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on Resource Economics |
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Issue of 2018‒06‒18
five papers chosen by |
| By: | Raouf Boucekkine (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université - EHESS - École des hautes études en sciences sociales, IMéRA - Institute for Advanced Studies - Aix-Marseille University, IUF - Institut Universitaire de France - M.E.N.E.S.R. - Ministère de l'Éducation nationale, de l’Enseignement supérieur et de la Recherche); Giorgio Fabbri (GAEL - Laboratoire d'Economie Appliquée de Grenoble - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - INRA - Institut National de la Recherche Agronomique - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes); Salvatore Federico (Università degli Studi di Siena, Dipartimento di Economia Politica e Statistica); Fausto Gozzi (Dipartimento di Economia e Finanza, Università Luiss - Guido Carli) |
| Abstract: | We solve a linear-quadratic model of a spatio-temporal economy using a polluting one-input technology. Space is continuous and heterogenous: locations differ in productivity, nature self-cleaning technology and environmental awareness. The unique link between locations is transboundary pollution which is modelled as a PDE diffusion equation. The spatio-temporal functional is quadratic in local consumption and linear in pollution. Using a dynamic programming method adapted to our infinite dimensional setting, we solve the associated optimal control problem in closed-form and identify the asymptotic (optimal) spatial distribution of pollution. We show that optimal emissions will decrease at given location if and only if local productivity is larger than a threshold which depends both on the local pollution absorption capacity and environmental awareness. Furthermore, we numerically explore the relationship between the spatial optimal distributions of production and (asymptotic) pollution in order to uncover possible (geographic) Environmental Kuznets Curve cases. |
| Keywords: | growth,geography,transboundary pollution,infinite dimensional optimal control problems |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-01792440&r=res |
| By: | Armel Ngami (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université - EHESS - École des hautes études en sciences sociales); Thomas Seegmuller (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université - EHESS - École des hautes études en sciences sociales) |
| Abstract: | This paper analyses the effect of a pay-as-you-go pension system on the evolution of capital and pollution, and on the efficiency of an environmental versus health policy. In an overlapping generations model (OLG), we introduce endogenous longevity that depends on pollution and health expenditures. Global dynamics may display multiple balanced growth paths (BGP). We show that by discouraging savings, a policy that promotes the pension system enlarges the environmental poverty trap. More surprisingly, the environmental policy has contrasted effects according to the significance of the pension system. If it has a low size, a raise of the environmental policy enlarges the environmental poverty trap and leads to a rise in capital over pollution at the highest stationary equilibrium. In contrast, in economies where intergenerational solidarity is well developed, capital over pollution decreases at the highest BGP. In such a case, the environmental policy does not necessarily lead to a better longevity and growth. |
| Keywords: | longevity,environment,health,pension system,growth,pollution |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-01798710&r=res |
| By: | Soheil Shayegh (Fondazione Eni Enrico Mattei (FEEM)); Valentina Bosetti (Fondazione Eni Enrico Mattei (FEEM) and Bocconi University); Simon Dietz (London School of Economics); Johannes Emmerling (Fondazione Eni Enrico Mattei (FEEM)); Christoph Hambel (Goethe University Frankfurt); Svenn Jensen (Oslo Metropolitan University); Holger Kraft (Goethe University Frankfurt); Massimo Tavoni (Fondazione Eni Enrico Mattei (FEEM) and Politecnico di Milano); Christian Traeger (University of Oslo and University of California Berkeley); Rick Van der Ploeg (University of Oxford) |
| Abstract: | Over the last few decades, integrated assessment models (IAM) have provided insight into the relationship between climate change, economy, and climate policies. The limitations of these models in capturing uncertainty in climate parameters, heterogeneity in damages and policies, have given rise to skepticism about the relevance of these models for policy making. IAM community needs to respond to these critics and to the new challenges posed by developments in the policy arena. New climate targets emerging from the Paris Agreement and the uncertainty about the signatories’ commitment to Nationally Determined Contributions (NDCs) are prime examples of challenges that need to be addressed in the next generation of IAMs. Given these challenges, calculating the social cost of carbon requires a new framework. This can be done by computing marginal abatement cost in cost-effective settings which provides different results than those calculated using constrained cost-benefit analysis. Here we focus on the areas where IAMs can be deployed to asses uncertainty and risk management, learning, and regional heterogeneity in climate change impacts. |
| Keywords: | Integrated Assessment Models, Climate Policy, Carbon, Uncertainty |
| JEL: | Q54 |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:fem:femwpa:2018.19&r=res |
| By: | Antonia Díaz (Universidad Carlos III de Madrid); Gustavo A. Marrero (Universidad de La Laguna); Luis Puch (Universidad Complutense de Madrid); Jesús Rodríguez-López (U. Pablo de Olavide) |
| Abstract: | This paper explores how changes in energy intensity and the switch to renewables can boost economic growth. In doing so, we implement a dynamic panel data approach on a sample of 134 countries over the period 1960 to 2010. We incorporate a set of control variables, related to human and physical capital, socio-economic conditions, and policies which are widely used in the associated literature. According to our results, and given the current state of technology, improving energy intensity is an approach that could reconcile growth and the environment at the worldwide level. Moving to conventional renewables (biomass and hydro) may reduce CO2 emissions, consistent with the related literature, although we do not find evidence that supports a growth enhancing effect. However, moving to frontier renewables (wind, solar, wave or geothermic) does reconcile the reduction of CO2 emissions with economic growth. Our results are robust to the specification of the dynamic panel with respect to three alternative methods, namely, the pooled OLS regression, the regression under fixed effects, and the GMM estimation. |
| Keywords: | Economic growth, energy intensity, renewable energy, dynamic panel data models. |
| JEL: | C23 C33 O5 Q2 Q3 Q41 Q43 Q42 Q48 |
| Date: | 2018–06 |
| URL: | http://d.repec.org/n?u=RePEc:pab:wpaper:18.08&r=res |
| By: | Alistair Hunt (University of Bath); Nick Dale (University of Bath) |
| Abstract: | This paper gives an overview of economic assessments of the benefits of the control of formaldehyde and reflects on developments in its risk management and regulation. Formaldehyde is used in the manufacture of resins, as a disinfectant and fixative and as a preservative in consumer products. Formaldehyde exposure can be harmful to human health. |
| Keywords: | Cost-benefit analysis, environmental health valuation, formaldehyde, non-market valuation, regulatory impact assessment |
| JEL: | Q51 Q52 Q53 |
| Date: | 2018–06–06 |
| URL: | http://d.repec.org/n?u=RePEc:oec:envaaa:134-en&r=res |