Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper examines bias in online charitable microfinance lending. We find that charitable lenders on a large peer-to-peer online microfinance website appear to favor more attractive, lighter-skinned, and less obese borrowers. Borrowers who appear more needy, honest and creditworthy also receive funding more quickly. These effects are quantitatively significant: Borrowers with beauty one standard deviation above average are treated as though they are requesting approximately 11% less money. Statistical discrimination does not appear to explain our findings, as these borrower attributes are uncorrelated with loan performance or borrower enterprise performance. The evidence suggests implicit bias could explain our findings: more experienced lenders, who may rely less on implicit attitudes, appear to exhibit less bias than inexperienced lenders.