Numerological Heuristics and Credit Risk in Peer-to-Peer Lending

被引:1
|
作者
Hu, Maggie Rong [1 ]
Li, Xiaoyang [2 ]
Shi, Yang [3 ]
Zhang, Xiaoquan [4 ,5 ]
机构
[1] Chinese Univ Hong Kong, Business Sch, Shatin, NT, Hong Kong, Peoples R China
[2] Hong Kong Polytech Univ, Sch Accounting & Finance, PolyU Business Sch, Hung Hom,Kowloon, Hong Kong, Peoples R China
[3] Univ Melbourne, Fac Business & Econ, Dept Finance, Melbourne, Vic 3010, Australia
[4] Tsinghua Univ, Sch Econ & Management, Dept Management Sci & Engn, Shenzhen 518055, Peoples R China
[5] Chinese Univ Hong Kong, Business Sch, Hong Kong, Peoples R China
关键词
credit risk; numerological heuristics; round-number heuristic; lucky-number heuristic; information asymmetry; P2P lending; SUPERSTITIOUS BELIEFS; ONLINE; INFORMATION; EMBEDDEDNESS; INCENTIVES; PRECISION; PATTERNS; JUDGMENT; BEHAVIOR; IMPACT;
D O I
10.1287/isre.2023.1202
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Heuristics are mental shortcuts that have ubiquitous influences on decision making. We investigate whether and how different heuristics have distinct effects in the context of peer-to-peer (P2P) lending. Drawing on theories on the roles that heuristics play in decision making, we conjecture that when borrowers use different heuristics based on distinct motives to set their loan amounts, their funding success and repayment performance also differ. Using detailed P2P lending data from a Chinese P2P lending platform, we examine two important numerological heuristics, the round-number heuristic and the lucky-number heuristic, which are observable in over 80% of the submitted loan amounts. We find that round-number loans are less likely to get funded and exhibit poor repayment performance after being funded, whereas lucky-number loans exhibit the opposite pattern. These findings, which we attribute to the different motives behind the borrowers' heuristic choices, challenge the conventional understanding that generally treats all heuristics as behavioral biases. Our results are robust to various identification strategies, including coarsened exact matching and instrumental variable estimation. Our paper sheds new light on the heterogeneity of heuristics and their distinctive implications for the credit market.
引用
收藏
页码:1744 / 1760
页数:18
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