Advertisement

Environmental Modeling & Assessment

, Volume 22, Issue 4, pp 323–343 | Cite as

The Effect of Green Investments in an Agent-Based Climate-Economic Model

  • Sylvie Geisendorf
  • Christian KlippertEmail author
Article
  • 229 Downloads

Abstract

Climate-economic modeling often relies on macroeconomic integrated assessment models (IAMs) that in general try to capture how the combined system reacts to different policies. Irrespective of the specific modeling approach, IAMs suffer from two notable problems. First, although policies and emissions are dependent on individual or institutional behavior, the models are not able to account for the heterogeneity and adaptive behavior of relevant actors. Second, the models unanimously consider mitigation actions as costs instead of investments: an arguable definition, given that all other expenditures are classified as investments. Both are challenging if the long-term development of climate change and the economy shall be analyzed. This paper therefore proposes a dynamic agent-based model, based on the battle of perspectives approach (Janssen [1]; Janssen and de Vries [2]; Geisendorf [3, 4]) that details the consequences of various behavioral assumptions. Furthermore, expenditures for climate protection, e.g., the transition of the energy system to renewables, are regarded as investments in future technologies with promising growth rates and the potential to incite further growth in adjoining sectors (Jaeger et al. [5]). The paper analyzes how a different understanding of climate protection expenditures changes the system’s dynamic and, thus, the basis for climate policy decisions. The paper also demonstrates how erroneous perceptions impact on economic and climate development, underlining the importance to acknowledge heterogeneous beliefs and behavior for the success of climate policy.

Keywords

Climate change Energy policy Energy transition Green investments Agent-based modeling Learning by doing 

Notes

Acknowledgements

We are grateful for the constructive and useful advice received from participants at the WEHIA conference, the ICP workshop, and the ICYESS conference as well as from two unknown reviewers. We thank Ms. Elisabeth Nevins Caswell of Effectual Editorial Services for proofreading the text.

References

  1. 1.
    Ziervogel, G., Bithell, M., Washingoton, R., & Downing, T. (2005). Agent based social simulation: a method for assessing the impact of seasonal climate forecast applications among smallholder farmers. Agricultural Systems, 83(1), 1–26.CrossRefGoogle Scholar
  2. 2.
    Entwisle, B., Malanson, G., Rindfuss, R. R., & Walsh, S. J. (2008). An agent-based model of household dynamics and land use change. Journal of Land Use Science, 3(1), 73–93.CrossRefGoogle Scholar
  3. 3.
    Goulder, L. H., & Mathai, K. (2000). Optimal CO2 abatement in the presence of induced technological change. Journal of Environmental Economics and Management, 39(1), 1–38. doi: 10.1006/jeem.1999.1089.CrossRefGoogle Scholar
  4. 4.
    Fingleton, B., & McCombie, J. S. L. (1998). Increasing returns and economic growth: some evidence for manufacturing from the European Union regions. Oxford Economic Papers, 50, 89–105.CrossRefGoogle Scholar
  5. 5.
    Castelnuovo, E., Galeotti, M., Gambarelli, G., & Vergalli, S. (2005). Learning-by-doing vs. learning by researching in a model of climate change policy analysis. Ecological Economics, 54, 261–276. doi: 10.1016/j.ecolecon.2004.12.036.CrossRefGoogle Scholar
  6. 6.
    Ackermann, F., DeCanio, S. J., Howarth, R. B., & Sheeran, K. (2009). Limitations of integrated assessment models of climate change. Climatic Change, 95, 297–315. doi: 10.1007/s10584-009-9570-x.CrossRefGoogle Scholar
  7. 7.
    Dowlatabadi, H. (1995). Integrated assessment models of climate change. An incomplete overview. Energy Policy, 23(4/5), 289–296.CrossRefGoogle Scholar
  8. 8.
    Hof, A. F., Hope, C. W., Lowe, J., Mastrandrea, M. D., Meinshausen, M., & van Vuuren, D. P. (2012). The benefits of climate change mitigation in integrated assessment models. The role of the carbon cycle and climate component. Climatic Change, 113, 897–917. doi: 10.1007/s10584-011-0363-7.CrossRefGoogle Scholar
  9. 9.
    Parson, E. A., & Fischer-Vanden, K. (1999). Integrated assessment models of global climate change. Annual Review of Energy and the Environment, 22, 589–628.CrossRefGoogle Scholar
  10. 10.
    van Vuuren, D. P., Lowe, J., Stehfest, E., Gohar, L., Hof, A., & Hope, C. (2011). How well do integrated assessment models simulate climate change? Climatic Change, 104, 255–285. doi: 10.1007/s10584-009-9764-2.CrossRefGoogle Scholar
  11. 11.
    Bachner, G., Bednar-Friedl, B., Nabernegg, S., & Steininger, K. W. (2015). Maroeconomic evaluation of climate change in Austria: a comparsion across impact fields and total effects. In K. W. Steininger, M. König, B. Bednar-Friedl, L. Kranzl, & F. Prettenthaler (Eds.), Economic evaluation of climate change impacts: development of a cross-sectoral framework and results for Austria (pp. 415–440). Cham: Springer.Google Scholar
  12. 12.
    Ciscar, J. C., Iglesias, A., Feyen, L., Szabó, L., Van Regemorter, D., Amleung, B., Nicholls, R., Watkiss, P., Christensen, O. B., Dankers, R., Garotte, L., Goodess, C. M., Hunt, A., Moreno, A., Richards, J., & Soria, A. (2011). Physical and economic consequences of climate change in Europe. PNAS, 108(7), 2678–2683.CrossRefGoogle Scholar
  13. 13.
    Aaheim, A., Gopalakrishnan, R., Chaturvedi, R. K., Ravindranath, N. H., Sagadevan, A. D., Sharma, N., & Wei, T. (2011). A macroeconomic analysis of adaptation to climate change impacts on forests in India. Mitigation and Adaptation Strategies for Global Change, 16, 229–245.CrossRefGoogle Scholar
  14. 14.
    Aaheim, A., Amundsen, H., Dokken, T., & Wei, T. (2012). Impacts and adaptation to climate change in European economies. Global Environmental Change, 22(4), 959–968.CrossRefGoogle Scholar
  15. 15.
    Ciscar, J. C., & Dowling, P. (2014). Integrated assessment of climate impacts and adaptation in the energy sector. Energy Economics, 46, 531–538.CrossRefGoogle Scholar
  16. 16.
    Ackermann, F., Stanton, E. A., & Bueno, R. (2013). CRED: a new model of climate and development. Ecological Economics, 85, 166–176. doi: 10.1016/j.ecolecon.2011.04.006.CrossRefGoogle Scholar
  17. 17.
    Anthoff, D., & Tol, R. S. J. (2009). The impact of climate change on the balanced growth equivalent: an application of FUND. Environmental and Resource Economics, 43(3), 351–367.CrossRefGoogle Scholar
  18. 18.
    Barker, T., Anger, A., Chewpreecha, U., & Pollitt, H. (2012). A new economics approach to modelling policies to achieve global 2020 targets for climate stabilisation. International Review of Applied Economics, 26(2), 205–221. doi: 10.1080/02692171.2011.631901.CrossRefGoogle Scholar
  19. 19.
    Hope, C. W. (2009). How deep should the deep cuts be? Optimal CO2 emissions over time under uncertainty. Climate Policy, 9, 3–8.CrossRefGoogle Scholar
  20. 20.
    Hope, C.W. (2011). The social cost of CO2 from the PAGE09 model. Economics: The Open-Access, Open-Assessment E-Journal, 39 (Special Issue).Google Scholar
  21. 21.
    Maisonnave, H., Pycroft, J., Saveyn, B., & Ciscar, J. (2012). Does climate policy make the EU economy more resilient to oil price rises? A CGE analysis. Energy Policy, 47, 172–179. doi: 10.1016/j.enpol.2012.04.053.CrossRefGoogle Scholar
  22. 22.
    Manne, A.S., Mendelsohn, R., Richels, R.G. (1994). MERGE: a model for evaluating regional and global effects of GHG reduction policies. In: Nakicenovic, N., Nordhaus, W.D., Richels, R., Toth, F.L. (Eds.), Integrative assessment of mitigation, impacts, and adaptation to climate change (pp. 143–172), CP-94-0, IIASA, Laxenburg, Austria.Google Scholar
  23. 23.
    Manne, R. S., & Richels, R. G. (2006). MERGE: an integrated assessment model for global climate change. In R. Loulou, J.-P. Waaub, & G. Zaccour (Eds.), Energy and environment (pp. 175–189). New York: Springer Science+Business Media.Google Scholar
  24. 24.
    Nordhaus, W. D. (1994). Managing the global commons: the economics of climate change. Cambridge, MA: MIT Press.Google Scholar
  25. 25.
    Nordhaus, W. D. (2008). A question of balance weighing the options on global warming policies. New Haven & London: Yale University Press.Google Scholar
  26. 26.
    Nordhaus, W., & Sztorc, P. (2013). DICE 2013R: introduction and user’s manual (2d ed.). New Haven: Yale University and the National Bureau of Economic Research.Google Scholar
  27. 27.
    Rotmans, J. (1990). IMAGE: An integrated model to assess the greenhouse effect. Ph.D. thesis, Dordrecht (Netherlands): Kluwer Academic Publishing.Google Scholar
  28. 28.
    Stern, N. (2007). The economics of climate change: the Stern review. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  29. 29.
    Wang, K., Wang, C., & Chen, J. (2009). Analysis of the economic impact of different Chinese climate policy options based on a CGE model incorporating endogenous technological change. Energy Policy, 37(8), 2930–2940. doi: 10.1016/j.enpol.2009.03.023.CrossRefGoogle Scholar
  30. 30.
    Weber, M., Barth, V., & Hasselmann, K. (2005). A multi-actor dynamic integrated assessment model (MADIAM) of induced technological change and sustainable economic growth. Ecological Economics, 54, 306–327. doi: 10.1016/j.ecolecon.2004.12.035.CrossRefGoogle Scholar
  31. 31.
    Janssen, M.A. (1996). Meeting targets: tools to support integrated assessment modelling of global change. PhD Thesis, ISBN 90–9009908-5, University of Maastricht, the Netherlands.Google Scholar
  32. 32.
    Janssen, M. A., & de Vries, B. (1998). The battle of perspectives: a multi-agent model with adaptive responses to climate change. Ecological Economics, 26, 43–65.CrossRefGoogle Scholar
  33. 33.
    Geisendorf, S. (2016). The impact of personal beliefs on climate change: the “battle of perspectives” revisited. Journal of Evolutionary Economics, 26, 551–580.CrossRefGoogle Scholar
  34. 34.
    Jaeger, C., Paroussos, L., Mangalagiu, D., Kupers, R., Mandel, A., Tàbara, D. (2011). A new growth path for Europe: generating prosperity and jobs in the low-carbon economy. Report for the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety.Google Scholar
  35. 35.
    Acemoglu, D., Aghion, P., Burzstyn, L., & Hemous, D. (2012). The environment and directed technical change. American Economic Review, 102(1), 131–166. doi: 10.1257/aer.102.1.131.CrossRefGoogle Scholar
  36. 36.
    Barker, T., & Scrieciu, S. (2010). Modelling low climate stabilization with E3MG: towards a ‘new economics’ approach to simulating energy-environment-economy system dynamics. Energy Journal, 31, 137–164.CrossRefGoogle Scholar
  37. 37.
    Fankhauser, S., & Tol, R. S. J. (2005). On climate change and economic growth. Resource Energy Economics, 27, 1–17. doi: 10.1016/j.reseneeco.2004.03.003.CrossRefGoogle Scholar
  38. 38.
    Von Borgstede, C., Andersson, M., & Johnsson, F. (2013). Public attitudes to climate change and carbon mitigation—implications for energy-associated behaviours. Energy Policy, 57, 182–193. doi: 10.1016/j.enpol.2013.01.051.CrossRefGoogle Scholar
  39. 39.
    Harrod, R. F. (1939). An essay in dynamic theory. The Economics Journal, 49(193), 14–33.CrossRefGoogle Scholar
  40. 40.
    Solow, R. M. (1956). A contribution to the theory of economic growth. Quarterly Journal of Economics, 70(1), 65–94.CrossRefGoogle Scholar
  41. 41.
    Kupers, R., Mangalagiu, D. (2010). Climate change policy: positive or negative economic impact? Why? ECF Working Paper, 1/2010.Google Scholar
  42. 42.
    Gerlagh, R., & van der Zwaan, B. (2003). Gross world product and consumption in a global warming model with endogenous technological change. Resource and Energy Economics, 25, 35–57.CrossRefGoogle Scholar
  43. 43.
    Manne, A., & Richels, R. (2004). The impact of learning-by-doing on the timing and costs of CO2 abatement. Energy Economics, 26, 603–619. doi: 10.1016/j.eneco.2004.04.033.CrossRefGoogle Scholar
  44. 44.
    Fischer, C., Toman, M., Withagen, C. (2002). Optimal investment in clean production capacity. Discussion Paper. Resources for the future, 02–38, available at http://www.rff.org.
  45. 45.
    Rozenberg, J., Vogt-Schilb, A., Hallegatte, S. (2013). How capital-based instruments facilitate the transition toward a low-carbon economy: a tradeoff between optimality and acceptability. World Bank Policy Research, 6609.Google Scholar
  46. 46.
    Simon, H. A. (1997). Models of bounded rationality. Cambridge and Mass: The MIT Press.Google Scholar
  47. 47.
    Tversky, A., & Kahneman, D. (1974). Judgement under uncertainty: heuristics and biases. Science, 158(4157), 1124–1131.CrossRefGoogle Scholar
  48. 48.
    Eurobarometer. (2008). Europeans attitudes towards climate change. European Commission, special Eurobarometer, 300.Google Scholar
  49. 49.
    Eurobarometer. (2009). Europeans attitudes towards climate change. European Commission, special Eurobarometer, 313.Google Scholar
  50. 50.
    Eurobarometer. (2011). Climate change. European Commission, special Eurobarometer, 372.Google Scholar
  51. 51.
    Rotmans, J. (1998). Methods for IA: the challenges and opportunities ahead. Environmental Modeling & Assessment, 3, 155–179.CrossRefGoogle Scholar
  52. 52.
    Patt, A., & Siebenhüner, B. (2005). Agent-based modeling and adaptation to climate change. Vierteljahrshefte zur Wirtschaftsforschung, 74, 310–320.CrossRefGoogle Scholar
  53. 53.
    Van den Bergh, J. C. J. M. (2007). Evolutionary thinking in environmental economics. Journal of Evolutionary Economics, 17, 521–549.CrossRefGoogle Scholar
  54. 54.
    Balbi, S., & Giupponi, C. (2010). Agent-based modelling of socio-ecosystems: a methodology for the analysis of climate change adaptation and sustainability. International Journal of Agent Technologies and Systems, 2(4), 17–38.CrossRefGoogle Scholar
  55. 55.
    An, L. (2011). Modeling human decisions in coupled human and natural systems: review of agent-based models. Ecological Modelling, 229, 25–36.CrossRefGoogle Scholar
  56. 56.
    Gsottbauer, E., & van den Bergh, J. C. J. M. (2013). Bounded rationality and social interaction in negotiating a climate agreement. International Environmental Agreements: Politics, Law and Economics, 13(3), 225–249.CrossRefGoogle Scholar
  57. 57.
    Miller, B. W., & Morisette, J. T. (2014). Integrating research tools to support the management of social-ecological systems under climate change. Ecology and Society, 19(3), 41.CrossRefGoogle Scholar
  58. 58.
    Natarajan, S., Padget, J., & Elliott, L. (2011). Modelling UK domestic energy and carbon emissions: an agent-based approach. Energy and Buildings, 43(10), 2602–2612.CrossRefGoogle Scholar
  59. 59.
    Aurbacher, J., Parker, P. S., Calberto Sánchez, G. A., Steinbach, J., Reinmuth, E., Ingwersen, J., & Dabbert, S. (2013). Influence of climate change on short term management of field crops—a modelling approach. Agricultural Systems, 119, 44–57.CrossRefGoogle Scholar
  60. 60.
    Golub, A., Narita, D., & Schmidt, A. G. W. (2014). Uncertainty in integrated assessment models of climate change: alternative analytical approaches. Environmental Modeling and Assessment, 19, 99–109.CrossRefGoogle Scholar
  61. 61.
    Boschetti, F. (2012). A computational model of mental model used to reason about climate change. Environmental Modeling & Assessment, 15(1).Google Scholar
  62. 62.
    UNEP FSF. (2012). Global trends in renewable energy investment 2012. Frankfurt: Frankfurt School of Finance and Bloomberg New Energy Finance.Google Scholar
  63. 63.
    Arrow, K. J. (1962). The economic implications of learning by doing. Review on Economic Studies, 29(3), 155–173.CrossRefGoogle Scholar
  64. 64.
    Meier-Reimer, E., & Hasselmann, K. (1987). Transport and storage of CO2 in the ocean—an inorganic ocean-circulation carbon cycle model. Climate Dynamics, 2, 63–90.CrossRefGoogle Scholar
  65. 65.
    IPCC (2013). Climate change 2013: the physical science basis. Working Group I contribution to the IPCC 5th assessment report—changes to the underlying scientific/technical assessment. Unpublished.Google Scholar
  66. 66.
    Hammitt, J. K., Lempert, R. J., & Schlesinger, M. E. (1992). A sequential-decision strategy for abating climate change. Nature, 357, 315–318.CrossRefGoogle Scholar
  67. 67.
    IPCC (2007). Climate change 2007. Synthesis report. Contribution of Working Groups I, II and III to the fourth assessment report of the Intergovernmental Panel on Climate Change (Core writing team: Pachauri, R.K. and Reisinger, A.), IPCC, Geneva, Switzerland.Google Scholar
  68. 68.
    Holland, J. H., & Miller, J. H. (1991). Artificial adaptive agents in economic theory. American Economic Review, 81, 365–370.Google Scholar
  69. 69.
    Geisendorf, S. (2011). Internal selection and market selection in economic genetic algorithms. Journal of Evolutionary Economics, 21(5), 817–841.CrossRefGoogle Scholar
  70. 70.
    Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning. Reading: Addison-Wesley.Google Scholar
  71. 71.
    Mitchell, M. (1997). An introduction to genetic algorithms (3rd ed.). Cambridge: MIT Press.Google Scholar
  72. 72.
    Asici, A. A., Aghion, A., & Bünül, Z. (2012). Green new deal: a green way out of the crisis? Environmental Policy & Governance, 22, 295–306. doi: 10.1002/eet.1594.CrossRefGoogle Scholar
  73. 73.
    Barbier, E. B. (2010). Global governance: the G20 and a global green new deal. Economics: The Open-Access, Open-Assessment E-Journal, 4(2), 1–35. doi: 10.5018/economics-ejournal.ja.2010-2.Google Scholar
  74. 74.
    Barbier, E. B. (2011). Linking green stimulus, energy efficiency and technological innovation: the need for complementary policies. Berkeley: Conference Paper.Google Scholar
  75. 75.
    Bowen, A., Fankhauser, S., Stern, N., Zenghelis, D. (2009). An outline of the case for a ‘green’ stimulus. In: Grantham Research Institute on Climate Change and the Environment, Centre for Climate Change Economics and Policy (eds.), Policy Brief February 2009.Google Scholar
  76. 76.
    Jänicke, M. (2012). “Green growth”: from a growing eco-industry to economic sustainability. Energy Policy, 48, 13–21. doi: 10.1016/j.enpol.2012.04.045.CrossRefGoogle Scholar
  77. 77.
    Jochem, E., & Jaeger, C. (2008). Investments for a climate-friendly Germany. Potsdam: BMU http://www.bmu.de/en/service/publications/downloads/details/artikel/investments-for-a-climate-friendly-germany/?tx_ttnews[backPid]=196 (accessed.Google Scholar
  78. 78.
    Oikonomou, V., Patel, M., & Worrell, E. (2006). Climate policy: bucket or drainer? Energy Policy, 34(18), 3656–3668. doi: 10.1016/j.enpol.2005.08.012.CrossRefGoogle Scholar
  79. 79.
    Romer, P. M. (1986). Increasing returns and long-run growth. Journal of Political Economics, 94(5), 1002–1037.CrossRefGoogle Scholar
  80. 80.
    World Bank (2013). Dataset of total final consumption. Available at www.data.worldbank.org (accessed 25.11.2013).
  81. 81.
    IMF (2013). World economic outlook database, April 2013. Available at http://www.imf.org/external/data.htm (accessed 25.11.2013).
  82. 82.
    IEA. (2008). Energy technology perspectives. Paris: OECD/IEA.Google Scholar
  83. 83.
    Hübler, M., Baumstark, L., Leimbach, M., Edenhofer, O., & Bauer, N. (2012). An integrated assessment model with endogenous growth. Ecological Economics, 83, 118–131. doi: 10.1016/j.ecolecon.2012.07.014.CrossRefGoogle Scholar
  84. 84.
    Kemfert, C. (2005). Induced technological change in a multi-regional, multi-sectoral, integrated assessment model (WIAGEM): impact assessment of climate policy strategies. Ecological Economics, 54, 293–305. doi: 10.1016/j.ecolecon.2004.12.031.CrossRefGoogle Scholar
  85. 85.
    Romer, P. M. (1987). Growth based on increasing returns due to specialization. American Economic Review, 77(2), 56–62.Google Scholar
  86. 86.
    Ickes, B.W. (1996). Endogenous growth models. Available at: http://econ.la.psu.edu/~bickes/endogrow.pdf (accessed 15.11.2013).
  87. 87.
    NOAA National Centers for Environmental Information, State of the Climate: Global Analysis for Annual 2015, published online January 2016, retrieved on January 9, 2017 from http://www.ncdc.noaa.gov/sotc/global/201513.
  88. 88.
    Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1991). Anomalies: the endowment effect, loss aversion, and status quo bias. The Journal of Economic Perspectives, 5(1), 193–206.CrossRefGoogle Scholar
  89. 89.
    Rachlinski, J.J. (2000). The psychology of global climate change. 2000 U.Ill. L. Rev. University of Illinois Law Review, 2000(1).Google Scholar
  90. 90.
    Thaler, R. (1980). Toward a positive theory of consumer choice. Journal of Economic Behavior and Organization, 1, 39–60.CrossRefGoogle Scholar
  91. 91.
    Williams III, R. C. (2010). Setting the initial time-profile of climate policy. The Economics of Environmental Policy Phase-In. NBER Working Paper Series, 16120.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.ESCP Europe, Business School Berlin, Chair of Environment and EconomicsBerlinGermany
  2. 2.SustBusy: Business and Society—Towards a Sustainable WorldResearch Center at ESCP Europe Business School BerlinBerlinGermany
  3. 3.Competence Centre for Climate Mitigation and Adaptation (CliMA)KasselGermany

Personalised recommendations