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Green Technology Adoption under Uncertainty, Increasing Returns, and Complex Adaptive Dynamics

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  • Sanjit Dhami
  • Paolo Zeppini

Abstract

We consider firms’ choices between a clean technology that benefits, and a dirty technology that harms, the environment. Green firms are more suited to the clean, and brown firms are more suited to the dirty technology. We use a model derived from complexity theory that takes account of true uncertainty and increasing returns to technology adoption. We examine theoretically, the properties of the long-run equilibrium, and provide simulated time paths of technology adoption, using plausible dynamics. The long-run outcome is an ‘emergent property’ of the system, and it unpredictable despite there being no external technological or preference shocks. We describe the role of taxes and subsidies in facilitating adoption of the clean technology; the conflict between optimal Pigouvian taxes and adoption of clean technologies; the optimal temporal profile of subsidies; and the desirability of an international fund to provide technology assistance to poorer countries. Finally, we extend our model to stochastic dynamics in which firms experiment with technological alternatives, and demonstrate the existence of punctuated equilibria.

Suggested Citation

  • Sanjit Dhami & Paolo Zeppini, 2024. "Green Technology Adoption under Uncertainty, Increasing Returns, and Complex Adaptive Dynamics," CESifo Working Paper Series 10900, CESifo.
  • Handle: RePEc:ces:ceswps:_10900
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    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10900.pdf
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    References listed on IDEAS

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    1. Nicholas Bloom & John Van Reenen & Heidi Williams, 2019. "A toolkit of policies to promote innovation," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 10.
    2. 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.
    3. Zeppini, Paolo, 2015. "A discrete choice model of transitions to sustainable technologies," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 187-203.
    4. 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.
    5. 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.
    6. William Nordhaus, 2019. "Climate Change: The Ultimate Challenge for Economics," American Economic Review, American Economic Association, vol. 109(6), pages 1991-2014, June.
    7. 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.
    8. 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.
    9. 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.
    10. Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
    11. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    12. 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.
    13. 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.
    14. Brian Arthur, W. & Ermoliev, Yu. M. & Kaniovski, Yu. M., 1987. "Path-dependent processes and the emergence of macro-structure," European Journal of Operational Research, Elsevier, vol. 30(3), pages 294-303, June.
    15. 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).
    16. 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.
    17. 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.
    18. Philippe Aghion & Peter Howitt, 1997. "Endogenous Growth Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262011662, December.
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    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

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