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ETS and Technological Innovation: A Random Matching Model

Author

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  • Antoci, Angelo
  • Borghesi, Simone
  • Sodini, Mauro

Abstract

The present paper investigates the functioning of an Emission Trading System (ETS) and its impact on the diffusion of environmental-friendly technological innovation in the presence of firms’ strategic behaviours and sanctions to non-compliant firms. For this purpose, we study an evolutionary game model with random matching, namely, a context in which a population of firms interact through pairwise random matchings. We assume that each firm has to decide whether to adopt a new clean technology or keep on using the old technology that requires pollution permits to operate and that the strategy whose expected payoff is greater than the average payoff spreads within the population at the expense of the alternative strategy (the so-called replicator dynamics). We investigate the technological dynamics and the stationary states that emerge from the model. From the analysis of the model, we show that by properly modifying the penalty on non-compliant firms, it is possible to shift from one dynamic regime to another and that an increase in permits trade can promote the diffusion of innovative pollution-free technologies.

Suggested Citation

  • Antoci, Angelo & Borghesi, Simone & Sodini, Mauro, 2012. "ETS and Technological Innovation: A Random Matching Model," Climate Change and Sustainable Development 139508, Fondazione Eni Enrico Mattei (FEEM).
    • Handle: RePEc:ags:feemcl:139508
    DOI: 10.22004/ag.econ.139508
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    Cited by:

    1. A. Antoci & S. Borghesi & M. Sodini, 2017. "Water Resource Use and Competition in an Evolutionary Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(8), pages 2523-2543, June.
    2. Frédéric Branger & Oskar Lecuyer & Philippe Quirion, 2013. "The European Union Emissions Trading System : should we throw the flagship out with the bathwater ?," CIRED Working Papers hal-00866408, HAL.
    3. Sanjay Patnaik, 2020. "Emissions permit allocation and strategic firm behavior: Evidence from the oil sector in the European Union emissions trading scheme," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 976-995, March.
    4. Zeppini, Paolo, 2015. "A discrete choice model of transitions to sustainable technologies," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 187-203.
    5. Paolo Zeppini, 2014. "A discrete choice model of transitions to sustainable technologies: speed limits and optimal monetary policies," Department of Economics Working Papers 28/14, University of Bath, Department of Economics.

    More about this item

    Keywords

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    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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