Published Papers

Fraud indicators in the Paycheck Protection Program (PPP) COVID relief program are highly geographically concentrated. Zip codes and counties with high rates of suspicious PPP loans exhibit strong social connections to one another with evidence of fraud spreading spatially over time through social connections. Individuals in suspicious social media groups have higher rates of PPP fraud, and socially connected zip codes frequently use the same specific FinTech lenders, consistent with social connections influencing particular loan decisions. Our findings suggest that more proactive data analysis in fraud prevention, detection, and prosecution is needed to prevent the social spread of fraudulent schemes.

People often cite family and friends as important sources of financial advice. We study the impact of this social financial advice by using comprehensive administrative data on social networks and an identification strategy leveraging job switches to financial advisor roles. Gaining access to social financial advice significantly increases stock market participation. This effect declines in social distance, persists across socioeconomic groups, is absent for safe assets, and does not extend to other finance professionals. Our results are consistent with complementarity of investment expertise with client-facing skills being essential for advisors to successfully convert their social connections into investors.

We experimentally examine the channels underlying peer effects in financial markets. We hypothesize that individuals are uncertain about how to process informationregarding financial markets and thus look among their peers for someone who is more capable of processing the information - an expert. Our experimental evidence supportsthis hypothesis: Peers with higher relative expertise are followed more strongly. In our experiments, peers do not possess additional information to ensure that our results aredriven by the ability to process common information. We therefore introduce a new channel to the peer effects literature - information processing.

We analyze a unique hybrid robo-advisory setting where portfolio management is automated, but clients are quasi-randomly assigned to human financial advisors who deliver all remaining wealth management services, including behavioral coaching and relationship support. We show that advisors of different types cause variation in client retention, especially during market downturns. To interpret these effects, we estimate a structural model in which advisors influence both investor learning about the automated solution and the perceived utility of remaining enrolled, independent of performance. Effective human advisors generate significant surplus for both clients and the firm through these informational and behavioral channels.

Can social norms give rise to distorted information in China? We observe that China's leading social norm related to alcohol consumption and social drinking enhance earnings management. An analysis of toxic alcohol scandals supports a causal interpretation. Further evidence suggests that the influence of alcohol may come from the negative externality that it creates, which is propagated by corporate leaders and cannot be attenuated by market-oriented institutions. Our results reveal a social norm externality that may have important normative implications.

As emerging FinTech platforms face pressure in efficiently managing credit risk, the human emotional spectrum of FinTech platform borrowers within social media becomes a potential source for gaining insight into and evaluating their financial behaviors. Collaborating with an Asian FinTech platform, we investigate the impact of social media emotions on a platform's loan-approval decisions and repayment-reminder interventions before due dates. We demonstrate that anger at the pre-approval stage has a U-shaped relationship with platform borrowers' default probability. We reveal what we call "a bright side of anger" with respect to curbing financial credit risk: moderate intensity of anger at the pre-approval stage suggests a lower loan default probability. We also find that the average happiness tendency of platform delinquent borrowers' at the pre-maturity stage becomes informative and valuable, as it shows a U-shaped relationship with loan default; as for anger, it does not work therein. Furthermore, our field experiment indicates that a positive-expectation reminder is useful for prompting repayment when delinquent borrowers are in strong emotional intensities, regardless of anger or happiness. However, a negative-consequence reminder results in a higher default probability for delinquent borrowers who maintain high immediate happiness before the loan maturity dates. We draw on the classical appraisal theory of emotions and the feelings-as-information theory to interpret our findings. We offer non-trivial theoretical and practical implications to support FinTech platform credit risk decision-making by investigating the value of social media emotions and advocating for cross-functional coordination between debt approval and debt collection departments.

We provide evidence for a new propagation mechanism of wealth inequality and mobility. Using unique administrative data and a quasi-field experiment of exogenous assignment, we find that educated entrants, faced with greater local wealth inequality and salient cases of wealth mobility, take financial, real, and self-employment risks and reach higher positions in the wealth distribution, while the less educated do not. This is driven by poorer communities with more salient cases of wealth mobility, consistent with peer exposure rather than supply-side effects. We find no evidence for other channels, such as obtaining higher-paying more secure jobs, relocating, or reducing debt.

This paper tests how people's moral values influence their views of debt contracts. We ask participants to make decisions about debt contracts in different hypothetical situations (vignettes). We separately measure their moral values using the Moral Foundations Questionnaire (Graham et al., 2009). We have three main sets of findings. First, differences in moral values strongly explain the cross-section of participants' debt decisions. Participants with more conservative values show more support for credit score-based loan pricing, stricter forms of collateral, and tougher bankruptcy resolution. Second, when we randomly change the economic costs and benefits of debt within our vignettes, we find that participants change their answers in the direction predicted by economic theory. Third, participants' beliefs of the functioning of the credit market strongly correlate with their moral values. Participants with conservative values are more likely to believe that strict enforcement and risk-based loan pricing provide incentives and are economically efficient. More liberal participants believe that insurance against unlucky shocks are important. Consistent with moral values being distinct from Bayesian beliefs, financial literacy does not attenuate moral values in shaping beliefs about what is economically efficient.

Using friendship data from Facebook, we find that among three aspects of social capital, Economic Connectedness - the fraction of one's social network with high income, has the strongest and most robust relationship with stock market and saving participation. One standard-deviation greater Economic Connectedness is associated with 10.6% greater stock market participation and 9.2% greater saving participation. Evidence from non-local friendships supports a causal link between household financial behavior and the income of one's friends. Our results indicate that the effect of Economic Connectedness on participation derives from opportunities to interact with high-SES individuals rather than from class-based friending propensities.

We measure popular sentiment toward finance by applying a large language model to millions of books published in eight countries over hundreds of years. We extensively validate this measure both internally and externally. We document persistent differences in finance sentiment across countries despite ample time-series variation. Books written in the languages of more capitalist countries discuss finance in a more positive context. Finance sentiment is correlated with survey-based measures of financial market participation and income inequality. Finance sentiment declines one year before rather than after financial crises. Positive shocks to finance sentiment are followed by higher output and credit growth.

We document a causal effect of social interactions on investor behavior using the number of local soccer games as a measure of social interaction intensity. Social transmission is identifiable in buy but not sell trades. Social Interaction Intensity (SII) increases the sensitivity of buying to past buys, particularly in riskier stocks. This sensitivity is an increasing and convex function of past returns, with higher SII further amplifying the effect. Social interactions cause an extremity shift wherein existing shareholders increase their positions, especially within demographically homogeneous communities. Higher social interaction intensity increases the sensitivity of individual investors' trading volume and portfolio riskiness to past trades. At the market level, SII increases the sensitivity of stock trading volume and retail ownership percentage to past buys.

Using a semisupervised topic model on 7 million New York Times articles spanning 160 years, we test whether topics of media discourse predict future stock market excess returns to test rational and behavioral hypotheses about market valuation of disaster risk. Media discourse data address the challenge of sample size even when disasters are rare. Our methodology avoids look-ahead bias and addresses semantic shifts. Our discourse topics positively predicts market excess returns, with War having an out-of-sample R^2 of 1.35%. We call this effect the war return premium. The war return premium has increased in more recent time periods.