Rational Herding in Microloan Markets

Microloan markets allow individual borrowers to raise funding from multiple individual lenders. We use a unique panel dataset which tracks the funding dynamics of borrower listings on Prosper.com, the largest microloan market in the United States. We find evidence of rational herding among lenders. Well-funded borrower listings tend to attract more funding after we control for unobserved listing heterogeneity and pay-off externalities. Moreover, instead of passively mimicking their peers (irrational herding), lenders engage in active observational learning (rational herding); they infer the creditworthiness of borrowers by observing peer lending decisions, and use publicly observable borrower characteristics to moderate their inferences. Counterintuitively, obvious defects (e.g., poor credit grades) amplify a listing's herding momentum, as lenders infer superior creditworthiness to justify the herd. Similarly, favorable borrower characteristics (e.g., friend endorsements) weaken the herding effect, as lenders attribute herding to these observable merits. Follow-up analysis shows that rational herding beats irrational herding in predicting loan performance.

Juanjuan Zhang is interested in how people learn by observing others' behaviors ("observational learning"). Her empirical studies investigate the impact of consumer observational learning in a variety of markets, including microfinance, online communities, real estate, and organ transplant adoption. The findings have informed her theoretical exploration of firm-side responses to harness the power of observation learning. She finds that, counter-intuitively, "demarketing" can be an optimal popularity management strategy. Her recent work extends the understanding of observational learning into the intra-personal domain, where she studies amnesia and memory manipulation.

A related topic that intrigues Zhang is how information itself can be a product and how it is produced. This perspective allows her to analyze why firms would continue bad products, why personalization may damage profits, and how companies should manage consumers' self-discovery of their preferences.

Zhang's research has been published in top academic journals such as Marketing Science and Management Science. Her paper on observational learning in the transplant kidney market won the 2010 Frank M. Bass Award for the best marketing paper derived from a Ph.D. thesis published in an INFORMS-sponsored journal, and was finalist for the 2010 John D. C. Little Award for the best marketing paper published in Marketing Science or Management Science.

Juanjuan Zhang earned a B.Econ. from Tsinghua University in 2000, and a Ph.D. in Business Administration from the University of California, Berkeley in 2006.