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Evaluating Emissions Reductions through the Regional Greenhouse Gas Initiative: A State and Plant-Level Analysis
by Nicholas Vassilios Papavassiliou
Abstract
In this study, I examine the impact of the Regional Greenhouse Gas Initiative (RGGI) on emission reductions in the electricity sector, focusing on three critical dimensions. First, I analyze temporal trends in emissions reductions to evaluate whether previously demonstrated progress has slowed as states exhaust low-cost mitigation pathways. Second, I assess regional impacts within electricity grid management areas, particularly the Pennsylvania-Jersey-Maryland Interconnection Regional Transmission Organization (PJM ISO) where participating and non participating states coexist, including investigating emissions leakage where reductions in RGGI states are offset by increases in neighboring non-RGGI states. Third, I extend the analysis to other greenhouse gases and co-pollutants. Employing difference indifferences and synthetic control methods, the findings show that the RGGI has a significant on the intensive margin, significantly reducing operating hours and heat input across all types of power plants. Alongside these reductions, RGGI spurs net facility exits and promotes fuel switching toward lower-carbon sources. As a result, both pollutant intensity and aggregate emissions decline over time, underscoring the program’s effectiveness. Examining these shifts in the context of regional electricity grids indicates that comprehensive coverage across interconnected markets can minimize leakage and better achieve environmental objectives, offering insights for the design of future regional climate policies.
Professor Jeffrey DeSimone, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: Q41, Q48, Q52, Q58
Keywords: Cap-and-Trade, Emissions Leakage, Environmental Policy, Regional Greenhouse
Gas Initiative
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Who Gets Wind? Investigating Economic Attributes of Iowa Counties Prior to Wind Turbine Development
by Karianna Klassen
Abstract
Iowa is a national leader in wind energy, producing nearly two-thirds of its electricity from wind turbines. However, the development of wind energy infrastructure across the state has been uneven—some counties host hundreds of turbines while others have none. This paper investigates whether county-level economic conditions influence the likelihood of wind turbine development. Using panel data from 1990 to 2023 and a two-way fixed effects regression framework, I examine the relationship between wind energy development and three economic indicators: farm income per capita, non-farm income per capita, and unemployment rate. I control for political affiliation, farming success, prior turbine presence, land availability, and demographic variables. Contrary to existing qualitative literature that suggests economic need drives local acceptance of wind projects, my analysis finds that these economic indicators are not statistically significant predictors of turbine development. One exception is political affiliation, which in some regressions indicates that a higher share of Democratic votes is associated with a lower probability of turbine development—contradicting national-level trends linking Democratic support with renewable energy expansion. All models have low between-county explanatory power (R² < 0.05), suggesting that factors not captured in county-level economic data—such as individual landowner decisions, developer strategies, or transmission infrastructure—may better explain wind energy siting patterns. These findings call for deeper investigation into localized, non-economic factors that shape renewable energy development, particularly as the push toward decarbonization accelerates.
Professor Jeffrey DeSimone, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: O13, R11, Q42,
Keywords: Wind Energy, Renewable Development, Agriculture
The Effect of Community Uninsurance Rates on Access to Health Care among the Insured
by Isabella Antonio
Abstract
While the direct effects of being uninsured have been studied extensively, there is significantly less research on how a high community uninsured rate can impact health care access for insured individuals. Using data from SMART BRFSS, I examine the effect of community uninsured rates on access to health care for insured individuals ages 18 to 64 years old. Controlling for MMSA-level fixed effects and year fixed effects, I estimate the effect of community uninsurance on the likelihood of an insured individual skipping care due to cost, the likelihood of an insured individual having at least one personal doctor, and the likelihood of an insured individual delaying a physical exam, cholesterol check, or pap smear. Results suggest that a 10 percentage point increase in the community uninsured rate decreases the likelihood of an insured individual having at least one personal doctor by 0.304 percentage points and increases the likelihood of delaying a physical exam, cholesterol check, or pap smear by 0.590 to 2.31 percentage points. These findings suggests that policies aimed at reducing the uninsured rate, such as the Affordable Care Act and Medicaid expansion, may produce widespread benefits for all Americans, both the uninsured and the insured.
Professor Jeffrey DeSimone, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: I1, I11, I13
Keywords: Health insurance, Health care access
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