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Magnitude effects in lending and borrowing:Empirical evidence from a P2P platform

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  • Breuer, Wolfgang

    (RWTH Aachen University, Germany)

  • Soypak, Can K.

    (RWTH Aachen University, Germany)

  • Steininger, Bertram

    (Department of Real Estate and Construction Management, Royal Institute of Technology)

Abstract

For varying borrowing and lending amounts, the corresponding subjective discount rates will also vary. A situation where high amounts correspond to lower discount rates is called a conventional magnitude effect, while the op-posite is called a reverse magnitude effect. We present an overview of the theoretical arguments for both kinds of magnitude effects. Against this back-ground, we then offer the first comprehensive empirical analysis of this issue based on real-life transaction data. To do so, we rely on more than 9,000 credit applications from the formerly largest German peer-to-peer (P2P) lending platform, Smava, between February 2007 and April 2013. We con-firm that there is a conventional magnitude effect for lending money to oth-ers but a reverse magnitude effect for borrowing decisions. We suggest, as an explanation for our findings, the prevalence of cost-based determinants of magnitude effects in this special setting.

Suggested Citation

  • Breuer, Wolfgang & Soypak, Can K. & Steininger, Bertram, 2020. "Magnitude effects in lending and borrowing:Empirical evidence from a P2P platform," Working Paper Series 20/4, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    • Handle: RePEc:hhs:kthrec:2020_004
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    1. Breuer, Wolfgang & Soypak, Can K. & Steininger, Bertram, 2020. "Conventional or Reverse Magnitude Effect for Negative Outcomes: A Matter of Framing," Working Paper Series 20/16, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.

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    More about this item

    Keywords

    Discounting anomalies; magnitude effects; P2P platform; time preferences;
    All these keywords.

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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