Energy production, distribution, and pollution controls: Combining engineering and economic analysis to enhance efficiency and policy design

Three published articles are presented which focus on enhancing various aspects of the energy supply chain. While each paper adopts a different methodology, all three combine engineering data and/or techniques with economic analysis to improve efficiency or policy design within energy markets. The first paper combines a chemical engineering plant design model with an economic assessment of product enhancements within an ethanol production facility. While a new chemical process is shown to achieve greater ethanol yields, the animal feed by-products are denatured and decrease in value due to the degradation of a key nutritional amino acid. Overall, yield increases outweigh any costs, providing additional value to firms adopting this process. The second paper uses a mixed integer linear model to assess the optimal location of cellulosic ethanol production facilities within the state of Indiana. Desired locations with low costs are linked to regions with high yield corn growth, as these areas provide an abundance of corn stover, a by-product of corn and a cellulosic source of ethanol. The third paper implements experimental economic methods to assess the effectiveness of policies intended to control prices in emissions permit markets. When utilizing reserve permit auctions as an alternative to setting explicit maximum prices, prices are elevated beyond the theoretical predictions of the model within the conditions of the experiment. The most likely cause of higher prices is the negotiating power provided to sellers by grandfathering permits as evidenced by higher than expected welfare gains to sellers. Before presenting the articles, a discussion is introduced regarding the role of assumptions used by economists. For each article, a key assumption is highlighted and the consequences of making a different assumption are provided. Whether the consequences are large or small, the benefits of elucidating our models with assumptions based on real world behaviors are clearly demonstrated