Environmental and Resource Economics

, Volume 62, Issue 2, pp 329–357 | Cite as

A Third Wave in the Economics of Climate Change

  • J. Doyne Farmer
  • Cameron HepburnEmail author
  • Penny Mealy
  • Alexander Teytelboym


Modelling the economics of climate change is daunting. Many existing methodologies from social and physical sciences need to be deployed, and new modelling techniques and ideas still need to be developed. Existing bread-and-butter micro- and macroeconomic tools, such as the expected utility framework, market equilibrium concepts and representative agent assumptions, are far from adequate. Four key issues—along with several others—remain inadequately addressed by economic models of climate change, namely: (1) uncertainty, (2) aggregation, heterogeneity and distributional implications (3) technological change, and most of all, (4) realistic damage functions for the economic impact of the physical consequences of climate change. This paper assesses the main shortcomings of two generations of climate-energy-economic models and proposes that a new wave of models need to be developed to tackle these four challenges. This paper then examines two potential candidate approaches—dynamic stochastic general equilibrium (DSGE) models and agent-based models (ABM). The successful use of agent-based models in other areas, such as in modelling the financial system, housing markets and technological progress suggests its potential applicability to better modelling the economics of climate change.


Climate change Integrated assessment models Agent based models DSGE models Uncertainty Technological innovation Heterogeneity Damage function 


  1. Acemoglu D, Aghion P, Bursztyn L, Hemous D (2012) The environment and directed technical change. Am Econ Rev 102(1):131–166CrossRefGoogle Scholar
  2. Ackerman F, DeCanio SJ, Howarth RB, Sheeran K (2009) Limitations of integrated assessment models of climate change. Clim Change 95(3–4):297–315CrossRefGoogle Scholar
  3. Ackerman F, Stanton EA, Bueno R (2013) Epstein–Zin utility in DICE: Is risk aversion irrelevant to climate policy? Environ Resour Econ 56(1):73–84. doi: 10.1007/s10640-013-9645-z CrossRefGoogle Scholar
  4. Aghion P, Howitt P (1992) A model of growth through creative destruction. Econometrica 60(2):323–351CrossRefGoogle Scholar
  5. Aghion P, Dechezleprêtre A, Hemous D, Martin R, Van Reenen J (2014a) Carbon taxes, path dependency and directed technical change: evidence from the auto industry. J Political Econ.
  6. Aghion P, Hepburn C, Teytelboym A, Zenghelis D (2014b) Path dependence, innovation, and the economics of climate change. Centre for Climate Change Economics and Policy/Grantham Research Institute on Climate Change and the Environment Policy Paper & Contributing paper to New Climate EconomyGoogle Scholar
  7. Allais M (1953) Le comportement de l’Homme Rationnel Devant Le Risque: Critique Des Postulats et Axiomes de l’Ecole Americaine. Econometrica 21(4):503–546CrossRefGoogle Scholar
  8. Allen F, Gale D (2000) Financial contagion. J Polit Econ 108(1):1–33CrossRefGoogle Scholar
  9. Allen F, Frame DJ (2007) Call off the quest. Science 318(5850):582–583CrossRefGoogle Scholar
  10. An L (2012) Modeling human decisions in coupled human and natural systems: review of agent-based models. Ecol Model 229:25–36CrossRefGoogle Scholar
  11. Anderson PW, Arrow KJ, Pines D (eds) (1988) The economy as a complex evolving system. Addison-Wesley, Redwood CityGoogle Scholar
  12. Anderson B, Borgonovo E, Galeotti M, Roson R (2014) Uncertainty in climate change modeling: can global sensitivity analysis be of help? Risk Anal 34(2):271–293. doi: 10.1111/risa.12117 CrossRefGoogle Scholar
  13. Anthoff D, Tol RSJ (2013) The uncertainty about the social cost of carbon: a decomposition analysis using fund. Clim Change 117(3):515–530CrossRefGoogle Scholar
  14. Arent DJ, Tol RSJ, Faust E, Hella JP, Kumar S, Strzepek KM, Tóth FL, Yan D (2014) Key economic sectors and services. In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL (eds) Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 659–708Google Scholar
  15. Arthur WB (1991) Designing economic agents that act like human agents: a behavioral approach to bounded rationality. Am Econ Rev 81(2):353–359Google Scholar
  16. Arthur WB (2006) Out-of-equilibrium economics and agent-based modeling. Handbook of computational economics. Retrieved from
  17. Arthur WB (2013) Complexity economics: a different framework for economic thought. SFI Working Paper 2013-04-012Google Scholar
  18. Axtell R (1999) The emergence of firms in a population of agents: local increasing returns, unstable Nash equilibria, and power law size distributions. Brookings Institution Working PaperGoogle Scholar
  19. Axtell R (2013) Endogenous firms and their dynamics. Working paper,
  20. Axelrod R (1997) The complexity of cooperation: agent-based models of competition and collaboration. Princeton University Press, PrincetonGoogle Scholar
  21. Atkinson G, Dietz S, Helgeson J, Hepburn C, Saelen H (2009) Siblings, not triplets: social preferences for risk, inequality and time in discounting climate change. Econ E-J 2009-14Google Scholar
  22. Aymanns C, Farmer JD (2015) The dynamics of the leverage cycle. J Econ Dyn Control 50:155–179CrossRefGoogle Scholar
  23. Balbi S, Giupponi C (2009) Reviewing agent-based modelling of socio-ecosystems: a methodology for the analysis of climate change adaptation and sustainability. Available at SSRN 1457625.
  24. Baldwin E (2015) Choosing in the dark: incomplete preferences, and climate policy. MimeoGoogle Scholar
  25. Barabasi AL, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512CrossRefGoogle Scholar
  26. Batty M (2009) Urban modeling. In: International encyclopedia of human geography. Elsevier, OxfordGoogle Scholar
  27. Beinhocker ED (2006) The origin of wealth: evolution, complexity and the radical remaking of economics. Harvard Business School Press, BostonGoogle Scholar
  28. Benhabib J, Day RH (1981) Rational choice and erratic behaviour. Rev Econ Stud 48(3):459–471
  29. Benhabib J, Day RH (1982) A characterization of erratic dynamics in the overlapping generations model. J Econ Dyn Control 4(1):37–55CrossRefGoogle Scholar
  30. Benhabib J, Farmer REA (1994) Indeterminacy and increasing returns. J Econ Theory 63(1):19–41. doi: 10.1006/jeth.1994.1031 CrossRefGoogle Scholar
  31. Blanchard OJ, Summers LH (1987) Hysteresis in unemployment. Eur Econ Rev 31(1–2):288–295CrossRefGoogle Scholar
  32. Bonabeau E (2002) Agent-based modeling: methods and techniques for simulating human systems. In: Proceedings of the National Academy of Sciences of the United States of America 99(suppl. 3):7280–7287Google Scholar
  33. Bonaccorsi A, Rossi C (2003) Why open source software can succeed. Res Policy 32(7):1243–1258CrossRefGoogle Scholar
  34. Bosetti V, Carraro C, Massetti E, Tavoni M (2008) International energy R&D spillovers and the economics of greenhouse gas atmospheric stabilization. Energy Econ 30(6):2912–2929CrossRefGoogle Scholar
  35. Bosetti V, Carraro C, Massetti E, Sgobbi A, Tavoni M (2009) Optimal energy investment and R&D strategies to stabilize atmospheric greenhouse gas concentrations. Resour Energy Econ 31(2):123–137CrossRefGoogle Scholar
  36. Bousquet F, Page C (2004) Multi-agent simulations and ecosystem management: a review. Ecol Model 176(3–4):313–332. doi: 10.1016/j.ecolmodel.2004.01.011 CrossRefGoogle Scholar
  37. Brekke KA, Johansson-Stenman O (2008) The behavioural economics of climate change. Oxf Rev Econ Policy 24(2):280–297CrossRefGoogle Scholar
  38. Bretschger L, Vinogradova A (2014) Growth and mitigation policies with uncertain climate damage.
  39. Brown DG, Robinson DT (2006) Effects of heterogeneity in residential preferences on an agent-based model of urban sprawl. Ecol Soc 11(1):46Google Scholar
  40. Bryant BP, Lempert RJ (2010) Thinking inside the box: a participatory, computer-assisted approach to scenario discovery. Technol Forecast Soc Change 77(1):34–49CrossRefGoogle Scholar
  41. Burke M, Dykema J, Lobell DB, Miguel E, Satyanath S (2015) Incorporating climate uncertainty into estimates of climate change impacts. Rev Econ Stat 97(2):461–471. doi: 10.1162/REST CrossRefGoogle Scholar
  42. Burgermeister J (2007) Missing carbon mystery: case solved? Nat Rep Clim Change 3:36–37. doi: 10.1038/climate.2007.35 Google Scholar
  43. Butler MP, Reed PM, Fisher-Vanden K, Keller K, Wagener T (2014) Inaction and climate stabilization uncertainties lead to severe economic risks. Clim Change 127(3–4):463–474. doi: 10.1007/s10584-014-1283-0
  44. Caccioli F, Bouchaud JP, Farmer JD (2012) Impact-adjusted valuation and the criticality of leverage. Risk 74–77Google Scholar
  45. Cai Y, Judd KL, Lontzek TS (2012) DSICE: a dynamic stochastic integrated model of climate and economy. Working Paper No. 12-02, The Center for Robust Decision Making on Climate and Energy PolicyGoogle Scholar
  46. Cai Y, Judd KL, Lontzek TS (2013) The social cost of stochastic and irreversible climate change. NBER Working Paper No. 18704Google Scholar
  47. Cai Y, Judd KL, Lenton TM, Lontzek TS, Narita D (2015) Environmental tipping points significantly affect the cost-benefit assessment of climate policies. Proc Natl Acad Sci 201503890. doi: 10.1073/pnas.1503890112
  48. Caldara D, Fernandez-Villaverde J, Rubio-Ramirez JF, Yao W (2012) Computing DSGE models with recursive preferences and stochastic volatility. Rev Econ Dyn 15(2):188–206CrossRefGoogle Scholar
  49. Cane MA, Miguel E, Burke M, Hsiang SM, Lobell DB, Meng CK, Satyanath S (2014) Temperature and violence. Nat Clim Change 4:234–235CrossRefGoogle Scholar
  50. Canova F (2008) How Much Structure in Empirical Models? In: Mills T, Patterson K (eds) Palgrave handbook of econometrics, vol 2, Applied Econometrics. Palgrave MacmillanGoogle Scholar
  51. Canova F, Sala L (2009) Back to square one: identification issues in DSGE models. J Monet Econ 56(4):431–449Google Scholar
  52. Carbon Tracker Initiative (2013) Unburnable Carbon 2013: Wasted capital and stranded assets. Report in collaboration with the Grantham Research Institute on Climate Change and the Environment, LSE.
  53. Carrillo-Hermosilla J (2006) A policy approach to the environmental impacts of technological lock-in. Ecol Econ 58:717–742CrossRefGoogle Scholar
  54. Cass D, Shell K (1983) Do sunspots matter? J Polit Econ 91(2):193–227. doi: 10.1086/261139 CrossRefGoogle Scholar
  55. Cincotti S, Raberto M, Teglio A (2010) Credit money and macroeconomic instability in the agent-based model and simulator Eurace. Econ Open-Access Open-Assess E-J 4:2010–2026CrossRefGoogle Scholar
  56. Clarke L, Edmonds J, Krey V, Richels R, Rose S, Tavoni M (2009) International climate policy architectures: overview of the EMF 22 International Scenarios. Energy Economics 31(suppl. 2)Google Scholar
  57. Clarke L, Jiang K, Akimoto K, Babiker M, Blanford G, Fisher-Vanden K, Hourcade J-C, Krey V, Kriegler E, Löschel A, McCollum D, Paltsev S, Rose S, Shukla PR, Tavoni M, van der Zwaan BCC, van Vuuren DP (2014) Assessing transformation pathways. In: Edenhofer O, Pichs-Madruga R, Sokona Y, Farahani E, Kadner S, Seyboth K, Adler A, Baum I, Brunner S, Eickemeier P, Kriemann B, Savolainen J, Schlömer S, von Stechow C, Zwickel T, Minx JC (eds). Climate change 2014: mitigation of climate change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
  58. Cole HL, Kehoe TJ (2000) Self-fulfilling debt crises. Rev Econ Stud 67(1):91–116. doi: 10.2307/2567030 CrossRefGoogle Scholar
  59. Cooper R (1999) Coordination games: complementarities and macroeconomics. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  60. Crost B, Traeger CP (2013) Optimal climate policy: uncertainty versus Monte Carlo. Econ Lett 120(3):552–558. doi: 10.1016/j.econlet.2013.05.019 CrossRefGoogle Scholar
  61. Dawid H, Gemkow S, Harting P, Neugart M (2009) One the effects of skill upgrading in the presence of spatial labor market frictions: an agent-based analysis of spatial policy design. J Artif Soc Soc Simul 12(4):5.
  62. Day RH (1982) Irregular growth cycles. Am Econ Rev 72(3):406–414Google Scholar
  63. Day RH (1983) The emergence of chaos from classical economic growth. Q J Econ 98(2). President & Fellows of Harvard University: 201–13.
  64. Deissenberg C, van der Hoog S, Dawid H (2008) EURACE: a massively parallel agent-based model of the European economy. Appl Math Comput 204(2):541–552. doi: 10.1016/j.amc.2008.05.116 CrossRefGoogle Scholar
  65. Del Negro M, Eggertsson G, Ferrero A, Kiyotaki N (2011) The great escape? A quantitative evaluation of the fed’s liquidity facilities. Staff Report. Federal Reserve Bank of New York, 520Google Scholar
  66. Delre S, Jager W, Bijmolt T, Janssen M (2007) Targeting and timing promotional activities: an agent-based model for the takeoff of new products. J Bus Res 60(8):826–835CrossRefGoogle Scholar
  67. Desmarchelier B, Djellal F, Gallouj F (2013) Environmental policies and eco-innovations by service firms: an agent-based model. Technol Forecast Soc Change 80(7):1395–1408CrossRefGoogle Scholar
  68. Diamond PA (1982) Aggregate demand management in search equilibrium. J Polit Econ 90(5):881–894. doi: 10.1086/261099 CrossRefGoogle Scholar
  69. Diaz DB (2014) Estimating global damages from sea level rise with the coastal impact and adaption model CIAM, FEEM Note di Lavoro working paper series, originally presented at European Summer School in Resource and Environmental Economics San Servolo, Venice, Italy July 12Google Scholar
  70. Dietz S, Hepburn C (2013) Benefit-cost analysis of non-marginal climate and energy projects. Energy Econ 40:61–71CrossRefGoogle Scholar
  71. Dietz S, Stern N (2015) Endogenous growth, convexity of damages and climate risk?: how Nordhaus’ framework supports deep cuts in carbon emissions. Econ J 125(583):574–620CrossRefGoogle Scholar
  72. Ebi KL, Hallegatte S, Kram T, Arnell NW, Carter TR, Edmonds J, Zwickel T (2014) A new scenario framework for climate change research: background, process, and future directions. Clim Change 122(3):363–372. doi: 10.1007/s10584-013-0912-3 CrossRefGoogle Scholar
  73. Eboli F, Parrado R, Roson R (2010) Climate-change feedback on economic growth: explorations with a dynamic general equilibrium model. Environ Dev Econ 15(5):515–533CrossRefGoogle Scholar
  74. Embrechts P, Klüppelberg C, Mikosch T (1997) Modelling extremal events for insurance and finance. Springer, BerlinCrossRefGoogle Scholar
  75. Epstein JM (1999) Agent-based computational models and generative social science. Generative Social Science: Studies in Agent-Based Computational Modelling. Retrieved from
  76. Epstein JM (2000) Learning to be thoughtless: social norms and individual computation. Working Paper No. 6, 2000. The Brookings Institution and Santa Fe Institute, Center on Social and Economic DynamicsGoogle Scholar
  77. Epstein JM (2002) Modeling civil violence: an agent-based computational approach. Proc Natl Acad Sci USA 99(suppl. 3):7243–7250CrossRefGoogle Scholar
  78. Epstein JM (2009) Modelling to contain pandemics. Nature 460(7256):687–687. doi: 10.1038/460687a CrossRefGoogle Scholar
  79. Epstein L, Zin SE (1989) Substitution, risk aversion, and the temporal behavior of consumption and asset returns: a theoretical framework. Econometrica 57(4):937–969. doi:  10.2307/1913778
  80. Epstein L, Zin SE (1991) Substitution, risk aversion, and the temporal behavior of consumption and asset returns: an empirical analysis. J Political Econ. doi:  10.1086/261750
  81. Faber A, Valente M, Janssen P (2010) Exploring domestic micro-cogeneration in the Netherlands: an agent-based demand model for technology diffusion. Energy Policy 38(6):2763–2775CrossRefGoogle Scholar
  82. Faglio G, Roventini A (2012) Macroeconomic policy in DSGE and agent-basd models. Working Paper 2012-17, EconomixGoogle Scholar
  83. Farmer REA, Guo JT (1994) Real business cycles and the animal spirits hypothesis. J Econ Theory 63(1):42–72CrossRefGoogle Scholar
  84. Farmer JD, Foley D (2009) The economy needs agent-based modelling. Nature 460(7256):685–686. doi: 10.1038/460685a CrossRefGoogle Scholar
  85. Farmer JD, Geanakoplos J (2009) Hyperbolic discounting is rational: valuing the far future with uncertain discount rates,
  86. Farmer JD, Hepburn C (2014) Less precision, more truth: uncertainty in climate economics and macroprudential policy. Paper Prepared for Bank of England Interdisciplinary Workshop on 2 April 2014 on “The Role of Uncertainty in Central Bank Policy.”
  87. Farmer JD, Lafond F (2015) How predictable is technological progress? SSRN Working Paper 2566810Google Scholar
  88. Farmer JD, Geanakoplos J, Masoliver J, Montero M, Perello P (2014) Discounting the distant future. J Public Econ.
  89. Fukač M, Pagan A (2010) Limited information estimation and evaluation of DSGE models. J Appl Econom 25(1):55–70Google Scholar
  90. Frenken K, Izquierdo L, Zeppini P (2012) Branching innovation, recombinant innovation, and endogenous technological transitions. Environ Innov Soc Transit 4:25–35CrossRefGoogle Scholar
  91. Galí J (2009) Monetary policy, inflation, and the business cycle: an introduction to the new keynesian framework. Princeton University Press, PrincetonGoogle Scholar
  92. Galla T, Farmer JD (2013) Complex dynamics in learning complicated games. Proc Natl Acad Sci 110(4):1232–1236CrossRefGoogle Scholar
  93. Geanakoplos J, Axtell R, Farmer JD, Howitt P, Conlee B, Goldstein J, Hendrey M, Palmer N, Yang C-Y (2012) Getting at systemic risk via an agent-based model of the housing market. Am Econ Rev 102(3):53–58CrossRefGoogle Scholar
  94. Gerali A, Neri S, Sessa L, Signoretti FM (2010) Credit and banking in a DSGE model of the Euro area. J Money Credit Bank 42(6):107–141CrossRefGoogle Scholar
  95. Germann T, Kadau K, Longini I, Macken C (2006) Mitigation strategies for pandemic influenza in the United States. Proc Natl Acad Sci 103(15):5935–5940CrossRefGoogle Scholar
  96. Gerst M, Wang P, Borsuk M (2013a) Discovering plausible energy and economic futures under global change using multidimensional scenario discovery. Environ Model Softw 44:7686Google Scholar
  97. Gerst M, Wang P, Roventini A, Fagiolo G, Dosi G, Howarth R, Borsuk M (2013b) Agent-based modeling of climate policy: an introduction to the ENGAGE multi-level model framework. Environ Model Softw 44:62–75. doi: 10.1016/j.envsoft.2012.09.002 CrossRefGoogle Scholar
  98. Gilbert N, Terna P (2000) How to build and use agent-based models in social science. Mind Soc 1(1):57–72CrossRefGoogle Scholar
  99. Gillingham K, Newell RG, Pizer WA (2008) Modeling endogenous technological change for climate policy analysis. Energy Econ 30(6):2734–2753CrossRefGoogle Scholar
  100. Gintis H (2007) The dynamics of general equilibrium*. Econ J 117(523):1280–1309. doi: 10.1111/j.1468-0297.2007.02083.x CrossRefGoogle Scholar
  101. Giupponi C, Borsuk M, Vries B, Hasselmann K (2013) Innovative approaches to integrated global change modelling. Environ Model Softw 44:1–9. doi: 10.1016/j.envsoft.2013.01.013 CrossRefGoogle Scholar
  102. Golosov M, Hassler J, Krusell P, Tsyvinski A (2014) Optimal taxes on fossil fuel in general equilibrium. Econometrica 82(1):41–88CrossRefGoogle Scholar
  103. Gomez W (2014) A DSGE model with loss aversion in consumption and leisure: an explanation for business cycles asymmetries. Working Paper No. 011100Google Scholar
  104. Gowdy JM (2008) Behavioral economics and climate change policy. J Econ Behav Organ 68(3):632–644. doi: 10.1016/j.jebo.2008.06.011 CrossRefGoogle Scholar
  105. Grauwe P (2010) The scientific foundation of dynamic stochastic general equilibrium (DSGE) models. Public Choice 144(3):413–443CrossRefGoogle Scholar
  106. Grimm V (1999) Ten years of individual-based modeling in ecology: what have we learned and what could we learn in the future? Ecol Model 115:129–148CrossRefGoogle Scholar
  107. Grimm V, Railsback SF (2012) Designing, formulating, and communicating agent-based models. In: Heppenstall AJ, Crooks AT, See LM, Batty M (eds) Agent-based models of geographical systems. Springer, Netherlands, pp 361–377CrossRefGoogle Scholar
  108. Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, DeAngelis DL (2006) A standard protocol for describing individual-based and agent-based models. Ecol Model 198(1):115–126CrossRefGoogle Scholar
  109. Grimm V, Berger U, DeAngelis DL, Polhill JG, Giske J, Railsback SF (2010) The ODD protocol: a review and first update. Ecol Model 221(23):2760–2768CrossRefGoogle Scholar
  110. Groom B, Hepburn C, Koundouri P, Pearce D (2005) Declining discount rates: the long and the short of it. Environ Resour Econ 32(4):445–493. doi: 10.1007/s10640-005-4681-y CrossRefGoogle Scholar
  111. Guerrero O, Axtell R (2013) Employment growth through labor flow networks. PLoS ONE 8(5). doi:  10.1371/journal.pone.0060808
  112. Halloran M, Ferguson N, Eubank S, Longini I, Cummings D, Lewis B, Cooley P (2008) Modeling targeted layered containment of an influenza pandemic in the United States. Proc Natl Acad Sci 105(12):4639–4644. doi: 10.1073/pnas.0706849105 CrossRefGoogle Scholar
  113. Hansen AH (1939) Economic progress and declining population growth. Am Econ Rev 29(1):1–15Google Scholar
  114. Harberger AC (1959) Using the resources at hand more effectively. Am Econ Rev 49(2):134–146Google Scholar
  115. Hasselmann K, Kovalevsky D (2013) Simulating animal spirits in actor-based environmental models. Environ Model Softw 44:10–24. doi: 10.1016/j.envsoft.2012.04.007 CrossRefGoogle Scholar
  116. Hasselmann K, Jaeger C, Leipold G, Mangalagiu D, Tabara J (2013) Reframing the problem of climate change: from zero sum game to win–win solutions. RoutlegeGoogle Scholar
  117. Hassler J, Krusell P (2012) Economics and climate change: integrated assessment in a multi-region world. J Eur Econ Assoc 10(5):974–1000CrossRefGoogle Scholar
  118. Heal G, Millner A (2014) Uncertainty and decision making in climate change economics. Rev Environ Econ Policy 8(1):120–137CrossRefGoogle Scholar
  119. Heckman JJ (2001) Micro data, heterogeneity, and the evaluation of public policy: Nobel lecture. J Polit Econ 109(4):673–748. doi: 10.1086/322086 CrossRefGoogle Scholar
  120. Helgeson JF (2007) Climate ethics survey: disentangling public risk preference from inequality & time. Msc Environmental Change & Management Dissertation,
  121. Hepburn C, Stern N (2008) A new global deal on climate change. Oxf Rev Econ Policy 24:259–279. doi: 10.1093/oxrep/grn020 CrossRefGoogle Scholar
  122. Hepburn C, Koundouri P, Panopoulou E, Pantelidis T (2009) Social discounting under uncertainty: a cross-country comparison. J Environ Econ Manag 57(2):140–150. doi: 10.1016/j.jeem.2008.04.004 CrossRefGoogle Scholar
  123. Hepburn C, Duncan S, Papachristodoulou A (2010) Behavioural economics, hyperbolic discounting and environmental policy. Environ Resour Econ 46(2):189–206. doi: 10.1007/s10640-010-9354-9 CrossRefGoogle Scholar
  124. Hoel M, Karp L (2001) Taxes and quotas for a stock pollutant with multiplicative uncertainty. J Public Econ 82:91–114. doi: 10.1016/S0047-2727(00)00136-5 CrossRefGoogle Scholar
  125. Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann ArborGoogle Scholar
  126. Holland JH, Miller JH (1991) Artificial adaptive agents in economic theory. Am Econ Rev Pap Proc 81(2):365–370Google Scholar
  127. Holcombe M, Coakley S, Kiran M, Chin S, Greenough C, Worth D, Neugart M (2013) Large-scale modeling of economic systems. Complex Syst 22(2):175–191Google Scholar
  128. Holmstrom B, Tirole J (1997) Financial intermediation, loanable funds, and the real sector. Q J Econ 112(3):663–691CrossRefGoogle Scholar
  129. Hope C (2013) Critical issues for the calculation of the social cost of CO2: why the estimates from PAGE09 are higher than those from PAGE2002. Clim Change 117(3):531–543. doi: 10.1007/s10584-012-0633-z CrossRefGoogle Scholar
  130. Hope C, Anderson J, Wenman P (1993) Policy analysis of the greenhouse effect: an application of the PAGE model. Energy Policy 21(3):327–338. doi: 10.1016/0301-4215(93)90253-C CrossRefGoogle Scholar
  131. Howitt P (2012) What have central bankers learned from modern macroeconomic theory? J macroecon 34(1):11–22CrossRefGoogle Scholar
  132. Hsiang SM, Meng KC, Cane MA (2011) Civil conflicts are associated with the global climate. Nature 476:438–441. doi: 10.1038/nature10311 CrossRefGoogle Scholar
  133. Interagency Working Group on Social Cost of Carbon (2010) Social cost of carbon for regulatory impact analysis under executive order 12866. United States Government.
  134. IPCC (2001) Climate change 2001: working group III: mitigation. Cambridge University Press, CambridgeGoogle Scholar
  135. IPCC (2014) Summary for policymakers. In: Edenhofer O, Pichs-Madruga R, Sokona Y, Farahani E, Kadner S, Seyboth K, Adler A, Baum I, Brunner S, Eickemeier P, Kriemann B, Savolainen J, Schlömer S, von Stechow C, Zwickel T, Minx JC (eds) Climate change 2014: mitigation of climate change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
  136. Iyer GC, Clarke LE, Edmonds JA, Flannery BP, Hultman NE, McJeon HC, Victor DG (2015) Improved representation of investment decisions in assessments of CO2 mitigation. Nat Clim Change 5:436–440. doi: 10.1038/nclimate2553 CrossRefGoogle Scholar
  137. Janssen MA, de Vries B (1998) The battle of perspectives: a multi-agent model with adaptive responses to climate change. Ecol Econ 26(1):43–65Google Scholar
  138. Janssen MA, Ostrom E (2006) Empirically based, agent-based models. Ecol Soc 11(2):37 Retrieved from
  139. Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica, 47. The Econometric Society: 263–92Google Scholar
  140. Kelly DL, Kolstad CD (1999) Bayesian learning, growth, and pollution. J Econ Dyn Control 23:491–518CrossRefGoogle Scholar
  141. Kelly DL, Kolstad CD (2001) Solving infinite horizon growth models with an environment sector. Comput Econ 182:217–231CrossRefGoogle Scholar
  142. Kirman AP (1992) Whom or what does the representative agent represent? J Econ Perspect 6(2):117–136CrossRefGoogle Scholar
  143. Kirman AP (1997) The economy as an evolving network. J Evolut Econ 7(4):339–353Google Scholar
  144. Kirman AP (2008) Economy as a complex system. In: Durlauf SN, Blume LE (ed) The New palgrave dictionary of economics, 2nd edn. Palgrave MacmillanGoogle Scholar
  145. Kolstad C, Urama K, Broome J, Bruvoll A, Cariño Olvera M, Fullerton D, Gollier C, Hanemann WM, Hassan R, Jotzo F, Khan MR, Meyer L, Mundaca L (2014) Social, economic and ethical concepts and methods. In: Edenhofer O, Pichs-Madruga R, Sokona Y, Farahani E, Kadner S, Seyboth K, Adler A, Baum I, Brunner S, Eickemeier P, Kriemann B, Savolainen J, Schlömer S, von Stechow C, Zwickel T, Minx JC (eds) Climate change 2014: mitigation of limate change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovern- mental Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
  146. Köszegi B, Rabin M (2006) A model of reference-dependent preferences. Q J Econ 121(4):1133–1165Google Scholar
  147. Krey V, Masera O, Blanford G, Bruckner T, Cooke R, Fisher-Vanden K, Haberl H, Hertwich E, Kriegler E, Mueller D, Paltsev S, Price L, Schlömer S, Ürge-Vorsatz D, van Vuuren D, Zwickel T (2014) Annex II: metrics & methodology. In: Edenhofer O, Pichs-Madruga R, Sokona Y, Farahani E, Kadner S, Seyboth K, Adler A, Baum I, Brunner S, Eickemeier P, Kriemann B, Savolainen J, Schlömer S, von Stechow C, Zwickel T, Minx JC (eds) Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
  148. Krugman P (1991) History versus expectations. Q J Econ 106(2):651–67.
  149. Krussel P, Smith Jr AA (2009) Macroeconomics and global climate change: transition for a many-region economy. MimeoGoogle Scholar
  150. Kunreuther H, Gupta S, Bosetti V, Cooke R, Dutt V, Ha-Duong M, Held H, Llanes-Regueiro J, Patt A, Shittu E, Weber E (2014) Integrated risk and uncertainty assessment of climate change response policies. In: Edenhofer O, Pichs-Madruga R, Sokona Y, Farahani E, Kadner S, Seyboth K, Adler A, Baum I, Brunner S, Eickemeier P, Kriemann B, Savolainen J, Schlömer S, von Stechow C, Zwickel T, Minx JC (eds) Climate change 2014: mitigation of climate change. contribution of working group iii to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  151. Law AM (2009) How to build valid and credible simulation models. In: Simulation conference (WSC), Proceedings of the 2009 Winter pp 24–33. IEEEGoogle Scholar
  152. Lemoine D, Traeger C (2014) Watch your step: optimal policy in a tipping climate. Am Econ J Econ Policy 61 B:137–166. doi: 10.1257/pol.6.1.137 CrossRefGoogle Scholar
  153. Lenton TM, Held H, Kriegler E, Hall J, Lucht W, Rahmstorf S, Schellnhuber HJ (2008) Tipping elements in the earth’s climate system. Proc Natl Acad Sci USA 105:1786–1793. doi: 10.1073/pnas.0705414105 CrossRefGoogle Scholar
  154. Ligtenberg A, Bregt AK, Van Lammeren R (2001) Multi-actor-based land use modelling: spatial planning using agents. Landsc Urban Plan 56(1):21–33CrossRefGoogle Scholar
  155. Lim M, Metzler R, Bar-Yam Y (2007) Global pattern formation and ethnic/cultural violence. Science 317(5844):1540–1544. doi: 10.1126/science.1142734 CrossRefGoogle Scholar
  156. Lobell DB, Roberts MJ, Schlenker W, Braun N, Little BB, Rejesus RM, Hammer GL (2014) Greater sensitivity to drought accompanies maize yield increase in the US midwest. Science 344(6183):516–519. doi: 10.1126/science.1251423 CrossRefGoogle Scholar
  157. Lontzek TS, Cai Y, Judd KL, Lenton TM (2015) Stochastic integrated assessment of climate tipping points indicates the need for strict climate policy. Nat Clim Change 5:441–444. doi: 10.1038/nclimate2570 CrossRefGoogle Scholar
  158. Löschel A (2002) Technological change in economic models of environmental policy: a survey. Ecol Econ 43(2–3):105–126CrossRefGoogle Scholar
  159. Luderer G, Pietzcker RC, Bertram C et al (2013) Economic mitigation challenges: how further delay closes the door for achieving climate targets. Environ Res Lett 8(3):034033. doi: 10.1088/1748-9326/8/3/034033 CrossRefGoogle Scholar
  160. Ma T, Nakamori Y (2005) Agent-based modeling on technological innovation as an evolutionary process. Eur J Oper Res 166(3):741–755CrossRefGoogle Scholar
  161. Ma T, Grubler A, Nakamori Y (2009) Modeling technology adoptions for sustainable development under increasing returns, uncertainty, and heterogeneous agents. Eur J Oper Res 195(1):296–306CrossRefGoogle Scholar
  162. Macal CM, North MJ (2010) Tutorial on agent-based modelling and simulation. J Simul 4:151–162CrossRefGoogle Scholar
  163. Manne A, Mendelsohn R, Richels R (1995) MERGE: a model for evaluating regional and global effects of GHG reduction policies. Energy Policy 23(1):17–34CrossRefGoogle Scholar
  164. Maréchal K (2007) The economics of climate change and the change of climate in economics. Energy Policy 35(10):5181–5194CrossRefGoogle Scholar
  165. Martin IWR, Pindyck RS (2014) Averting catastrophes: the strange economics of scylla and charybdis. NBER Working Paper 20215Google Scholar
  166. Matsuyama K (1991) Increasing returns, industrialization, and indeterminacy of equilibrium. Q J Econ 106(2):617–650. doi: 10.2307/2937949 CrossRefGoogle Scholar
  167. Matthews R, Gilbert N, Roach A, Polhill J, Gotts N (2007) Agent-based land-use models: a review of applications. Landsc Ecol 22(10):1447–1459. doi: 10.1007/s10980-007-9135-1 CrossRefGoogle Scholar
  168. Metcalf GE, Stock J (2015) The role of integrated assessment models in climate policy: a user’s guide and assessment. Working paper,
  169. Miller JH, Page SE (2007) Complex adaptive systems: an introduction to computational models of social life. Princeton University Press, PrincetonGoogle Scholar
  170. Millner A, Simon D, Geoffrey H (2013) Scientific ambiguity and climate policy. Environ Resour Econ 55(1):21–46. doi: 10.1007/s10640-012-9612-0
  171. Moore FC, Diaz DB (2015) Temperature impacts on economic growth warrant stringent mitigation policy. Nat Clim Change. doi: 10.1038/nclimate2481
  172. Moss S, Pahl-Wostl C, Downing T (2001) Agent-based integrated assessment modelling: the example of climate change. Integr Assess 2(1):17–30. doi: 10.1023/A:1011527523183 CrossRefGoogle Scholar
  173. Nagy B, Farmer JD, Bui Q, Trancik J (2013) Statistical basis for predicting technological progress. PloS One 8(2):e52669CrossRefGoogle Scholar
  174. Nordhaus WD (1994) Managing the global commons: the economics of climate change. MIT Press, CambridgeGoogle Scholar
  175. Nordhaus WD (2010) Economic aspects of global warming in a post-Copenhagen environment. Proc Natl Acad Sci USA 107(26):11721–11726CrossRefGoogle Scholar
  176. Nordhaus WD, Yang Z (1996) A regional dynamic general-equilibrium model of alternative climate-change strategies. Am Econ Rev 86(4):741–765Google Scholar
  177. Nordhaus W, Sztorc P (2013) DICE 2013R: introduction and user’s manual.
  178. O’Donoghue T, Rabin M (1999) Doing it now or later. Am Econ Rev 89(1):103–24.
  179. Obstfeld M (1986) Rational and self-fulfilling balance-of-payments crises. Am Econ Rev 76(1):72–81. doi: 10.1126/science.151.3712.867a Google Scholar
  180. O’Neill BC, Kriegler E, Riahi K, Ebi KL, Hallegatte S, Carter TR, van VuurenDP(2014) A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Clim Change 122:387–400. doi: 10.1007/s10584-013-0905-2
  181. Paltsev S, Reilly JM, Jacoby HD, Eckaus RS, Mcfarland J, Sarofim M, Asadoorian M, Babiker M (2005) MIT joint program on the science and policy of global change (EPPA) model: version 4. Policy analysis report no. 125, p 78Google Scholar
  182. Parker D, Manson S, Janssen M, Hoffmann M, Deadman P (2003) Multi-agent systems for the simulation of land-use and land-cover change: a review. Ann Assoc Am Geogr 93(2):314–337CrossRefGoogle Scholar
  183. Peck SC, Teisberg TJ (1992) CETA: a model for carbon emissions trajectory assessment. Energy J 13(1):55–77CrossRefGoogle Scholar
  184. Pindyck RS (2013) Climate change policy: what do the models tell us? J Econ Lit 51(3):860–872CrossRefGoogle Scholar
  185. Pindyck RS (2015) The use and misuse of models for climate policy. Working paper,
  186. Pittel K (2002) Sustainability and endogenous growth. Edward Elgar PublishingGoogle Scholar
  187. Poledna S, Thurner S, Farmer JD, Geanakoplos J (2014) Leverage-induced systemic risk under Basle II and other credit risk policies. J Bank Finance 42(1):199–212CrossRefGoogle Scholar
  188. Popp D (2004) ENTICE: Endogenous Technological Change in the DICE Model ofglobal warming. J Environ Econ Manag 48(1):742–768Google Scholar
  189. Powell W (2007) Approximate dynamic programming: solving the curses of dimensionality. Wiley, New YorkCrossRefGoogle Scholar
  190. Raberto M, Teglio A, Cincotti S (2012) Debt deleveraging and business cycles/ an agent-based perspective. Econ Open-Access Open-Assess E-J 6(2012-27)Google Scholar
  191. Rabin M (1993) Incorporating fairness into game theory and economics. Am Econ Rev 83(5):1281–1302Google Scholar
  192. Rabin M (2000) Risk aversion and expected utility theory: a calibration theorem. Econometrica 68(5):1281–1292CrossRefGoogle Scholar
  193. Railsback S, Lytinen S, Jackson S (2006) Agent-based simulation platforms: review and development recommendations. Simulation 82(9):609–623CrossRefGoogle Scholar
  194. Revesz RL, Howard PH, Arrow K, Goulder LH, Kopp RE, Livermore MA, Oppenheimer M, Sterner T (2014) Global warming: improve economic models of climate change. Nature 508:173–175CrossRefGoogle Scholar
  195. Rezai A, van der Ploeg F (2014) Intergenerational inequality aversion, growth and the role of damages: Occam’s rule for theglobal carbon tax. Centre for Economic Policy Research, London.
  196. Richiardi M, Leombruni R, Saam N, Sonnessa M (2006) A common protocol for agent-based social simulation. J Artif Soc Soc Simul 9(1):15. Retrieved from
  197. Roe GH, Baker MB (2007) Why Is Climate Sensitivity so Unpredictable?Science 318(5850):629–632. doi: 10.1126/science.1144735
  198. Romer PM (1990) Endogenous technological change. J Polit Econ 98(5):71–102CrossRefGoogle Scholar
  199. Roozmand O, Ghasem-Aghaee N, Hofstede G, Nematbakhsh M, Baraani A, Verwaart T (2011) Agent-based modeling of consumer decision making process based on power distance and personality. Knowl-Based Syst 24(7):1075–1095CrossRefGoogle Scholar
  200. Sassi O, Crassous R, Hourcade JC, Gitz V, Waisman H, Guivarch C (2010) IMACLIM-R: a modelling framework to simulate sustainable development pathways. Int J Global Environ Issues 10(1–2):5–24CrossRefGoogle Scholar
  201. Schlenker W, Hanemann WM, Fisher AC (2005) Will US agriculture really benefit from global warming? Accounting for irrigation in the hedonic approach. Am Econ Rev 95(1):395–406CrossRefGoogle Scholar
  202. Schularick M, Taylor MA (2012) Credit booms gone bust: monetary policy, leverage cycles, and financial crises. Am Econ Rev 102(2):1029–1061CrossRefGoogle Scholar
  203. Schwarz N, Ernst A (2009) Agent-based modeling of the diffusion of environmental innovations: an empirical approach. Technol Forecast Soc Change 76(4):497–511CrossRefGoogle Scholar
  204. Schweizer VJ, O’Neill BC (2013) Systematic construction of global socioeconomic pathways using internally consistent element combinations. Clim Change 2014:1–15. doi: 10.1007/s10584-013-0908-z Google Scholar
  205. Shafiei E, Thorkelsson H, Ásgeirsson E, Davidsdottir B, Raberto M, Stefansson H (2012) An agent-based modeling approach to predict the evolution of market share of electric vehicles: a case study from Iceland. Technol Forecast Soc Change 79(9):1638–1653CrossRefGoogle Scholar
  206. Shleifer A (1986) Implementation cycles. J Polit Econ 94(6):1163–1190CrossRefGoogle Scholar
  207. Solow RM (1956) A contribution to the theory of economic growth. Q J Econ 70(1):65–94CrossRefGoogle Scholar
  208. Smulders S, Di Maria C (2012) The cost of environmental policy under induced technical change. CESifo working paper no. 3886. Scholar
  209. Stern N (2007) Stern review: the economics of climate change. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  210. Stern N (2013) The structure of economic modeling of the potential impacts of climate change: grafting gross underestimation of risk onto already narrow science models. J Econ Lit 51(3):838–859CrossRefGoogle Scholar
  211. Sun J, Tesfatsion L (2007) Dynamic testing of wholesale power market designs: an open-source agent-based framework. Comput Econ 30(3):291–327CrossRefGoogle Scholar
  212. Tesfatsion L (2002) Hysteresis in an evolutionary labour market with adaptive search. In: Chen SH (ed) Evolutionary computation in economics and finance. Physica-Verlag Heidelberg, New York, pp 189–210CrossRefGoogle Scholar
  213. Thurner S, Farmer JD, Geanakoplos J (2012) Leverage causes fat tails and clustered volatility. Quant Finance 12(5):695–707CrossRefGoogle Scholar
  214. Tol RSJ (1997) On the optimal control of carbon dioxide emissions: an application of fund. Environ Model Assess 2(3):151–163CrossRefGoogle Scholar
  215. Traeger CP (2014) A 4-stated DICE: quantitatively addressing uncertainty effects in climate change. Environ Resour Econ 59(1):1–37. doi: 10.1007/s10640-014-9776-x CrossRefGoogle Scholar
  216. Traeger CP (2015) Analytic integrated assessment and uncertainty. Working paper,
  217. van der Meijden G, Smulders S (2014) Carbon lock-in: the role ofexpectations. Tinbergen Institute discussion paper 14-100/VIII.
  218. Van der Mensbrugghe D (2010) The environmental impact and sustainability applied general equilibrium (ENVISAGE) model. Version 7:1Google Scholar
  219. Vivid Economics (2013) The macroeconomics of climate change. Report prepared for DEFRAGoogle Scholar
  220. Waisman H, Guivarch C, Grazi F, Hourcade JC (2012) The imaclim-R model: infrastructures, technical inertia and the costs of low carbon futures under imperfect foresight. Clim Change 114(1):101–120. doi: 10.1007/s10584-011-0387-z CrossRefGoogle Scholar
  221. Webster M, Santen N, Parpas P (2012) An approximate dynamic programming framework for modeling global climate policy under decision-dependent uncertainty. CMS 93:339–362. doi: 10.1007/s10287-012-0147-1 CrossRefGoogle Scholar
  222. Weidlich A, Veit D (2008) A critical survey of agent-based wholesale electricity market models. Energy Econ 30(4):17281759. doi: 10.1016/j.eneco.2008.01.003 CrossRefGoogle Scholar
  223. Weitzman ML (1974) Prices versus quantities. Rev Econ Stud 41(4):477–491CrossRefGoogle Scholar
  224. Weitzman ML (1998) Why the far-distant future should be discounted at its lowest possible rate? J Environ Econ Manag 36(3):201–208Google Scholar
  225. Weitzman ML (2001) Gamma discounting. Am Econ Rev 91(1):261–271CrossRefGoogle Scholar
  226. Weitzman ML (2009) On modeling and interpreting the economics of catastrophic climate change. Rev Econ Stat 91(1):1–19CrossRefGoogle Scholar
  227. Weitzman ML (2011) Fat-tailed uncertainty in the economics of catastrophic climate change. Rev Environ Econ Policy 5(2):275–292CrossRefGoogle Scholar
  228. Weitzman ML (2013) Tail-hedge discounting and the social cost of carbon. J Econ Lit 51(3):873–882CrossRefGoogle Scholar
  229. Weyant JP (2009) A perspective on integrated assessment: an editorial comment. Clim Change 95(3–4):317–323CrossRefGoogle Scholar
  230. Wolf S, Fürst S, Mandel A, Lass W, Lincke D, Pablo-Martí F, Jaeger C (2013) A multi-agent model of several economic regions. Environ Model Softw 44:25–43. doi: 10.1016/j.envsoft.2012.12.012 CrossRefGoogle Scholar
  231. Woodford M (1986) Stationary sunspot equilibria in a finance constrained economy. J Econ Theory 40(1):128–137. doi: 10.1016/0022-0531(86)90011-6 CrossRefGoogle Scholar
  232. Zhang T, Zhang D (2007) Agent-based simulation of consumer purchase decision-making and the decoy effect. J Bus Res 60(8):912–922CrossRefGoogle Scholar
  233. Zhang B, Zhang Y, Bi J (2011) An adaptive agent-based modeling approach for analyzing the influence of transaction costs on emissions trading markets. Environ Model Softw 26(4):482491. doi: 10.1016/j.envsoft.2010.10.011 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • J. Doyne Farmer
    • 1
    • 2
    • 3
  • Cameron Hepburn
    • 1
    • 4
    • 5
    Email author
  • Penny Mealy
    • 1
    • 4
  • Alexander Teytelboym
    • 1
    • 4
  1. 1.Institute for New Economic Thinking at the Oxford Martin SchoolUniversity of OxfordOxfordUK
  2. 2.Santa Fe InstituteSanta FeUSA
  3. 3.Mathematical InstituteUniversity of OxfordOxfordUK
  4. 4.Smith School of Enterprise and the EnvironmentUniversity of OxfordOxfordUK
  5. 5.Grantham Research InstituteLondon School of Economics and Political ScienceLondonUK

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