IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_10364.html
   My bibliography  Save this paper

Green Technology Adoption, Complexity, and the Role of Public Policy: A Simple Theoretical Model

Author

Listed:
  • Sanjit Dhami

Abstract

We consider technology choices between green and brown technologies by firms. We use insights from complexity theory and also take account of true uncertainty in designing public policy. The green technology offers relatively higher returns to scale from adoption, and there are type-contingent differences among firms in their suitability for the green technology. We show that the long-run outcome is unpredictable despite there being no fundamental uncertainty in the model; small accidents of history can lead to large effects; and the final outcome is an ‘emergent property’ of the system. We describe the role of taxes and subsidies in facilitating adoption of the green technology. We also consider issues of the conflict between optimal Pigouvian taxes and green technology adoption; optimal temporal profile of subsidies; and the desirability of an international fund to provide technology assistance to poorer countries. Despite the simplicity of the framework, several novel results are demonstrated that typically do not arise in the standard analysis of the problem.

Suggested Citation

  • Sanjit Dhami, 2023. "Green Technology Adoption, Complexity, and the Role of Public Policy: A Simple Theoretical Model," CESifo Working Paper Series 10364, CESifo.
  • Handle: RePEc:ces:ceswps:_10364
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10364.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stern, Nicholas, 2022. "A time for action on climate change and a time for change in economics," LSE Research Online Documents on Economics 113456, London School of Economics and Political Science, LSE Library.
    2. Nicholas Bloom & John Van Reenen & Heidi Williams, 2019. "A toolkit of policies to promote innovation," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 10.
    3. Nordhaus, William D, 1991. "To Slow or Not to Slow: The Economics of the Greenhouse Effect," Economic Journal, Royal Economic Society, vol. 101(407), pages 920-937, July.
    4. Carlos Alós-Ferrer & Ernst Fehr & Nick Netzer, 2021. "Time Will Tell: Recovering Preferences When Choices Are Noisy," Journal of Political Economy, University of Chicago Press, vol. 129(6), pages 1828-1877.
    5. Zeppini, Paolo, 2015. "A discrete choice model of transitions to sustainable technologies," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 187-203.
    6. Young, H. Peyton, 2006. "Social Dynamics: TheorY AND Applications," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 22, pages 1081-1108, Elsevier.
    7. Hottenrott, Hanna & Rexhäuser, Sascha & Veugelers, Reinhilde, 2016. "Organisational change and the productivity effects of green technology adoption," Resource and Energy Economics, Elsevier, vol. 43(C), pages 172-194.
    8. Nicholas Stern, 2022. "A Time for Action on Climate Change and a Time for Change in Economics," The Economic Journal, Royal Economic Society, vol. 132(644), pages 1259-1289.
    9. William Nordhaus, 2019. "Climate Change: The Ultimate Challenge for Economics," American Economic Review, American Economic Association, vol. 109(6), pages 1991-2014, June.
    10. Spyros Arvanitis & Marius Ley, 2013. "Factors Determining the Adoption of Energy-Saving Technologies in Swiss Firms: An Analysis Based on Micro Data," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 54(3), pages 389-417, March.
    11. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(2), pages 235-260.
    12. Nicholas Stern & Joseph Stiglitz & Charlotte Taylor, 2022. "The economics of immense risk, urgent action and radical change: towards new approaches to the economics of climate change," Journal of Economic Methodology, Taylor & Francis Journals, vol. 29(3), pages 181-216, July.
    13. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    14. Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
    15. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    16. Martin L. Weitzman, 2009. "On Modeling and Interpreting the Economics of Catastrophic Climate Change," The Review of Economics and Statistics, MIT Press, vol. 91(1), pages 1-19, February.
    17. Stucki, Tobias, 2019. "Which firms benefit from investments in green energy technologies? – The effect of energy costs," Research Policy, Elsevier, vol. 48(3), pages 546-555.
    18. William A. Brock & Steven N. Durlauf, 2002. "A Multinomial-Choice Model of Neighborhood Effects," American Economic Review, American Economic Association, vol. 92(2), pages 298-303, May.
    19. Cars Hommes, 2021. "Behavioral and Experimental Macroeconomics and Policy Analysis: A Complex Systems Approach," Journal of Economic Literature, American Economic Association, vol. 59(1), pages 149-219, March.
    20. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    21. Philippe Aghion & Peter Howitt, 1997. "Endogenous Growth Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262011662, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sanjit Dhami & Paolo Zeppini, 2024. "Green Technology Adoption under Uncertainty, Increasing Returns, and Complex Adaptive Dynamics," CESifo Working Paper Series 10900, CESifo.
    2. Zeppini, Paolo, 2015. "A discrete choice model of transitions to sustainable technologies," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 187-203.
    3. Zeppini, Paolo & van den Bergh, Jeroen C.J.M., 2020. "Global competition dynamics of fossil fuels and renewable energy under climate policies and peak oil: A behavioural model," Energy Policy, Elsevier, vol. 136(C).
    4. 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.
    5. Robin Cowan & William Cowan & G.M. Peter Swann, 2004. "Waves in consumption with interdependence among consumers," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 37(1), pages 149-177, February.
    6. Richard S.J. Tol, 2021. "Estimates of the social cost of carbon have not changed over time," Working Paper Series 0821, Department of Economics, University of Sussex Business School.
    7. Karacuka, Mehmet & Çatık, A. Nazif & Haucap, Justus, 2013. "Consumer choice and local network effects in mobile telecommunications in Turkey," Telecommunications Policy, Elsevier, vol. 37(4), pages 334-344.
    8. Dunia López-Pintado & Duncan J. Watts, 2008. "Social Influence, Binary Decisions and Collective Dynamics," Rationality and Society, , vol. 20(4), pages 399-443, November.
    9. Michihiro, Kandori & Rob, Rafael, 1998. "Bandwagon Effects and Long Run Technology Choice," Games and Economic Behavior, Elsevier, vol. 22(1), pages 30-60, January.
    10. Bruno Jullien & Alessandro Pavan & Marc Rysman, 2021. "Two-sided markets, pricing, and network effects," Post-Print hal-03828345, HAL.
    11. Neary, Philip R., 2012. "Competing conventions," Games and Economic Behavior, Elsevier, vol. 76(1), pages 301-328.
    12. Jia-Ping Huang & Yang Zhang & Juanxi Wang, 2023. "Dynamic effects of social influence on asset prices," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 671-699, July.
    13. H. Peyton Young, 1996. "The Economics of Convention," Journal of Economic Perspectives, American Economic Association, vol. 10(2), pages 105-122, Spring.
    14. Mercure, Jean-François, 2018. "Fashion, fads and the popularity of choices: Micro-foundations for diffusion consumer theory," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 194-207.
    15. H Peyton Young, 2014. "The Evolution of Social Norms," Economics Series Working Papers 726, University of Oxford, Department of Economics.
    16. Giovanni Pegoretti & Francesco Rentocchini & Giuseppe Vittucci Marzetti, 2012. "An agent-based model of innovation diffusion: network structure and coexistence under different information regimes," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 145-165, October.
    17. Richard S. J. Tol, 2021. "Estimates of the social cost of carbon have increased over time," Papers 2105.03656, arXiv.org, revised Aug 2022.
    18. Opolot, Daniel & Azomahou, Theophile, 2012. "Learning and convergence in networks," MERIT Working Papers 2012-074, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    19. Stern, Nicholas, 2022. "A time for action on climate change and a time for change in economics," LSE Research Online Documents on Economics 113456, London School of Economics and Political Science, LSE Library.
    20. Zoë Cullen & Chiara Farronato, 2021. "Outsourcing Tasks Online: Matching Supply and Demand on Peer-to-Peer Internet Platforms," Management Science, INFORMS, vol. 67(7), pages 3985-4003, July.

    More about this item

    Keywords

    technology choice; climate change; complexity; lock-in effects; increasing returns; green subsidies; public policy; Pigouvian taxes; stochastic dynamics;
    All these keywords.

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General
    • H32 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Firm

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_10364. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.