By Ryan B. Hoecker
This paper analyzes the municipal fringe of cities in Eastern North Carolina between 2006-2016, and how the values of individual properties on the outskirts can fluctuate after they are
incorporated within a city. A large portion of the research process consisted of manually recreating annexation ordinances from scanned photocopies on ArcGIS, creating the first geographic archive of annexations in North Carolina compatible with digital software. As environmental nuisances, such as landfills and hazardous waste sites, are often located on town borders, this study pays specific attention to how their presence affects the change in property values before and after annexation. Results show that incorporation brings with it higher property values, and that the impact of annexation is greater in the presence of nuisances that threaten water quality for private wells.
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Advisor: Christopher Timmins | JEL Codes: H79, Q53, R31
By Gabrielle Inder
This paper examines how information transfer about contamination levels found at brownfield sites capitalizes into nearby property values. More specifically, a hedonic model is used to test the impact on housing transaction prices when a binary measure (i.e. exceeding a threshold or not) or a continuous measure (i.e. chemical levels) is used. In the analysis, I exploit the variation in the contaminant thresholds, caused by regulatory conditions defined by the state of Massachusetts, holding the contaminant level constant. As thresholds are tied to neighborhood attributes in areas surrounding brownfields, threshold exceedance is potentially correlated to unobserved factors that impact housing values. An instrumental variables approach is used to create variation in threshold
exceedance through the use of an instrument that measures the presence to underground aquifers. After instrumenting for threshold exceedance, my estimates indicate that a 10.8% decrease in housing values occurs when a contaminant threshold is exceeded, while the continuous measures of toxicity indicate a negative but insignificant effect. These findings suggest that policy makers should consider information conveyance when creating policies to inform homeowners of pollution presence, as improved information provision may increase public awareness about local environmental concerns.
Advisor: Christopher Timmins, Michelle Connolly | JEL Codes: C26, Q5, Q53 | Tagged: Brownfields, Hedonic Analysis, Housing Markets, Instrumental Variables, Pollution
The Role of Income in Environmental Justice: A National Analysis of Race, Housing Markets, and Air Pollution
By Christopher Brown
Historically, evidence has shown that minority populations in the United States suffer a disproportionate burden of pollution compared to whites. This study examines whether this burden could be the result of income disparities between whites and minorities, acting through the housing market. We look at 324 Metropolitan Statistical Areas (MSA’s) in the United States as defined by the Economic and Social Research Institute. Using demographic data from the 2000 Decennial Census and pollution data from the 1999 national Air Toxic Assessments, we compare the race-income correlation in each MSA for four races (white, black, Latino, and Asian) with the race-income.
JEL Codes: Q53, Q56 | Tagged:
By Marissa Meir
Environmental injustice is a theory that claims distributions of toxic, hazardous and dangerous waste facilities are disproportionately located in low-income communities of color. This paper empirically demonstrates an alternative cause of environmental injustice- that low-income minorities are less likely to receive sizeable enough loans to buy a house in a cleaner area. It highlights a significant time in history, from 1999 to 2007, when wealth constraints were eased and loan amounts increased for people with the same income. The results show that minorities increase their demand of environmental goods given an increase in loan amounts, suggesting that people of color care about environmental quality, but, due to wealth constraints, do not have the same opportunities
in the housing market.
Advisor: Christopher Timmins | JEL Codes: P46, P48, Q50, Q53, Q56, Q58, R20, R21, R31, R32 | Tagged: