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Learning by Doing with Asymmetric Information: Evidence from Prosper.com

Author

Listed:
  • Seth M. Freedman
  • Ginger Zhe Jin

Abstract

Using peer-to-peer (P2P) lending as an example, we show that learning by doing plays an important role in alleviating the information asymmetry between market players. Although the P2P platform (Prosper.com) discloses part of borrowers' credit histories, lenders face serious information problems because the market is new and subject to adverse selection relative to offline markets. We find that early lenders did not fully understand the market risk but lender learning is effective in reducing the risk over time. As a result, the market excludes more and more sub-prime borrowers and evolves towards the population served by traditional credit markets.

Suggested Citation

  • Seth M. Freedman & Ginger Zhe Jin, 2011. "Learning by Doing with Asymmetric Information: Evidence from Prosper.com," NBER Working Papers 16855, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16855
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    References listed on IDEAS

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    1. Igal Hendel & Aviv Nevo & François Ortalo-Magné, 2009. "The Relative Performance of Real Estate Marketing Platforms: MLS versus FSBOMadison.com," American Economic Review, American Economic Association, vol. 99(5), pages 1878-1898, December.
    2. Xavier Vives, 1993. "How Fast do Rational Agents Learn?," Review of Economic Studies, Oxford University Press, vol. 60(2), pages 329-347.
    3. Ginger Zhe Jin & Andrew Kato, 2007. "Dividing Online and Offline: A Case Study," Review of Economic Studies, Oxford University Press, vol. 74(3), pages 981-1004.
    4. Alma Cohen & Peter Siegelman, 2010. "Testing for Adverse Selection in Insurance Markets," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(1), pages 39-84.
    5. Byoung Jun & Xavier Vives, 1996. "Learning and Convergence to a Full-Information Equilibrium are not Equivalent," Review of Economic Studies, Oxford University Press, vol. 63(4), pages 653-674.
    6. Timothy C. Salmon, 2001. "An Evaluation of Econometric Models of Adaptive Learning," Econometrica, Econometric Society, vol. 69(6), pages 1597-1628, November.
    7. Sharpe, Steven A, 1990. " Asymmetric Information, Bank Lending, and Implicit Contracts: A Stylized Model of Customer Relationships," Journal of Finance, American Finance Association, vol. 45(4), pages 1069-1087, September.
    8. Iyer, Rajkamal & Khwaja, Asim Ijaz & Luttmer, Erzo F. P. & Shue, Kelly, 2009. "Screening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending?," Working Paper Series rwp09-031, Harvard University, John F. Kennedy School of Government.
    9. Oren Rigbi, 2013. "The Effects of Usury Laws: Evidence from the Online Loan Market," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1238-1248, October.
    10. Seth Freedman & Ginger Zhe Jin, 2008. "Do Social Networks Solve Information Problems for Peer-to-Peer Lending? Evidence from Prosper.com," Working Papers 08-43, NET Institute.
    11. Uta Schönberg, 2007. "Testing for Asymmetric Employer Learning," Journal of Labor Economics, University of Chicago Press, vol. 25, pages 651-691.
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    Citations

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    Cited by:

    1. Rajkamal Iyer & Asim Ijaz Khwaja & Erzo F. P. Luttmer & Kelly Shue, 2016. "Screening Peers Softly: Inferring the Quality of Small Borrowers," Management Science, INFORMS, vol. 62(6), pages 1554-1577, June.
    2. Iván Abarca, 2018. "Desarrollo del Crowdfunding en Chile," Working Papers Central Bank of Chile 815, Central Bank of Chile.
    3. Oleksandr Talavera & Haofeng Xu, 2018. "Role of Verification in Peer-to-Peer Lending," Working Papers 2018-25, Swansea University, School of Management.
    4. Chen, Ning & Ghosh, Arpita & Lambert, Nicolas S., 2011. "Auctions for Social Lending: A Theoretical Analysis," Research Papers 2078, Stanford University, Graduate School of Business.
    5. Belleflamme, Paul & Omrani, Nessrine & Peitz, Martin, 2015. "The economics of crowdfunding platforms," Information Economics and Policy, Elsevier, vol. 33(C), pages 11-28.
    6. Oren Rigbi, 2013. "The Effects of Usury Laws: Evidence from the Online Loan Market," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1238-1248, October.
    7. repec:pal:compes:v:60:y:2018:i:1:d:10.1057_s41294-017-0045-1 is not listed on IDEAS
    8. Miller, Sarah, 2015. "Information and default in consumer credit markets: Evidence from a natural experiment," Journal of Financial Intermediation, Elsevier, vol. 24(1), pages 45-70.
    9. Chen, Ning & Ghosh, Arpita & Lambert, Nicolas S., 2014. "Auctions for social lending: A theoretical analysis," Games and Economic Behavior, Elsevier, vol. 86(C), pages 367-391.
    10. Freedman, Seth & Jin, Ginger Zhe, 2017. "The information value of online social networks: Lessons from peer-to-peer lending," International Journal of Industrial Organization, Elsevier, vol. 51(C), pages 185-222.
    11. BELLEFLAMME, Paul & LAMBERT, Thomas & SCHWIENBACHER, Armin, 2011. "Crowdfunding: tapping the right crowd," CORE Discussion Papers 2011032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. repec:spt:apfiba:v:7:y:2017:i:3:f:7_3_8 is not listed on IDEAS
    13. Benjamin Edelman, 2012. "Using Internet Data for Economic Research," Journal of Economic Perspectives, American Economic Association, vol. 26(2), pages 189-206, Spring.
    14. Ajay K. Agrawal & Christian Catalini & Avi Goldfarb, 2011. "The Geography of Crowdfunding," NBER Working Papers 16820, National Bureau of Economic Research, Inc.
    15. Jagtiani, Julapa & Lemieux, Catharine, 2017. "Fintech Lending: Financial Inclusion, Risk Pricing, and Alternative Information," Working Papers 17-17, Federal Reserve Bank of Philadelphia.

    More about this item

    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

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