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Infinite Dimensional Duality Theory Applied to Investment Strategies in Environmental Policy

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  • Laura Scrimali

    (Università di Catania)

Abstract

In this paper, we develop an infinite dimensional Lagrangian duality framework for modeling and analyzing the evolutionary pollution control problem. Specifically, we examine the situation in which different countries aim at determining the optimal investment allocation in environmental projects and the tolerable pollutant emissions, so as to maximize their welfare. We state the equilibrium conditions underlying the model, and provide an equivalent formulation in terms of an evolutionary variational inequality. Moreover, by means of infinite dimensional duality tools, we prove the existence of Lagrange multipliers that play a fundamental role in order to describe countries’ decision-making processes.

Suggested Citation

  • Laura Scrimali, 2012. "Infinite Dimensional Duality Theory Applied to Investment Strategies in Environmental Policy," Journal of Optimization Theory and Applications, Springer, vol. 154(1), pages 258-277, July.
  • Handle: RePEc:spr:joptap:v:154:y:2012:i:1:d:10.1007_s10957-012-9995-7
    DOI: 10.1007/s10957-012-9995-7
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    1. Antonino Maugeri & Laura Scrimali, 2016. "A New Approach to Solve Convex Infinite-Dimensional Bilevel Problems: Application to the Pollution Emission Price Problem," Journal of Optimization Theory and Applications, Springer, vol. 169(2), pages 370-387, May.
    2. Ciarcià, Carla & Daniele, Patrizia, 2016. "New existence theorems for quasi-variational inequalities and applications to financial models," European Journal of Operational Research, Elsevier, vol. 251(1), pages 288-299.
    3. Laura Scrimali, 2022. "On the Stability of Coalitions in Supply Chain Networks via Generalized Complementarity Conditions," Networks and Spatial Economics, Springer, vol. 22(2), pages 379-394, June.
    4. Patrizia Daniele & Sofia Giuffrè & Antonino Maugeri & Fabio Raciti, 2014. "Duality Theory and Applications to Unilateral Problems," Journal of Optimization Theory and Applications, Springer, vol. 162(3), pages 718-734, September.

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