Embedded Files
Working Papers
Oil Shocks and Suicide
With Alexander James and Makenzi Scott
Revise and Resubmit/Conditional Acceptance at Energy Economics
Working paper available at SSRN
We estimate the effect of positive and negative oil shocks on suicide. Using restricted-use, U.S. state-level mortality data, we find that economic losses increase suicide risk and that economic gains have little effect. From 2015-2020, at least 6,000 people in the United States died by suicide as a result of declining oil prices. Exploring sources of heterogeneity, effects are largely driven by men, people without college degrees, and racial minorities. Results are robust to various modeling decisions and assumptions and are not easily explained by compositional changes. Implications are discussed, particularly as they relate to the clean energy transition.
Television as an Economic Development Strategy
With Alexander James and Hannah Hennighausen
Writing and Analysis
This paper investigates the economic impact of the television series Deadwood on the real estate price and income in Lawrence County, South Dakota (home to the town of Deadwood). Using a synthetic control approach, we construct a counterfactual version of Deadwood to estimate what housing prices and local income levels would have been in the absence of the show. Our results indicate that the airing of Deadwood led to a significant increase in home prices and household income, suggesting that media-driven tourism and heightened visibility can produce measurable local economic effects. These findings contribute to the literature on media influence and place-based economic development, demonstrating that entertainment media can serve as a catalyst for real-world economic change in small communities.
Economics of Birding-Related Recreation and Tourism in Alaska
With Sonja Kolstoe and Aaron Enriquez
Working Paper
Bird watching is a growing sector of nature-based tourism, and the migratory breeding grounds in Alaska attract birdwatchers from around the world. This paper estimates the economic value of bird watching in Alaska using crowdsourced checklist submissions from eBird as a proxy for individuals' choices of when and where to go birding. We present a comprehensive methodology for identifying methods of travel in a complex travel environment before estimating the consumer surplus of bird watching both during major birding migration season and across the year across the state of Alaska.
Natural-Resource Shocks and Voter Turnout: Evidence from the Behavioral Response to Fracking
With Alexander James
Restricted Use Census Project - Analysis and Drafting Phase
While it is well known that people with low incomes are less likely to vote, causal inference is challenging due to various sources of endogeneity. Energy booms, which tend to increase regional income and employment, have been shown to reduce aggregate voter turnout, leading some to question the relationship between income and voter turnout. However, existing literature cannot distinguish between variation in individual voter behavior (i.e. voters turning into nonvoters) from compositional changes (i.e., nonvoters moving into boom towns). Leveraging a difference-in-differences estimation strategy that exploits exogenous variation in the production of shale oil and gas, we estimate the causal effect of the local fracking boom on individual-level voter turnout in the United States. Building on existing literature, we distinguish between changes in voter behavior and changes in the composition of the electorate.
When Flames Meet Fenders: Wildfire and Wildlife-Vehicle Collisions
Working Paper, Writing Phase
We estimate the dynamic causal effect of wildfire on wildlife-vehicle collisions. Combining comprehensive spatial data on collision locations with federal wildfire perimeters, we apply a Callaway and Sant’Anna [2021] staggered difference-in-differences estimator to crash counts inside burn footprints and buffer zones extending outward from each fire. We document a sharp and growing reaccumulation of collisions inside the burn scar itself: rather than emptying the area, fire draws wildlife back over the post-fire recovery window, and collisions climb steadily for at least four years after ignition. This effect is largest and most immediate for small fires, consistent with the “green magnet” mechanism in which rapid post-fire vegetation regrowth attracts herbivores. Buffer-zone effects are positive but attenuate with distance, and a clear dose-response pattern in fire size governs how far and how persistently the disruption propagates. GPS telemetry on deer, elk, and pronghorn corroborates the displacement-and-return mechanism at the level of individual animal movement. These findings clarify a direct, cascading channel through which natural disasters affect transportation safety and inform the spatial targeting of post-fire wildlife mitigation
Peer Reviewed Papers
Catastrophic Wildfires and Suicide
With Alexander James, Hannah Hennighausen, and Nino Abashidze
Published (Jul. 2026) in Environmental and Resource Economics
We estimate the impact of catastrophic wildfires on suicide. Leveraging an eight-
year panel of county-by-month restricted-use mortality data for California, we find that
catastrophic wildfires result in a 47% increase in the suicide rate (roughly nine excess
suicides) in the six-month aftermath of an event. Exploring sources of heterogeneity,
effects are largely driven by males. Mechanisms are explored and suggest that both
the loss of property and the direct loss of life play a role. There is no evidence that
the mechanism is smoke exposure. These findings are robust to various modeling
assumptions and decisions, suggesting that catastrophic wildfires may be deadlier and
more expensive than previously thought.
The public overestimates and prefers greater tolerance for grizzly bear encounters than defined by the United States management guidelines
With Ian Fletcher, Todd Cherry, David Finnoff, and Jacob Hochard
Published (Nov. 2025) in Nature Communications Earth and Environment
Large predators are returning to landscapes where they have been absent for centuries, but human preferences complicate their recovery. Communities often resist predator recovery because of perceived risks, limiting what managers call social carrying capacity, or the level of human tolerance for coexisting with wildlife. Yet practical methods for measuring and integrating social carrying capacity into management decisions remain limited. To address this, we combine geospatial and survey data to model individual tolerance for the frequency and severity of grizzly bear encounters. The resulting estimates predict and map zip code-level tolerance across the region. Findings show that people tend to overestimate management’s tolerance of encounters than current federal guidelines. This approach provides a pragmatic tool to incorporate social carrying capacity into decisions about predator recovery and reintroduction, helping balance ecological goals with public acceptance.
Bayesian Inferences for Counterrorism Policy
Published (Feb. 2023) in Terrorism and Political Violence with Kevin Dayaranta and Mary Catherine Legrid
This study employs hierarchical Bayesian analysis of terrorist attacks to provide a retrospective analysis of the war in Afghanistan between 2002 and 2018. We examine the relationship between U.S. troop levels, target type, and the severity of attacks in terms of the number killed or wounded. We find that although some targets might have become better fortified after enduring attacks (such as police departments), terrorists would subsequently succeed in either attacking other targets (such as educational institutions) or even those same targets in subsequent years. Our analysis also finds that increases in U.S. troop levels throughout much of the conflict did not seem to quell violence, although explanations of this phenomenon are considerably more nuanced after taking expert opinion into account. We hope our analysis provides a useful retrospective analysis of the U.S. War in Afghanistan for policymakers to assess how or if security measures in the country could have been improved over the course of the conflict. Our modeling framework, however, is easily generalizable to other conflicts worldwide and thus provides a useful statistical tool for analyzing terrorism in many other settings as well.
An Analysis of Voter Turnout in U.S. Presidential Elections via Closed-Form Bayesian Inferences
Published (Nov. 2022) in Stats with Kevin Dayaratna and Jesse Crosson
Understanding the factors that influence voter turnout is a fundamentally important question in public policy and political science research. Bayesian logistic regression models are useful for incorporating individual level heterogeneity to answer these and many other questions. When these questions involve incorporating individual level heterogeneity for large data sets that include many demographic and ethnic subgroups, however, standard Markov Chain Monte Carlo (MCMC) sampling methods to estimate such models can be quite slow and impractical to perform in a reasonable amount of time. We present an innovative closed form Empirical Bayesian approach that is significantly faster than MCMC methods, thus enabling the estimation of voter turnout models that had previously been considered computationally infeasible. Our results shed light on factors impacting voter turnout data in the 2000, 2004, and 2008 presidential elections. We conclude with a discussion of these factors and the associated policy implications. We emphasize, however, that although our application is to the social sciences, our approach is fully generalizable to the myriads of other fields involving statistical models with binary dependent variables and high-dimensional parameter spaces as well.
Media References/Projects
Celebrity animals and visitors’ perceptions of wildlife risk
With Todd Cherry and Lynne Lewis
Featured Article at Park Science
We collected wildlife risk perceptions from 688 Grand Teton National Park visitors during the summer of 2024. If a trailhead sign for wildlife risk was associated with a generic grizzly bear, 52 percent of respondents said they would either cancel their plans or move to a new trailhead. But if the grizzly bear was a celebrity (specifically, Grizzly 399), about half as many people (27 percent) said they would cancel or move. Among the visitors with knowledge about Grizzly 399, that number dropped to only 14 percent. Many more people continued with their plans when the heightened risk was associated with a celebrity animal, but they also said they would be more cautious. Understanding how people respond to changes in wildlife risk is important, but equally important is how these responses may differ across settings. The influence of wildlife celebrity status on visitor behavior matters when trying to protect people and animals in national parks and other public lands.
“Earth Day Through the Economic Lens”
Chandler Hubbard and Quill Robinson, 2021, for American Conservation Coalition.
“To Reach Younger Audiences, Policymakers Should Turn to the Environment”
Nick Loris and Chandler Hubbard, 2020, for the Daily Signal.
“Look to Native Americans’ Forest Management for Better Wildfire Abatement”
Nick Loris and Chandler Hubbard, 2020, for the Daily Signal.
“Esports Win Probability: A Role Specific Look into League of Legends”
Chandler Hubbard, 2020, for the Samford Center for Sports Analytics.
Google Sites
Report abuse