Working Papers

Do online consumer reviews affect restaurant demand? I investigate this question using a novel dataset combining reviews from the website Yelp.com and restaurant data from the Washington State Department of Revenue. Because Yelp prominently displays a restaurant's rounded average rating, I can identify the causal impact of Yelp ratings on demand with a regression discontinuity framework that exploits Yelp's rounding thresholds. I present three findings about the impact of consumer reviews on the restaurant industry: (1) a one-star increase in Yelp rating leads to a 5-9 percent increase in revenue, (2) this effect is driven by independent restaurants; ratings do not affect restaurants with chain affiliation, and (3) chain restaurants have declined in market share as Yelp penetration has increased. This suggests that online consumer reviews substitute for more traditional forms of reputation. I then test whether consumers use these reviews in a way that is consistent with standard learning models. I present two additional findings: (4) consumers do not use all available information and are more responsive to quality changes that are more visible and (5) consumers respond more strongly when a rating contains more information. Consumer response to a restaurant's average rating is affected by the number of reviews and whether the reviewers are certified as "elite" by Yelp, but is unaffected by the size of the reviewers' Yelp friends network.

Using detailed project-level data, we document a novel mechanism through which information externalities distort investment. Firms anticipate information spillover from peers' investment decisions and delay project exercise to learn from their peers' outcomes. To establish a causal interpretation of our results, we exploit local exogenous variation from the 1800s that shapes the number of peers that a firm can learn from today. The strategic learning incentive is most salient for projects with uncertain profitability, when peers' underlying assets are similar, and in environments where peers are skilled. Finally, our results suggest that the anticipation of peer information dampens aggregate investment.

We find that among stocks dominated by retail investors, the lottery anomaly is amplified by high investor attention (proxied by high analyst coverage, salient earnings surprises, or recency of extreme positive returns) and intense social interactions (proxied by Facebook social connectedness or population density near firm headquarters). Such stocks' lottery features attract greater Google search volume and retail net buying, followed by more negative earnings surprises and lower announcement-period returns. The findings provide insight into the roles of attention and social interaction in securities markets, and support the hypothesis that these forces contribute to investor attraction to lottery stocks.

I review the empirical literature on word of mouth (WOM) among investors. I begin with an outline of the empirical challenges that WOM research faces and possible strategies to overcome those challenges. I then discuss recent studies on WOM among retail and institutional investors. The research to date provides compelling evidence that WOM importantly determines investment decisions. On balance, the information transmitted through WOM does not appear to help investors make better investment decisions. I explore possible reasons. I also discuss potential asset pricing implications, the emergence of social technologies, and possible avenues for future research.

We employ sLDA to extract the narratives discussed by Shiller (2019) from 7 million NYT articles over 150 years. The estimation addresses look-ahead bias and changes in semantics. Panic and the narrative index positively predict market return and negatively predict volatility. Panic presents time-varying risk aversion. The narrative predictability increases recently at both market and portfolio and monthly and daily intervals. The narrative index constructed from 2 million WSJ articles over 130 years retains its predictive power, but Stock Bubble emerges as a negative market predictor. Media customizes their narratives to their readers, having a diverse effect on the market.

Can entertaining mass media programs influence individual consumption and savings decisions? I study this question by examining the impact of the Dave Ramsey Show, an iconic US radio talk show which encourages people to spend less and save more. To that end, I combine household-level expenditure records from a large scanner panel with fine-grained information about the geographic coverage of the radio show over time. Exploiting the quasi-natural experiment created by the staggered expansion of the radio show from 2004 to 2019, I find that exposure to the radio show decreases monthly household expenditures. This effect is driven by households with initially high expenditures relative to their income. In a mechanism experiment, I document that listening to the radio show has a persistent effect on people's attitudes towards consumption and debt. This suggests that attitudinal changes are a key mechanism driving behavioral change. My findings highlight the potential of entertaining mass media programs for interventions aimed at changing people's financial decisions.

Using two proxies for investors' political affiliation, we document sharp differences in stock returns between firms likely dominated by Democratic investors (blue stocks) and those dominated by Republican investors (red stocks) during the COVID pandemic. Red stocks have 20 basis points higher risk-adjusted returns than blue stocks on COVID news days (Partisan Return Gap). Lockdown policies, COVID cases, industry and firm fundamentals only explain at most 25% of the return gap. Polarized political beliefs about COVID, revealed through people's social distancing behaviors and their Stock-Twits, contribute to about 40% of the return gap beyond the fundamental channel. Our paper provides partisanship as a novel aspect in understanding abnormal stock returns during the pandemic.

This paper studies the long-term effects of redlining policies that restricted access to credit in urban communities. For empirical identification, we use a regression discontinuity design that exploits boundaries from maps created by the Home Owners Loan Corporation (HOLC) in 1940. We find that "redlined" neighborhoods have 4.8% lower home prices in 1990 relative to adjacent areas. This finding is robust to the exclusion of boundaries that coincide with the physical features of cities (e.g., rivers, landmarks). Moreover, we show that housing characteristics varied smoothly at the boundaries when the maps were created. Evidence suggests lower property values may be driven by negative externalities associated with fewer owner-occupied homes and more vacant structures. Overall, our results indicate the effects of discriminatory credit rationing can persist decades after such practices are formally discontinued.

Financial decisions in today's society are made in environments that involve color stimuli. In this paper, we perform an empirical analysis of the effects of color on investment behavior. First, we find that when investors are displayed potential losses in red, risk taking is reduced. Second, when investors are shown past negative stock price paths in red, expectations about future stock returns are reduced. Consistent with red causing "avoidance behavior", red color reduces investors' propensity to purchase stocks. The findings are robust to a series of checks involving colorblind investors and alternative colors to control for salience effects. Finally, the effects are muted in a cultural setting, e.g., China, where red is not used to visualize financial losses. A contribution of this study is to introduce hypotheses from color psychology and visual science to enhance our understanding of the behavior of individual investors.

Financial history studies facts and institutions of the past. Such facts and institutions are interesting subjects in themselves, or they can help us interpret the present through analogy. History & Finance reverses the role of history in finance research: it exploits natural experiments of the past as a means to directly explaining current financial outcomes through the long-run persistence of economic and social phenomena. I first define the History & Finance approach and its relationship to Economic and Financial history. Then, I survey the work based on History & Finance across the subfields of finance. I discuss the challenges raised by History & Finance, and how researchers have thus far tackled them. Finally, I comment on the avenues for future research that History & Finance opens to finance scholars and economic historians alike.

Despite the focus of entrepreneurial finance research on high-tech innovation, more than 75% of innovations are new processes and products in traditional manufacturing. I show that basic education is a key determinant of innovation in traditional industries. I document that manufacturers in European regions with 10% more high school graduates file 15% more patents, and invest 4% more in capital expenditures. To absorb spatially correlated unobservables, I construct Virtual Regions that only exploit the variation in basic education across nearby locations. To address the possibility of reverse causality, I establish that regional basic education persists for decades, and I use the quasi-exogenous diffusion of the printing press after 1450 to instrument for historical basic education. The results offer a human capital channel for innovation that feeds into the innovation-to-investment literature in finance.

I test a set of predictions that constitute an identity theory of choice under risk using large-scale artefactual field experiments. Men whose identity is primed or threatened invest more in risky opportunities than other men and women. They become overconfident even in pure games of chance with no scope for skill, which is consistent with the motivated-beliefs channel identity theory postulates. The effects are stronger for men who are more likely to commit to male identity - older men and men in the Southern US. I show identity theory can contribute to explain negative-expected-value investment by risk-averse agents (e.g., trading individual stocks) and overinvestment in delegated choice under risk (e.g., managerial overinvestment) using simple financial opportunities. Because behaving in line with their identity increases men's utility, departures from expected utility theory are not necessarily suboptimal in this identity theory of choice under risk.