Science, Technology, and Public Policy

In order to make R&D funding decisions to meet particular goals, such as mitigating climate change or improving energy security, or to estimate the social returns to R&D, policy makers need to combine the information provided in this study on cost reduction potentials with an analysis of the macroeconomic implications of these technological changes. The authors conclude with recommendations for future directions on energy expert elicitations.

Harvard Kennedy School (HKS) doctoral student Daniel Velez Lopez is researching air pollution in Mexico and whether the country is willing to pay the costs to reduce it. HKS student Jennifer Kao is interviewing academics, investors, and government officials working to generate and commercialize clean energy innovations in the United Kingdom.

The Science, Technology, and Public Policy (STPP) Programis seeking a new colleague to manage, coordinate, and conduct research for a major research project. The project examines a wide range of issues focusing on innovations, climate mitigation, and sustainable energy alternatives in China, the United States, and the European Union.

Characterizing the future performance of energy technologies can improve the development of energy policies that have net benefits under a broad set of future conditions. In particular, decisions about public investments in research, development, and demonstration (RD&D) that promote technological change can benefit from (1) an explicit consideration of the uncertainty inherent in the innovation process and (2) a systematic evaluation of the tradeoffs in investment allocations across different technologies. To shed light on these questions, over the past five years several groups in the United States and Europe have conducted expert elicitations and modeled the resulting societal benefits. In this paper, the authors discuss the lessons learned from the design and implementation of these initiatives.

Characterization of the anticipated performance of energy technologies to inform policy decisions increasingly relies on expert elicitation. Knowledge about how elicitation design factors impact the probabilistic estimates emerging from these studies is, however, scarce. We focus on nuclear power, a large-scale low-carbon power option, for which future cost estimates are important for the design of energy policies and climate change mitigation efforts. We use data from three elicitations in the USA and in Europe and assess the role of government research, development, and demonstration (RD&D) investments on expected nuclear costs in 2030.

Probabilistic estimates of the cost and performance of future nuclear energy systems under different scenarios of government research, development, and demonstration (RD&D) spending were obtained from 30 U.S. and 30 European nuclear technology experts. The majority expected that such RD&D would have only a modest effect on cost, but would improve performance in other areas, such as safety, waste management, and uranium resource utilization. The U.S. and E.U. experts were in relative agreement regarding how government RD&D funds should be allocated, placing particular focus on very high temperature reactors, sodium-cooled fast reactors, fuels and materials, and fuel cycle technologies.