1,721,323 research outputs found

    Dynamic Games with Nature: Designing Policy under Ambiguity

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    Environmental and resource economics is permeated by economic and environmental uncertainties. The expected utility framework founded by von Neumann and Morgenstern and later extended to subjective probability by Savage is the traditional framework for dealing with risk in economics. Frank Knight suggested the need to distinguish between risk and uncertainty for situations where there is ignorance or not enough information to assign probabilities — objective or subjective — to events. Knightian uncertainty, or ambiguity, is an appropriate framework for studying environmental management issues, given the complexities and the multiple sources of underlying uncertainties. Decisionmaking under ambiguity has been based on the maxmin expected utility. Robust control, by using maxmin rules and by introducing a fictitious adversarial agent referred to as Nature, provides policies under ambiguity. In robust rules the lower bounds to the rule’s performance are determined by Nature, and management can be regarded as a game between the regulator and Nature. The regulator maximizes her/his objective, while Nature “tries” to minimize the regulator’s objective. The outcome of this game determines regulation under ambiguity. This paper presents methods for studying environmental and resource management issues and designing robust policies under ambiguity or Knightian uncertainty and ambiguity aversion. In particular, robust control methods are applied to a differential game associated with a problem of international pollution control. Optimal robust feedback rules and state variable paths are derived. The differential game framework is also extended to recently developed deterministic robust control methods which allow direct comparisons between cooperative and noncooperative outcomes

    ENERGY BALANCE CLIMATE MODELS, DAMAGE RESERVOIRS, AND THE TIME PROFILE OF CLIMATE CHANGE POLICY

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    In particular, we differentiate between two types of damages from climate change, traditional gradually increasing damages and a damage reservoir type, where the latter represents a finite source of economic damage associated with the movement of the ice line. Damage reservoirs in the context of climate change can be regarded as sources of damage that eventually will cease to exist when the source of the damage has been depleted.We identify ice caps and permafrost as typical damage reservoirs, where the state of the reservoir is connected to the latitudinal position of the ice line

    Pollution Control: When, and How, to be Precautious

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    The precautionary principle (PP) applied to environmental policy stipulates that, in the presence of physical uncertainty, society must take robust preventive action to guard against worst-case outcomes. It follows that the higher the degree of uncertainty, the more aggressive this preventive action should be. This normative maxim is explored in the case of a stylized dynamic model of pollution control under Knightian uncertainty. At time 0 a decision-maker makes a one-time investment in damage-control technology and subsequently decides on a desirable dynamic emissions policy. Adopting the robust control framework of Hansen and Sargent [10], we investigate optimal damage-control and mitigation policies. We show that optimal investment in damage control is always increasing in the degree of uncertainty, thus confirming the conventional PP wisdom. Optimal mitigation decisions, however, need not always comport with the PP and we provide analytical conditions that sway the relationship one way or the other. This result is interesting when contrasted to a model with fixed damage-control technology, in which it can be easily shown that a PP vis-a-vis mitigation unambiguously holds. We conduct a set of numerical experiments to determine the sensitivity of our results to specific functional forms of damage-control cost. We find that when the cost of damage-control technology is low enough, damage-control investment and mitigation may act as substitutes and a PP with respect to the latter can be unambiguously irrational.Risk, Ambiguity, Robust Control, Precautionary Principle, Pollution Control

    Optimal Control and Spatial Heterogeneity: Pattern Formation in Economic-Ecological Models

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    This paper extends Turing analysis to standard recursive optimal control frameworks in economics and applies it to dynamic bioeconomic problems where the interaction of coupled economic and ecological dynamics under optimal control over space creates (or destroys) spatial heterogeneity. We show how our approach reduces the analysis to a tractable extension of linearization methods applied to the spatial analog of the well known costate/state dynamics. We explicitly show the existence of a non-empty Turing space of diffusive instability by developing a linear-quadratic approximation of the original non-linear problem. We apply our method to a bioeconomic problem, but the method has more general economic applications where spatial considerations and pattern formation are important. We believe that the extension of Turing analysis and the theory associated with the dispersion relationship to recursive infinite horizon optimal control settings is new.Spatial analysis, Pattern formation, Turing mechanism, Turing space, Pontryagin’s principle, Bioeconomics

    Dynamic Contingent Valuation and Choice Modelling for Ecosystem Services

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    Non market valuation and bio economic modelling are combined in a dynamic model of ecosystem services. A mathematical proof demonstrates that the imputed price of natural capital contains all non market values and that scarcity rent is the total value of ecosystem services. A dynamic demand system, including characteristics is derived. New methods are developed for dynamic welfare analysis and both revealed and stated preference methods are proposed for estimating the price of natural capital. Estimation is simple if we avoid surveying consumers who degrade the ecosystem and instead consult owners who accrue the scarcity rent and conserve for the future.Non market valuation, ecosystem services, Lancaster demand, welfare analysis, analytical solutions, Demand and Price Analysis, Environmental Economics and Policy, Research Methods/ Statistical Methods, Q57, Q51, Q56,
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