Teaching the Complex Dynamics of Clean Energy Subsidies With the Help of a Model-as-Game

Author:

Hittinger Eric1,Miao Qing1,Williams Eric2

Affiliation:

1. 1Department of Public Policy, Rochester Institute of Technology, Rochester, NY, USA

2. 2Golisano Institute for Sustainability, Rochester Institute of Technology, Rochester, NY, USA

Abstract

The economic and policy justifications for clean energy subsidies are complex and difficult to internalize. A subsidy induces additional consumers to buy, reducing carbon emissions through reduced fossil fuel consumption. Over the long term, subsidies encourage industry investment and cost reductions. Ideally, subsidies can be removed when the technology is broadly competitive. Deciding on an appropriate level of government subsidy is complex because a decision-maker should balance government expenditures and benefits over both time and space. A subsidy can be excessive when government costs are too high and/or many consumers would have purchased the unsubsidized product, but can also be too low if insufficient to encourage adoption. In order to educate non-experts on these ideas, we created a case study about the topic, consisting of teaching materials and a cooperative multiplayer game that is playable in small groups in 15–30 min. We have used the case study in both university courses and public-facing events and believe that it would be of interest as teaching material for cost-benefit analysis, government subsidy design, clean energy policy, and science and technology policy education or training. After 15 min with the game, players have a basic understanding of all the important factors and dynamics of subsidy design. For the reader, this article offers a specific example of how to translate a sophisticated technoeconomic decision model into an educational game and includes rules and supplementary materials needed to cover the topic of subsidy design and to try the game in courses and general public settings.

Publisher

University of California Press

Subject

General Environmental Science,Renewable Energy, Sustainability and the Environment,Education

Reference9 articles.

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2. Azevedo, I., Donti, P., Horner, N., Schivley, G., Siler-Evans, K., & Vaishnav, P. (2019). Electricity marginal factors estimates. Retrieved October 30, 2019, fromhttps://cedm.shinyapps.io/MarginalFactors/

3. Heo, J., & Adams, P. J. (2015). The estimating air pollution social impact using regression (EASIUR) model. Retrieved October 30, 2019, fromhttps://barney.ce.cmu.edu/~jinhyok/easiur/

4. Hittinger, E., Williams, E., Miao, Q., Tibebu, T. (2022). How to design clean energy subsidies that work—Without wasting money on free riders. TheConversation.com. https://theconversation.com/how-to-design-clean-energy-subsidies-that-work-without-wasting-money-on-free-riders-191635

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