
Contents
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16.1 Introduction 16.1 Introduction
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16.2 The Model 16.2 The Model
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16.3 Dynamics of the Game 16.3 Dynamics of the Game
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16.3.1 Dynamics of the Game When the Payoff Matrix A Applies 16.3.1 Dynamics of the Game When the Payoff Matrix A Applies
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16.3.2 Dynamics of the Game When the Payoff Matrix C Applies 16.3.2 Dynamics of the Game When the Payoff Matrix C Applies
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16.3.3 Dynamics of the Game When θ is Endogenous 16.3.3 Dynamics of the Game When θ is Endogenous
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16.3.3.1 Case b > 0 16.3.3.1 Case b > 0
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16.3.3.2 Case b < 0 16.3.3.2 Case b < 0
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16.4 Conclusions 16.4 Conclusions
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Acknowledgments Acknowledgments
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Notes Notes
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References References
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16 Emission Trading Systems and Technological Innovation: A Random Matching Model
Get accessAngelo Antoci, Professor of Mathematical Economics, University of Sassari, Italy.
Simone Borghesi, Researcher, Departments of Political Science, Law, Economics, and Government, University of Siena.
Mauro Sodini, Researcher, Department of Economics of Management, University of Pisa.
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Published:05 May 2015
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Abstract
The present chapter paper investigates the functioning of an emission trading system and its impact on the diffusion of environmentally friendly technological innovation in the presence of firms' strategic behaviors and sanctions to non compliant firms. For this purpose, we study an evolutionary game model with random matching, namely, a context in which firms interact through pairwise random matchings and have to decide whether to adopt a new clean technology or keep using the old technology that requires pollution permits to operate. We investigate the technological dynamics emerging from the model and show that by properly modifying the penalty on non compliant firms, it is possible to shift from one dynamic regime to another, increase permits trade, and promote the diffusion of innovative technologies
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