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
Impact of Utility-Scale Solar Farms on Property Values in North Carolina
By Megan Wang
Abstract
The aim of this paper is to investigate impacts of utility-scale solar farms on surrounding property values. Using data from CoreLogic, the Energy Information Administration (EIA), and the US Census Bureau, this study identifies a 12% statistically significant increase in sale values associated with high-income residential homes within three miles of a solar farm. However, low-income homes built near solar farms are associated with a -1.4% decrease in sale values.
As North Carolina continues to expand solar energy, specifically through photovoltaic utilities, understanding the impact of solar development on surrounding communities should be a priority and policies should aim to prevent property devaluations in low-income neighborhoods caused by solar farms.
Professor Christopher Timmins, Faculty Advisor
JEL Codes: Q42, R11
The Impact of Fossil Fuel Prices on Alternative Energy Stocks
By Roman Milioti
The purpose of this paper is to determine if fossil fuel price fluctuations can influence the price alternative energy stock valuations. Employing a Lag Augmented VAR analysis, the research analyzes how natural gas and WTI oil prices impact the price of an alternative energy index. The analysis reveals that neither the price of natural gas nor the price of WTI have a statistically significant positive impact of the price of the alternative energy index. The results are attributed to natural gas and alternative energy acting as both substitutes and compliments given renewable
energy intermittency.
Advisor: Gale Boyd, Kent Kimbrough | JEL Codes: G12, Q42
Optimizing the Electricity Bill Creating a two-part electricity tariffs to induce a targeted level of rooftop solar adoption while meeting utility operating expenses
By Hoel Weisner
Renewable energy technologies are a much needed, clean alternative to the conventional fossil fuel electricity power plants of the last century. The market for installing solar panels on rooftops is a highly promising avenue for expanding the use of these technologies, but its profitability depends significantly on the electricity prices offered by electric utilities. Investing in solar panels offset a percentage of the electricity purchased from the utility. This paper models the investment decision of electricity consumers and looks at what the optimal per unit price of electricity should be in order to make building solar panels a profitable decision for a target share of households. The model shows how this optimal rate decreases at lower prices of investing, when the share of utility-purchased electricity offset by the panels increases, and when the target level of solar adoption decreases. Finally, it looks at how this per unit rate impacts the utility’s decision to set a fixed monthly charge for electricity in order to recover all of its operating expenses.
Advisor: Leslie Marx, Alison Hagy, Kent Kimbrough | JEL Codes: L94, Q42, Q48 | Tagged: Electricity Price, Renewable Energy, Solar Electricity
Shale Gas Development and Housing Value in the United Kingdom: Impact of the 13th Onshore Licensing, 2008
By Esther Lho
While shale gas is a prospective energy source, it is known to bring environmental deficits to the drilling neighborhood. Because of such concerns, property values fluctuate upon the possibility of shale gas fracturing. This paper examines the change in housing prices before and after the release of the 13th onshore oil and gas licensing round, which took place in 2008 when shale gas was increasingly being considered as the alternative to ease the United Kingdom’s dependency on coal. Results suggest that the 2008 licensing has caused a 3% decrease in housing price growth rate for the licensed areas.
Advisor: Christopher Timmins | JEL Codes: Q42, Q5, Q51 | Tagged: Consumer Expectation, Fracturing, Hedonic Price, Housing Prices, Property valuation, Shale Gas, United Kingdom
