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Following a brief review of the management of environmental externalities under strategic interactions in the traditional temporal domain, results are extended to the spatiotemporal domain. Conditions for spatial open-loop and feedback Nash equilibria, along with conditions for the benchmark cooperative solution, are presented and compared. A simplified numerical example illustrates the spatial patterns emerging at a steady state under Fickian diffusion and dispersal kernels, and the inefficiency of spatially flat emission taxes. This conceptual framework could provide new research areas.

This short paper provides a modeling framework for unifying the economy, climate change and the outbreak of infectious diseases such as the recent COVID-19 pandemic. We stress that continuous growth of consumption activities, capital accumulation and climate change could increase the potential of the epidemic, its contact number or the probability of its arrival. This framework of analysis allows us to think of infectious disease policies in two stages. In the short run, containment policies like social distancing could help to stop the epidemic. In the medium and the long run, economic policies could help to reduce the potential of the epidemic or the probability of its emergence.

Non-point-source (NPS) pollution refers to a form of pollution in which neither the source nor the size of specific emissions can be observed or identified with sufficient accuracy. In NPS pollution the ambient concentration of pollutants associated with the individually unobserved emissions is typically observed. NPS pollution due to agricultural runoff is a major source of water pollution, eutrophication, and hypoxia. Due to informational asymmetries and stochastic effects, the use of traditional environmental policy instruments such as emissions taxes or tradable quotas to regulate NPS pollution is very difficult. This article reviews the main theoretical approaches, up to the present, to the regulation of NPS pollution—input-based schemes, ambient schemes, and endogenous monitoring—and discusses issues associated with NPS pollution regulation and their relation to the theoretically proposed instruments.

This paper studies the role of social networks in the management of natural resources. We consider a finite number of agents who exploit a specific natural resource. Harvesting is subject to three external effects, namely resource stock externalities, crowding externalities, and collaboration spillovers. We show that the structure of the social network—defined by the presence of collaboration links between individual agents—determines the equilibrium and the optimal harvesting amount. We then allow the agents to make decisions about creating or eliminating cooperation links, which endogenizes the structure of the network and is proved to affect total harvesting and aggregate welfare. Conservation plans are shown to change the regulator’s objective and increase even further the gap between the decentralized and the optimal outcomes. We show that the optimal policy depends explicitly on the structure of the network and the ‘centrality’ of the associated agents. Finally, introducing heterogeneity is proved to affect both individual profits and the incentives to create cooperation links.

We study a dynamic game of climate policy design in terms of emissions and solar radiation management (SRM) involving two heterogeneous countries or group of countries. Countries emit greenhouse gasses (GHGs), and can block incoming radiation by unilateral SRM activities, thus reducing global temperature. Heterogeneity is modelled in terms of the social cost of SRM, the environmental damages due to global warming, the productivity of emissions in terms of generating private benefits, the rate of impatience, and the private cost of geoengineering. We determine the impact of asymmetry on mitigation and SRM activities, concentration of GHGs, and global temperature, and we examine whether a tradeoff actually emerges between mitigation and SRM. Our results could provide some insights into a currently emerging debate regarding mitigation and SRM methods to control climate change, especially since asymmetries seem to play an important role in affecting incentives for cooperation or unilateral actions.

We examine whether environmental protection enhances international trade in a model of an international duopoly where production uses a depletable resource and generates cross-border pollution, and firms export their output to a world-market. Governments control pollution via either an emission tax, with revenue being used either to finance public pollution abatement or being refunded to the emitting firm contingent on reducing the cost of private pollution abatement (revenue-recycling), or an environmentally related standard. We evaluate these policies in terms of promoting exports, conserving the endowment of the natural resource, reducing pollution, and enhancing welfare. Our results indicate that in most cases, (1) revenue recycling is an export-contracting but resource preserving policy which also encourages firms’ pollution abatement activity, (2) public pollution abatement is an export-promoting but resource depleting policy. When the public sector is efficient in abating pollution, then overall pollution level across countries is lower compared to their level under tax-revenue recycling. Both policies entail ambiguous welfare effects. Environmental standards relative to public abatement is an export-contracting but resource preserving policy. Relative to revenue recycling work in the opposite way; they are always, however, welfare-enhancing.

The present paper is devoted to the study of robust control problems of parabolic stochastic partial differential equations under model uncertainty. To be more precise, the robust control problem under investigation is expressed as a stochastic differential game in a real separable infinite dimensional Hilbert space. By resorting to the theory of mild solutions, we prove that the elliptic partial differential equation associated with the problem at hand, also known as the Hamilton-Jacobi-Bellman-Isaacs equation, admits a unique solution, which is the value function of the game. Furthermore, we investigate the problem of existence of an optimal control pair that satisfies a saddle point property. Finally, as a demonstration of the proposed approach, we apply our results to the study of a certain robust control problem arising in the spatiotemporal management of natural resources.

Mechanisms generating patterns in spatial domains have been extensively studied in biology, but also in economics in the context of new economic geography. The Turing mechanism or Turing diffusion-induced instability has been central to the understanding of forces which endogenously generate spatial patterns, but in a context where agents do not explicitly optimize an objective. The present paper reviews tools to study, in the spirit of Turing's analysis, a mechanism generating optimal diffusion-induced instability where optimizing agents generate optimal agglomerations. By extending the maximum principle to the optimal control of partial differential equations, it is shown how under certain conditions it will be optimal to design controls so that the price-quantity system implied by the costate–state functions of the optimal control of distributed parameter systems induces optimal spatial patterns. These methods might be useful in studying pattern formation both in problems of resource management and of economic development.