Can individual investors learn from experience in online P2P lending? Evidence from China

ZhouPing Li, RuYi Ge, XiaoShuang Guo and Lingfei Cai

The North American Journal of Economics and Finance, 2021, vol. 58, issue C

Abstract: This study utilizes an account-level dataset from a large Chinese online peer-to-peer (P2P) lending platform (PPdai.com) to examine whether and how P2P investors rationally learn from their experience. First, this study uses a Cox proportional hazard model to explore the influence of an investor’s initial ability on exit behavior. Then, a normal learning model is used to estimate the relationship between investor performance and experience. Finally, we develop a two-stage learning model to analyze the extent to which improvements in investor performance are driven by the effect of endogenous exit and the extent to which they are driven by increases in experience. The empirical results show that P2P investors learn rationally in two ways: the first way is by learning about their ability; the second way is by learning to improve their performance. The implications of these findings include the following: (a) P2P investors learn from experience to improve their performance without a guarantee mechanism; (b) Both ways of learning play an important role in alleviating investors’ adverse selection; and (c) for P2P platforms, introducing tests or screening mechanisms to reveal new investors’ ability and to exclude investors with low ability might be more valuable than retaining all investors.

Keywords: Online peer-to-peer lending; Investor learning; Endogenous exit; Two-step selection model; Experience (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:58:y:2021:i:c:s1062940821001406

DOI: 10.1016/j.najef.2021.101524

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