Here are reviewed several broad policy tools for accelerating clean energy deployment, improving efficiency, and phasing out pollution and emissions. Research and development as a clean energy deployment mechanism is discussed in more detail in elsewhere.
We estimate the following average values of building new power plants. We recommend the construction of solar PV plants, followed by onshore wind power, where feasible. Details are in our assessments of individual energy production technologies.
The benefits of new plants include possibly cheaper electricity, reduction of greenhouse gases and other pollution, and the cost reduction of similar future technology through learning-by-doing. No learning-by-doing effect for nuclear power was identified in the literature; hence the cost/benefit ratio of that technology is rather poor.
We emphasize that the values above are averages, and particular values for a given project varies considerably.
The world invested nearly two trillion dollars in energy projects in 2018 as follows.
Investment trends point to ongoing advancement of renewable energy in the power sector, but little progress in transportation or industry. The International Energy Agency 1 projects that world investment in low-carbon energy must nearly double by the late 2020s to meet their Sustainable Development Scenario, which is compatible with two degrees Celsius of global warming.
Economists generally believe that a broad carbon price should be a central component of reducing emissions 2. Following are some estimated costs of reducing emissions by several other policy tools, which may function as alternatives or supplements to carbon pricing.
The cost of a product tends to fall as more is produced. The effect, identified by Wright 4 in the context of aircraft, can be quantified and modeled. Cost reduction through production is an essential element of bringing a clean energy technology to commercial maturity. Following are observed learning rates for select technologies. The learning rate is the percent cost reduction that is observed for doubling cumulative production.
Not all of the cost decline observed for a growing technology is necessarily a result of learning curves. Some of the decline may be the result of other technological improvements that would occur regardless of how much the technology is deployed 10.
Several lines of evidence suggest that it takes about 20 years--sometimes much less and sometimes much more--for an idea to progress from scientific research to commercial technology 11, 12, 13, 14.
International agreements, such as the United Nations Framework Convention on Climate Change, Kyoto Protocol, and Paris Agreement, can help reduce emissions, but only if followed by additional policy tools. Evidence from the Kyoto Protocol is weak but suggests that it has resulted in modest emissions reductions.
These values may be offset by the self-selection problem--that countries may have adopted targets that they would have achieved anyway 16--or the phenomenon of "exporting emissions", or importing emissions-intensive products from countries without climate change targets 15.
International Energy Agency. "World Energy Investment 2019". May 2019. ↩ ↩2
National Research Council; Policy and Global Affairs; Board on Science, Technology, and Economic Policy; Committee on the Effects of Provisions in the Internal Revenue Code on Greenhouse Gas Emissions; William D. Nordhaus, Stephen A. Merrill, and Paul T. Beaton, Editors. Effects of U.S. Tax Policy on Greenhouse Gas Emissions. The National Academies Press. 2013. ↩ ↩2
Greenstone, M., Nath, I. "Do Renewable Portfolio Standards Deliver?". Working Paper, Energy Policy Institute at the University of Chicago. May 2019. ↩
Wright, T. "Factors Affecting the Cost of Airplanes". Journal of the Aeronautical Sciences 3(4), pp. 122-128. February 1936. ↩ ↩2
Chen, X., Kotlyarevsky, A., Kumiega, A., Terry, J., Wu, B., Goldberg, S., Hoffman, E. "Small Modular Nuclear Reactors: Parametric Modeling of Integrated Reactor Vessel Manufacturing Within A Factory Environment Volume 2, Detailed Analysis". Department of Energy, Office of Nuclear Energy. August 2013. ↩
Goldie-Scot, L. "A Behind the Scenes Take on Lithium-ion Battery Prices". BloombergNEF. March 2019. ↩
Hax, A., Majluf, N. "Competitive Cost Dynamics: The Experience Curve". INFORMS Journal on Applied Analytics 12(5), pp. 50-61. October 1982. ↩
Reeves, M., Stalk, G., Scognamiglio, F. "BCG Classics Revisited: The Experience Curve". Boston Consulting Group. May 2013. ↩
Samadi, S. "The experience curve theory and its application in the field of electricity generation technologies - A literature review". Renewable and Sustainable Energy Reviews 82(3), pp. 2346-2364. February 2018. ↩
Nordhaus, W. D. "The Perils of the Learning Model for Modeling Endogenous Technological Change". The Energy Journal 35(1). January 2014. ↩
Adams, J. D. "Fundamental Stocks of Knowledge and Productivity Growth". Journal of Political Economy 98(4), pp. 673-702. August 1990. ↩
Baldos, U. L. C., Viens, F. G., Hertel, T. W., Fuglie, K. O. "R&D Spending, Knowledge Capital, and Agricultural Productivity Growth: A Bayesian Approach". American Journal of Agricultural Economics 101(1), pp. 291-310. January 2019. ↩
Clancy, M. "How long does it take to go from science to technology?". New Things Under the Sun. Agust 2021. ↩
Marx, M., Fuegi, A. "Reliance on Science by Inventors: Hybrid Extraction of In-Text Patent-to-Article Citations". NBER Working Paper No. w27987. October 2020. ↩
Aichele, R., Felbermayr, G. "Kyoto and the carbon footprint of nations". Journal of Environmental Economics and Management 63(3), pp. 336-354. May 2012. ↩ ↩2
Grunewald, N., Martínez-Zarzoso, I. "Did the Kyoto Protocol fail? An evaluation of the effect of the Kyoto Protocol on CO2 emissions". Environment and Development Economics 21(1), pp. 1-22. March 2015. ↩ ↩2
Iwata, H., Okada, K. "Greenhouse gas emissions and the role of the Kyoto Protocol". Environmental Economics and Policy Studies 16, pp. 325-342. 2014. ↩