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

Jiajun Jiang, Yu-Jane Liu and Ruichang Lu

Journal of Comparative Economics, 2020, vol. 48, issue 2, 302-324

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.

Keywords: Peer-to-peer lending; Local bias; Asymmetric information; Social trust (search for similar items in EconPapers)
JEL-codes: G11 G18 G29 G41 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S014759671930099X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jcecon:v:48:y:2020:i:2:p:302-324

DOI: 10.1016/j.jce.2019.11.001

Access Statistics for this article

Journal of Comparative Economics is currently edited by D. Berkowitz and G. Roland

More articles in Journal of Comparative Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().