Adoption of electricity generating technologies under long-term climate policy uncertainty
Artikel i vetenskaplig tidskrift, 2009

This paper presents a real options model where multiple options are evaluated simultaneously so that the effect of the individual options on each other is accounted for. We apply this model to the electricity sector, where we analyze three typical technologies based on fossil fuel, fossil fuel with carbon capture and renewable energy, respectively. In this way, we can analyze the transition from CO2-intensive to CO2-neutral electricity production in the face of rising and uncertain CO2 prices. In addition, such a modelling approach enables us to estimate precisely the expected value of (perfect) information, i.e. the willingness of investors and producers to pay for information about the correct CO2 price path. As can be expected, the expected value of information rises with increasing CO2 price uncertainty. In addition, the larger the price uncertainty, the larger are the cumulative CO2 emissions over the coming century. The reason for this is that the transition to less CO2-intensive technologies is increasingly postponed with rising CO2 price uncertainty. By testing different price processes (geometric Brownian motion versus jump processes with different jump frequencies), we can also make useful recommendations concerning the importance of policy predictability. We find that it is better to have climate change policies that are stable over a certain length of time and change abruptly than less abrupt but more frequently changing policies. Less frequent fluctuations reduce the expected value of information and result in smaller cumulative CO2 emissions.

Real options

Energy policy uncertainty

Expected value of information


S. Fuss

International Institute for Applied Systems Analysis, Laxenburg

Daniel Johansson

Chalmers, Energi och miljö, Fysisk resursteori

Göteborgs universitet

J. Szolgayova

Comenius University

International Institute for Applied Systems Analysis, Laxenburg

M. Obersteiner

International Institute for Applied Systems Analysis, Laxenburg

Energy Policy

1873-6777 (ISSN)

Vol. 37 733-743



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