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Social Capital, Trusting, and Trustworthiness: Evidence from Peer-to-Peer Lending

Published online by Cambridge University Press:  12 April 2021

Iftekhar Hasan Open the ORCID record for Iftekhar Hasan [Opens in a new window] ,
Qing He  and
Haitian Lu
Iftekhar Hasan
Affiliation:
Fordham University Gabelli School of Businessihasan@fordham.edu
Qing He*
Affiliation:
Renmin University of China School of Finance and China Financial Policy Research Center
Haitian Lu
Affiliation:
Hong Kong Polytechnic University Faculty of Businesshaitian.lu@polyu.edu.hk
*
qinghe@ruc.edu.cn (corresponding author)
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Abstract

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How does social capital affect trust? Evidence from a Chinese peer-to-peer lending platform shows that regional social capital affects the trustee’s trustworthiness and the trustor’s trust propensity. Ceteris paribus, borrowers from regions with higher social capital receive larger bids from individual lenders and have higher funding success, larger loan sizes, and lower default rates, especially for low-quality borrowers. Lenders from regions with higher social capital take higher risks and have higher default rates, especially for inexperienced lenders. Cross-regional transactions are most (least) likely to be realized between parties from regions with high (low) social capital.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 57 , Issue 4 , June 2022 , pp. 1409 - 1453
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

We appreciate helpful comments from James Ang (the referee) and Jarrad Harford (the editor). We are grateful for helpful comments from colleagues at our respective institutions. He gratefully acknowledges the funding support from the National Social Science Foundation of China (19AJY028, 20ZDA053). Lu gratefully acknowledges the funding support from the Hong Kong government (RGC/GRF Project 15605715) and HK Interactive Lab Limited. We also thank Xiaoyang Li and Jishuang Yu for excellent research assistance. The authors remain responsible for all errors and omissions.

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