An inconvenient cost: The effects of climate change on municipal bonds 2020, Journal of Financial Economics 135 (2), 468-482
GARP Oustanding Paper in Risk Management Award at Eastern Finance Association Meeting (2018)
Presentations: Midwest Finance Association (2018), Eastern Finance Association (2018), Financial Management Association Special PhD Paper Presentations (2018), Saint Louis University, University of Kentucky
Abstract: Counties more likely to be affected by climate change pay significantly more in underwriting fees and initial yields to issue long-term municipal bonds compared to counties that are unlikely to be affected by climate change. This difference disappears when comparing short-term municipal bonds, implying the market prices climate change risks for long-term securities only. The higher issuance costs for climate risk counties are driven by bonds with lower credit ratings. Investor attention appears to be an important factor, as the difference in issuance costs on bonds issued by climate and non-climate affected counties increases after the release of the 2006 Stern Review on climate change.
On the capital market consequences of alternative data: Evidence from outer space (with Zsolt Katona, Panos Patatoukas, and Jean Zeng)
Presentations: 9th Miami Behavioral Finance Conference Doctoral Poster Session, the Future of Financial Information conference (Stockholm, 2019), the 6th University of Connecticut Finance Conference (2020, canceled), SEC, Financial Management Association (2019), University of Kentucky, University of Florida
Abstract: We study the emergence of satellite imagery of parking lot traffic across major U.S. retailers as a source of alternative data in capital markets. We find that while measures of parking lot traffic from outer space embed timely value-relevant information, stock prices do not incorporate this information prior to the public disclosure of retailer performance for the quarter. This creates opportunities for sophisticated investors, who can afford to incur the costs of acquiring and processing satellite imagery data, to formulate profitable trading strategies at the expense of individual investors, who tend to be on the other side of the trade. Our evidence suggests that unequal access to alternative data increases information asymmetry among market participants without necessarily facilitating stock price discovery.
Presentations: University of Kentucky, University of Missouri, Miami University, New Technologies in Finance Conference (Columbia Business School), Wolfe Research NLP and Machine Learning Investment Mangement Conference (2020), the 2nd Future of Financial Information conference (Stockholm, 2020), European Finance Association (2020, scheduled), Northern Finance Association (2020, scheduled)
Abstract: We study the effect of geographically diverse information on sell-side research analysts' individual and consensus forecasts. Using data from satellite images of parking lots of US retailers, we first document that the car counts contain valuable information in aggregate. However, analysts tend to overweight their own forecast in the direction of local car counts relative to other analysts covering the same firm at the same time but in different locations. We find when firms have more geographically concentrated analyst coverage the consensus forecast error is higher, even after controlling for the number of analysts. Analyses using within-firm variation and exogenous shocks in geographic coverage due to brokerage closures suggest this relation is causal.
Abstract: I use Walmart's decision to discontinue sales of certain gun ammunition, ban open carry in stores, and encourage enactment of gun control policy as a setting to study how consumers respond when firms make political statements. Using smartphone-location data to measure foot traffic, I find store visits to Walmart decreased by 3.2% relative to competitors after Walmart’s statement. Store visits in highly Republican counties decreased by 10% but increased by 3.4% in highly Democratic counties. The effect is temporary when viewed in aggregate but persists in highly Republican counties. Further, remaining customers spent 3.5% more time in stores. The results highlight the challenges firms face when navigating an increasingly polarized political landscape.
Covid Economics, 4, 103-127, April 2020
Abstract: Social distancing is vital to mitigate the spread of the novel coronavirus. We use geolocation data to document that political beliefs present a significant limitation to the effectiveness of state-level social distancing orders. Residents in Republican counties are less likely to completely stay at home after a state order has been implemented relative to those in Democratic counties. We also find that Democrats are less likely to respond to a state-level order when it is issued by a Republican governor relative to one issued by a Democratic governor. These results are robust to controlling for other factors including time, geography, local COVID-19 cases and deaths, and other social distancing orders. We conclude that bipartisan support is essential to maximize the effectiveness of social distancing orders.
Unmasking Partisanship: How Polarization Influences Public Responses to Collective Risk (with Maria Milosh, David Van Dijcke, and Austin Wright)
Abstract: Political polarization and competing narratives can undermine public policy implementation. Partisanship may play a particularly important role in shaping heterogeneous responses to collective risk during periods of crisis when political agents manipulate signals received by the public (i.e., alternative facts). We study these dynamics in the United States, focusing on how partisanship has influenced the use of face masks to stem the spread of COVID-19. Using a wealth of micro-level data, machine learning approaches, and a novel quasi-experimental design, we document four facts:
(1) mask use is robustly correlated with partisanship;
(2) the impact of partisanship on mask use is not offset by local policy interventions;
(3) partisanship is the single most important predictor of local mask use, not COVID severity or local policies;
(4) Trump’s unexpected mask use at Walter Reed on July 11, 2020 significantly increased social media engagement with and positive sentiment towards mask-related topics.
These results unmask how partisanship undermines effective public responses to collective risk and how messaging by political agents can increase public engagement with mask use.