Jing Meng: Climate change and technology innovation

Conduct a systematic comparison of probabilistic technology cost forecasts produced by expert elicitation and model-based methods

Title

Jing Meng: Climate change and technology innovation

Time

March 24, 2022

1:15PM - 2:30PM ET

Venue

Online via zoom.

About

Forecasting is essential to design efforts to address climate change. We conduct a systematic comparison of probabilistic technology cost forecasts produced by expert elicitation and model-based methods. We assess their performance by generating probabilistic cost forecasts of energy technologies rooted at various years in the past and then comparing these with observed costs in 2019. Model-based methods outperformed expert elicitations both in terms of capturing 2019 observed values and producing forecast medians that were closer to the observed values. However, all methods underestimated technological progress in almost all technologies. We also produce 2030 cost forecasts and find that elicitations generally yield narrower uncertainty ranges than model-based methods and that model-based forecasts are lower for more modular technologies.

Speaker

Bio

Dr Jing Meng is an Associate Professor at The Bartlett School of Sustainable Construction, University College London (UCL). Her research focus is climate change and air pollution policies, including theories and modelling of environmental economics, technology innovation and sustainable consumption and trade policies. Jing receives her PhD degree in Environmental Geography from Peking University. Jing also holds a bachelor’s degree in Building Environment and Energy Engineering from Huazhong University of Science and Technology. Jing is an associate editor of the Journal of Cleaner Production and a section editor of Energy and Buildings. She is also a fellow of Cambridge centre for Environment, Energy and Natural Resource Governance at the University of Cambridge.

Readings

• Meng, Jing, Rupert Way, Elena Verdolini, and Laura Diaz Anadon. 2021. “Comparing Expert Elicitation and Model-Based Probabilistic Technology Cost Forecasts for the Energy Transition.” Proceedings of the National Academy of Sciences 118 (27). https://doi.org/10.1073/pnas.1917165118.

• Nemet, G. F. (2021). Improving the crystal ball. Nature Energy, 6(9), 860-861. https://doi.org/10.1038/s41560-021-00903-9

• Trancik, Jessika E. 2021. “Testing and Improving Technology Forecasts for Better Climate Policy.” Proceedings of the National Academy of Sciences 118 (35): e2109417118. https://doi.org/10.1073/pnas.2109417118.