Working Papers

We examine how research posted by "social media analysts" (SMAs)" -- individuals posting equity research online via social media investment platforms" -- is related to research subsequently produced by professional sell-side equity analysts. Using data from Seeking Alpha, we find that the market reaction to sell-side analyst research is substantially reduced when the analyst research is preceded by the report of an SMA, and that this is particularly true of sell-side analysts' earnings forecasts. We further find that this effect is more pronounced when SMA reports contain more decision-useful language, are produced by SMAs with greater expertise, and relate to firms with greater retail investor ownership. We also provide evidence that the attenuated response to sell-side research is most likely explained by SMA research preempting information in sell-side research and that analysts respond to SMA preemption with bolder and more disaggregated forecasts. Collectively, our results suggest that equity research posted online by SMAs provides investors with information that is similar to but arrives earlier than sell-side equity research, and speak to the connected and evolving roles of information intermediaries in capital markets.

Companies donating in the aftermath of large-scale disasters often suffer public backlash and managers systematically fail to understand what corresponds to a donation that stakeholders perceive as contextually appropriate. We attribute this to the level of uncertainty that obscures the relative social value of a donation because accurate information about impacts is not available for months. We argue that stakeholders rely on a company's pre-disaster reputation as a heuristic to make judgments of its philanthropy. Thus, regardless of the amount of aid given, well-regarded firms obtain rents from responding first to a disaster, and this spills over to companies in the same industry that match their donations; the opposite applies to firms with an unfavorable reputation, and to those that imitate their gifts. Analyses of donations by the largest 2,000 companies worldwide to every major epidemic, natural disaster, and terrorist attack from 2007 to 2019 support this argument and show that this heuristic effect does not transfer to firms donating different amounts. The estimates survive a battery of time-varying and joint fixed effects and tests of confounders. They confirm that reputation is a stronger rent determinant than donation amount. We discuss ways to improve managerial philanthropic decisions in similar settings.

This study constructs a novel measure that aims to capture face-to-face private communications between firm managers and sell-side analysts by mapping detailed, large-volume taxi trip records from New York City to the GPS coordinates of companies and brokerages. Consistent with earnings releases prompting needs for private communications, we observe that daily taxi ride volumes between companies and brokerages increase significantly around earnings announcement dates (EAD) and reach their peak on EAD. After controlling for an extensive set of fixed effects (firm, analyst, and year) and other potential confounding factors, we find that increases in ride volumes around EAD are negatively associated with analysts' earnings forecast errors in periods after EAD and positively associated with the profitability of recommendations issued after EAD (but these effects dissipate over longer horizons). Our results suggest that analysts may obtain a private source of information orthogonal to their pre-existing information from these in-person meetings, which may help them better understand the implications of current earnings signals for future earnings.

Prior research finds that online social media usage may lower self-control and encourage indulgent behavior in laboratory subjects. We find that corporate CEOs show similar tendencies: CEOs with online social media presence are more likely to succumb to lower self-control and abuse their information advantage to profit from unethical insider trades. Specifically, CEOs' social media presence strongly predicts their insider trading activity in terms of incidence, intensity (amount and frequency), and profitability. We further find that the effect is driven by insider buys (not by sells) and is more pronounced for opportunistic buys which tend to contain more material non-public information.

This paper examines how labor frictions affect investment rate and new firm entry. Using matched employee-employer data from LinkedIn, I first show that increases in the enforceability of non-compete agreements lead to widespread declines in employee departures across seniority levels, driven by workers in knowledge-intensive occupations. Investment rates at existing firms increase, especially for firms that employ more skilled workers. This comes at the expense of new firm entry, which declines substantially in knowledge-intensive sectors. The results suggest that labor frictions play an important role in investment decisions, and that NCs may factor into slowing business dynamism.

We examine worker reactions to firms' credit deterioration using anonymized networking activity on LinkedIn. In the weeks immediately following a negative credit event, connection activity increases at affected firms across the credit rating distribution, pointing to costs beyond those originating from bankruptcy. Heightened networking activity is associated with contemporaneous and future departures, especially at highly-rated firms. Other negative events like missed earnings and equity sell recommendations do not trigger similar reactions. Overall, our results indicate that the latent build-up of connections triggered by credit deterioration represents a source of fragility for firms.

We provide the first analysis of the risk exposure and consequent risk-adjusted performance of impact investing funds, private market funds with dual financial and social goals. We introduce a new dataset of impact fund cash flows constructed directly from financial statements. When accounting for market risk exposure, impact funds underperform the market, but outperform venture capital (VC) funds, consistent with the presence of frictions in private markets. Impact funds perform on par with funds matched on size, asset class, and vintage years. We exploit known distortions in measures of VC performance to characterize the risk profile of impact funds. Impact funds have substantially lower market beta than VC funds, contradicting the idea of sustainability as a "luxury good." Adding factors does not change the estimate of performance.

We develop a measure of corporate culture using coworker connectivity on LinkedIn's platform, and show it is strongly correlated with positive employee relations and satisfaction. Using state-level changes to employment agreements as shocks to explicit contracts, we find that these changes significantly impact employees in weakly connected firms, but have little to no effect on those at strongly connected firms. Our results suggest that firms with strong corporate culture are less dependent on explicit contracts to retain human capital. We document implications for firms' investment decisions and other outcomes.

Over the past decade, limited partners have increased capital allocations to socially driven private equity funds with the goal to generate long-term impact alongside financial returns. To understand funds' abilities to meet these goals, we gather detailed mission and financial data from 53 impact investing private equity funds, representing 557 individual investments. In our sample we find that while fund managers are overwhelmingly optimistic about mission preservation, few exits have any contractual statements about preserving mission. Regarding financial performance, our set of market-rate-seeking funds achieved gross results comparable to non-impact investment options along a broad range of measures, suggesting it is possible to generate market returns as an impact fund.

Tesla is an American electric vehicle and clean energy company. They are based in Palo Alto, California and their product base consists of electric cars, battery energy storage, solar panels, and solar roof tiles. On an average day in 2021, Tesla stock sells for $700/share. We will review historical Tesla data and examine whether this particular stock is worth the investment. In addition to historical data, this research reviews the effect of traditional news and social media on human behavior. Exploring social media analytics, investor sentiment and behavior in hopes to gauge how these factors can impact Tesla and whether this should be taken into consideration prior to the investment.

Does partisan perception shape the flow of international capital? We provide evidence from two settings, syndicated corporate loans and equity mutual funds, to show that ideological alignment with foreign governments affects the cross-border capital allocation by U.S. institutional investors. Moreover, we find that ideological alignment with foreign countries also affects investments of non-U.S. investors and can explain patterns in bilateral FDI flows. Our empirical strategy ensures that direct economic effects of foreign elections or bilateral ties between countries are not driving the result. Combined, our findings imply that partisan perception is a global phenomenon and its economic effects transcend national borders.

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.