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Energy efficiency policies in an agent-based macroeconomic model

Author

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  • Marco Amendola
  • Francesco Lamperti
  • Andrea Roventini
  • Alessandro Sapio

Abstract

Improvements in energy efficiency can help facing the on-going climate and energy crises, yet the energy intensity of economic activities at the global level in recent years has decreased more slowly than it is required to achieve climate goals. Based on this premise, the paper builds a macroeconomic agent-based K+S model to study the effects of different policies on energy efficiency. In the model, energy efficiency of capital goods improves as the outcome of endogenous, bottom-up technical change. Public policies analysed range from indirect policies based on taxes, incentives, and subsidies, rooted in the traditional role of the State as fixing market failures, to direct technological policies, akin to the entrepreneurial state approach, in which a public research laboratory invests in R&D with the aim to establish a new technological paradigm on energy efficiency. Simulation results show that while most policies tested are effective in reducing energy intensity, the public research lab is extremely effective in promoting energy efficiency without deteriorating macroeconomic and public finance conditions. The superiority of the national lab policy, however, emerges on a relatively long time-horizon, highlighting the importance of governments that are patient enough to wait for the returns of that policy and the necessity to complement this strategy with more ''ready to use'' indirect measures. Additionally, results indicate that the macroeconomic rebound effect induced by most of the policies is rather small. Concerns about macroeconomic rebound effects are, therefore, most likely often overstated.

Suggested Citation

  • Marco Amendola & Francesco Lamperti & Andrea Roventini & Alessandro Sapio, 2023. "Energy efficiency policies in an agent-based macroeconomic model," LEM Papers Series 2023/20, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  • Handle: RePEc:ssa:lemwps:2023/20
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    1. Dechezlepretre, Antoine & Martin, Ralf & Mohnen, Myra, 2014. "Knowledge spillovers from clean and dirty technologies," LSE Research Online Documents on Economics 60501, London School of Economics and Political Science, LSE Library.
    2. repec:hal:spmain:info:hdl:2441/4h9cnu4n2k8tfri093jil1d739 is not listed on IDEAS
    3. Mariana Mazzucato, 2018. "Mission-oriented innovation policies: challenges and opportunities," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(5), pages 803-815.
    4. Nicholas Bloom & John Van Reenen & Heidi Williams, 2019. "A toolkit of policies to promote innovation," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 10.
    5. Giorgio Fagiolo & Andrea Roventini, 2017. "Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(1), pages 1-1.
    6. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2018. "Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model," Ecological Economics, Elsevier, vol. 150(C), pages 315-339.
    7. Guerini, Mattia & Harting, Philipp & Napoletano, Mauro, 2022. "Governance structure, technical change, and industry competition," Journal of Economic Dynamics and Control, Elsevier, vol. 135(C).
    8. Marcello Nieddu & Filippo Bertani & Linda Ponta, 2022. "The sustainability transition and the digital transformation: two challenges for agent-based macroeconomic models," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 193-226, April.
    9. G Dosi & M C Pereira & A Roventini & M E Virgillito, 2018. "Causes and consequences of hysteresis: aggregate demand, productivity, and employment," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(6), pages 1015-1044.
    10. Dani Rodrik, 2014. "Green industrial policy," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 30(3), pages 469-491.
    11. Dosi, Giovanni & Fagiolo, Giorgio & Roventini, Andrea, 2010. "Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1748-1767, September.
    12. Stern, David I., 2020. "How large is the economy-wide rebound effect?," Energy Policy, Elsevier, vol. 147(C).
    13. Karen Turner, 2013. ""Rebound" Effects from Increased Energy Efficiency: A Time to Pause and Reflect," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    14. Kenneth Gillingham & Matthew J. Kotchen & David S. Rapson & Gernot Wagner, 2013. "The rebound effect is overplayed," Nature, Nature, vol. 493(7433), pages 475-476, January.
    15. Mariana Mazzucato & Caetano C.R. Penna, 2016. "Beyond market failures: the market creating and shaping roles of state investment banks," Journal of Economic Policy Reform, Taylor and Francis Journals, vol. 19(4), pages 305-326, October.
    16. Sarah Kaplan & Keyvan Vakili, 2015. "The double-edged sword of recombination in breakthrough innovation," Strategic Management Journal, Wiley Blackwell, vol. 36(10), pages 1435-1457, October.
    17. Mariana Mazzucato, 2016. "From market fixing to market-creating: a new framework for innovation policy," Industry and Innovation, Taylor & Francis Journals, vol. 23(2), pages 140-156, February.
    18. Giovanni Dosi & Andrea Roventini & Emanuele Russo, 2021. "Public policies and the art of catching up: matching the historical evidence with a multicountry agent-based model [Catching up, forging ahead, and falling behind]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(4), pages 1011-1036.
    19. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    20. repec:hal:spmain:info:hdl:2441/hiaqa97n684boj041a440irqd is not listed on IDEAS
    21. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    22. Francesco Lamperti & Valentina Bosetti & Andrea Roventini & Massimo Tavoni, 2019. "The public costs of climate-induced financial instability," Nature Climate Change, Nature, vol. 9(11), pages 829-833, November.
    23. Voigt, Sebastian & De Cian, Enrica & Schymura, Michael & Verdolini, Elena, 2014. "Energy intensity developments in 40 major economies: Structural change or technology improvement?," Energy Economics, Elsevier, vol. 41(C), pages 47-62.
    24. Zsuzsanna Csereklyei, M. d. Mar Rubio-Varas, and David I. Stern, 2016. "Energy and Economic Growth: The Stylized Facts," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    25. Stock, James H. & Watson, Mark W., 1999. "Business cycle fluctuations in us macroeconomic time series," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 1, pages 3-64, Elsevier.
    26. Jürgen Kruse & Heike Wetzel, 2016. "Editor's Choice Energy Prices, Technological Knowledge, and Innovation in Green Energy Technologies: a Dynamic Panel Analysis of European Patent Data," CESifo Economic Studies, CESifo Group, vol. 62(3), pages 397-425.
    27. Dosi, Giovanni, 1993. "Technological paradigms and technological trajectories : A suggested interpretation of the determinants and directions of technical change," Research Policy, Elsevier, vol. 22(2), pages 102-103, April.
    28. Mulder, Peter & de Groot, Henri L.F., 2012. "Structural change and convergence of energy intensity across OECD countries, 1970–2005," Energy Economics, Elsevier, vol. 34(6), pages 1910-1921.
    29. Saunders, Harry D., 2013. "Historical evidence for energy efficiency rebound in 30 US sectors and a toolkit for rebound analysts," Technological Forecasting and Social Change, Elsevier, vol. 80(7), pages 1317-1330.
    30. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    31. Geller, Howard & Harrington, Philip & Rosenfeld, Arthur H. & Tanishima, Satoshi & Unander, Fridtjof, 2006. "Polices for increasing energy efficiency: Thirty years of experience in OECD countries," Energy Policy, Elsevier, vol. 34(5), pages 556-573, March.
    32. Glen P. Peters & Robbie M. Andrew & Josep G. Canadell & Sabine Fuss & Robert B. Jackson & Jan Ivar Korsbakken & Corinne Le Quéré & Nebojsa Nakicenovic, 2017. "Key indicators to track current progress and future ambition of the Paris Agreement," Nature Climate Change, Nature, vol. 7(2), pages 118-122, February.
    33. Mauro Napoletano & Andrea Roventini & Sandro Sapio, 2006. "Are Business Cycles All Alike? A Bandpass Filter Analysis of the Italian and US Cycles," Rivista italiana degli economisti, Società editrice il Mulino, issue 1, pages 87-118.
    34. Petrick, Sebastian, 2013. "Carbon efficiency, technology, and the role of innovation patterns: Evidence from German plant-level microdata," Kiel Working Papers 1833, Kiel Institute for the World Economy (IfW Kiel).
    35. Blake LeBaron & Leigh Tesfatsion, 2008. "Modeling Macroeconomies as Open-Ended Dynamic Systems of Interacting Agents," American Economic Review, American Economic Association, vol. 98(2), pages 246-250, May.
    36. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
    37. David I. Stern, 2017. "How accurate are energy intensity projections?," Climatic Change, Springer, vol. 143(3), pages 537-545, August.
    38. Mariana Mazzucato & Caetano C.R. Penna, 2016. "Beyond market failures: the market creating and shaping roles of state investment banks," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 19(4), pages 305-326, October.
    39. G. Marangoni & M. Tavoni & V. Bosetti & E. Borgonovo & P. Capros & O. Fricko & D. E. H. J. Gernaat & C. Guivarch & P. Havlik & D. Huppmann & N. Johnson & P. Karkatsoulis & I. Keppo & V. Krey & E. Ó Br, 2017. "Sensitivity of projected long-term CO2 emissions across the Shared Socioeconomic Pathways," Nature Climate Change, Nature, vol. 7(2), pages 113-117, February.
    40. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.
    41. Dimos, Christos & Pugh, Geoff, 2016. "The effectiveness of R&D subsidies: A meta-regression analysis of the evaluation literature," Research Policy, Elsevier, vol. 45(4), pages 797-815.
    42. Hafner, Sarah & Anger-Kraavi, Annela & Monasterolo, Irene & Jones, Aled, 2020. "Emergence of New Economics Energy Transition Models: A Review," Ecological Economics, Elsevier, vol. 177(C).
    43. Dosi, Giovanni, 1988. "Sources, Procedures, and Microeconomic Effects of Innovation," Journal of Economic Literature, American Economic Association, vol. 26(3), pages 1120-1171, September.
    44. Foray, D. & Mowery, D.C. & Nelson, R.R., 2012. "Public R&D and social challenges: What lessons from mission R&D programs?," Research Policy, Elsevier, vol. 41(10), pages 1697-1702.
    45. David Popp, 2002. "Induced Innovation and Energy Prices," American Economic Review, American Economic Association, vol. 92(1), pages 160-180, March.
    46. Giovanni Dosi, 2000. "Sources, Procedures, and Microeconomic Effects of Innovation," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 2, pages 63-114, Edward Elgar Publishing.
    47. Dosi, Giovanni & Llerena, Patrick & Labini, Mauro Sylos, 2006. "The relationships between science, technologies and their industrial exploitation: An illustration through the myths and realities of the so-called `European Paradox'," Research Policy, Elsevier, vol. 35(10), pages 1450-1464, December.
    48. Kimura, Osamu, 2010. "Public R&D and commercialization of energy-efficient technology: A case study of Japanese projects," Energy Policy, Elsevier, vol. 38(11), pages 7358-7369, November.
    49. Magnus Moglia & Aneta Podkalicka & James McGregor, 2018. "An Agent-Based Model of Residential Energy Efficiency Adoption," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(3), pages 1-3.
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    Energy efficiency policies; Sustainability; Rebound effect; Agent-based modelling.;
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