(with Carlos Avenancio-Leon and Troup Howard)
SSRN link
We explore long-run racial polarization induced by the original Food Stamps Program: a major policy choice to expand the social safety net in the United States in the 1960s and 1970s. Combining the county-level rollout with an experience-exposure DiD design, we use voter microdata for 175M Americans to compare lifetime voting patterns as of 2020 between those who experienced this expansion of the safety net as adults and those who came of age in a world where Food Stamps was an established feature of the redistributive landscape. Exposure to Food Stamps rollout generates large racial political polarization that persists fifty years later: White people are more likely to register and vote as Republicans, and Black voters are more likely to register and vote as Democrats. These effects are not driven by age, historical experiences, life cycle factors, or changing racial attitudes over the 20th century. We link these findings to a model of partisan competition which illustrates why parties may seek advantage by deliberately politicizing voter perceptions of public policies. Using congressional speeches, survey data, and voting outcomes from the rollout period, we show that short-run evidence is consistent with polarization unfolding in ways suggested by our model. Our results suggest that today's politicization of public policies can be highly consequential tomorrow: in this setting, we find electoral impacts persisting for at least a half-century.
(with Matteo Benetton, Marina Niessner and Jan Toczynski)
SSRN link
Celebrities have long leveraged their influence to shape outcomes in politics, marketing, and now in cryptocurrency markets. Using survey, market, and transaction-level data, we examine the persuasion rates of celebrity cryptocurrency endorsements on Twitter. Investors appear to treat celebrity tweets as financial advice: controlling for news, the probability of cryptocurrency investment by individuals on tweet days increases by 14%, with stronger effects for first-time investors. The tweets also impact equilibrium outcomes: market trading volume increases by 11% in the hour following a celebrity tweet. Finally, a representative retail investor who buys following these tweets earns negative returns after transaction costs.
(with Joey Engelberg, Asaf Manela, and Luka Vulicevic)
SSRN link
Cutting-edge LLMs are trained on recent data, creating a concern about look-ahead bias. We propose a solution called entity neutering: using LLMs to find and remove all identifying information from text. Our procedure uses an LLM agent that iteratively (i) masks entity-related terms and (ii) paraphrases the text until an independent LLM fails to recognize the target company from the text. In a sample of 250,000 financial news articles we verify that, after neutering, ChatGPT and other LLMs identify the subject firm at the rate of random chance. Among the unidentified articles, the sentiment extracted from the raw text and the neutered text agree more than 95\% of the time and have similar return predictability, with the difference providing an upper bound on look-ahead bias. The evidence here suggests that LLMs are able to effectively neuter text while maintaining semantic content. For look-ahead bias, LLMs can be both the problem and the solution.
(with Tony Cookson, Runjing Lu, and Marina Niessner)
SSRN link
This paper develops daily market-wide sentiment and attention indexes derived from millions of posts across major investor social media platforms. We find that sentiment extrapolates from past market-wide returns and exhibits a strong reversal. In contrast, attention predicts negative returns as a continuation of previous trends. The two indexes have distinct predictions for aggregate trading: abnormal trading rises when sentiment is low and attention is high. To identify the drivers of attention and sentiment, we use a shock to data sharing networks: We find sentiment spreads through real firm connections while attention does not. Moreover, attention rises after abnormally high trading, while sentiment rises after abnormally high returns. This extrapolative return pattern is asymmetric, primarily driven by negative market jumps. These findings provide new evidence on the daily market dynamics of sentiment and attention.
(with Tony Cookson and Benedict Guttman-Kenney)
SSRN link
We study the assimilation of immigrants into American consumer credit markets. Although immigrants enter America without an American credit history, we find that immigrants are positively selected: immigrants' average credit scores at age thirty are 20 points higher than non-immigrants, and this gap widens with age. Despite immigrants' greater creditworthiness, they---especially those who arrive later in life---have lower average credit card limits for a decade after entering America. Immigrants are less likely than non-immigrants to hold auto loans, a gap that persists by age forty and is explained by an immigrant aversion to purchasing autos with debt.
(with
Gordon Dahl,
Joey Engelberg
and
Runjing Lu)
SSRN linkVoxEU
We estimate that 3.1% of US voters, or 6.1 million individuals, were registered to vote in two states in 2020, opening up the possibility for them to choose where to vote. Double registrants are concentrated in the wealthiest zipcodes and respond to both incentives and costs, disproportionately choosing to vote in swing states (higher incentive) and states which automatically send out mail-in ballots (lower cost). We call this behavior Cross-State Strategic Voting. While others have documented strategic incentives on who to vote for, this paper is the first to consider strategic incentives on where to vote.
(with
Joey Engelberg,
Runjing Lu
and
Rick Townsend)
SSRN link
We document political sentiment effects on U.S. inventors. Democratic inventors
are more likely to patent (relative to Republicans) after the 2008 election of Obama
but less likely after the 2016 election of Trump. These effects are at least twice as
strong among politically active Democrats and are present even within firms and
within firm × technology. We also show that partisans tend to cluster in technologies
(e.g., Democrats in Biotechnology and Republicans in Weapons), so that sentiment
effects aggregate up to more patents in the technologies dominated by the winning
party.
(with
Joseph Engelberg,
Jorge Guzman
and
Runjing Lu)
SSRN link SocArXiv link
Republicans start more firms than Democrats. In a sample of 40 million party-identified Americans between 2005 and 2017, we find that 5.5% of Republicans and 3.7% of Democrats become entrepreneurs. This partisan entrepreneurship gap is time-varying: Republicans increase their relative entrepreneurship during Republican administrations and decrease it during Democratic administrations, amounting to a partisan reallocation of 170,000 new firms over our 13-year sample. We find sharp changes in partisan entrepreneurship around the elections of President Obama and President Trump, and the strongest effects among the most politically active partisans: those that donate and vote.
Best Paper Prize in Corporate Finance at the 2022
MFA Conference
(with
Tony Cookson,
and
Marina Niessner)
SSRN link
Social media has become an integral part of the financial information environment, changing the way financial information is produced, consumed and distributed. This article surveys the financial social media literature, distinguishing between research using social media as a lens to shed light on more general financial behavior and research exploring the effects of social media on financial markets. We also review the social media data landscape.
(with
Tony Cookson,
Runjing Lu
and
Marina Niessner)
SSRN link Data (PC1s, 2012-2021)
We examine social media attention and sentiment from three major platforms: Twitter, StockTwits, and Seeking Alpha. We find that, even after controlling for firm disclosures and news, attention is highly correlated across platforms, but sentiment is not: its first principal component explains little more variation than purely idiosyncratic sentiment. Using market events, we attribute differences across platforms to differences in users (e.g., professionals versus novices) and differences in platform design (e.g., character limits in posts). We also find that sentiment and attention contain different return-relevant information. Sentiment predicts positive next-day returns, but attention predicts negative next-day returns. These results highlight the importance of considering both social media sentiment and attention, and of distinguishing between different investor social media platforms.
Editor's choice, Journal of Financial Economics
Best Paper Prize in Investments and Asset pricing at the 2023
MFA Conference
Best Paper Award 11th Michigan State FCU Conference, 2022
(with
Anne Duquerroy
and
Christophe Cahn)
SSRN link SocArXiv link
Firms with only one bank relationship make up the majority of firms in many economies. This paper explores whether policy-driven lending is differentially transmitted to single-bank firms in comparison with the multibank firms that are the focus of the literature. Using unique variation in the ECB’s very long-term refinancing operations (VLTROs), which affected lending to firms discontinuously across credit ratings but within banks, we find selective transmission of VLTRO liquidity to single-bank firms. Banks apply higher lending standards to single-bank firms, with banking relationships determining both new lending and lending maturity. By contrast, banks appear to transmit policy lending near-uniformly across multibank firms.
(with
Tony Cookson
and
Joey Engelberg)
SSRN linkSocArXiv linkSlidesData
We find evidence of selective exposure to confirmatory information among 300,000 users on the investor social network StockTwits. Self-described bulls are 5 times more likely to follow a user with a bullish view of the same stock than self-described bears. This tendency is strong even among professional investors and is more pronounced on earnings announcement days. Placing oneself in an information “echo chamber” generates significant differences in the newsfeeds of bulls and bears: over a 50-day period, a bull will see 70 more bullish messages and 15 fewer bearish messages than a bear over the same period. Selective exposure creates “information silos” in which the diversity of received signals is high across users’ newsfeeds but is low within users’ newsfeeds. Finally, we show that this siloing of information is positively related to trading volume.
(with
Gordon Dahl
and
Runjing Lu)
SSRN linkSocArXiv linkNBER WPCo-author videoSlides
Changes in political leadership drive large changes in economic optimism. We exploit the surprise 2016 election of Trump to identify the effects of a shift in political power on one of the most consequential household decisions: whether to have a child. Republican-leaning counties experience a sharp and persistent increase in fertility relative to Democratic counties: a 0.7 to 1.4% increase in annual births, depending on the intensity of partisanship. Hispanics, a group targeted by Trump, see fertility fall relative to non-Hispanics, especially compared to rural or evangelical whites. Further, following Trump pre-election campaign visits, relative Hispanic fertility declines.
(with
Tony Cookson
and
Joey Engelberg)
SSRN linkSocArXiv linksentiment time series
We use party-identifying language – like “Liberal Media” and “MAGA”– to identify Republican users on the investor social platform StockTwits. Using a difference-in-difference design, we find that the beliefs of partisan Republicans about equities remain relatively unfazed during the COVID-19 pandemic, while other users become considerably more pessimistic. In cross-sectional tests, we find Republicans become relatively more optimistic about stocks that suffered the most from COVID-19, but more pessimistic about Chinese stocks. Finally, stocks with the greatest partisan disagreement on StockTwits have significantly more trading in the broader market, explaining 28% of the increase in stock turnover during the pandemic.
(with Antoinette Schoar)
SSRN linkNon-technical summaryAppendix 1Survey AppendixAppendix 2
Using a survey of 800 Chief Executive Officers (CEOs) in 22 emerging economies, we show that CEOs' management styles and philosophies vary with the ownership and governance structure of their firms. Founders and CEOs of firms with greater family involvement display a greater stakeholder focus and feel more accountable to employees and banks than to shareholders. They also have a more hierarchical management approach, and see their role as maintaining the status quo rather than bringing about change. In contrast, CEOs of non-family firms emphasize shareholder-value-maximization. Finally, firm-level variation in ownership is as important in explaining management philosophies as cross-country or industry-level differences.
(with Patricio Toro)
Government credit guarantees for bank loans direct vast volumes of credit and are the main policy tool used to improve firms' access to credit. This paper examines Chile’s credit guarantee scheme, which is similar to that of many OECD countries. Using a regression discontinuity design around the eligibility cutoff we find that guarantees more than double firms' borrowing without detectable increases in default rates. We also show that banks use guarantees to build new borrower relationships, an important and poorly understood process. The scheme also has an amplification effect: firms increase borrowing from other banks following a guarantee. Finally, we show that firms use the credit increase to significantly scale up their sales and employment. The fact that guarantees are not a common pool resource in this policy design is critical to understanding these results.
In 2020, Chileans would head to the ballot box to decide their country’s future. Many international observers credited Chile’s decades of neoliberal governance with turning the country into Latin America’s “Tiger,” a prosperous, diversified economy on its way to becoming the continent’s first developed country. But in October of 2019, a mass protest movement ground the country to a halt and shocked its political class, showing the world a different Chile—one defined by inequality, social distrust, and a young generation of political activists. As Chile prepared to vote in the fall of 2020 on whether to adopt a new constitution, could it sculpt a more equitable society while remaining “the exception” on a continent known for its political instability? Or would Chile’s prosperity go the same way as its neoliberal experiment?