移动互联网是否带来行为偏误——来自网络借贷市场的新证据

Whether Mobile Internet Access Leads to Behavioral Bias:Evidence from an Online Peer-to-peer Lending Market

本文讨论了使用移动互联网进行投资,相较于传统网络投资方式,可能产生的新型行为偏误。结果发现,在其他因素相同的情况下,投资者使用手机进行投资时更偏好于排名靠前的投资标的。利用网贷市场的交易数据,本文证实了手机投资者的排序偏好,并且发现排序偏好降低了投资绩效,这说明其中可能存在非理性的行为偏误。本文进一步发现,手机更高的信息搜索成本、受到更多的外部干扰都能解释移动投资者的行为偏误。金融素养差异无法解释这一新型行为偏误。从投资者保护的角度看,本文结果说明,针对不同投资渠道应当制定不同的风险提示与信息披露标准,提高移动互联网投资者的福利。

Summary:Mobile internet access allows financial services to be used with fewer restrictions on times and places,but these benefits also come with costs.Studies find that the cost of obtaining information on mobile devices is higher than it is on computers,making computers more suitable for exploratory tasks.However,there are few studies linking mobile internet access to investment behavior.We examine the behavioral biases of mobile investors and identify the underlying channels.We use the transaction records of all investors from 2011 to 2015 on a major domestic online peer-to-peer(P2P)lending marketplace to study investment behavior.Since the establishment of the first P2P platform in the U.K.in 2005,the P2P lending market has experienced exponential growth,becoming a compelling topic in the industry and for researchers.China s P2P lending market has been the world s largest P2P market since 2014.However,the rapid growth of these new markets has brought challenges to regulators.Therefore,a better understanding of investors behavior is important for implementing regulatory policies.China s P2P lending market is an ideal setting for studying the impact of mobile internet access on investment behavior.The P2P platform we study allows investors to access the platform using either a web page on a computer or a mobile app,and it introduced mobile investments in mid-2014,giving us the opportunity to study how the same investor behaves when using different investment methods.We investigate the behavioral bias of ranking preferences.Our empirical results show that mobile investors are more inclined to invest in top-ranked loans even though the ranking is unrelated to the loan characteristics.This result is significant when controlling for the fixed effects of loans,investors and time and adjusting for the correlation of residuals.After excluding alternative explanations such as herding,risk preferences and sample selection bias,mobile investors still show stronger ranking preferences than do computer investors.Additionally,the default rates are positively correlated with rankings,with the correlation more significant for mobile investors,which further indicates that the ranking preference is a behavioral bias.We then identify underlying channels through which mobile internet access affects investment behavior.First,the cost of searching for information on mobile devices is higher.When information is more complex,investors focus on more salient options.We find that when the number of loans on the list increases,the difference in the ranking preferences of mobile and computer investors increases,consistent with the information cost channel.Second,the ease of use of the mobile app makes it possible for investors to make financial decisions in more distracting environments.On weekdays,the P2P platform issues new loans at a fixed time.On weekends,the platform lists new issues randomly.When loans are released at random times,mobile investors are more vulnerable to distracting environments.We find that the transactions occurring at random times show a larger gap in the ranking preferences of mobile and computer investors,consistent with the environmental distraction channel.Third,we examine the financial literacy channel.For people with low financial literacy,the quality of financial decision-making depends on the way the information is presented.We use investment experience as a proxy for financial literacy and find that the difference in the ranking preferences of mobile and computer investors is not smaller for investors with high financial literacy.These results do not support the financial literacy channel.The contributions of this paper are threefold.First,to our best knowledge,it is the first paper to study differences in the investment behavior of mobile and computer investors.Understanding these differences is key to evaluating the welfare impact of new technologies.Second,we provide new evidence for ranking preferences.Using data from the P2P platform,we provide clean and reliable evidence on ranking preferences and identify the underlying mechanism.Third,our results have significant policy implications.Regulatory authorities should adopt different information disclosure standards for mobile platforms to improve the welfare of mobile investors.