The United States has adopted fuel economy standards that require increases in the on-road efficiency of new passenger vehicles, with the goal of reducing petroleum use, as well as (more recently) greenhouse gas (GHG) emissions. Understanding the cost and effectiveness of this policy, alone and in combination with economy-wide policies that constrain GHG emissions, is essential to inform coordinated design of future climate and energy policy. In this work we use a computable general equilibrium model, the MIT Emissions Prediction and Policy Analysis (EPPA) model, to investigate the effect of combining a fuel economy standard with an economy-wide GHG emissions constraint in the United States. First, a fuel economy standard is shown to be at least five to fourteen times less cost effective than a price instrument (fuel tax) when targeting an identical reduction in cumulative gasoline use. Second, when combined with a cap-and-trade (CAT) policy, the fuel economy standard increases the cost of meeting the GHG emissions constraint by forcing expensive reductions in passenger vehicle gasoline use, displacing more cost-effective abatement opportunities. Third, the impact of adding a fuel economy standard to the CAT policy depends on the availability and cost of abatement opportunities in transport—if advanced biofuels provide a cost-competitive, low carbon alternative to gasoline, the fuel economy standard does not bind and the use of low carbon fuels in passenger vehicles makes a significantly larger contribution to GHG emissions abatement relative to the case when biofuels are not available. This analysis underscores the potentially large costs of a fuel economy standard relative to alternative policies aimed at reducing petroleum use and GHG emissions. It also demonstrates the importance of jointly considering the effects of multiple policies aimed at reducing petroleum use and GHG emissions, and the associated economic costs.

Following the failure in 2010 to pass a comprehensive cap-and-trade bill in the United States, analysts and policymakers have called for new or more stringent policies to curb GHG emissions in the electric power sector. In his 2011 State of the Union address, President Obama announced the goal of producing 80 percent of electricity from “clean” energy sources by 2035. The idea of a federal clean energy standard (CES) has been garnering bi-partisan support in Washington, D.C., and at latest count, thirty-six states (plus the District of Columbia) already employ renewable energy standards (RES) or CES programs, most of them mandating that 15 to 25 percent of total electricity production by 2020 has to come from renewable or “clean” sources (DSIRE, 2011). Energy standards in existing and proposed regulation differ with regard to the list of fuel sources included. Unlike a RES program, most CES proposals would credit not only renewable sources, like wind, solar, bio-power, hydropower and geothermal, but would also credit non-emitting non-renewable sources like nuclear energy, and would give partial crediting to certain other technologies, such as gas and coal technologies with carbon capture and storage (CCS), and natural gas combined cycle plants.

This paper examines the efficiency and distributional implications of RES and CES regulation in the U.S. electric power sector employing a numerical general equilibrium model that is uniquely well suited to assessing both economy-wide and electric sector impacts. We investigate the impacts of introducing a federal energy standard, formulated with and without a particular emphasis on incentivizing renewable energy, on economy-wide costs and emissions reductions, relating these impacts to changes in electricity capacity and generation (shifts to low carbon fuels and renewable sources), and changes in general equilibrium products and factor prices.

The electric power sector, which accounts for approximately 40% of U.S. carbon dioxide emissions, will be a critical component of any policy the U.S. government pursues to confront climate change. In the context of uncertainty in future policy limiting emissions, society faces the following question: What should the electricity mix we build in the next decade look like? We can continue to focus on conventional generation or invest in low-carbon technologies. There is no obvious answer without explicitly considering the risks created by uncertainty.

This research investigates socially optimal near-term electricity investment decisions under uncertainty in future policy. It employs a novel framework that models decision-making under uncertainty with learning in an economy-wide setting that can measure social welfare impacts. Specifically, a computable general equilibrium (CGE) model of the U.S. is formulated as a two-stage stochastic dynamic program focused on decisions in the electric power sector.

In modeling decision-making under uncertainty, an optimal electricity investment hedging strategy is identified. Given the experimental design, the optimal hedging strategy reduces the expected policy costs by over 50% compared to a strategy derived using the expected value for the uncertain parameter; and by 12-400% compared to strategies developed under a perfect foresight or myopic framework. This research also shows that uncertainty has a cost, beyond the cost of meeting a policy. Results show that uncertainty about the future policy increases the expected cost of policy by over 45%. If political consensus can be reached and the climate science uncertainties resolved, setting clear, long-term policies can minimize expected policy costs.

Ultimately, this work demonstrates that near-term investments in low-carbon technologies should be greater than what would be justified to meet near-term goals alone. Near-term low-carbon investments can lower the expected cost of future policy by developing a less carbon-intensive electricity mix, spreading the burden of emissions reductions over time, and helping to overcome technology expansion rate constraints—all of which provide future flexibility in meeting a policy. The additional near-term cost of low-carbon investments is justified by the future flexibility that such investments create. The value of this flexibility is only explicitly considered in the context of decision-making under uncertainty.

The residential sector in the U.S. is responsible for about 20% of the country’s primary energy use (EIA, 2011). Studies estimate that efficiency improvements in this sector can reduce household energy consumption by over 25% by 2020 (McKinsey Global Energy and Materials, 2009). In this thesis, given the increasing amount of attention that both policy-makers and industry are giving to residential energy use, I examine the implications of end-use electrification and efficiency improvements in households. In particular, I focus on high efficiency electric technologies for heating and cooling (referred to as HVAC) needs. Advancements in technologies such as heat pumps are beginning to make the economic case for switching from end-uses of gas to end-uses of electricity in the residential sector. I examine the implications of such end-use electrification, ranging from its impact on energy consumption to its contribution to the abatement of greenhouse gas (GHG) emissions.

I use the MIT Emissions Prediction and Policy Analysis (EPPA) model, a computable general equilibrium model, to analyze the research question. The EPPA model captures full economy-wide impacts of policy mandates and technology changes. First, I added further detail to household energy consumption in the model. Then, I introduced technology changes corresponding to advanced electric technologies for residential heating and cooling and tested their impact with policies that either support or inhibit their entry into the marketplace.

I find two interesting results from the analysis. First, if policies are enacted to support advanced electric HVAC technologies, they displace end-uses of gas and increase household electricity consumption. Second, household end-use electrification in the U.S. leads to an increase in overall emissions in the economy, given that the overall emissions of any electric appliance depend not only on the end-use efficiency of the appliance but also on the efficiency of generating and distributing electricity. Thus, end use electrification only helps in emissions abatement if the power sector becomes less carbon intensive.