Yellow_star_thistleResearch interests: I am an environmental and resource economist. I work on problems of resource management and decision-making under environmental risk and uncertainty. I work in several applied areas including disease, invasive species, endangered species, fisheries and climate change. My methods include econometrics, dynamic optimization, and Bayesian learning processes.

Current projects:

COVID-19: social distancing COVID-19: vaccine prioritization  Invasives and trade Shadow value viability Approximate dynamic programming Amphibian ecosystem services and malaria

Daily mean mobility measures in the United States from mobile devices for weekdays, Jan. 1 to April 21, 2020 by quintiles of median income (blue: lowest, yellow: highest) at the census tract (left panels) or county (right panels) level.

COVID-19 and social distancing: In the absence of a vaccine, social distancing is a key tool to reduce the transmission of COVID-19. We show that social distancing following US state-level emergency declarations substantially varies by income. Using mobile device location data and an event study design focusing on behavior subsequent to state emergency orders, we document a reversal in the ordering of social distancing by income: wealthy areas went from most mobile before the pandemic to least mobile, while, for multiple measures, the poorest areas went from least mobile to most. Previous research has shown that lower income communities have higher levels of preexisting health conditions and lower access to healthcare. Combining this with our core finding—that lower income communities exhibit less social distancing—suggests a double burden of the COVID-19 pandemic with stark distributional implications.

Joakim A. Weill, Matthieu Stigler, Olivier Deschenes, Michael R. Springborn. Social distancing responses to COVID-19 emergency declarations strongly differentiated by income. Proceedings of the National Academy of Sciences, 2020, 202009412.

Media coverage: LA Times, Wired, New York Post, The Sac Bee, CBS Sacramento, KNX 1070 Newsradio Los Angeles

 

I discussed this research as a panelist on UC Davis LIVE: COVID-19 Edition – Transportation, mobility and society.

The optimal allocation of vaccines (vertical axes) between demographic groups for each decision period (horizontal axis in panel A-C) under the Base scenario. The three rows represent each objective, to minimize deaths (A), minimize years of life lost (YLL, B) and minimize infections (C). In the bars for the six decision periods show the percentage of vaccines allocated to a specific group (indicated by a letter, color, and stars indicating essential worker groups) in that period. The two final columns show cumulative measures at the end of month six, the percent of vaccines allocated to each group (D-F), and the percent of each group that has been vaccinated (G-I). The whiskers on each bar represent the sensitivity of the optimal solution to small deviations in the outcome, specifically the range of allocations resulting in outcomes within 0.25% of the optimal solution.

COVID-19 vaccine prioritization:  We explore the optimal allocation over time of limited COVID-19 vaccine supply in the U.S. across demographic groups differentiated by age and essential worker status. Disease dynamics are modeled using a compartmental model parameterized to capture existing knowledge of COVID-19. We consider three alternatives objectives: minimizing expected cases, years of life lost, or deaths. We allow for vaccine prioritization to change over time (each month for several months) in response to changes in underlying population conditions (shares of the population in different disease states).

Media coverage: Undark 

Event study estimates show that malaria cases (per 1,000 population, vertical axis) increase following Bd-driven date of amphibian decline (DoD).

Loss of amphibian ecosystem services and incidence of malaria in Central America:  Biodiversity loss from the impacts of invasive pests and pathogens has led massive environmental change. However, measuring the impact on human welfare is often elusive. We leverage a natural experiment involving an invasion wave of the fungal pathogen Batrachochytrium dendrobatidis (Bd) through Central America.  We match data on loss of amphibians –and the natural disease vector (mosquito) control they represent–with data on annual malaria cases at the cantón (“county”) level. We provide the first causal estimate of the impact of amphibian declines on an important human health outcome. The results have implications for international live species trading policies and the value of conservation.

Plant material imports to the U.S. and discoveries of non-native “true bugs” (hemiptera) by region, 1854-2012.

Invasive species and trade: What is the risk of unintentionally delivering invasive hitchhikers via international trade? How does this risk change over time and vary by trading partner? In this project our leading analysis  uses 150 years of ecological and economic data in the United States to understand the dynamics of establishments.

Working paper: Matthew MacLachlan, Andrew Liebhold and Michael R. Springborn. The hitchhiker’s guide to the greenery: estimating dynamics of 150 years of trade‐driven non‐native species introductions via plant material.

Click “Show more” below for a video animation of the import-introduction process and additional project information.


Optimal control effort for predatory trout (color bar) to ensure endangered chub viability given populations (Donovan et al. forthcoming)

Shadow value viability–safely avoiding dangerous thresholds:  Climate change mitigation, endangered species conservation and controlling infectious diseases are examples of a class of management problems with two key features: (1) avoiding thresholds–like 1.5 degrees Celsius warming, extinction, or outbreak–is key; (2) damages from violating the threshold are extreme but impossible to estimate with precision.  Instead of maximizing ill-captured net benefits, pragmatic focus turns to avoiding the threshold with a given confidence at the least possible cost.

Such problems are notoriously difficult to solve (given loss of the Markov property from the “joint-chance constraint” created by the confidence-constrained objective).  We develop a novel “shadow value viability” approach to solve the problem which also returns important economic intuition about the implicit cost of violating the threshold.

Click “Show more” below for papers on this topic.


Visualization of the forward dynamic programming updating step where simulated observations are incorporated into the value function (V) using regression (Springborn and Faig, under review)

Approximate dynamic programming: Ecosystem-based management demands that decisions account for more than just a homogeneous resource stock–stock diversity (genetics, age, etc.) and conditions of the ecosystem economic system all matter.  Standard dynamic optimization techniques (e.g. value function iteration) become unwieldy under large state spaces and/or complex uncertainty.  We adapt approximate dynamic programming (ADP)–novel to environmental and resource economics–to overcome computational limitations.  The simulation-based approach allows for a large state space easily incorporates complex, multiple uncertainty without the need for quadrature.

Click “Show more” below for papers under review on this topic.