Date:
The Growth Lab's Research Seminar series is a weekly seminar that brings together researchers from across the academic spectrum who share an interest in growth and development.
Speaker: Bessie Noll, Doctoral Researcher at ETH Zürich
In this seminar, Bessie will walk through the motivation, methods, and results of her research as well expand on the question of why certain technologies learn faster than others using innovation and technology complexity theory as explanatory factors. The presentation will conclude with thoughts on how this work may impact or inform larger climate models.
Location: HYBRID W-434 A.B. HKS (Harvard Community) / Zoom
Whether attending in person or virtually, please register in advance.
About the Speaker: Bessie Noll is a Postdoctoral researcher with the Energy and Technology Policy Group (EPG) at ETH Zürich. In September 2023, she successfully defended her PhD, presenting a dissertation that aims to enhance our comprehension of how public policy can accelerate transformative change in the road transport sector towards low-carbon technologies. In particular, the thesis argues that policymakers need up-to-date, quantitative, approaches to evaluate and project dynamic technology competition and to assess prospective policy impacts on the transition.
Her current research explores two distinct areas. The first focuses on improving the representation of technological innovation in Integrated Assessment Models, looking specifically at technology complexity to understand why some technologies learn faster than others. The second focuses on the low-carbon transport transition in Africa, assessing the role of battery electric versus synthetic fuel vehicles as options for decarbonizing passenger transport.
Paper: The effects of local interventions on global technological change through spillovers: A modeling framework and application to the road- freight sector
Abstract
To address global sustainability challenges, (public) policy interventions are needed to induce or accelerate technological change. While most policy interventions occur on the local level, their innovation effects can spill over to other jurisdictions, potentially having global impact. These spillovers can increase or reduce the incentive for interventions. Lacking to date are computational models that capture these spillover dynamics. In this study, we devise a conceptual and methodological approach to quantify ex ante the effects of local demand-side interventions on global competition between incumbent and novel technologies. We apply these frameworks to the case of commercial road-freight, assessing global spillover effects due to different demand-pull interventions and shocks.
The presentation will walk through the motivation, methods, and results of this study, and as well expand on the question of why certain technologies learn faster than others using innovation and technology complexity theory as explanatory factors. The presentation will conclude with thoughts on how this work may impact or inform larger climate models.