This dissertation examines the employment impacts of investments in renewable energy and energy efficiency in the U.S. A broad expansion of the use of renewable energy in place of carbon-based energy, in addition to investments in energy efficiency, comprise a prominent strategy to slow or reverse the effects of anthropogenic climate change. This study first explores the literature on the employment impacts of these investments. This literature to date consists mainly of input-output I-O) studies or case studies of renewable energy and energy efficiency REEE). Researchers are constrained, however, by their ability to use the I-O model to study REEE, since currently industrial codes do not recognize this industry as such. I develop and present two methods to use the I-O framework to overcome this constraint: the synthetic and integrated approaches. In the former, I proxy the REEE industry by creating a vector of final demand based on the industrial spending patterns of REEE firms as found in the secondary literature. In the integrated approach, I collect primary data through a nationwide survey of REEE firms and integrate these data into the existing I-O tables to explicitly identify the REEE industry and estimate the employment impacts resulting from both upstream and downstream linkages with other industries. The size of the REEE employment multiplier is sensitive to the choice of method, and is higher using the synthetic approach than using the integrated approach. I find that using both methods, the employment level per $1 million demand is approximately three times greater for the REEE industry than for fossil fuel FF) industries. This implies that a shift to clean energy will result in positive net employment impacts. The positive effects stem mainly from the higher labor intensity of REEE in relation to FF, as well as from higher domestic content and lower average wages. The findings suggest that as we transition away from a carbon-based energy system to more sustainable and low-carbon energy sources, approximately three jobs will be created in clean energy sectors for each job lost in the fossil fuel sector.

My dissertation focuses on the influence of politics, policies, and markets in determining oil and natural gas and wind energy development. In the first chapter, I examine the role of federal elected political influence and market factors in determining the acres of oil and natural gas leases issued on Bureau of Management BLM) lands in the western United States between 1978 and 2008. I seek to determine if the political party and ideology of the federal political environment influence the number of acres that are leased and if there is disparate federal political influence in states that have a large amount of federal lands. Using a random effects Tobit model for a 17-state sample of the westernmost states in the contiguous United States, I find that more conservative federal political influence leads to additional leasing. The results are consistent across Senate committee leaders, Senate majority leadership, and the Presidents office. The further found that the influence of politics on leasing is not stronger in states with more federal lands. In the second chapter, I analyze the influence of state and federal political party changes and market factors on state oil and natural gas permitting. My findings, using a first-differenced empirical model for two samples, a 19-state sample, from 1990–2007, and a 14-state sample, from 1977–2007, indicate that the influence of state political party changes are trumped by economic factors. Oil and gas prices are the main drivers of permitting changes, while the state political party changes for the state legislatures and Governors office are consistently not significant. In the third chapter I focus on the role of electricity markets and renewable energy regulation in wind development across the United States. My findings, using a random effects Tobit model with a 25-state sample, from 1994–2008, indicate that the implementation of state Renewables Portfolio Standards RPS), the Federal Production Tax Credit PTC), and Green Power Purchase Programs GPP) positively influence a states wind capacity. The influence of green power purchase programs continues to increase in the years after implementation, while for RPS it diminishes. The role of market factors is less significant.

This dissertation is composed of three separate essays in the field of energy economics. In the first paper, both data envelopment analysis and stochastic production frontier estimation are employed to provide empirical evidence on the revenue efficiency of national oil companies NOCs) and private international oil companies IOCs). Using a panel of 80 oil producing firms, the analysis suggests that NOCs are generally less efficient at generating revenue from a given resource base than IOCs, with some exceptions. Due to differing firm objectives, however, structural and institutional features may help explain much of the inefficiency. The second paper analyzes the relationship between economic development and the demand for energy. Energy consumption is modeled using panel data from 1990 to 2004 for 50 countries spanning all levels of development. We find the relationship between energy consumption and economic development corresponds to the structure of aggregate output and the nature of derived demand for electricity and direct-use fuels in each sector. Notably, the evidence of non-constant income elasticity of demand is much greater for electricity demand than for direct-use fuel consumption. In addition, we show that during periods of rapid economic development, one in which the short-term growth rate exceeds the long-run average, an increase in aggregate output is met by less energy-efficient capital. This is a result of capital being fixed in the short-term. As additional, more efficient capital stock is added to the production process, the short-term increase in energy intensity will diminish. In the third essay, we develop a system of equations to estimate a model of motor vehicle fuel consumption, vehicle miles traveled and implied fuel efficiency for the 67 counties of the State of Florida from 2001 to 2008. This procedure allows us to decompose the factors of fuel demand into elasticities of vehicle driving demand and fuel efficiency. Particular attention is paid to the influence of the price of fuel, the sale of goods and services, vehicle ownership and population density on each component of our model.

In a merit-order electricity pool market, generating companies Gencos) game with their offered incremental cost to meet the electricity demand and earn bigger market shares and higher profits. However when the demand is treated as a random variable instead of as a known constant, these Genco gaming strategies become more complex. After a brief introduction of electricity markets and gaming, the effects of demand uncertainty on strategic gaming are studied in two parts: 1) Demand modelled as a discrete random variable 2) Demand modelled as a continuous random variable. In the first part, we proposed an algorithm, the discrete stochastic strategy DSS) algorithm that generates a strategic set of offers from the perspective of the Gencos profits. The DSS offers were tested and compared to the deterministic Nash equilibrium NE) offers based on the predicted demand. This comparison, based on the expected Genco profits, showed the DSS to be a better strategy in a probabilistic sense than the deterministic NE. In the second part, we presented three gaming strategies: 1) Deterministic NE 2) No-Risk 3) Risk-Taking. The strategies were then tested and their profit performances were compared using two assessment tools: a) Expected value and standard deviation b) Inverse cumulative distribution. We concluded that despite yielding higher profit performance under the right conjectures, Risk-Taking strategies are very sensitive to incorrect conjectures on the competitors gaming decisions. As such, despite its lower profit performance, the No-Risk strategy was deemed preferable.

Government programs designed to decrease resource consumption, improve productivity and capitalize on extended daylight hours in the summer have been developed and implemented throughout the world for nearly three hundred years. In 2005, The United States government adopted an extended daylight savings program that increases the number of weeks where the country observes Daylight Saving Time (DST) from 31 to 35 weeks. The program took effect in March 2007. Arguments in support of DST programs highlight the portion of electricity consumption attributed to residential lighting in the evening hours. Adjusting clocks forward by one hour in summer months is believed to reduce electricity consumption due to lighting and therefore significantly reduce residential energy consumption during the period of DST. This paper evaluates the efficacy of the changes to DST resulting from the Energy Policy Act of 2005. The study focuses on changes to household electricity consumption during the extended four weeks of DST. Arizona, one of two states that continue to opt out of DST serves as the study’s control for a comparison with neighboring states, Colorado, Nebraska, Nevada, New Mexico, Oklahoma, Texas and Utah. Results from the regression analysis of a Difference in Difference model indicate that contrary to evaluations by Congress and the Department of Energy, the four week period of Extended Daylight Saving Time does not produce a significant decrease in per capita electricity consumption in Southwestern states.

Biofuels have been promoted to achieve energy security and as a solution to reducing greenhouse gas GHG) emissions from the transportation sector. This dissertation presents a framework to examine the extent to which biofuel policies reduce gasoline consumption and GHG emissions and their implications for land allocation among food and fuel crops, food and fuel prices and social welfare. It first develops a stylized model of the food and fuel sectors linked by a limited land availability to produce food and fuel crops. It then analyzes the mechanisms through which biofuel mandates and subsidies affect consumer choices and differ from a carbon tax policy. A dynamic, multi-market equilibrium model, Biofuel and Environmental Policy Analysis Model BEPAM), is developed to estimate the welfare costs of these policies and to explore the mix of biofuels from corn and various cellulosic feedstocks that are economically viable over the 2007-2022 period under alternative policies. It distinguishes biofuels produced from corn and several cellulosic feedstocks including crop residues corn stover and wheat straw) and bioenergy crops miscanthus and switchgrass). A crop productivity model MISCANMOD is used to simulate the yields of miscanthus and switchgrass. The biofuel policies considered here include the biofuel mandate under the Renewable Fuel Standard RFS), various biofuel subsidies and import tariffs. The effects of these policies are compared to those of a carbon tax policy that is directly targeted to reduce GHG emissions. The stylized model shows that a carbon tax can reduce gasoline consumption and lower GHG emissions, and is likely to increase biofuel consumption with a higher elasticity of substitution between gasoline and biofuels and an elastic supply of gasoline. A biofuel mandate would reduce gasoline consumption, but the effects on GHG emissions depend on parameters in the fuel sector, such as the demand elasticity of miles, the elasticity of substitution between gasoline and biofuels and the supply elasticity of gasoline. A biofuel mandate accompanied with subsidies would create incentives to increase the consumption of the blended fuel by lowering its price. Gasoline consumption and GHG emissions would increase under the mandate and subsidy relative to a mandate alone. The numerical simulation is used to analyze the impacts of biofuel mandate and subsidies relative to a carbon tax. We find a biofuel mandate alone leads to a welfare gain of 0.1% while reducing GHG emissions by 1% relative to a carbon tax of $30 per ton of CO2e Carbon dioxide equivalent). However, it would increase corn and soybean prices in 2022 by 19% and 20% relative to the carbon tax. The provision of biofuel subsidies that accompany the mandate under the RFS significantly changes the mix of bofuels in favor of cellulosic biofuels produced from high yielding perennial grasses and reduces the adverse impact of RFS alone on food prices. Biofuel mandates and subsidies also reduce GHG emissions by 3% relative to the carbon tax but at a welfare cost of $106 B relative to the tax. To meet the cellulosic biofuel mandates, a mix of feedstocks corn stover, wheat straw, switchgrass and miscanthus) is used, where the mix differs over time, with biofuels from miscanthus meeting about 90% of the cellulosic ethanol produced between 2007- 2022. Corn stover comes primarily from the plain states while wheat straw is collected mainly in the central and northern plains and western mountain states. Production of miscanthus is more concentrated in the Great Plains and in the Midwest and along lower reaches of the Mississippi river. Switchgrass, though not as competitive as miscanthus in terms of yields and costs of production in most parts of the country, is still produced in a significant amount in northern and central Texas and Wisconsin where miscanthus yields are relatively low. We then analyze the implications of imposing import tariffs on biofuels for social welfare and GHG emissions in an open economy considering trade in biofuels. When biofuel mandates and subsidies are in place, the imposition of import tariffs would significantly reduce the imports of sugarcane ethanol by 28% relative to biofuel mandates and subsidies. It also results in a higher GHG intensity of the blended fuel and marginally increases GHG emissions but raises social welfare by 0.01% relative to biofuel mandates and subsidies.

Infrastructure systems support human activities in transportation, communication, water use, and energy supply. The dissertation research focuses on critical transportation infrastructure and renewable energy infrastructure systems. The goal of the research efforts is to improve the sustainability of the infrastructure systems, with an emphasis on economic viability, system reliability and robustness, and environmental impacts. The research efforts in critical transportation infrastructure concern the development of strategic robust resource allocation strategies in an uncertain decision-making environment, considering both uncertain service availability and accessibility. The study explores the performances of different modeling approaches i.e., deterministic, stochastic programming, and robust optimization) to reflect various risk preferences. The models are evaluated in a case study of Singapore and results demonstrate that stochastic modeling methods in general offers more robust allocation strategies compared to deterministic approaches in achieving high coverage to critical infrastructures under risks. This general modeling framework can be applied to other emergency service applications, such as, locating medical emergency services. The development of renewable energy infrastructure system development aims to answer the following key research questions: 1) is the renewable energy an economically viable solution? 2) what are the energy distribution and infrastructure system requirements to support such energy supply systems in hedging against potential risks? 3) how does the energy system adapt the dynamics from evolving technology and societal needs in the transition into a renewable energy based society? The study of Renewable Energy System Planning with Risk Management incorporates risk management into its strategic planning of the supply chains. The physical design and operational management are integrated as a whole in seeking mitigations against the potential risks caused by feedstock seasonality and demand uncertainty. Facility spatiality, time variation of feedstock yields, and demand uncertainty are integrated into a two-stage stochastic programming SP) framework. In the study of Transitional Energy System Modeling under Uncertainty, a multistage stochastic dynamic programming is established to optimize the process of building and operating fuel production facilities during the transition. Dynamics due to the evolving technologies and societal changes and uncertainty due to demand fluctuations are the major issues to be addressed.

Many national and regional governments have been promoted biofuels as a strategy to mitigate the climate change effects of the existing petroleum-based transportation system. New performance-based policies such as the California Low-Carbon Fuel Standard and the US Renewable Fuel Standard use Life Cycle Assessment LCA) to estimate greenhouse gas GHG) emissions to determine the life cycle global warming effects of each fuel production pathway. However, the current generation of policies have largely ignored the highly uncertain and often subjective nature of LCA assessments. Considering these uncertainties raises questions about the appropriateness of using an LCA-based estimate as a performance metric in public policy. The objective of this dissertation is to characterize—qualitatively and quantitatively—the many data, parameter, model, and decision uncertainties inherent to estimates of the life cycle climate effects of transportation fuels, and to critically examine the robustness of these policies to these uncertainties. As demonstrated herein, LCA-based fuel regulations may accomplish much less than expected, and have the potential to cause more climate change than a business-as-usual scenario absent biofuels. Alternative policies that acknowledge uncertainty and respect the limitations of LCA—and thus of our understanding of the benefits of LCA-based policies—can be more robust in achieving GHG reductions.

In the U.S., high-speed passenger rail has recently become an active political topic, with multiple corridors currently being considered through federal and state level initiatives. One frequently cited benefit of high-speed rail proposals is that they offer a transition to a more sustainable transportation system with reduced greenhouse gas emissions and fossil energy consumption. This study investigates the feasibility of high-speed rail development as a long-term greenhouse gas emission mitigation strategy while considering major uncertainties in the technological and operational characteristics of intercity travel. First, I develop a general model for evaluating the emissions impact of intercity travel modes. This model incorporates aspects of life-cycle assessment and technological forecasting. The model is then used to compare future scenarios of energy and greenhouse gas emissions associated with the development of high-speed rail and other intercity travel technologies. Three specific rail corridors are evaluated and policy guidelines are developed regarding the emissions impacts of these investments. The results suggest prioritizing high-speed rail investments on short, dense corridors with fewer stops. Likewise, less emphasis should be placed on larger investments that require long construction times due to risks associated with payback of embedded emissions as competing technology improves.

This dissertation examines the cultural politics of energy development on the Navajo (Dine) Nation in the Southwestern United States (Arizona and New Mexico) through an ethnographic study of Desert Rock, a coal-fired power plant proposed by the Navajo Nation government. Since its initial proposal in 2003, the proposed plant has spawned widespread controversy both among tribal members and in the greater region, despite its unbuilt, emergent status. This dissertation follows the actors engaged in this debate, showing how Desert Rock became a fulcrum for urgent negotiations of Navajo identity and indigeneity, sustainable development, tribal sovereignty, and expert knowledge. I argue that these dynamics constitute landscapes of power, where Navajo people understand their region in large part through the political history of energy minerals； negotiate difference (ethnic, gender, and epistemic) through engagements with infrastructure and ecology； create a space for cultural artifacts that envision the effects of energy development on Navajo lands and bodies； contest and articulate particular meanings of sovereignty； mobilize expertise and new practices of knowledge production； and finally, forge new ethical subject positions vis-a-vis debates over technology and the environment. Showing how legacies of extraction on the Navajo Nation are both material and epistemological, the dissertation puts the politics of energy into conversation with the politics of knowledge production, especially as these bear on contemporary anthropological practice. I draw on three types of qualitative data: (1) interviews with a diverse range of people invested in the Navajo Nation’s energy development outcomes； (2) participant observation in energy-related events and collaboration with members of a Navajo environmental organization； and (3) discourse analysis of newspaper articles, grassroots research reports, tribal government reports, and public hearings. This dissertation contributes to the interdisciplinary fields of political ecology, science and technology studies, critical indigenous studies, and nascent work in the anthropology of energy, illuminating how a particular conflict over natural resource management and energy infrastructure galvanized diverse modes of knowledge, energy activism, and identifications with environmentalism. Effectively, the contested technology generated an enduring legacy for the future of energy policy and activism on the Navajo Nation and greater Southwestern region.