Signaling in Online Credit Markets
本文利用关于贷款特征与借款人还款的详细数据，研究信号传递如何影响在线信贷市场的均衡结果与福利。我们构建并估计了一个均衡模型，其中借款人可以通过保留利率传递其违约风险信号。我们将存在信号传递与不存在信号传递的市场分别与无不对称信息的基准情形进行比较，发现逆向选择摧毁了高达34%的总剩余，而其中最多78%可通过信号传递得以恢复。我们还估计出部分市场的供给曲线呈向后弯曲形态，这与Stiglitz和Weiss在1981年所作出的预测相一致。
英文原文
We study how signaling affects equilibrium outcomes and welfare in an online credit market, using detailed data on loan characteristics and borrower repayment. We build and estimate an equilibrium model in which a borrower may signal her default risk through the reserve interest rate. Comparing markets with and without signaling relative to the benchmark with no asymmetric information, we find that adverse selection destroys as much as 34% of total surplus, up to 78% of which can be restored with signaling. We also estimate backward-bending supply curves for some markets, consistent with the prediction made by Stiglitz and Weiss in 1981.