Environmental Modeling & Assessment

, Volume 17, Issue 1–2, pp 123–136 | Cite as

Mitigation Portfolio and Policy Instruments When Hedging Against Climate Policy and Technology Uncertainty

  • Enrica De CianEmail author
  • Tavoni Massimo


In this paper, we use a stochastic integrated assessment model to evaluate the effects of uncertainty about future carbon taxes and the costs of low-carbon power technologies. We assess the implications of such ambiguity on the mitigation portfolio under a variety of assumptions and evaluate the role of emission performance standards and renewable portfolios in accompanying a market-based climate policy. Results suggest that climate policy and technology uncertainties are important with varying effects on all abatement options. The effect varies with the technology, the type of uncertainty, and the level of risk. We show that carbon price uncertainty does not substantially change the level of abatement, but it does have an influence on the mitigation portfolio, reducing in particular energy R&D investments in advanced technologies. When investment costs are uncertain, investments are discouraged, especially during the early stages, but the effect is mitigated for the technologies with technological learning prospects. Overall, these insights support some level of regulation to encourage investments in coal equipped with carbon capture and storage and clean energy R&D.


Climate change Information and uncertainty Mitigation 


C73 H23 Q54 


  1. 1.
    Bahn, O., Haurie, A., & Malham, R. (2008). A stochastic control model for optimal timing of climate policies. Automatica, 44, 1545–1558.CrossRefGoogle Scholar
  2. 2.
    Baker, E., & Shittu, E. (2006). Profit maximizing R&D investment in response to a random carbon tax. Resource and Energy Economics, 28, 105–192.CrossRefGoogle Scholar
  3. 3.
    Blanford, G. J. (2009). R&D investment strategy for climate change. Energy Economics, 31(S1), S27–S36.CrossRefGoogle Scholar
  4. 4.
    Borer, M. J., & Wustenhagen, M. (2009). Which renewable energy policy is a venture capitalist' s best friend? Empirical evidence from a survey of international cleantech investors. Energy Policy, 37(12), 4997–5006.CrossRefGoogle Scholar
  5. 5.
    Bosetti, V., Carraro, C., Massetti, E., Tavoni, M. (2006). WITCH: A world induced technical change hybrid model. The Energy Journal, Special Issue. Hybrid Modeling of Energy-Environment Policies: Reconciling Bottom-up and Top-down, 13–38 (2006).Google Scholar
  6. 6.
    Bosetti, V., Carraro, C., Sgobbi, A., & Tavoni, M. (2009). Delayed action and uncertain targets. How much will climate policy cost? Climatic Change, 96(3), 299–312.CrossRefGoogle Scholar
  7. 7.
    Bosetti, V., & Tavoni, M. (2009). Uncertain R&D, backstop technology and GHGs stabilization. Energy Economics, 31, S18–S26.CrossRefGoogle Scholar
  8. 8.
    Bosetti, V., Carraro, C., Duval, R., Tavoni, M. (2010). What should we expect from innovation? A model-based assessment of the environmental and mitigation cost implications of climate-related R&D. FEEM Working Paper No. 42, Milan.Google Scholar
  9. 9.
    De Cian, E., Tavoni, M. (2010). The role of international carbon offsets in a second-best climate policy: A numerical evaluation. FEEM Working Paper, No. 33, Milan.Google Scholar
  10. 10.
    Dixit, A., & Pindyck, R. S. (1994). Investment under uncertainty. Princeton: Princeton Univ Press.Google Scholar
  11. 11.
    Ecofys (2009). Scenarios on the introduction of CO2 emission performance standards for the EU power sector.
  12. 12.
    Fisher, A. (2003). Irreversibility and catastrophic risk in climate change. In E. van Ierland, H. Weikard, & J. Wesseler (Eds.), Risk and uncertainty in environmental and resource economics. Wagenigen: Wagenigen University.Google Scholar
  13. 13.
    Fisher, A., & Narain, U. (2003). Global warming, endogenous risk, and irreversibility. Environmental and Resource Economics, 25, 395–416.CrossRefGoogle Scholar
  14. 14.
    Goulder, L. H., & Schneider, S. H. (1999). Induced technological change and the attractiveness of CO2 abatement policies. Resource and Energy Economics, 21(3–4), 211–253.CrossRefGoogle Scholar
  15. 15.
    Ha-Duong, M., Grubb, M. J., & Hourcade, J. C. (1997). Influence of socioeconomic inertia and uncertainty on optimal CO2 emission abatement. Nature, 30, 270–273.Google Scholar
  16. 16.
    Hendricks, C., Graus, W., Bergen, F. (2004). Global carbon dioxide storage potential and costs, Rijksinstituut voor Volksgezondheit en Milieu, TNO/ECOFYS.Google Scholar
  17. 17.
    Johansson, D. J. A., Persson, U. M., & Azar, C. (2008). Uncertainty and learning: Implications for the trade-off between short-lived and long-lived greenhouse gases. Climatic Change, 88(3–4).Google Scholar
  18. 18.
    Johnstone, N., Haščič, I., & Popp, D. (2010). Renewable energy policies and technological innovation: Evidence based on patent counts. Environmental and Resource Economics, 45, 133–155.CrossRefGoogle Scholar
  19. 19.
    Karp, L., & Zhang, J. (2006). Regulation with anticipated learning about environmental damages. Journal of Environmental Economics and Management, 51, 259–280.CrossRefGoogle Scholar
  20. 20.
    Keller, K., Bolker, B. M., & Bradford, D. F. (2004). Uncertain climate thresholds and optimal economic growth. Journal of Environmental Economics and Management, 48, 723–741.CrossRefGoogle Scholar
  21. 21.
    Kolstad, C. (1996). Fundamental irreversibilities in stock externalities. Journal of Public Economics, 60, 221–233.CrossRefGoogle Scholar
  22. 22.
    Kolstad, C. (1996). Learning and stock effects in environmental regulations: The case of greenhouse gas emissions. Journal of Environmental Economics and Management, 31, 1–18.CrossRefGoogle Scholar
  23. 23.
    \Kriegler, E., Lorenz, A., Schmidt, M. (2010). The effect of uncertainty about catastrophic climate damages on optimal abatement levels revisited, presented at the International Energy Workshop,!D3_Kriegler.pdf
  24. 24.
    Loulou, R., Labriet, M., & Kanudia, A. (2009). Deterministic and stochastic analysis of alternative climate targets under differentiated cooperation regimes. Energy Economics, 31(S2), S131–S143.CrossRefGoogle Scholar
  25. 25.
    Manne, A., & Richels, R. (1995). The greenhouse debate. Economic efficiency, burden sharing and hedging strategies. The Energy Journal, 16(4), 1–37.CrossRefGoogle Scholar
  26. 26.
    Massetti, E., Nicita, L. (2010). Optimal R&D investments and the cost of GHG stabilization when knowledge spills across sectors. CESifo Working Paper No 2988.Google Scholar
  27. 27.
    Nemet, G. F. (2010). Robust incentives and the design of a climate change governance regime. Energy Policy, 38(11), 7216–7225.CrossRefGoogle Scholar
  28. 28.
    Nordhaus, W. D., & Popp, D. (1997). What is the value of scientific knowledge? An application to global warming using the price model. Energy Journal, 18(1), 1–45.Google Scholar
  29. 29.
    Nordhaus, W. D. (2007). A question of balance. Cambridge: MIT Press.Google Scholar
  30. 30.
    Nordhaus, W. D. (2007). A review of the stern review on the economics of climate change. Journal of Economic Literature, 45, 686–702.CrossRefGoogle Scholar
  31. 31.
    Otto, V. M., Löschel, A., & Reilly, J. (2008). Directed technical change and differentiation of climate policy. Energy Economics, 30(6), 2855–2878.CrossRefGoogle Scholar
  32. 32.
    Pindyck, R. (1992). Investments of uncertain costs. NBER Working Paper, No.4175.Google Scholar
  33. 33.
    Pindyck, R. (2000). Irreversibilites and the timing of environmental policy. Resource and Energy Economics, 22, 233–259.CrossRefGoogle Scholar
  34. 34.
    Popp, D. (2006). R&D subsidies and climate policy: Is there a free lunch? Climatic Change, 77(3–4), 311–341.CrossRefGoogle Scholar
  35. 35.
    Rothschild, M., & Stiglitz, J. (1970). Increasing risk I: A definition. Journal of Economic Theory, 2, 225–243.CrossRefGoogle Scholar
  36. 36.
    Roughgarden, T., & Schneider, S. H. (1999). Climate change policy: Quantifying uncertainties for damages and optimal carbon taxes. Energy Policy, 27, 415–429.CrossRefGoogle Scholar
  37. 37.
    Ulph, A., & Ulph, D. (1997). Global warming, irreversibility and learning. The Economic Journal, 107, 636–650.CrossRefGoogle Scholar
  38. 38.
    Wigley, T. M. L., Richels, R., & Edmonds, J. (1996). Economic and environmental choices in the stabilization of atmospheric CO2 concentrations. Nature, 379, 240–243.CrossRefGoogle Scholar
  39. 39.
    Yohe, G., Andronova, N., & Schlesinger, M. (2004). To hedge or not against an uncertain climate future. Science, 306, 416–417.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Fondazione Eni Enrico MatteiMilanItaly
  2. 2.Princeton UniversityPrincetonUSA

Personalised recommendations