IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v13y2023i4p21582440231201378.html
   My bibliography  Save this article

Relationship Between Interest Rate and Risk of P2P Lending in China Based on the Skew-Normal Panel Data Model

Author

Listed:
  • Rendao Ye
  • Ya Lin

Abstract

This study examines the relationship between interest rate and defunct platform risk of China’s peer-to-peer (P2P) lending platforms. P2P lending provides an alternative funding source for individuals and micro-enterprises and offers a new investment tool for households. But the frequent collapses of many platforms were huge losses to market participants and even led to a decline in China’s P2P lending industry. In this study, weekly data of 76 platforms from December 3, 2017, to October 6, 2019, are employed, and empirical research based on the normal and skew-normal panel data model respectively is conducted. Statistical indicators prove that the skew-normal panel data model is preferable to another one in modeling the data set of interest rates. The empirical results show that China’s P2P market is efficient overall. But the positive correlation between the interest rate and risk is not significant for platforms with excessively high interest rates, whose interest rates are more determined by the types of ownership. The findings and implications are provided in the end.

Suggested Citation

  • Rendao Ye & Ya Lin, 2023. "Relationship Between Interest Rate and Risk of P2P Lending in China Based on the Skew-Normal Panel Data Model," SAGE Open, , vol. 13(4), pages 21582440231, October.
  • Handle: RePEc:sae:sagope:v:13:y:2023:i:4:p:21582440231201378
    DOI: 10.1177/21582440231201378
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440231201378
    Download Restriction: no

    File URL: https://libkey.io/10.1177/21582440231201378?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. A. Azzalini & A. Capitanio, 1999. "Statistical applications of the multivariate skew normal distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 579-602.
    2. GUO, Jianfeng & LIU, Xiaojie & CUI, Changnan & GU, Fu, 2021. "Influence of nonspecific factors on the interest rate of online peer-to-peer microloans in China," Finance Research Letters, Elsevier, vol. 41(C).
    3. Mingfeng Lin & Nagpurnanand R. Prabhala & Siva Viswanathan, 2013. "Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 59(1), pages 17-35, August.
    4. Sune Karlsson & Jimmy Skoglund, 2004. "Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects," Empirical Economics, Springer, vol. 29(1), pages 79-88, January.
    5. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    6. Daowen Zhang & Marie Davidian, 2001. "Linear Mixed Models with Flexible Distributions of Random Effects for Longitudinal Data," Biometrics, The International Biometric Society, vol. 57(3), pages 795-802, September.
    7. Jefferson Duarte & Stephan Siegel & Lance Young, 2012. "Trust and Credit: The Role of Appearance in Peer-to-peer Lending," Review of Financial Studies, Society for Financial Studies, vol. 25(8), pages 2455-2484.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jing Zhang & Wei Zhang & Yuelei Li & Shuxing Yin, 2021. "Seeking excess returns under a posted price mechanism: Evidence from a peer‐to‐peer lending market," Manchester School, University of Manchester, vol. 89(5), pages 486-506, September.
    2. Manconi, Alberto & Braggion, Fabio & Zhu, Haikun, 2018. "Can Technology Undermine Macroprudential Regulation? Evidence from Peer-to-Peer Credit in China," CEPR Discussion Papers 12668, C.E.P.R. Discussion Papers.
    3. M. Teimourian & T. Baghfalaki & M. Ganjali & D. Berridge, 2015. "Joint modeling of mixed skewed continuous and ordinal longitudinal responses: a Bayesian approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(10), pages 2233-2256, October.
    4. Ye, Rendao & Wang, Tonghui & Gupta, Arjun K., 2014. "Distribution of matrix quadratic forms under skew-normal settings," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 229-239.
    5. Xueru Chen & Xiaoji Hu & Shenglin Ben, 2021. "How do reputation, structure design and FinTech ecosystem affect the net cash inflow of P2P lending platforms? Evidence from China," Electronic Commerce Research, Springer, vol. 21(4), pages 1055-1082, December.
    6. Lourdes Montenegro & Víctor Lachos & Heleno Bolfarine, 2010. "Inference for a skew extension of the Grubbs model," Statistical Papers, Springer, vol. 51(3), pages 701-715, September.
    7. Peng Wang & Haichao Zheng & Dongyu Chen & Liangchao Ding, 2015. "Exploring the critical factors influencing online lending intentions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-11, December.
    8. Dongyu Chen & Xiaolin Li & Fujun Lai, 2023. "Shill bidding in lenders’ eyes? A cross-country study on the influence of large bids in online P2P lending," Electronic Commerce Research, Springer, vol. 23(2), pages 1089-1114, June.
    9. de Roure, Calebe & Pelizzon, Loriana & Tasca, Paolo, 2016. "How does P2P lending fit into the consumer credit market?," Discussion Papers 30/2016, Deutsche Bundesbank.
    10. Dorfleitner, Gregor & Rad, Jacqueline & Weber, Martina, 2017. "Pricing in the online invoice trading market: First empirical evidence," Economics Letters, Elsevier, vol. 161(C), pages 56-61.
    11. Teply, Petr & Polena, Michal, 2020. "Best classification algorithms in peer-to-peer lending," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    12. José María Liberti & Mitchell A. Petersen, 2018. "Information: Hard and Soft," NBER Working Papers 25075, National Bureau of Economic Research, Inc.
    13. Carla Martínez-Climent & Ana Zorio-Grima & Domingo Ribeiro-Soriano, 2018. "Financial return crowdfunding: literature review and bibliometric analysis," International Entrepreneurship and Management Journal, Springer, vol. 14(3), pages 527-553, September.
    14. Xuchen Lin & Xiaolong Li & Zhong Zheng, 2017. "Evaluating borrower’s default risk in peer-to-peer lending: evidence from a lending platform in China," Applied Economics, Taylor & Francis Journals, vol. 49(35), pages 3538-3545, July.
    15. Qizhi Tao & Yizhe Dong & Ziming Lin, 2017. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 19(3), pages 425-441, June.
    16. José Jacinto Bilau & Jorge Pires, 2018. "What Drives The Funding Success Of Reward-Based Crowdfunding Campaigns?," Poslovna izvrsnost/Business Excellence, Faculty of Economics and Business, University of Zagreb, vol. 12(2), pages 27-40.
    17. Jianrong Yao & Jiarui Chen & June Wei & Yuangao Chen & Shuiqing Yang, 2019. "The relationship between soft information in loan titles and online peer-to-peer lending: evidence from RenRenDai platform," Electronic Commerce Research, Springer, vol. 19(1), pages 111-129, March.
    18. Jiang, Jinglin & Liao, Li & Wang, Zhengwei & Zhang, Xiaoyan, 2021. "Government Affiliation and Peer-To-Peer Lending Platforms in China," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 87-106.
    19. Huaiqing Wang & Kun Chen & Wei Zhu & Zhenxia Song, 2015. "A process model on P2P lending," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-8, December.
    20. Lu, Haitian & Wang, Bo & Wang, Haizhi & Zhao, Tianyu, 2020. "Does social capital matter for peer-to-peer-lending? Empirical evidence," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:sagope:v:13:y:2023:i:4:p:21582440231201378. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.