Math. Model. Nat. Phenom.
Volume 14, Number 1, 2019
Economics and the environment: distributed optimal control models
|Number of page(s)||18|
|Published online||02 April 2019|
Geographic environmental Kuznets curves: the optimal growth linear-quadratic case
Aix-Marseille University (Aix-Marseille School of Economics and IMéRA), CNRS, EHESS and Ecole Centrale de Marseille, Senior Member of the Institut Universitaire de France,
2 Univ. Grenoble Alpes, CNRS, INRA, Grenoble INP, GAEL, 38000 Grenoble, France.
3 Università degli Studi di Siena, Dipartimento di Economia Politica e Statistica, Siena, Italy.
4 Dipartimento di Economia e Finanza, LUISS Guido Carli, Rome, Italy.
* Corresponding author: firstname.lastname@example.org
Accepted: 13 December 2018
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.
Mathematics Subject Classification: 49J20 / 35K10 / 35Q93
Key words: Growth / geography / transboundary pollution / infinite dimensional optimal control problems
© The authors. Published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.