Combining Expert Opinions to Support Decisions

1. Combining Expert Opinions to Support Decisions Hadley Patten Advisor: Professor Erin Baker University of Massachusetts Amherst Abstract As carbon emissions into the earth’s atmosphere increase, the effects of global warming become increasingly pronounced. We must look towards sustainable energy technologies, such as solar, nuclear, carbon capture and storage, bio-electricity, and biofuels, in order to decrease and stabilize emissions. While industrial advances are incremental and predictable, there is little research done on how different levels of funding could prompt a major breakthrough in the technological field. We investigate the potential of investments into these individual technologies in order to help policy makers and businesses make decisions. By aggregating expert elicitations performed by UMass, Harvard, and FEEM (Fondazione Eni Enrico Mattei), we can provide the probability of success of technologies over a large range of funding levels. These probability distributions will represent the opinions of a wide range of experts across the globe. Methodology Interpolate/Project values to encompass wide range of funding Perform expert elicitations Aggregate across experts FEEM Result: A model that outputs a distribution displaying the probability of success of achieving a range of electricity costs, given that the government funds research of bio-electricity at that specific amount. Interpolate/Project values to encompass wide range of funding Select level of funding up to $5B Perform expert elicitations Aggregate across experts Harvard Interpolate/Project values to encompass wide range of funding Aggregate across experts Perform expert elicitations UMass Pool of experts Figure 1: Graph answers the following question: Provided a certain level of funding, what is the probability of success (represented by 10th, 50th, and 90th percentiles) that certain electricity costs will be achieved? Figure 2: If $700M is allocated towards bio-electricity research, what is the probability of success of a range of electricity costs? The aggregated distribution in yellow represents the opinions of a wide range of experts across the globe. Conclusion: This model can be used as a tool for decision makers when deciding where to allocate money. $700M Figure 2: Aggregation of Distributions Bio-electricity • Future Work • Analyze data and create complementary model for biofuel, solar, CCS, and nuclear data. • Rather than using interpolations and linear projections, fit line graph to an S-curve for more realistic projections. • Write methodology and report. This work is supported in part by the National Science Foundation. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the National Science Foundation.