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Social heterogeneity and local bias in peer-to-peer lending – evidence from China

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  • Jiang, Jiajun
  • Liu, Yu-Jane
  • Lu, Ruichang

Abstract

This paper investigates the presence of local bias in the peer-to-peer (P2P) lending market and explores the social heterogeneous factors that may affect the formulation of the investor's local bias. We find that local biases are commonly present among investors. Investors have a 9.3% higher probability and put 105% more money in lending to local borrowers. We also find that overinvesting in local loans is correlated with higher default risk, lower recovery rate, and lower realized return, suggesting the underperformance of these locally biased investors. By taking advantage of the diverse local culture and institutional features in China, we further show that social heterogeneity, including geography, language, and social trust, affects the degree of local biases in the P2P lending market. We propose two debiasing techniques from the P2P platforms’ perspective.

Suggested Citation

  • Jiang, Jiajun & Liu, Yu-Jane & Lu, Ruichang, 2020. "Social heterogeneity and local bias in peer-to-peer lending – evidence from China," Journal of Comparative Economics, Elsevier, vol. 48(2), pages 302-324.
  • Handle: RePEc:eee:jcecon:v:48:y:2020:i:2:p:302-324
    DOI: 10.1016/j.jce.2019.11.001
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    3. Arif Perdana & Pearpilai Jutasompakorn & Sunghun Chung, 2023. "Shaping crowdlending investors’ trust: Technological, social, and economic exchange perspectives," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-17, December.
    4. Samuel Ribeiro-Navarrete & Juan Piñeiro-Chousa & M. Ángeles López-Cabarcos & Daniel Palacios-Marqués, 2022. "Crowdlending: mapping the core literature and research frontiers," Review of Managerial Science, Springer, vol. 16(8), pages 2381-2411, November.
    5. Jin, Ming & Liu, Jinshan & Chen, Zhongfei, 2022. "Impacts of social trust on corporate leverage: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 505-521.
    6. Said Kaawach & Oskar Kowalewski & Oleksandr Talavera, 2023. "Automatic vs Manual Investing: Role of Past Performance," Discussion Papers 23-04, Department of Economics, University of Birmingham.
    7. Li, Jianwen, 2023. "MSMEs meet FinTech: Chance or challenge?," Finance Research Letters, Elsevier, vol. 57(C).
    8. Kee Hoon Chung & Hyeok Yong Kwon, 2021. "Trust and the protection of property rights: evidence from global regions," Public Choice, Springer, vol. 189(3), pages 493-513, December.
    9. Li, Jianwen & Zhang, Bo & Jiang, Mingming & Hu, Jinyan, 2023. "Homophilous intensity in the online lending market: Bidding behavior and economic effects," Journal of Banking & Finance, Elsevier, vol. 152(C).
    10. Jianwen Li & Jinyan Hu, 2022. "Migrants and default: Evidence from China," International Review of Finance, International Review of Finance Ltd., vol. 22(3), pages 472-505, September.
    11. Jin, Ming & Yin, Mingmei & Chen, Zhongfei, 2021. "Do investors prefer borrowers from high level of trust cities? Evidence from China’s P2P market," Research in International Business and Finance, Elsevier, vol. 58(C).

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    More about this item

    Keywords

    Peer-to-peer lending; Local bias; Asymmetric information; Social trust;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G29 - Financial Economics - - Financial Institutions and Services - - - Other
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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