Using a large dataset obtained from ＂Paipaidai,＂ an online peer-to-peer lending platform in China, we examine whether credit officers＇ mood affects the efficiency of credit approval from a perspective of individual...Using a large dataset obtained from ＂Paipaidai,＂ an online peer-to-peer lending platform in China, we examine whether credit officers＇ mood affects the efficiency of credit approval from a perspective of individual decision-making. Refering to studies in psychology and financial economics, we employ season, temperature and weather as mood proxies, and control the variables related to the quality of the loan to study credit approval behavior under different mood conditions. The results suggest that the efficiency of credit approval by individual credit officers is significantly correlated with their mood--a positive mood improves efficiency, while a negative mood reduces it. Specifically, loans examined under better mood conditions （e.g., during spring, comfortable temperatures, and sunny days） have a significantly higher probability of approval, but a lower probability of default if approved; and those examined under poorer mood conditions show a lower probability of approval and a higher probability of default if approved. This effect of mood is even stronger when a loan application is more complex, atypical, or unusual to evaluate. Moreover, investor sentiment, denoted by closed-end fund premiums, has the same effect on credit approval as well.展开更多
A dramatic surge in online peer-to-peer(P2P)lending emerged in China,where(under conditions of credit deficiency)it took only three years for the size of the P2P lending market in China to reach four times that of the...A dramatic surge in online peer-to-peer(P2P)lending emerged in China,where(under conditions of credit deficiency)it took only three years for the size of the P2P lending market in China to reach four times that of the United States and ten times that of the United Kingdom.The literature indicates that ownership structure is an important factor that influences P2P lending firms’performance,while research on the underlying mechanisms remain insufficient.This study analyzes the data of P2P lending companies between June 2016 and March 2017.The results demonstrate that although ownership structure has minimal direct effect on the turnover volume and number of lenders and borrowers,it moderates the effects of firm age,interest rate,and loan term on firm performance.These results enrich the property theory and shed light on how P2P lending firms with different ownership structures could succeed when there is institutional deficiency.展开更多
This study investigates the effect of voluntary disclosures on lending decisions in the repeated game.Using a unique dataset from a peer-to-peer lending platform,"ppdai" (poipaidai),we document that voluntar...This study investigates the effect of voluntary disclosures on lending decisions in the repeated game.Using a unique dataset from a peer-to-peer lending platform,"ppdai" (poipaidai),we document that voluntary disclosures in the repeated game play a stronger role in promoting funding success than those in the one-shot game.We argue that voluntary disclosures improve the bidding activity in the repeated game through which they increase funding success.In addition,the greater impact of voluntary disclosures on funding success in the repeated game only holds for loans without a personal guarantee attribution.Our extended results suggest that the subjective voluntary disclosures in the repeated game have greater information content only when borrowers have a successful borrowing experience.We also point out that voluntary disclosures in the repeated game are associated with a lower probability of default.Our results are robust to the Heckman two-step estimation that addresses the self-selection effect and a specification designed to rule out the alternative explanation from reputation in the repeated game.Our study provides new insights into the real effects of costless,voluntary and unverifiable disclosures on lending decisions.展开更多
For the first time,this paper uses the operation data of 575 online P2P lending platforms to test whether investors have a strong risk awareness of online lending products.It is found that investors’behavior shows a ...For the first time,this paper uses the operation data of 575 online P2P lending platforms to test whether investors have a strong risk awareness of online lending products.It is found that investors’behavior shows a certain risk awareness,both for the individual risk of specific platforms and for the overall market risk of the industry.On the one hand,raising interest rates and shortening the term does attract more investment,but for potentially problematic platforms,the effect of attracting investment is significantly worse,with excessive interest rates on the platforms even causing investors to invest less.On the other hand,when there are more online lending platforms in the market,investors will behave more cautiously.展开更多
提出一种改进Armstrong模型的网络借贷(网贷)平台定价方法。该方法在Armstrong模型中引入不同质量借款用户的间接网络外部性,基于双边市场理论构建了垄断条件下的P2P(peer to peer)网贷平台定价模型。通过对该模型求导计算来分析用户效...提出一种改进Armstrong模型的网络借贷(网贷)平台定价方法。该方法在Armstrong模型中引入不同质量借款用户的间接网络外部性,基于双边市场理论构建了垄断条件下的P2P(peer to peer)网贷平台定价模型。通过对该模型求导计算来分析用户效用与平台利润最大化的关系,得到网贷平台对借款用户和投资用户的最优定价。选取某网贷平台一年期的交易数据,利用最小二乘法进行实证分析,结果表明,借款用户网络外部性负向影响网贷平台对借款用户的定价,正向影响网贷平台对投资用户的定价,其影响的程度与平台上高质量借款用户占比有关,若网贷平台中的高质量借款用户占比降低,平台将提高对借款用户定价,同时降低平台对投资用户定价,反之则反之。展开更多
文摘Using a large dataset obtained from ＂Paipaidai,＂ an online peer-to-peer lending platform in China, we examine whether credit officers＇ mood affects the efficiency of credit approval from a perspective of individual decision-making. Refering to studies in psychology and financial economics, we employ season, temperature and weather as mood proxies, and control the variables related to the quality of the loan to study credit approval behavior under different mood conditions. The results suggest that the efficiency of credit approval by individual credit officers is significantly correlated with their mood--a positive mood improves efficiency, while a negative mood reduces it. Specifically, loans examined under better mood conditions （e.g., during spring, comfortable temperatures, and sunny days） have a significantly higher probability of approval, but a lower probability of default if approved; and those examined under poorer mood conditions show a lower probability of approval and a higher probability of default if approved. This effect of mood is even stronger when a loan application is more complex, atypical, or unusual to evaluate. Moreover, investor sentiment, denoted by closed-end fund premiums, has the same effect on credit approval as well.
文摘A dramatic surge in online peer-to-peer(P2P)lending emerged in China,where(under conditions of credit deficiency)it took only three years for the size of the P2P lending market in China to reach four times that of the United States and ten times that of the United Kingdom.The literature indicates that ownership structure is an important factor that influences P2P lending firms’performance,while research on the underlying mechanisms remain insufficient.This study analyzes the data of P2P lending companies between June 2016 and March 2017.The results demonstrate that although ownership structure has minimal direct effect on the turnover volume and number of lenders and borrowers,it moderates the effects of firm age,interest rate,and loan term on firm performance.These results enrich the property theory and shed light on how P2P lending firms with different ownership structures could succeed when there is institutional deficiency.
基金This study is supported by National Natural Science Foundation of China(No.71272150)National Social Science Foundation of China(No.15AZD012)Social Science Research Fund of Inner Mongolia Autonom ous Region in China(2017NDC145).
文摘This study investigates the effect of voluntary disclosures on lending decisions in the repeated game.Using a unique dataset from a peer-to-peer lending platform,"ppdai" (poipaidai),we document that voluntary disclosures in the repeated game play a stronger role in promoting funding success than those in the one-shot game.We argue that voluntary disclosures improve the bidding activity in the repeated game through which they increase funding success.In addition,the greater impact of voluntary disclosures on funding success in the repeated game only holds for loans without a personal guarantee attribution.Our extended results suggest that the subjective voluntary disclosures in the repeated game have greater information content only when borrowers have a successful borrowing experience.We also point out that voluntary disclosures in the repeated game are associated with a lower probability of default.Our results are robust to the Heckman two-step estimation that addresses the self-selection effect and a specification designed to rule out the alternative explanation from reputation in the repeated game.Our study provides new insights into the real effects of costless,voluntary and unverifiable disclosures on lending decisions.
文摘For the first time,this paper uses the operation data of 575 online P2P lending platforms to test whether investors have a strong risk awareness of online lending products.It is found that investors’behavior shows a certain risk awareness,both for the individual risk of specific platforms and for the overall market risk of the industry.On the one hand,raising interest rates and shortening the term does attract more investment,but for potentially problematic platforms,the effect of attracting investment is significantly worse,with excessive interest rates on the platforms even causing investors to invest less.On the other hand,when there are more online lending platforms in the market,investors will behave more cautiously.
文摘提出一种改进Armstrong模型的网络借贷(网贷)平台定价方法。该方法在Armstrong模型中引入不同质量借款用户的间接网络外部性,基于双边市场理论构建了垄断条件下的P2P(peer to peer)网贷平台定价模型。通过对该模型求导计算来分析用户效用与平台利润最大化的关系,得到网贷平台对借款用户和投资用户的最优定价。选取某网贷平台一年期的交易数据,利用最小二乘法进行实证分析,结果表明,借款用户网络外部性负向影响网贷平台对借款用户的定价,正向影响网贷平台对投资用户的定价,其影响的程度与平台上高质量借款用户占比有关,若网贷平台中的高质量借款用户占比降低,平台将提高对借款用户定价,同时降低平台对投资用户定价,反之则反之。
