Advancing Clean Energy

Innovation Decision Science

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Energy Innovation Framework

A strategic condition framework and information system to support energy policy and innovation


We wonder…
What are the likely effects of a carbon tax, R&D subsidy, or other policy on energy innovation?

Research Question: Can we develop a better framework for public policy and innovation that usefully leverages existing economic theory?

Research Task: Characterize the competitive forces present in clean energy value chains and draw out the implications for innovation and policy.

Background: Clean energy technologies exist in markets characterized by imperfections. Known market failures include negative externalities & R&D spillovers. Imperfect competition, however, is less well understood. If it is pervasive in clean energy value chains, there are important theoretical implications for modeling the cost and quantity/quality of related technologies as firms can artificially constrain prices and/or limit product offerings. There are also implications for modeling innovation, with firms potentially having slack resources to invest in R&D, on the one hand, or to complacently not innovate, on the other hand.

Task Overview: Map clean energy value chains. Create information layers for each step. Use data to test theories, inviting collaborators to use data.

Research Team: Margaret Taylor (PI), Sydny Fujita, David Jacobowitz, Sarah Price, Hung-Chia Yang, & Jingjing Zhang

Funding Information: LDRD 2018, Advancing Clean Energy Innovation Decision Science: Activity 1

More: 
LDRD 2018: Activity 1
Energy Innovation SPARK: A curated data aggregation, research, and analysis enabling platform, which makes valuable market structure and knowledge condition information on energy value chains accessible to decision-makers, entrepreneurs, and analysts.

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