May 12, 2021, 12:30–13:30
This paper studies the value of privacy, for individuals, using data from large-scale field experiments that vary disclosure requirements for loan applicants and loan terms on an online peer-to-peer lending platform in China. I find that loan applicants attach positive value to personal data: Lower disclosure requirements significantly increase the rate at which applications are completed. I quantify the monetary value of personal data—and the welfare effect of various disclosure policies—by developing a structural model that links individuals’ disclosure, borrowing, and repayment decisions. Using detailed application-level data, I estimate that social network ID and employer contact are valued at 230 RMB (i.e., $33, or 70% of the average daily salary in China); for successful borrowers, this accounts for 8% of the average net present value of a loan. Requiring answers to these application questions reduces borrower welfare by 13% and costs the platform $0.50 in expected revenue per applicant.