Peer effects in the online peer-to-peer lending market: Ex-ante selection and ex-post learning

Kung-Cheng Ho, Yan Gu, Cheng Yan and Giray Gözgör

International Review of Financial Analysis, 2024, vol. 92, issue C

Abstract: This study investigates peer effects in the online peer-to-peer (P2P) lending market using data from a Chinese online lending platform, Renrendai. The empirical results indicate that both the borrowers' success rate in obtaining loans and the default rate after loans are deemed non-coercive among their peers, referred to as the peer effects of lending and peer effects of default, respectively. The peer effect of lending is more pronounced in high-risk cities, whereas the peer effect of defaulting is more pronounced for borrowers with more difficulty obtaining loans, indicating ex-ante selection and ex-post learning mechanisms, respectively. The peer effects of lending promote P2P lending market efficiency, and the peer effects of defaulting inhibit market efficiency. Collectively, our results suggest that both lenders and borrowers follow peer effects to reduce information asymmetry in P2P lending markets.

Keywords: P2P lending; Peer effect; Ex-ante selection; Ex-post learning; Information asymmetry (search for similar items in EconPapers)
JEL-codes: G23 G30 G32 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:92:y:2024:i:c:s1057521923005720

DOI: 10.1016/j.irfa.2023.103056

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