Working Paper: NBER ID: w29268
Authors: Kei Kawai; Ken Onishi; Kosuke Uetake
Abstract: 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 a market 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 of Stiglitz & Weiss (1981).
Keywords: signaling; online credit markets; adverse selection; welfare; peer-to-peer lending
JEL Codes: D82; G21; L15
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| reserve interest rate (E43) | borrower creditworthiness (G51) |
| reserve interest rate (E43) | funding probability (G17) |
| reserve interest rate (E43) | contract interest rates (E43) |
| borrower creditworthiness (G51) | funding probability (G17) |
| high reserve rates (E52) | higher probability of loan funding (G21) |
| high reserve rates (E52) | less favorable contract interest rate (E43) |
| high reserve rates (E52) | higher likelihood of default (G33) |
| signaling (L96) | mitigate inefficiencies caused by adverse selection (D82) |
| signaling (L96) | restore surplus lost due to adverse selection (D82) |