IDEAS home Printed from https://ideas.repec.org/a/spr/joevec/v23y2013i2p271-293.html
   My bibliography  Save this article

An evolutionary model of energy transitions with interactive innovation-selection dynamics

Author

Listed:
  • Karolina Safarzyńska
  • Jeroen Bergh

Abstract

We develop a stylized application of a new evolutionary model to study an energy transition in electricity production. The framework describes a population of boundedly rational electricity producers who decide each period on the allocation of profits among different energy technologies. They tend to invest in below-average cost energy technologies, while also devoting a small fraction of profits to alternative technological options and research on recombinant innovation. Energy technologies are characterized by costs falling with cumulative investments. Without the latter, new technologies have no chance to become cost competitive. We study the conditions under which a new energy technology emerges and technologies coexist. In addition, we determine which investment heuristics are optimal in the sense of minimizing the total cost of electricity production. This is motivated by the idea that, while diversity contributes to system adaptability (innovation) and resilience to unforeseen contingencies (keeping options open), a high cost will discourage investments in it. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Karolina Safarzyńska & Jeroen Bergh, 2013. "An evolutionary model of energy transitions with interactive innovation-selection dynamics," Journal of Evolutionary Economics, Springer, vol. 23(2), pages 271-293, April.
    • Handle: RePEc:spr:joevec:v:23:y:2013:i:2:p:271-293
    DOI: 10.1007/s00191-012-0298-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00191-012-0298-9
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00191-012-0298-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wood, Geoffrey & Dow, Stephen, 2011. "What lessons have been learned in reforming the Renewables Obligation? An analysis of internal and external failures in UK renewable energy policy," Energy Policy, Elsevier, vol. 39(5), pages 2228-2244, May.
    2. David M. Newbery, 2005. "Electricity liberalization in Britain: The quest for a satisfactory wholesale market design," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 43-70.
    3. Grubb, Michael & Butler, Lucy & Twomey, Paul, 2006. "Diversity and security in UK electricity generation: The influence of low-carbon objectives," Energy Policy, Elsevier, vol. 34(18), pages 4050-4062, December.
    4. Shimon Awerbuch, 2006. "Portfolio-Based Electricity Generation Planning: Policy Implications For Renewables And Energy Security," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 11(3), pages 693-710, May.
    5. Olsson, Ola & Frey, Bruno S, 2002. "Entrepreneurship as Recombinant Growth," Small Business Economics, Springer, vol. 19(2), pages 69-80, September.
    6. Canning, David, 1992. "Average behavior in learning models," Journal of Economic Theory, Elsevier, vol. 57(2), pages 442-472, August.
    7. Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
    8. Jonathan Kohler, Michael Grubb, David Popp and Ottmar Edenhofer, 2006. "The Transition to Endogenous Technical Change in Climate-Economy Models: A Technical Overview to the Innovation Modeling Comparison Project," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 17-56.
    9. Martin L. Weitzman, 1998. "Recombinant Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(2), pages 331-360.
    10. Karsten Neuhoff, 2005. "Large-Scale Deployment of Renewables for Electricity Generation," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 21(1), pages 88-110, Spring.
    11. van den Bergh, Jeroen C.J.M., 2008. "Optimal diversity: Increasing returns versus recombinant innovation," Journal of Economic Behavior & Organization, Elsevier, vol. 68(3-4), pages 565-580, December.
    12. Horst Hanusch & Andreas Pyka (ed.), 2007. "Elgar Companion to Neo-Schumpeterian Economics," Books, Edward Elgar Publishing, number 2973.
    13. Sabine Messner, 1997. "Endogenized technological learning in an energy systems model," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 291-313.
    14. Thomas, Steve, 2006. "The British Model in Britain: Failing slowly," Energy Policy, Elsevier, vol. 34(5), pages 583-600, March.
    15. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    16. Elliott, David, 1996. "Renewable energy policy in the UK: Problems and opportunities," Renewable Energy, Elsevier, vol. 9(1), pages 1308-1311.
    17. Yildizoglu, Murat, 2002. "Competing R&D Strategies in an Evolutionary Industry Model," Computational Economics, Springer;Society for Computational Economics, vol. 19(1), pages 51-65, February.
    18. Bomze Immanuel M. & Burger Reinhard, 1995. "Stability by Mutation in Evolutionary Games," Games and Economic Behavior, Elsevier, vol. 11(2), pages 146-172, November.
    19. Jacobsson, Staffan & Johnson, Anna, 2000. "The diffusion of renewable energy technology: an analytical framework and key issues for research," Energy Policy, Elsevier, vol. 28(9), pages 625-640, July.
    20. Stirling, Andy, 2010. "Multicriteria diversity analysis: A novel heuristic framework for appraising energy portfolios," Energy Policy, Elsevier, vol. 38(4), pages 1622-1634, April.
    21. Nikolaos Kouvaritakis & Antonio Soria & Stephane Isoard, 2000. "Modelling energy technology dynamics: methodology for adaptive expectations models with learning by doing and learning by searching," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 14(1/2/3/4), pages 104-115.
    22. Martin A. Nowak & Natalia L. Komarova & Partha Niyogi, 2002. "Computational and evolutionary aspects of language," Nature, Nature, vol. 417(6889), pages 611-617, June.
    23. Tsur, Yacov & Zemel, Amos, 2007. "Towards endogenous recombinant growth," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3459-3477, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Herrmann, J.K. & Savin, I., 2017. "Optimal policy identification: Insights from the German electricity market," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 71-90.
    2. Tommaso Ciarli & Karolina Safarzynska, 2020. "Sustainability and Industrial Challenge: The Hindering Role of Complexity," SPRU Working Paper Series 2020-18, SPRU - Science Policy Research Unit, University of Sussex Business School.
    3. Max Rånge & Mikael Sandberg, 2016. "Windfall gains or eco-innovation? ‘Green’ evolution in the Swedish innovation system," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 18(2), pages 229-246, April.
    4. F. Knobloch & J. -F. Mercure, 2016. "The behavioural aspect of green technology investments: a general positive model in the context of heterogeneous agents," Papers 1603.06888, arXiv.org.
    5. Frank Beckenbach & Maria Daskalakis & David Hofmann, 2018. "Agent-Based Analysis of Industrial Dynamics and Paths of Environmental Policy: The Case of Non-renewable Energy Production in Germany," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 953-994, October.
    6. Valeria Costantini & Francesco Crespi, 2013. "Public policies for a sustainable energy sector: regulation, diversity and fostering of innovation," Journal of Evolutionary Economics, Springer, vol. 23(2), pages 401-429, April.
    7. Moallemi, Enayat A. & de Haan, Fjalar J. & Webb, John M. & George, Biju A. & Aye, Lu, 2017. "Transition dynamics in state-influenced niche empowerments: Experiences from India's electricity sector," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 129-141.
    8. Wood, Aaron D. & Mason, Charles F. & Finnoff, David, 2016. "OPEC, the Seven Sisters, and oil market dominance: An evolutionary game theory and agent-based modeling approach," Journal of Economic Behavior & Organization, Elsevier, vol. 132(PB), pages 66-78.
    9. Herrmann, Johannes & Savin, Ivan, 2015. "Evolution of the electricity market in Germany: Identifying policy implications by an agent-based model," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112959, Verein für Socialpolitik / German Economic Association.
    10. Jean-François Mercure, 2015. "An age structured demographic theory of technological change," Journal of Evolutionary Economics, Springer, vol. 25(4), pages 787-820, September.
    11. Mercure, J.-F. & Pollitt, H. & Chewpreecha, U. & Salas, P. & Foley, A.M. & Holden, P.B. & Edwards, N.R., 2014. "The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sector," Energy Policy, Elsevier, vol. 73(C), pages 686-700.
    12. Bernardo, Giovanni & D'Alessandro, Simone, 2014. "Transition to sustainability? Feasible scenarios towards a low-carbon economy," MPRA Paper 53746, University Library of Munich, Germany.
    13. Castrejon-Campos, Omar & Aye, Lu & Hui, Felix Kin Peng, 2022. "Effects of learning curve models on onshore wind and solar PV cost developments in the USA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).

    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. Safarzynska, Karolina & van den Bergh, Jeroen C.J.M., 2011. "Beyond replicator dynamics: Innovation-selection dynamics and optimal diversity," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 229-245, May.
    2. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    3. Safarzyńska, Karolina & Brouwer, Roy & Hofkes, Marjan, 2013. "Evolutionary modelling of the macro-economic impacts of catastrophic flood events," Ecological Economics, Elsevier, vol. 88(C), pages 108-118.
    4. Safarzyńska, Karolina & Frenken, Koen & van den Bergh, Jeroen C.J.M., 2012. "Evolutionary theorizing and modeling of sustainability transitions," Research Policy, Elsevier, vol. 41(6), pages 1011-1024.
    5. del Río, Pablo & Bleda, Mercedes, 2012. "Comparing the innovation effects of support schemes for renewable electricity technologies: A function of innovation approach," Energy Policy, Elsevier, vol. 50(C), pages 272-282.
    6. Gillingham, Kenneth & Newell, Richard G. & Pizer, William A., 2008. "Modeling endogenous technological change for climate policy analysis," Energy Economics, Elsevier, vol. 30(6), pages 2734-2753, November.
    7. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2023. "Hindcasting to inform the development of bottom-up electricity system models: The cases of endogenous demand and technology learning," Applied Energy, Elsevier, vol. 340(C).
    8. Tooraj Jamasb & Michael Pollitt, 2005. "Deregulation and R&D in network industries: the case of the electricity industry," Working Papers EPRG 0502, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    9. Pettersson, Fredrik, 2007. "Carbon pricing and the diffusion of renewable power generation in Eastern Europe: A linear programming approach," Energy Policy, Elsevier, vol. 35(4), pages 2412-2425, April.
    10. Karsten Neuhoff, 2008. "Learning by Doing with Constrained Growth Rates: An Application to Energy Technology Policy," The Energy Journal, , vol. 29(2_suppl), pages 165-183, December.
    11. Lohwasser, Richard & Madlener, Reinhard, 2013. "Relating R&D and investment policies to CCS market diffusion through two-factor learning," Energy Policy, Elsevier, vol. 52(C), pages 439-452.
    12. Martin Kalthaus, 2020. "Knowledge recombination along the technology life cycle," Journal of Evolutionary Economics, Springer, vol. 30(3), pages 643-704, July.
    13. Loschel, Andreas, 2002. "Technological change in economic models of environmental policy: a survey," Ecological Economics, Elsevier, vol. 43(2-3), pages 105-126, December.
    14. Krysiak, Frank C., 2011. "Environmental regulation, technological diversity, and the dynamics of technological change," Journal of Economic Dynamics and Control, Elsevier, vol. 35(4), pages 528-544, April.
    15. Berglund, Christer & Soderholm, Patrik, 2006. "Modeling technical change in energy system analysis: analyzing the introduction of learning-by-doing in bottom-up energy models," Energy Policy, Elsevier, vol. 34(12), pages 1344-1356, August.
    16. van den Heuvel, Stijn T.A. & van den Bergh, Jeroen C.J.M., 2009. "Multilevel assessment of diversity, innovation and selection in the solar photovoltaic industry," Structural Change and Economic Dynamics, Elsevier, vol. 20(1), pages 50-60, March.
    17. Junginger, Martin & de Visser, Erika & Hjort-Gregersen, Kurt & Koornneef, Joris & Raven, Rob & Faaij, Andre & Turkenburg, Wim, 2006. "Technological learning in bioenergy systems," Energy Policy, Elsevier, vol. 34(18), pages 4024-4041, December.
    18. Colombelli, Alessandra & Quatraro, Francesco, 2018. "New firm formation and regional knowledge production modes: Italian evidence," Research Policy, Elsevier, vol. 47(1), pages 139-157.
    19. Lehmann, Paul & Gawel, Erik, 2013. "Why should support schemes for renewable electricity complement the EU emissions trading scheme?," Energy Policy, Elsevier, vol. 52(C), pages 597-607.
    20. Reinhard Haas & Marlene Sayer & Amela Ajanovic & Hans Auer, 2023. "Technological learning: Lessons learned on energy technologies," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(2), March.

    More about this item

    Keywords

    Bounded rationality; Energy transition; Investment theory; Learning curve; B52; L94; O32; O33; Q42; Q54;
    All these keywords.

    JEL classification:

    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

    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:spr:joevec:v:23:y:2013:i:2:p:271-293. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.