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The effect of access to clean technology on pollution reduction: An experiment

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  • Pevnitskaya, Svetlana
  • Ryvkin, Dmitry

Abstract

We use a laboratory experiment to study decisions in a dynamic game where firms' private production leads to accumulation of a public bad, such as pollution. Firms have an option to invest in clean technology, which proportionally lowers their emissions, or contributions to the public bad. The main treatment variable is the type of access to clean technology, or benefits from such investment, which can be private or common. Under private access, investment reduces the firm's own propensity to pollute. Under common access, each firm's investment reduces all firms' propensity to pollute. For each treatment, we characterize the Markov perfect equilibrium and social optimum. The observed level of the public bad is lower with common access. This result remains in the presence of communication. The option to communicate induces coordination of investments in clean technology at a higher level, leading to lower average pollution levels in both treatments.

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  • Pevnitskaya, Svetlana & Ryvkin, Dmitry, 2022. "The effect of access to clean technology on pollution reduction: An experiment," Games and Economic Behavior, Elsevier, vol. 136(C), pages 117-141.
    • Handle: RePEc:eee:gamebe:v:136:y:2022:i:c:p:117-141
    DOI: 10.1016/j.geb.2022.07.007
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    More about this item

    Keywords

    Dynamic games; Public bad; Experiment; Environmental economics;
    All these keywords.

    JEL classification:

    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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