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Computing Business-as-Usual with a Representative Agent and a Pollution Externality

Author

Listed:
  • Nikita Lyssenko

    (Carleton University)

  • Leslie M. Shiell

    (Department of Economics, University of Ottawa)

Abstract
Computing the no-policy equilibrium (business-as-usual) in a representative-agent (RA) model is complicated by the presence of a pollution externality, since simple optimization internalizes the pollution cost. Many researchers use ad hoc methods, but there is no way to know how reliable these are. A solution is presented in which the RA model is divided into N identical components, each identified with its own agent. Agents play a dynamic game, leading to a Nash equilibrium. For sufficiently large N, this approach keeps most of the pollution cost external, and in the limit it is equivalent to a myopic-firms model, in which the entire cost is external. This approach has the advantage of theoretical consistency, and empirical applications indicate that it is easily implemented.

Suggested Citation

  • Nikita Lyssenko & Leslie M. Shiell, 2004. "Computing Business-as-Usual with a Representative Agent and a Pollution Externality," Working Papers 0409E, University of Ottawa, Department of Economics.
    • Handle: RePEc:ott:wpaper:0409e
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    References listed on IDEAS

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    Cited by:

    1. Sebastian Galiani & Sebastian Miller & Omar Chisari, 2016. "Optimal Climate Change Adaptation and Mitigation Expenditures in Environmentally Small Economies," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Fall 2016), pages 65-94, October.
    2. Armon Rezai & Frederick Van Der Ploeg, 2017. "Abandoning Fossil Fuel: How Fast and How Much," Manchester School, University of Manchester, vol. 85(S2), pages 16-44, December.
    3. Shiell, Leslie & Lyssenko, Nikita, 2014. "Climate policy and induced R&D: How great is the effect?," Energy Economics, Elsevier, vol. 46(C), pages 279-294.
    4. Radulescu, Doina & Stimmelmayr, Michael, 2010. "The impact of the 2008 German corporate tax reform: A dynamic CGE analysis," Economic Modelling, Elsevier, vol. 27(1), pages 454-467, January.
    5. Omar Chisari & Sebastian Galiani & Sebastian Miller, 2013. "Optimal Adaptation and Mitigation to Climate Change in Small Environmental Economies," Research Department Publications IDB-WP-417, Inter-American Development Bank, Research Department.
    6. Armon Rezai & Frederick van der Ploeg & Cees Withagen, 2020. "Economic growth and the social cost of carbon: additive versus multiplicative damages," Chapters, in: Graciela Chichilnisky & Armon Rezai (ed.), Handbook on the Economics of Climate Change, chapter 9, pages 199-223, Edward Elgar Publishing.
    7. Armon Rezai & Frederick van der Ploeg & Cees Withagen, 2012. "The Optimal Carbon Tax and Economic Growth: Additive versus Multiplicative Damages," CEEES Paper Series CE3S-05/12, European University at St. Petersburg, Department of Economics.
    8. Anna Sophia Ciesielski, 2019. "Climate Change Expectations and Endogenous Economic Growth in the DICE Model," CESifo Working Paper Series 7761, CESifo.
    9. Yunchan Zhu & Shuo Han & Yimeng Zhang & Qi Huang, 2021. "Evaluating the Effect of Government Emission Reduction Policy: Evidence from Demonstration Cities in China," IJERPH, MDPI, vol. 18(9), pages 1-16, April.
    10. Armon Rezai, 2011. "The Opportunity Cost of Climate Policy: A Question of Reference," Scandinavian Journal of Economics, Wiley Blackwell, vol. 113(4), pages 885-903, December.

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    More about this item

    Keywords

    representative agent; externality; pollution;
    All these keywords.

    JEL classification:

    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

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