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on Resource Economics |
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Issue of 2018‒05‒28
three papers chosen by |
| By: | Raouf Boucekkine (Aix-Marseille Univ., CNRS, EHESS, Centrale Marseille, AMSE; Iméra; and Institut Universitaire de France); Giorgio Fabbri (Univ. Grenoble Alpes, CNRS, INRA, Grenoble INP, GAEL); Salvatore Federico (Università degli Studi di Siena, Dipartimento di Economia Politica e Statistica); Fausto Gozzi (Dipartimento di Economia e Finanza, 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 capacity 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 |
| JEL: | C61 C69 O44 R11 |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:aim:wpaimx:1813&r=res |
| By: | Tomas Balint (Université Paris 1 Panthéon-Sorbonne); Francesco Lamperti (Université Panthéon-Sorbonne - Paris 1 (UP1)); Antoine Mandel (Ecole d'Économie de Paris - Paris School of Economics); Mauro Napoletano (Observatoire français des conjonctures économiques); Andrea Roventini (Laboratory of Economics and Management (LEM)); Sandro Sapio (Universita degli studi di Napoli "Parthenope" [Napoli]) |
| Abstract: | Climate change is one of the most daunting challenges human kind has ever faced. In the paper, we provide a survey of the micro and macro economics of climate change from a complexity science perspective and we discuss the challenges ahead for this line of research. We identify four areas of the literature where complex system models have already produced valuable insights: (i) coalition formation and climate negotiations, (ii) macroeconomic impacts of climate-related events, (iii) energy markets and (iv) diffusion of climatefriendly technologies. On each of these issues, accounting for heterogeneity, interactions and disequilibrium dynamics provides a complementary and novel perspective to the one of standard equilibrium models. Furthermore, it highlights the potential economic benefits of mitigation and adaptation policies and the risk of under-estimating systemic climate change-related risks. |
| Date: | 2017–08 |
| URL: | http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/1nlv566svi86iqtetenms15tc4&r=res |
| By: | Niels Framroze Møller (DTU Management Engineering, Technical University of Denmark); Laura Mørch Andersen (Department of Food and Resource Economics, University of Copenhagen); Lars Gårn Hansen (Department of Food and Resource Economics, University of Copenhagen); Carsten Lynge Jensen (Department of Food and Resource Economics, University of Copenhagen) |
| Abstract: | The increasing deployment of renewables introduces substantial variability into the production of electricity, requiring demand to be more movable across time. We analyze data from a large Danish fi eld experiment (2015-2016) to investigate whether households can be prompted, via SMS messages, to move electricity consumption, and if so, whether these are motivated by pecuniary or environmental motives. To take heterogeneity fully into account we fi rst use general-to-speci c-based automatic model selection which allows for a different time-series regression for each of the 1488 households studied. From this we obtain a cross-section of estimated SMS effects which we then regress on the motive type. Since households can opt out there is a risk of self-selection. We therefore control for the size, income and average consumption of the household, and the age, educational- and labor market status of the SMS recipient. The results suggest that SMS messages can to some extent motivate households to move consumption. A stronger fi nancial motive seems more effective, whereas a purely environmental motive actually reduces the displaced amount. However, mixing financial and environmental motives seems the most effective. Finally, women and elderly people are more inclined to move consumption. |
| Keywords: | Household-level electricity demand, Automatic general-to-specific model selection, SMS messaging, field experimental data |
| JEL: | C2 C22 C5 Q4 |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:foi:wpaper:2018_06&r=res |