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.
Dr. Christopher Timmins, Faculty Advisor
JEL Classification: Q42, R11
Subprime’s Long shadow: Understanding subprime lending’s role in the St. Louis vacancy crisis
By Glen David Morgenstern
Abstract
Using loan-level data, this analysis attempts to connect the events of the subprime home loan boom to the current vacancy crisis in St. Louis, Missouri. Borrowers in Black areas in the north of St. Louis City and St. Louis County received subprime home loans at higher rates during the subprime boom period of 2003-2007 than those in White areas, with differences in balloon loans especially stark. Specifically, borrowers in Black neighborhoods received subprime loans more frequently than those with equal FICO scores in White neighborhoods. As a result of these differential loan terms, North City and inner ring “First Suburb” areas saw more foreclosure and
borrower payment delinquency, which in turn were highly associated with home vacancy, controlling for other risk factors. However, foreclosure was no longer a significant predictor of home vacancy
after controlling for demographic factors and FICO score, indicating that the unequal loan terms may have driven much of the increase in home vacancy in the St. Louis area since the Great Recession.
Professor Charles Becker, Faculty Advisor
JEL classification: R1; R3; R11; R31; J1; J15
Deciphering Chinese Financing To African Countries
By Gwen Geng
The paper considers what attracts Chinese aid and Chinese investment to African countries and what kinds of Chinese financing projects are more likely to have unrevealed financing amount. The main database used is AidData: China’s Official Finance to Africa 2000-2012. It contains 2356 Chinese financing projects to 50 African countries. The results suggest that Chinese aid supports less developed economies, while Chinese investment favors countries with resource abundance and political conditions conducive to profit-making. The findings show that projects with unrevealed funding amounts tend to fall under investment and the government sector among other categories, raising questions on financing secrecy.
Advisors: Robert Garlick and Michelle Connolly | JEL Codes: F13, F54, N47, N57, O24, R11, R15
Entrepreneurial Attractiveness: Amazon, Google, and the Search for Innovative Hot Spots
By Anna Katherine Kropf
Recent economic literature suggests that entrepreneurship in technological fields can spur economic growth, making it a popular topic for city development officials. Yet, this increasingly popular phenomenon is met by many economic questions. One of those questions is which characteristics of metropolitan areas are attractive to entrepreneurs. To answer the question of attractiveness on both the small business and corporate levels, I compare across two case studies: Amazon’s search for a second headquarters and Google’s tech hub network. Using principal component analysis, I statistically deduce seven components of attractiveness from an original 34 variables. These components are then weighted using three methods—a case study, a survey, and an empirical method—to produce comparable indices of attractiveness. Generally, I find that sizeable population and healthy economy are the strongest components. However, the statistically insignificant components that can change an urban area’s ranking considerably are talent and geographic network effects. Ultimately, creating policy to maximize these aspects can change a city’s innovative
trajectory.
Advisor: Dr. Charles Becker | JEL Codes: O, O3, R, R1, R11
The Impact of Suburbanization on Poverty Concentration: Using Transportation Networks to Predict the Spatial Distribution of Poverty
By Winston Riddick
The purpose of this paper is to investigate the determinants of concentrated poverty, a phenomenon where socioeconomically deprived groups are heavily concentrated in particular neighborhoods in a metropolitan area. Drawing on Land Use Theory and the Spatial Mismatch Hypothesis, I develop a theory that identifies suburbanization as a principal cause of poverty concentration. Using interstate highway expansion as a source of exogenous variation in suburbanization rates, I evaluate this relationship in 240 U.S. Metropolitan Statistical Areas (MSAs) from 1960-1990, with concentrated poverty measured at the tract level. Panel regressions with MSA Fixed Effects find a positive and significant relationship between highway expansion and increased poverty concentration under a variety of specifications, including alternative measures of highways and an instrumented measure of urban population decline.
Advisor: Charles Becker, Michelle Connolly | JEL Codes: I30, J61, R13, R40 | Tagged: Highways, Poverty Concentration, Spatial Mismatch, Suburbanization, Transportation Networks
