Schenker, Oliver (2011): How uncertainty reduces greenhouse gas emissions.
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China has becoming in 2006 the world’s largest emitter of greenhouse gases (GHG), responsible for one-fifth of world’s emissions from power generation. And further strong growth in this sector is to be expected. To provide these additional power generation capacities substantial investments in China’s energy infrastructure are necessary. But the potential investors are confronted with uncertainty in the design of China’s future climate policy, which might affect the profitability of GHG emitting power plants. It is the aim of this paper to investigate the role of uncertainty in China’s climate policy on investments in the electricity sector and its consequences for GHG emissions. We analyze the topic with a stochastic dynamic computable general equilibrium model with an extended energy sector and calibrated with Chinese data. The results show that uncertainty about the timing and extent of China’s climate policy lowers emissions compared to a world with perfect information. Uncertainty lowers the present value of coal-fired electricity in pre-policy periods and has so a positive effect for the environment.
|Item Type:||MPRA Paper|
|Original Title:||How uncertainty reduces greenhouse gas emissions|
|Keywords:||China; Energy Policy; Climate Policy; Investment under Uncertainty; Stochastic and Dynamic CGE Model|
|Subjects:||O - Economic Development, Technological Change, and Growth > O4 - Economic Growth and Aggregate Productivity > O41 - One, Two, and Multisector Growth Models
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C68 - Computable General Equilibrium Models
Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics > Q4 - Energy > Q41 - Demand and Supply
D - Microeconomics > D5 - General Equilibrium and Disequilibrium > D58 - Computable and Other Applied General Equilibrium Models
D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D80 - General
|Depositing User:||Oliver Schenker|
|Date Deposited:||21. Mar 2011 12:29|
|Last Modified:||12. Feb 2013 21:31|
Arrow, K. J. (1968): “Optimal Capital Policy with Irreversible Investment,” in Value,Capital and Growth, Papers in Honour of Sir John Hicks, ed. by J. Wolfe. Edinburgh University Press.
Black, F., and M. Scholes (1973): “The pricing of options and corporate liabilities,” The journal of political economy, 81(3), 637–654.
Blyth, W., R. Bradley, D. Bunn, C. Clarke, T. Wilson, and M. Yang (2007):“Investment risks under uncertain climate change policy,” Energy policy, 35(11), 5766–5773.
Böhringer, C., and T. Rutherford (2008): “Combining bottom-up and top-down,”Energy Economics, 30(2), 574–596.
BP (2009): “BP Statistical Review of World Energy 2009,” British Petroleum.
Clarke, L., J. Edmonds, V. Krey, R. Richels, S. Rose, and M. Tavoni (2009): “International climate policy architectures: Overview of the EMF 22 International Scenarios,” Energy Economics, 31, S64–S81.
Devarajan, S., and D. Go (1998): “The simplest dynamic general-equilibrium model of an open economy,” Journal of Policy Modeling, 20(6), 677–714.
Dixit, A. (1992): “Investment and Hysteresis,” Journal of Economic Perspectives, 6(1), 107–132.
Dixit, A., and R. Pindyck (1994): Investment under Uncertainty. Princeton University Press.
Energy Information Agency (2009): International Energy Outlook 2009. Energy Information Agency.
Fuss, S., J. Szolgayova, M. Obersteiner, and M. Gusti (2008): “Investment under market and climate policy uncertainty,” Applied Energy, 85(8), 708–721.
IEA (2007): World Energy Outlook 2007. OECD, Paris.
IEA (2010): “CO2 Emissions from Fuel Combustion - Highlights 2010,” International Energy Agency.
Lau, M. I., A. Pahlke, and T. F. Rutherford (2002): “Approximating Infinite-Horizon Models in a Complementarity Format: A Primer in Dynamic General Equilibrium Analysis,” Journal of Economic Dynamics & Control, 26, 577–609.
Laurikka, H., and T. Koljonen (2006): “Emissions trading and investment decisions in the power sector – a case study in Finland,” Energy Policy, 34(9), 1063–1074.
Meeraus, A., and T. Rutherford (2005): “Mixed complementarity formulations of stochastic equilibrium models with recourse, Presentation at the GOR Workshop “Optimization under Uncertainty”, Bad Honnef, Germany (October 20-21, 2005).,”available at http://www.mpsge.org/StochasticMCP.ppt.
Merton, R. (1973): “Theory of rational option pricing,” The Bell Journal of Economics and Management Science, pp. 141–183.
National Bureau of Statistics of China (2008): Chinese Statistical Yearbook 2008.
Chinese State Statistical Publishing House, Beijing. Pati˜no-Echeverri, D., P. Fischbeck, and E. Kriegler (2009): “Economic and environmental costs of regulatory uncertainty for coal-fired power plants,” Environmental Science & Technology, 43(3), 578–584.
Peters, G., C. Weber, D. Guan, and K. Hubacek (2007): “China’s Growing CO2 Emissions - A Race between Increasing Consumption and Efficiency Gains,” Environ. Sci. Technol, 41(17), 5939–5944.
Pindyck, R. (1991): “Irreversibility, Uncertainty, and Investment,” Journal of Economic Literature, 29(3), 1110–1148.
Rutherford, T. (1995): “Extension of GAMS for complementarity problems arising in applied economic analysis,” Journal of Economic Dynamics and Control, 19(8), 1299–1324.
Uzawa, H. (1969): “Time preference and the Penrose effect in a two-class model of economic growth,” The Journal of Political Economy, 77(4), 628–652.
Zhou, W., B. Zhu, S. Fuss, J. Szolgayov´a, M. Obersteiner, and W. Fei (2010):“Uncertainty modeling of CCS investment strategy in China’s power sector,” Applied Energy, 87(7), 2392–2400.