Terminating links between emission trading programs

Links between emission trading programs are not immutable, as highlighted by New Jersey׳s exit from the Regional Greenhouse Gas Initiative in 2011. This raises the question of what to do with existing permits that are banked for future use—choices that have consequences for market behavior in advance of, or upon speculation about, delinking. We consider two delinking policies. One differentiates banked permits by origin, the other treats banked permits the same. We describe the price behavior and relative cost-effectiveness of each policy. Treating permits differently generally leads to higher costs, and may lead to price divergence, even with only speculation about delinking.     

Uncertainty and allocation decisions involving unique environmental resources

The implications of the treatment of uncertainty in the definition of optimal investment criteria for irreversible allocations of unique environmental resources are considered herein. This analysis argues that the single-project, orientation of conventional cost-benefit analysis can lead to inconsistent decisions because it fails to take account of the potential for risk pooling across projects. In the models discussed in this paper uncertainty arises because the planner must estimate the net benefits associated with a mix of developed and preserved natural environments. The results suggest that the criteria for optimal investment plans will be affected by those factors influencing this uncertainty. Both the scale and timing of optimal investments may be altered from those prescribed with the conventional (Fisher-Krutilla-Cicchetti rule) framework when the potential for risk pooling is introduced. Thus, it is important to consider as a part of the specification of the objective function the factors which give rise to uncertainty.     

Environmental Policy and International Trade when Governments and Producers Act Strategically

Some environmentalists express concern that trade liberalization may damage the environment by giving governments incentives to relax environmental policies to give domestic producers a competitive advantage. Support for such concern may be given by models of imperfectly competitive trade where there may be “rent-shifting” incentives for governments to relax environmental policies. But there are also incentives for producers to act strategically, e.g., through their investment in R&D, and in this paper I extend the literature on strategic environmental policy by allowing for strategic behavior by producers as well as governments. I show that (i) allowing for producers to act strategically on balance reduces the incentive for governments to act strategically; (ii) allowing governments to act strategically increases the incentive for producers to act strategically; (iii) welfare is lower when both parties act strategically; and (iv) strategic behavior by producers and governments is greater when governments use emission taxes than when they use emission standards.     

Incorporating the Effects of Socioeconomic Uncertainty into Priority Setting for Conservation Investment

Abstract:  Uncertainty in the implementation and outcomes of conservation actions that is not accounted for leaves conservation plans vulnerable to potential changes in future conditions. We used a decision-theoretic approach to investigate the effects of two types of investment uncertainty on the optimal allocation of global conservation resources for land acquisition in the Mediterranean Basin. We considered uncertainty about (1) whether investment will continue and (2) whether the acquired biodiversity assets are secure, which we termed transaction uncertainty and performance uncertainty, respectively. We also developed and tested the robustness of different rules of thumb for guiding the allocation of conservation resources when these sources of uncertainty exist. In the presence of uncertainty in future investment ability (transaction uncertainty), the optimal strategy was opportunistic, meaning the investment priority should be to act where uncertainty is highest while investment remains possible. When there was a probability that investments would fail (performance uncertainty), the optimal solution became a complex trade-off between the immediate biodiversity benefits of acting in a region and the perceived longevity of the investment. In general, regions were prioritized for investment when they had the greatest performance certainty, even if an alternative region was highly threatened or had higher biodiversity value. The improved performance of rules of thumb when accounting for uncertainty highlights the importance of explicitly incorporating sources of investment uncertainty and evaluating potential conservation investments in the context of their likely long-term success.     

Green tax reform,endogenous innovation and the growth dividend

We study theoretically and numerically the effects of an environmental tax reform using endogenous growth theory. In the theoretical segment, mobile labor between manufacturing and R&D activities, and elasticity of substitution between labor and energy in manufacturing lower than unity allow for a growth dividend, even if we consider preexisting tax distortions. The scope for innovation is reduced when we consider direct financial investment in the lab, or elastic labor supply. We then apply the core theoretical model to a real growing economy and find that a boost in long-run economic growth following such a carbon policy is a possible outcome. Redistribution of additional carbon tax revenue by lowering capital taxation performs best in terms of effciency measured by aggregate welfare. In terms of equity among social segments the progressive character of lump-sum redistribution fails when we consider very high emissions reduction targets.     

Increased carbon dioxide availability alters phytoplankton stoichiometry and affects carbon cycling and growth of a marine planktonic herbivore

Rising levels of CO₂ in the atmosphere have led to increased CO₂ concentrations in the oceans. This enhanced carbon availability to the marine primary producers has the potential to change their nutrient stoichiometry, and higher carbon-to-nutrient ratios are expected. As a result, the quality of the primary producers as food for herbivores may change. Here, we present experimental work showing the effect of feeding Rhodomonas salina grown under different pCO₂ (200, 400 and 800 μatm) on the copepod Acartia tonsa. The rate of development of copepodites decreased with increasing CO₂ availability to the algae. The surplus carbon in the algae was excreted by the copepods, with younger stages (copepodites) excreting most of their surplus carbon through respiration and adult copepods excreting surplus carbon mostly as DOC. We consider the possible consequences of different excretory pathways for the ecosystem. A continued increase in the CO₂ availability for primary production, together with changes in the nutrient loading of coastal ecosystems, may cause changes in the trophic links between primary producers and herbivores.     

The environment as a factor of production

This paper uses firm-level data about electric utilities to develop an empirical model of how electric utilities use and bank SO₂ pollution permits under the Acid Rain Program. The empirical model considers emissions, fuels, and labor as variable inputs with quasi-fixed stocks of permits and capital. Consequently, substitution possibilities between the environment and other production factors can be measured and tested. The results reveal substantial substitution between emissions, permit stocks, capital, fuel, and labor. The empirical findings also indicate that firms bank permits primarily as a hedge against uncertainty and for other firm-specific reasons. Overall, the results suggest that cap-and-trade approaches can reduce the cost of meeting environmental goals by providing a mechanism for addressing regulatory and market risks and by signaling an appropriate price for factor use, especially irreversible capital investments.     

The environment as a factor of production

This paper uses firm-level data about electric utilities to develop an empirical model of how electric utilities use and bank SO₂ pollution permits under the Acid Rain Program. The empirical model considers emissions, fuels, and labor as variable inputs with quasi-fixed stocks of permits and capital. Consequently, substitution possibilities between the environment and other production factors can be measured and tested. The results reveal substantial substitution between emissions, permit stocks, capital, fuel, and labor. The empirical findings also indicate that firms bank permits primarily as a hedge against uncertainty and for other firm-specific reasons. Overall, the results suggest that cap-and-trade approaches can reduce the cost of meeting environmental goals by providing a mechanism for addressing regulatory and market risks and by signaling an appropriate price for factor use, especially irreversible capital investments.     

Choosing ecosystem service investments that are robust to uncertainty across multiple parameters

Info-gap decision theory facilitates decision making for problems in which uncertainty is large and probability distributions of uncertain variables are unknown. The info-gap framework allows the decision maker to maximize robustness to failure in the presence of uncertainty, where uncertainty is in the parameters of the model and failure is defined as the model output falling below some minimally acceptable performance threshold. Info-gap theory has found particular application to problems in conservation biology and ecological economics. In this study, we applied info-gap theory to an ecosystem services tradeoff case study in which a decision maker aiming to maximize ecosystem service investment returns must choose between two alternative land uses: native vegetation conservation or the establishment of an exotic timber plantation. The uncertain variables are the carbon price and the water price. With a "no-information" uncertainty model that assumes equal relative uncertainty across both variables, info-gap theory identifies a minimally acceptable reward threshold above which conservation is preferred, but below which plantation establishment is preferred. However, with an uncertainty model that allows the carbon price to be substantially more uncertain than the water price, conservation of native vegetation becomes an economically more robust investment option than establishing alien pine plantations. We explored the sensitivity of the results to the use of alternative uncertainty models, including asymmetric uncertainty in individual variables. We emphasize the general finding that the results of info-gap analyses can be sensitive to the choice of uncertainty model and that, therefore, future applications to ecological problems should be careful to incorporate all available qualitative and quantitative information relating to uncertainties or should at least justify the no-information uncertainty model.     

Prospect theory and energy efficiency

Investments in energy efficiency entail uncertainty, and when faced with uncertainty consumers have been shown to behave according to prospect theory: preferences are reference-dependent and exhibit loss aversion, and probabilities are subjectively weighted. Using data from a choice experiment eliciting prospect theory parameters, I provide evidence that loss-averse people are less likely to invest in energy efficiency. Then, I consider policy design under prospect theory when there are also externalities from energy use. A higher degree of loss aversion implies a higher subsidy to energy efficiency. Numerical simulations suggest that the impact of prospect theory on policy may be substantial.     

A density projection approach for non-trivial information dynamics: Adaptive management of stochastic natural resources

We demonstrate a density projection approximation method for solving resource management problems with imperfect state information. The method expands the set of partially-observed Markov decision process (POMDP) problems that can be solved with standard dynamic programming tools by addressing dimensionality problems in the decision maker's belief state. Density projection is suitable for uncertainty over both physical states (e.g. resource stock) and process structure (e.g. biophysical parameters). We apply the method to an adaptive management problem under structural uncertainty in which a fishery manager's harvest policy affects both the stock of fish and the belief state about the process governing reproduction. We solve for the optimal endogenous learning policy—the active adaptive management approach—and compare it to passive learning and non-learning strategies. We demonstrate how learning improves efficiency but typically follows a period of costly short-run investment.     

Social enquiry and the measurement of natural phenomena: the degradation of irrigation water in the Argolid Plain,Greece

Attempts to formulate appropriate policies for the management of agricultural systems are constrained by the limitations of acquiring information about changes in the natural system across space and through time. The adoption of natural science techniques to measure the transformation of natural phenomena requires considerable investment in time and expertise and may not always be capable of providing information about change in a way that meets the adaptive requirements of planning and policy. A more flexible approach to data collection will require the acceptance of less precise and more general physical data as the basis for understanding changes in complex agricultural systems. This raises interesting questions about the adoption of social enquiry techniques to provide information about changing natural phenomena. The progressive deterioration of water resources, as a result of intensive agricultural activity in the Argolid Plain of Greece, will be considered and the problems of measuring the extent of that degradation, and the processes leading to it, will be discussed.     

The Impact of Economics on Environmental Policy

Environmental economists have seen their ideas translated into the rough-and-tumble policy world for over two decades. They have witnessed the application of economic instruments to several environmental issues, including preserving wetlands, lowering lead levels, and curbing acid rain. This essay examines the impact of the rise of economics in the policy world on the making of environmental policy. I focus on two related, but distinct phenomena—the increasing interest in the use of incentive-based mechanisms, such as tradable permits, to achieve environmental goals; and the increasing interest in the use of analytical tools such as benefit–cost analysis in regulatory decision making.I argue that economists and economic instruments have had a modest impact on shaping environmental, health, and safety regulation, but that economists will play an increasingly important role in the future. Although the role of economics is becoming more prominent, it does not follow that environmental policy will become more efficient. This apparent inconsistency can be explained by the political economy of environmental policy.     

Optimal monitoring and control under state uncertainty: Application to lionfish management

State variables in many renewable resource management problems, such as the abundance of a fish stock, are imperfectly observed over time. In systems characterized by state uncertainty, decision makers often invest in monitoring to learn about the level of a stock. We develop a stochastic bioeconomic model of marine invasive species management under state uncertainty. The decision maker in our model simultaneously evaluates optimal investment in monitoring and population control. Using a recently-devised method for solving continuous-state Partially Observable Markov Decision Processes (POMDPs), we find that the ability to learn through monitoring can alter the role of population control in the optimal policy function, for example by reducing control intensity in favor of monitoring. Optimal monitoring depends on the management context, including in our application lionfish population structure. The rich transient dynamics of our model depend critically on the relationship between the initial conditions for information and invader abundance.     

An empirical analysis of economic strategies for controlling air pollution

In evaluating current environmental protection policy, economists often note that current regulations are more costly than necessary to meet environmental quality standards. While the a priori case is strong that current regulatory approaches are resulting in higher-than-necessary costs to attain environmental standards, there is relatively little empirical evidence to support this claim. The purpose of this paper is to supply some of the missing evidence by presenting the results of one study that assesses some of the potential savings associated with implementing economic, rather than command-and-control, regulatory approaches to abate one type of air pollution in one region of the country. Specifically, the paper examines the costs of meeting a prospective short-term standard for nitrogen dioxide under a range of alternative emissions control strategies for stationary sources of nitrogen oxide emissions in the Chicago Air Quality Control Region. The alternative strategies that are considered range from those that might result under current regulatory policy to those that economic policy approaches (such as emissions charges or marketable permits) are designed to implement. The analysis shows that the most efficient program of emissions controls may be more than an order of magnitude less costly than current regulatory strategies, and that economic approaches have additional advantages over more conventional regulatory approaches.     

Confronting Uncertainty and Missing Values in Environmental Value Transfer as Applied to Species Conservation

Abstract: The nonuse (or passive) value of nature is important but time‐consuming and costly to quantify with direct surveys. In the absence of estimates of these values, there will likely be less investment in conservation actions that generate substantial nonuse benefits, such as conservation of native species. To help overcome decisions about the allocation of conservation dollars that reflect the lack of estimates of nonuse values, these values can be estimated indirectly by environmental value transfer (EVT). EVT uses existing data or information from a study site such that the estimated monetary value of an environmental good is transferred to another location or policy site. A major challenge in the use of EVT is the uncertainty about the sign and size of the error (i.e., the percentage by which transferred value exceeds the actual value) that results from transferring direct estimates of nonuse values from a study to a policy site, the site where the value is transferred. An EVT is most useful if the decision‐making framework does not require highly accurate information and when the conservation decision is constrained by time and financial resources. To account for uncertainty in the decision‐making process, a decision heuristic that guides the decision process and illustrates the possible decision branches, can be followed. To account for the uncertainty associated with the transfer of values from one site to another, we developed a risk and simulation approach that uses Monte Carlo simulations to evaluate the net benefits of conservation investments and takes into account different possible distributions of transfer error. This method does not reduce transfer error, but it provides a way to account for the effect of transfer error in conservation decision making. Our risk and simulation approach and decision‐based framework on when to use EVT offer better‐informed decision making in conservation.     

Accounting for Complementarity to Maximize Monitoring Power for Species Management

To choose among conservation actions that may benefit many species, managers need to monitor the consequences of those actions. Decisions about which species to monitor from a suite of different species being managed are hindered by natural variability in populations and uncertainty in several factors: the ability of the monitoring to detect a change, the likelihood of the management action being successful for a species, and how representative species are of one another. However, the literature provides little guidance about how to account for these uncertainties when deciding which species to monitor to determine whether the management actions are delivering outcomes. We devised an approach that applies decision science and selects the best complementary suite of species to monitor to meet specific conservation objectives. We created an index for indicator selection that accounts for the likelihood of successfully detecting a real trend due to a management action and whether that signal provides information about other species. We illustrated the benefit of our approach by analyzing a monitoring program for invasive predator management aimed at recovering 14 native Australian mammals of conservation concern. Our method selected the species that provided more monitoring power at lower cost relative to the current strategy and traditional approaches that consider only a subset of the important considerations. Our benefit function accounted for natural variability in species growth rates, uncertainty in the responses of species to the prescribed action, and how well species represent others. Monitoring programs that ignore uncertainty, likelihood of detecting change, and complementarity between species will be more costly and less efficient and may waste funding that could otherwise be used for management. Contabilización de la Complementariedad para Maximizar el Poder de Monitoreo para el Manejo de Especies     

Enforcement and price controls in emissions trading

This paper examines how enforcement affects the structure and performance of emissions trading programs with price controls under uncertainty about firms' abatement costs. The analysis highlights how an enforcement strategy can cause abatement-cost risk to be transmitted to enforcement costs via the price of permits. When this occurs, accommodating the effect of abatement-cost risk with an optimal policy results in higher expected emissions and lower expected permit price than their second-best optimal values. However, it is possible to design an enforcement strategy that shields enforcement costs from abatement-cost risk by tying sanctions directly to permit prices. This enforcement strategy stabilizes enforcement effort, the optimal permit supply and price controls are independent of enforcement costs, and the policy produces the second-best optimal outcome.     

The importance of agricultural yield elasticity for indirect land use change: a Bayesian network analysis for robust uncertainty quantification

ABSTRACT

A major barrier to realising biofuels’ climate change mitigation potential is uncertainty concerning carbon emissions from indirect land use change (ILUC). Central to this uncertainty is the extent to which yields can respond dynamically to increased demand for agricultural commodities. This study examines the elasticity of soybean and corn yields in the USA for 1990–2017 using Bayesian network models to robustly quantify uncertainty. The central finding is that a single parameter value for yield elasticity does not adequately represent the effects of technology, policy and price pressures through time. The models demonstrate the limiting role of technological progress as well as farmers’ capital investment in response to system shocks. Results suggest evaluation of parameter uncertainty alone is unlikely to capture a full range of future ILUC scenarios and reiterate the need for ILUC studies to use probabilistic approaches as standard to robustly inform climate change mitigation policies.     

Software for prioritizing conservation actions based on probabilistic information

Marxan is the most common decision-support tool used to inform the design of protected-area systems. The original version of Marxan does not consider risk and uncertainty associated with threatening processes affecting protected areas, including uncertainty about the location and condition of species’ populations and habitats now and in the future. We described and examined the functionality of a modified version of Marxan, Marxan with Probability. This software explicitly considers 4 types of uncertainty: probability that a feature exists in a particular place (estimated based on species distribution models or spatially explicit population models); probability that features in a site will be lost in the future due to a threatening process, such as climate change, natural catastrophes, and uncontrolled human interventions; probability that a feature will exist in the future due to natural successional processes, such as a fire or flood; and probability the feature exists but has been degraded by threatening processes, such as overfishing or pollution, and thus cannot contribute to conservation goals. We summarized the results of 5 studies that illustrate how each type of uncertainty can be used to inform protected area design. If there were uncertainty in species or habitat distribution, users could maximize the chance that these features were represented by including uncertainty using Marxan with Probability. Similarly, if threatening processes were considered, users minimized the chance that species or habitats were lost or degraded by using Marxan with Probability. Marxan with Probability opens up substantial new avenues for systematic conservation planning research and application by agencies.