Do Lenders Value the Right Characteristics?: Evidence from Peer-to-Peer Lending
Using a unique dataset of peer-to-peer lending with detailed loan and borrower information, I study the following research questions:|1) What are the borrower characteristics that lenders value when choosing which loans to fund?; and (2) Do lenders value the correct characteristics with respect to minimizing to probability of default? In this online context, the researcher observes everything that the lender does, enabling unbiased estimation of the borrower characteristics that lenders favor. Estimating the characteristics that predict loan default is problematic due to selection at the funding state. I consider three potential strategies to address this issue:(1) restricting attention to borrower characteristics for which there is no evidence of selection in the first stage; (2) bounding the default estimates in the style of Lee (2009) and (3) exploiting variation in the probability of funding caused by contemporaneous competition on the platform. The evidence suggests that lenders give the correct weight to verified income levels, underestimate the importance of verified education level and marital status, and overestimate the importance of verified employment industry.
Friday Forum Spring quarter 2017 Schedule:
Humanities 1 Room 202
A weekly interdisciplinary colloquium series for sharing graduate research across the humanities. Join us for light refreshments and weekly presentations by your fellow graduate students.
April 21, 2017: Jaclyn N. Schultz, History
April 28, 2017: Baizhu Chen, Economics
May 5, 2017: Danielle Crawford, Literature
May 12, 2017: Kristen Laciste, HAVC
May 19, 2017: Kara Hisatake, Literature
May 26, 2017: Yuki Obayashi, Literature
June 2, 2017: Angela Nguyen, Psychology