsu

    (Adjunct Professor of Economics and Researcher of Mackenzie Center for Economic Freedom, Mackenzie Presbyterian University, Sao Paulo, Brazil)

  • Ana Maria Bianchi

    (Full Professor of The Faculty of Economics, Business Administration and Accounting of the University of Sao Paulo - USP, Sao Paulo, Brazil)

Abstract

The departure point of this paper is the conjecture that the search for big picture of corruption in the real world calls for new research and policy tools that draw on psychologically more realistic accounts of individual judgment and decision-making. In light with a growing literature that points to the major roles cognitive bias and social norms play in corrupt behaviors, we focus on presenting and discussing five main lessons from behavioral economics that enrichen the anti-corruption debate.

Suggested Citation

  • Roberta Muramatsu & Ana Maria Bianchi, 2021. "The big picture of corruption: Five lessons from Behavioral Economics," Journal of Behavioral Economics for Policy, Society for the Advancement of Behavioral Economics (SABE), vol. 5(S3), pages 55-62, October.
    • Handle: RePEc:beh:jbepv1:v:5:y:2021:i:s3:p:55-62
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    behavioral economics; corruption; methodology; experiments; policy;
    All these keywords.

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • B40 - Schools of Economic Thought and Methodology - - Economic Methodology - - - General
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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