Sample Working Papers and Publications

Introduction to the special issue on mathematical economic epidemiology models, with Raouf Boucekkine, Economic Theory (2024)

Abstract: The effects of the Covid-19 pandemic on global health and well-being, as well as on the global economy, have been devastating. Yet, Covid-19 was not the first, and will not be the last, zoonotic disease to affect humanity. Indeed, there is evidence that increased human-wildlife interface, together with ever expanding mobility around the globe, are contributing to an increased frequency of such events. Although the policy response to Covid-19 resulted in some successes, notably in the speed at which effective tests and, especially, vaccines against the SARS-CoV-2 virus were developed, the pandemic also exposed significant weaknesses in the ability of governments and institutions at all levels to respond in consistent, coordinated, and effective ways. These shortcomings point to the need for guidance from interdisciplinary approaches that incorporate social and economic factors, in addition to traditional epidemiological considerations. In terms of modeling, it has become apparent that standard epidemiological models, which are designed to describe the evolution of infections and the effect of policy under various intervention scenarios, are ill equipped to evaluate important tradeoffs, especially those related to the effects on economic well-being resulting from various mitigation policies, such as prolonged lock-downs. Hybrid epidemiological-economic (often termed epi-econ) models were developed in order to better inform policy makers about effective mitigation that is in line with efficiency, as well as with individual incentives. Methodologically, this implies a change of modeling focus from dynamical systems, the study (mainly through simulations) of SEIR-like systems of differential equations, to optimal control theory. The latter typically involves the explicit intertemporal optimization of a functional describing combined epidemiological and economic objectives, subject to a set of dynamic equations describing the joint evolution of economic and epidemiological variables of interest. While this approach has already been providing a host of new insights that will help policy address future pandemics, important open questions remain. 

Pollution and Labor Productivity: Evidence from Chilean Cities, with with Hasan Dudu, Charl Jooste, and James Robert Sampi Bravo, Policy Research working paper, World Bank Group (2022)

Abstract: We propose identification schemes that can be used in a variety of contexts to analyze the effects of pollution on labor productivity. Particulate matter (PM2.5) pollution data for Chile is collected and mapped to a city and industry-level labor productivity database. The endogeneity between labor productivity and pollution is controlled for by instrumenting on the presence of coal and diesel power plants. The microeconomic evidence is compared to macroeconomic correlations between pollution and labor productivity. A stylized macro model, typical of models used by policy planning ministries in several countries, is used to assist in the identification.

Balancing Economic and Epidemiological Interventions in the Early Stages of Pathogen Emergence, with Raouf Boucekkine, Giorgio Fabbri, Fausto Gozzi, Andrew P. Dobson, Mercedes Pascual, and Cristiano Ricci, Science Advances (2023)

Abstract: The global pandemic of Covid-19 has underlined the need for more coordinated responses to emergent pathogens. These responses need to balance epidemic control in ways that concomitantly minimize hospitalizations and economic damage. We develop a hybrid economic-epidemiological modelling framework that allows us to examine the interaction between economic and health impacts over the first period of pathogen emergence when lockdown and testing and isolation are the only means of containing the epidemic. A major part of our contribution involves a rigorous specification of this as a dynamic optimization problem, as well as using numerical methods to solve for the respective optimal policies under a variety of scenarios about model parameters. Testing and isolation emerges as a much more effective policy than lockdown, although if lockdown is quickly put in place it always beats the 'laissez faire' strategy of doing nothing.

Renewable Technology Adoption Costs and Economic Growth, with Bernardino Adao and Borghan Narajabad, Energy Economics (2024)

Abstract: In the presence of rapid technological progress, early technology adoption may result in large capital replacement costs. We develop an analytical Integrated Assessment Model that incorporates endogenous scrapping costs resulting from new technology adoption in renewable energy, as well as externalities associated with carbon emissions and renewable technology spillovers. We use our calibrated model to investigate the effects of the scrapping channel on renewable technology adoption and on the optimal energy transition. In the absence of a Pigouvian carbon tax, a second-best policy that incentivizes renewables through internalizing spillovers provides relatively small benefits and can even be detrimental to short-run growth. In contrast, the reduction in fossil fuel consumption resulting from internalizing technology spillovers is significantly larger if the Pigouvian tax is also in place. Comparing the status quo to the scenario where both policies are implemented results in a consumption-equivalent welfare gain of 1.4 percent. Our findings suggest that, in the presence of scrapping costs resulting from rapid technological progress, some caution might be warranted before concluding that direct subsidies are a suitable substitute for a Pigouvian carbon tax. When it comes to social welfare, carbon taxes and policies that promote renewables by eliminating spillover externalities are best thought of as complements rather than substitutes.

On Fixed Points of Locally and Pointwise Contractive Set-Valued Maps with an Application to the Existence of Nash Equilibrium in Games, Journal of Fixed Point Theory and Applications (2022)

Abstract: We establish the existence of fixed points for set-valued maps defined on metric spaces and satisfying a pointwise or a local version of Banach's contraction property. As an application, we demonstrate the existence of Nash equilibrium in a general class of strategic games played on metric spaces of strategies.

The Costs and Benefits of Primary Prevention of Zoonotic Pandemics, with Aaron Bernstein, Amy W. Ando, Mariana M. Vale, Binbin V. Li, Hongying Li, Jonah Busch, Colin Chapman, Margaret Kinnaird, Katarzyna Nowak, Marcia C. Castro, Carlos Zambrana-Torrelio, Jorge A. Ahumada, Lingyun Xiao, Patrick Roehrdanz, Les Kaufman, Lee Hannah, Peter Daszak, Stuart L. Pimm, and Andrew P. Dobson, Science Advances (2022)

Abstract: The COVID-19 pandemic was predicted but not prevented. Humans have extensive contact with wildlife known to harbor vast numbers of viruses, many of which have not yet spilled into humans. We define actions including better management of wildlife trade, prevention of deforestation, and better surveillance of pathogen spillover that constitute primary prevention for zoonotic viral emergence. We also compute the annualized damages from emerging viral zoonoses over the past seven decades. Primary prevention costs are ~1/150th the low-end estimate of the value of lives lost each year, which we estimate at US$520 billion. The full scale of our recommendations for primary prevention investments is justifiable based upon the ongoing annual damages from COVID-19 emergence.

Race, Local Pollution, and COVID-19 Deaths in Texas, with with Annie Xu, Chima Adiole, Nathan Botton, Sylvia Dee, Carrie Masiello, Mark Torres, and members of the Rice COVID-19 environmental project, Scientific Reports (2022)

Abstract: The costs of COVID-19 are extensive, and, like the fallout of most health and environmental crises in the US, there is growing evidence that these costs weigh disproportionately on communities of color. We investigated whether county-level racial composition and fine particulate pollution (PM2.5) are indicators for COVID-19 incidence and death rates in the state of Texas. Using county-level data, we ran linear regressions of percent minority as well as historic 2000-2016 PM2.5 levels against COVID-19 cases and deaths per capita. We found that a county's percent minority racial composition, defined as the percentage of population that identifies as Black or Hispanic/Latinx, highly correlates with COVID-19 case and death rates. Using Value-of-Statistical-Life calculations, we found that economic costs from COVID-19 deaths fall more heavily on Black and Hispanic residents in Harris County, the most populous county in Texas. We found no consistent evidence or significant correlations between historic county-average PM2.5 concentration and COVID-19 incidence or death. Our findings suggest that public health and economic aid policy should consider the racially-segregated burden of disease to better mitigate costs and support equity for the duration and aftermath of health crises.

COVID‑19 and the value of safe transport in the United States, with Kenneth B. Medlock III and Shih Yu (Elsie) Hung, Scientific Reports (2021)

Abstract: We investigate the connection between the choice of transportation mode used by commuters and the probability of COVID-19 transmission. This interplay might influence the choice of transportation means for years to come. We present data on commuting, socioeconomic factors, and COVID-19 disease incidence for several US metropolitan areas. The data highlights important connections between population density and mobility, public transportation use, race, and increased likelihood of transmission. We use a transportation model to highlight the effect of uncertainty about transmission on the commuters choice of transportation means. Using multiple estimation techniques, we found strong evidence that public transit ridership in several US metro areas has been considerably impacted by COVID-19 and by the policy responses to the pandemic. Concerns about disease transmission had a negative effect on ridership, which is over and above the adverse effect from the observed reduction in employment. The COVID-19 effect is likely to reduce the demand for public transport in favor of lower density alternatives. This change relative to the status quo will have implications for fuel use, congestion, accident frequency, and air quality. More vulnerable communities might be disproportionally affected as a result. We point to the need for additional studies to further quantify these effects and to assist policy in planning for the post-COVID-19 transportation future.

Walrasian Equilibrium in Nature, Proceedings of the National Academy of Sciences (2021)

Abstract: The interaction between land plants and mycorrhizal fungi (MF) forms perhaps the world`s most prevalent biological market. Most plants participate in such markets, in which MF collect nutrients from the soil and trade them with host plants in exchange for carbon. In a recent study, M. D. Whiteside et al. [Curr. Biol. 29, 2043-2050.e8 (2019)] conducted experiments that allowed them to quantify the behavior of arbuscular MF when trading phosphorus with their host roots. Their experimental techniques enabled the researchers to infer the quantities traded under multiple scenarios involving different amounts of phosphorus resources initially held by different MF patches. We use these observations to confirm a revealed preference hypothesis, which characterizes behavior in Walrasian equilibrium, a centerpiece of general economic equilibrium theory.

Conservation, Incentives, and Livestock Insurance: the Case of the Snow Leopard, Conservation Letters (2021)

Abstract: Livestock insurance consists of livestock owners pooling resources together in order to hedge against the risk of attacks by predators on their individual herds. We use an economic model to study optimal livestock insurance and to discuss its viability in improving outcomes for livestock owners. The benefit from insurance depends on the livestock owners' level of risk aversion. We calibrate the model using data from Project Snow Leopard and investigate the potential of livestock insurance for achieving conservation goals. The model predicts that leopard killings would decline under the proposed livestock insurance contract. The level of the decline depends on the degree of risk aversion. Our analysis calls for surveys that measure risk aversion of local livestock owners to be conducted in any situation where insurance is considered as a policy towards achieving conservation goals. Finally, we discuss how the proposed livestock insurance scheme could be implemented in practice.

A Double-Slit Experiment with Human Subjects, with John Duffy, PLOS ONE (2021)

Abstract: We study a sequence of ``double-slit`` experiments designed to perform repeated measurements of an attribute in a large pool of subjects using Amazon`s Mechanical Turk. Our findings contrast the prescriptions of decision theory in novel and interesting ways. The response to an identical sequel measurement of the same attribute can be at significant variance with the initial measurement. Furthermore, the response to the sequel measurement depends on whether the initial measurement has taken place. In the absence of the initial measurement, the sequel measurement reveals additional variability, leading to a multimodal frequency distribution which is largely absent if the first measurement has taken place.

Ecology and Economics for Pandemic Prevention, with Andrew P. Dobson, Stuart Pimm, Lee Hannah, Les Kaufman, Jorge A. Ahumada, Amy W. Ando, Aaron Bernstein, Jonah Busch, Peter Daszak, Jens Engelmann, Margaret Kinnaird, Binbin Li, Thomas Lovejoy, Katarzyna Nowak, Patrick Roehrdanz, and Mariana M. Vale, Science (2020)

Abstract: For a century, two new viruses per year have spilled from their natural hosts into humans. The MERS, SARS, and 2009 H1N1 epidemics, and the HIV and coronavirus disease 2019 (COVID-19) pandemics, testify to their damage. Zoonotic viruses infect people directly most often when they handle live primates, bats, and other wildlife (or their meat) or indirectly from farm animals such as chickens and pigs. The risks are higher than ever as increasingly intimate associations between humans and wildlife disease reservoirs accelerate the potential for viruses to spread globally. Here, we assess the cost of monitoring and preventing disease spillover driven by the unprecedented loss and fragmentation of tropical forests and by the burgeoning wildlife trade. Currently, we invest relatively little toward preventing deforestation and regulating wildlife trade, despite well-researched plans that demonstrate a high return on their investment in limiting zoonoses and conferring many other benefits. As public funding in response to COVID-19 continues to rise, our analysis suggests that the associated costs of these preventive efforts would be substantially less than the economic and mortality costs of responding to these pathogens once they have emerged.

Needed: Robustness in Climate Economics, in Coping with the Climate Crisis: Mitigation Policies and Global Coordination, R. Arezki, P. Bolton, K. El Aynaoui, and M. Obstfeld, Eds., Columbia University Press (2018)

Abstract: The unprecedented nature of climate change creates the need to consider model uncertainty in economic models that incorporate a feedback between the world economy and the environment. This, in turn, motivates the use of robust control optimization. This novel approach has several implications for optimal growth, emissions, the energy transition, and for economic policy. A more sizable Pigouvian tax on emissions is needed to support the socially efficient allocation. This is in sharp contrast with existing policies, which subsidize fossil fuel. The concern about model uncertainty adversely affects the use of the dirtier fossil fuel, such as coal. In the presence of the fundamental uncertainties associated with climate change, active policies that promote renewables constitute a form of insurance.

Robust Dynamic Energy Use and Climate Change, with Xin Li and Borghan Narajabad, Quantitative Economics (2016)

Abstract: We study a dynamic stochastic general equilibrium model in which agents are concerned about model uncertainty regarding climate change. An externality from greenhouse gas emissions damages the economy`s capital stock. We assume that the mapping from climate change to damages is subject to uncertainty, as opposed to risk, and we use robust control to study efficiency and optimal policy. We obtain a sharp analytical solution for the implied environmental externality and characterize dynamic optimal taxation. The optimal tax that restores the socially optimal allocation is Pigouvian. We study optimal output growth in the presence and in the absence of concerns about model uncertainty, and find that these can lead to substantially different conclusions regarding the optimal emissions and the optimal mix of fossil fuel. In particular, the optimal use of coal will be significantly lower on a robust path, while the optimal use of oil/gas will edge down.

Competitive Behavior in Market Games: Evidence and Theory, with John Duffy and Alexander Matros, Journal of Economic Theory (2011)

Abstract: We explore whether competitive outcomes arise in an experimental implementation of a market game, introduced by Shubik (1973). Market games obtain Pareto inferior (strict) Nash equilibria, in which some or possibly all markets are closed. We find that subjects do not coordinate on autarkic Nash equilibria, but favor more efficient Nash equilibria in which all markets are open. As the number of subjects participating in the market game increases, the Nash equilibrium they achieve approximates the associated competitive equilibrium of the underlying economy. Motivated by these findings, we provide a theoretical argument for why evolutionary forces can lead to competitive outcomes in market games.

Modeling the Experimental Process in the Social Sciences, Journal of Mathematical Economics (2010)

Abstract: Motivated by time-series experimental designs, we develop a model of the act of measurement in the social sciences. Meaningful measurements are represented by operators that obey a non-commutative algebra. Thus, the order in which information is extracted matters. In addition, responses to questions about an attribute depend on whether information about another attribute has previously been extracted. Measurement ``forces`` the subject to obtain one value of the attribute, the one measured by the observer. An uncertainty principle imposes a fundamental limit on the ability to extract detailed information about two distinct attributes within a short period of time.

Self-Organized Criticality in a Dynamic Entry Game, with Andreas Blume and John Duffy, Journal of Economic Dynamics and Control (2010)

Abstract: We investigate conditions under which self organized criticality (SOC) arises in a version of a dynamic entry game. In the simplest version of the game, there is a single location-a pool-and one agent is exogenously dropped into the pool every period.

Payoffs to entrants are positive as long as the number of agents in the pool is below a critical level. If an agent chooses to exit, he cannot re-enter, resulting in a future payoff of zero. Agents in the pool decide simultaneously each period whether to stay in or not. We characterize the symmetric mixed strategy equilibrium of the resulting dynamic game. We then introduce local interactions between agents that occupy neighboring pools and demonstrate that, under our payoff structure, local interaction effects are necessary and sufficient for SOC and for an associated power law to emerge. Thus, we provide an explicit game-theoretic model of the mechanism through which SOC can arise in a social context with forward looking agents.

Fashion Statement, Review of Economic Dynamics (2009)

Abstract: We study bilateral matching under private information about agents` characteristics. Assortative matching is the only equilibrium outcome in the absence of private information. When an information friction is present, the matching process can be improved if a payoff irrelevant variable which we term ``fashion`` is introduced. Informed agents choose to adopt fashion as a signaling device. If success in matching is observed, other agents can imitate the signal. Thus, for fashion to be useful, it must constantly change. If there are more than two types of agents, both ``high`` and ``low`` fashion are needed to facilitate assortative matching.

Directed Matching and Monetary Exchange, with Dean Corbae and Randall Wright, Econometrica (2003)

Abstract: We develop a model of monetary exchange where, as in the random matching literature, agents trade bilaterally and not through centralized markets. Rather than assuming they match exogenously and at random, however, we determine who meets whom as part of the equilibrium. We show how to formalize this process of directed matching in dynamic models with double coincidence problems, and present several examples and applications that illustrate how the approach can be used in monetary theory. Some of our results are similar to those in the random matching literature; others differ significantly.

On the Geography of Conventions, with Andreas Blume, Economic Theory (2003)

Abstract: We study an evolutionary model in which heterogenous boundedly rational agents interact locally in order to play a coordination game. Agents differ in their mobility with mobile agents being able to relocate within a country. We find that mobile agents enjoy a higher payoff and always benefit from increased mobility, while immobile agents benefit from increased mobility at low levels of mobility only. This wedge in payoffs weakly increases as mobility increases. Some extensions are discussed.