Published Papers

We find a negative relation between democracy and initial public offering (IPO) underpricing for a sample of 23,050 IPOs across 45 countries. The effect of democracy on underpricing is weaker for IPOs audited by Big 4 auditing firms, backed by venture capital firms, and with better disclosure specificity of use of proceeds. Democracy exerts a larger influence on underpricing for firms with higher agency problems, in countries with weaker institutional quality or shareholder protection, and during periods of high investor sentiment or economic policy uncertainty. Overall, our results highlight the importance of democracy in reducing IPO underpricing around the world.

We examine how increased competition stemming from an innovation in financial technology influences sell-side analyst research quality. We find that firms added to Estimize, an open platform that crowdsources short-term earnings forecasts, experience a pervasive and substantial reduction in consensus bias and a limited increase in consensus accuracy relative to matched control firms. Long-term forecasts and investment recommendations remain similarly biased, alleviating the concern that the documented reduction in bias is a response to broad economic forces. At the individual analyst level, we find that bias reduction is more pronounced among close-to-management analysts, and that more biased analysts respond by reducing their coverage of Estimize firms. The collective evidence suggests that competition from Estimize improves sell-side research quality by discouraging strategic bias.

Reactions to earnings calls are sensitive to subtle features of managers' speech, but little is known about the effect of nonnative accents in this setting. Nonnative-accented CEOs may avoid holding calls in English for fear of investors' negative stereotypes. However, theory indicates that stereotypes from the CEO position and nonnative accents conflict, and that the process of reconciling conflicting stereotypes requires effortful processing. We use a series of four experiments to test each link of the causal chain that we hypothesize based on this theory. We demonstrate that motivated investors reconcile conflicting stereotypes by inferring exceptional qualities, such as hard work and determination, that positively affect their impressions of nonnative-accented CEOs and, hence, of the company as an investment. We also show that, because bad news stimulates effortful processing, investors receiving bad (versus good) news are more likely to form a positive image of nonnative-accented CEOs and their companies.

Node characteristics and behaviors are often correlated with the structure of social networks over time. While evidence of this type of assortative mixing and temporal clustering of behaviors among linked nodes is used to support claims of peer influence and social contagion in networks, homophily may also explain such evidence.Here we develop a dynamic matched sample estimation framework to distinguish influence and homophily effects in dynamic networks,and we apply this framework to a global instant messaging network of 27.4 million users, using data on the day-by-day adoption of a mobile service application and users' longitudinal behavioral, demo-graphic, and geographic data. We find that previous methods over-estimate peer influence in product adoption decisions in this network by 300-700%, and that homophily explains>50% of the perceived behavioral contagion. These findings and methods are essential to both our understanding of the mechanisms that drive contagions in networks and our knowledge of how to propagate or combat them in domains as diverse as epidemiology, marketing, development economics, and public health.

We survey the recent, fast-growing literature on peer effects in networks. An important recurring theme is that the causal identification of peer effects depends on the structure of the network itself. In the absence of correlated effects, the reflection problem is generally solved by network interactions even in nonlinear, heterogeneous models. By contrast, microfoundations are generally not identified.We discuss and assess the various approaches developed by economists to account for correlated effects and network endogeneity in particular. We classify these approaches in four broad categories: random peers, random shocks, structural endogeneity, and panel data. We review an emerging literature relaxing the assumption that the network is perfectly known. Throughout, we provide a critical reading of the existing literature and identify important gaps and directions for future research.

We conduct an experiment to study whether individuals save more when information about the progress toward their self-set savings goal is shared with another village member (a "monitor"). We develop a reputational framework to explore how a monitor's effectiveness depends on her network position. Savers who care about whether others perceive them as responsible should save more with central monitors, who more widely disseminate information, and proximate monitors, who pass information to individuals with whom the saver interacts frequently. We randomly assign monitors to savers and find that monitors on average increase savings by 36%. Consistent with the framework, more central and proximate monitors lead to larger increases in savings. Moreover, information flows through the network, with 63% of monitors telling others about the saver's progress. Fifteen months after the conclusion of the experiment, other villagers have updated their beliefs about the saver's responsibility in response to the intervention.

This paper develops a model of the social and economic interaction of speculators in a securities or foreign exchange market. Both chartist and fundamentalist strategies are pursued by traders. The formalization of chartists behavior combines elements of mimetic contagion and trend chasing leading to waves of optimism or pessimism. Furthermore, changes of strategies from chartist to fundamentalist behavior and vice versa occur because speculators compare the performance of both strategies. The dynamic system under study encompasses the time development of the distribution of attitudes among traders as well as price adjustment. Chaotic attractors are found within a broad range of parameter values. The distributions of returns derived from chaotic trajectories of the model share important characteristics of empirical data: they exhibit high peaks around the mean as well as fat tails (leptokurtosis) and become less leptokurtotic under time aggregation.

This study extends the literature on the information content of stock message boards. To better understand the effect of online postings on trading activities and reduce the error due to stocks with small message board followings, we examine stocks with no fundamental news and high message posting activity. Such stocks tend to be of small firms with weak financials. For those stocks, we find a two-day pump followed by a two-day dump manipulation pattern among online traders, which suggests that an online stock message board can be used as a herding device to temporarily drive up stock prices. We also find that online traders' credit-weighted sentiment index, but not the number of postings, is positively associated with contemporaneous return and negatively predicts the return next day and two days later. Also, absolute sentiment is negatively related with contemporaneous and next day's intraday volatility and positively related with the proportion of volume in small-sized trades. We conclude that message board sentiment is an important predictor of trading-related activities.

This address considers the epidemiology of narratives relevant to economic fluctuations. The human brain has always been highly tuned toward narratives, whether factual or not, to justify ongoing actions, even such basic actions as spending and investing. Stories motivate and connect activities to deeply felt values and needs. Narratives "go viral" and spread far, even worldwide, with economic impact. The 1920-1921 Depression, the Great Depression of the 1930s, the so-called Great Recession of 2007-2009, and the contentious political-economic situation of today are considered as the results of the popular narratives of their respective times. Though these narratives are deeply human phenomena that are difficult to study in a scientific manner, quantitative analysis may help us gain a better understanding of these epidemics in the future.

Many people share investment ideas online. This study investigates whether individual investors trade on investment-related internet postings. We use unique data from a social trading platform that allow us to observe the shared portfolios of traders, their posted comments, and the replicating transactions of followers. We find robust evidence that followers increasingly replicate shared portfolios of traders after the posting of comments. However, postings do not help followers identify portfolios that deliver superior performance in the future. In a cross-sectional analysis, we show that it is mainly followers typically considered to be unsophisticated who trade after comment postings.

We present a model of media coverage of corporate announcements. Firms strategically use the media to communicate corporate announcements to a group of traders who observe announcements not directly but through media reports. Journalists strategically select which announcements to report to readers. Media coverage inadvertently incentivizes firms to manipulate the underlying announcements. In equilibrium, media coverage is tilted towards less manipulated negative news. The presence of financial journalists leads to more manipulation but makes stock prices more informative on average. We provide additional predictions regarding the media's impact on the quality of firm announcements and stock prices.