Emissions Targets and the Real Business Cycle: Intensity Targets versus Caps or Taxes

For reducing greenhouse gas emissions, intensity targets are attracting interest as a flexible mechanism that would better allow for economic growth than emissions caps. For the same expected emissions, however, the economic responses to unexpected productivity shocks differ. Using a real business cycle model, we find that a cap dampens the effects of productivity shocks in the economy. An emissions tax leads to the same expected outcomes as a cap but with greater volatility. Certainty-equivalent intensity targets maintain higher levels of labor, capital, and output than other policies, with lower expected costs and no more volatility than with no policy.emissions tax, cap-and-trade, intensity target, business cycle

Emissions Targets and the Real Business Cycle: Intensity Targets versus Caps or Taxes

For reducing greenhouse gas emissions, intensity targets are attracting interest as a flexible mechanism that would better allow for economic growth than emissions caps. For the same expected emissions, however, the economic responses to unexpected productivity shocks differ. Using a real business cycle model, we find that a cap dampens the effects of productivity shocks in the economy on all variables except for the shadow value of the emissions constraint. An emissions tax leads to the same expected outcomes as a cap but with greater volatility. Certainty-equivalent intensity targets maintain higher levels of labor, capital, and output than other policies, with lower expected costs and no more volatility than with no policy.emissions tax, cap-and-trade, intensity target, business cycle

Harnessing enforcement leverage at the border to minimize biological risk from international live species trade

Allocating inspection resources over a diverse set of imports to prevent entry of plant pests and pathogens presents a substantial policy design challenge. We model inspections of live plant imports and producer responses to inspections using a “state-dependent” monitoring and enforcement model. We capture exporter abatement response to a set of feasible inspection policies from the regulator. Conditional on this behavioral response, we solve the regulator’s problem of selecting the parameters for the state-dependent monitoring regime to minimize entry of infested shipments. We account for exporter heterogeneity, fixed penalties for noncompliance, imperfect abatement control and imperfect inspections at the border. Overall, we estimate that state-dependent targeting (based on historical interceptions) cuts the rate of infested shipments that are accepted by one-fifth, relative to uniformly allocated inspections

Learning about a Moving Target in Resource Management: Optimal Bayesian Disease Control

Resource managers must often make difficult choices in the face of imperfectly observed and dynamically changing systems (e.g., livestock, fisheries, water, and invasive species). A rich set of techniques exists for identifying optimal choices when that uncertainty is assumed to be understood and irreducible. Standard optimization approaches, however, cannot address situations in which reducible uncertainty applies to either system behavior or environmental states. The adaptive management literature overcomes this limitation with tools for optimal learning, but has been limited to highly simplified models with state and action spaces that are discrete and small. We overcome this problem by using a recently developed extension of the Partially Observable Markov Decision Process (POMDP) framework to allow for learning about a continuous state. We illustrate this methodology by exploring optimal control of bovine tuberculosis in New Zealand cattle. Disease testing—the control variable—serves to identify herds for treatment and provides information on prevalence, which is both imperfectly observed and subject to change due to controllable and uncontrollable factors. We find substantial efficiency losses from both ignoring learning (standard stochastic optimization) and from simplifying system dynamics (to facilitate a typical, simple learning model), though the latter effect dominates in our setting. We also find that under an adaptive management approach, simplifying dynamics can lead to a belief trap in which information gathering ceases, beliefs become increasingly inaccurate, and losses abound

Integrating invasion and disease in the risk assessment of live bird trade.

AimInternational trade in plants and animals generates significant economic benefits. It also leads to substantial unintended impacts when introduced species become invasive, causing environmental disturbance or transmitting diseases that affect people, livestock, other wildlife or the environment. Policy responses are usually only implemented after these species become established and damages are already incurred. International agreements to control trade are likewise usually based on selection of species with known impacts. We aim to further develop quantitative invasive species risk assessment for bird imports and extend the tool to explicitly address disease threats.LocationUnited States of America.MethodsWe use a two-step approach for rapid risk assessment based on the expected biological risks due to both the environmental and health impact of a potentially invasive wildlife species in trade. We assess establishment probability based on a model informed by historical observations and then construct a model of emerging infectious disease threat based on economic and ecological characteristics of the exporting country.ResultsWe illustrate how our rapid assessment tool can be used to identify high-priority species for regulation based on a combination of the threat they pose for becoming established and vectoring emerging infectious diseases.Main conclusionsOur approach can be executed for a species in a matter of days and is nested in an economic decision-making framework for determining whether the biological risk is justified by trade benefits

Bioeconomic Model of Rainbow Trout (\u3cem\u3eOncorhynchus mykiss\u3c/em\u3e) and Humpback Chub (\u3cem\u3eGila cypha\u3c/em\u3e) Management in the Grand Canyon

The Colorado River, from Glen Canyon Dam (GCD) to the Little Colorado River (LCR) confluence, includes both non-native Rainbow Trout (Oncorhynchus mykiss) and endangered native Humpback Chub (Gila cypha). While both Rainbow Trout and Humpback Chub are valued fish species in this system, Rainbow Trout can have a negative effect on Humpback Chub survival. We developed a bioeconomic model to determine management actions that minimize the costs of controlling Rainbow Trout abundance subject to achieving Humpback Chub population goals. The model is compartmentalized into population and management components. The population component characterizes the stylized dynamics of Rainbow Trout and Humpback Chub from GCD to the LCR confluence within the Colorado River. The management component of the model identifies Rainbow Trout mechanical removal strategies that achieve average annual juvenile Humpback Chub survival targets while minimizing management costs. This research is an interdisciplinary effort combining biological models and economic methods to address federal, state and tribal stakeholder resource goals related to Rainbow Trout and Humpback Chub management in this complex social-ecological system

Political economy of renewable resource federalism

Author Posting. © Ecological Society of America, 2021. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecological Applications 00 (2021): e2276, doi:10.1002/eap.2276.The authority to manage natural capital often follows political boundaries rather than ecological. This mismatch can lead to unsustainable outcomes, as spillovers from one management area to the next may create adverse incentives for local decision making, even within a single country. At the same time, one‐size‐fits‐all approaches of federal (centralized) authority can fail to respond to state (decentralized) heterogeneity and can result in inefficient economic or detrimental ecological outcomes. Here we utilize a spatially explicit coupled natural–human system model of a fishery to illuminate trade‐offs posed by the choice between federal vs. state control of renewable resources. We solve for the dynamics of fishing effort and fish stocks that result from different approaches to federal management that vary in terms of flexibility. Adapting numerical methods from engineering, we also solve for the open‐loop Nash equilibrium characterizing state management outcomes, where each state anticipates and responds to the choices of the others. We consider traditional federalism questions (state vs. federal management) as well as more contemporary questions about the economic and ecological impacts of shifting regulatory authority from one level to another. The key mechanisms behind the trade‐offs include whether differences in local conditions are driven by biological or economic mechanisms; degree of flexibility embedded in the federal management; the spatial and temporal distribution of economic returns across states; and the status‐quo management type. While simple rules‐of‐thumb are elusive, our analysis reveals the complex political economy dimensions of renewable resource federalism.This work was partially supported through the Ecological Federalism working group of the National Institute for Mathematical and Biological Synthesis, an Institute sponsored by the National Science Foundation through NSF Award (No. DBI‐1300426), with additional support from the Howard H. Baker Jr. Center for Public Policy and The University of Tennessee, Knoxville. M. G. Neubert acknowledges support from the U.S. National Science Foundation (DEB‐1558904) and from the J. Seward Johnson Endowment in support of the Woods Hole Oceanographic Institution’s Marine Policy Center. We would like to thank seminar participants at Oregon State University, Nature Policy Lab at U.C. Davis, and the 2019 Association of Environmental and Resource Economists Summer Conference for valuable comments and suggestions on earlier versions of this research

Climate-smart agriculture global research agenda: Scientific basis for action

Background: Climate-smart agriculture (CSA) addresses the challenge of meeting the growing demand for food, fibre and fuel, despite the changing climate and fewer opportunities for agricultural expansion on additional lands. CSA focuses on contributing to economic development, poverty reduction and food security; maintaining and enhancing the productivity and resilience of natural and agricultural ecosystem functions, thus building natural capital; and reducing trade-offs involved in meeting these goals. Current gaps in knowledge, work within CSA, and agendas for interdisciplinary research and science-based actions identified at the 2013 Global Science Conference on Climate-Smart Agriculture (Davis, CA, USA) are described here within three themes: (1) farm and food systems, (2) landscape and regional issues and (3) institutional and policy aspects. The first two themes comprise crop physiology and genetics, mitigation and adaptation for livestock and agriculture, barriers to adoption of CSA practices, climate risk management and energy and biofuels (theme 1); and modelling adaptation and uncertainty, achieving multifunctionality, food and fishery systems, forest biodiversity and ecosystem services, rural migration from climate change and metrics (theme 2). Theme 3 comprises designing research that bridges disciplines, integrating stakeholder input to directly link science, action and governance. Outcomes: In addition to interdisciplinary research among these themes, imperatives include developing (1) models that include adaptation and transformation at either the farm or landscape level; (2) capacity approaches to examine multifunctional solutions for agronomic, ecological and socioeconomic challenges; (3) scenarios that are validated by direct evidence and metrics to support behaviours that foster resilience and natural capital; (4) reductions in the risk that can present formidable barriers for farmers during adoption of new technology and practices; and (5) an understanding of how climate affects the rural labour force, land tenure and cultural integrity, and thus the stability of food production. Effective work in CSA will involve stakeholders, address governance issues, examine uncertainties, incorporate social benefits with technological change, and establish climate finance within a green development framework. Here, the socioecological approach is intended to reduce development controversies associated with CSA and to identify technologies, policies and approaches leading to sustainable food production and consumption patterns in a changing climate

Alternative futures for global biological invasions

Scenario analysis has emerged as a key tool to analyze complex and uncertain future socio-ecological developments. However, currently existing global scenarios (narratives of how the world may develop) have neglected biological invasions, a major threat to biodiversity and the economy. Here, we use a novel participatory process to develop a diverse set of global biological invasion scenarios spanning a wide range of plausible global futures through to 2050. We adapted the widely used “two axes” scenario analysis approach to develop four families of four scenarios each, resulting in 16 scenarios that were later clustered into four contrasting sets of futures. Our analysis highlights that socioeconomic developments and technological innovation have the potential to shape biological invasions, in addition to well-known drivers, such as climate and human land use change and global trade. Our scenarios partially align with the shared socioeconomic pathways created by the climate change research community. Several factors that drive differences in biological invasions were underrepresented in the shared socioeconomic pathways; in particular, the implementation of biosecurity policies. We argue that including factors related to public environmental awareness and technological and trade development in global scenarios and models is essential to adequately consider biological invasions in global environmental assessments and thereby obtain a more integrative picture of future social–ecological developments