Title: Constructing Localities: An empirical analysis of housing and its effect on population composition and local decision-making
Description:
As someone fascinated by movement and marginalized lives in an American context, I would like to explore the relationship between housing patterns, namely availability of affordable housing, and the socioeconomic and racial composition of an area over time. The specific research question my thesis will address is: What is the relationship between housing patterns of a county, its population composition, and its local voting outcomes? My main hypothesis is that local housing development policies are likely related to shifts in the socioeconomic and racial composition of a local population, which in turn may play a role in affecting local voting outcomes, whether that be in participation rates, distribution of votes between candidates, or even overall election outcomes. Empirically, my project will explore my research question using Virginia as a case. The work will proceed in two specific stages. In stage one, I will use quantitative methods to analyze Virginia counties over time. Specifically, I will study Virginia counties’ changing housing prices and regress the positive or negative change in housing values with shifts in the proportion of the population that is nonwhite or that pertains to a lower socioeconomic group. I will then map those changes to county voting dynamics to see if housing policy has an effect on voting patterns. Part of this cross-county analysis will involve analyzing the relationship between the range of available housing options in a given county and its population composition, under the belief that counties with a broader range of housing options will be more heterogenous or diverse in composition, over counties that typically possess a smaller range of home values. My presumption is that homogenous counties and heterogeneous will act differently in decision-making. In stage two of my study, I will employ qualitative methods in a deeper case analysis looking to tie specific locally-based housing policies to changes in county population composition. Although I have not yet chosen my cases for this part of the project, I have a few ideas already. For example, I could take Fairfax County’s 2010 “upzoning” policies, a rezoning endeavor centered on the promotion of affordable housing development, and compare that to Virginia Beach City’s Department of Housing and Neighborhood Preservation’s five-year plan calling for an aggressive approach to upgrading homes. In looking at both cases closely, I could analyze how these sudden shifts in housing values play out in altering the population landscape of the respective areas and how those shifts, in turn, may affect local decision-making. Not only is the relationship between housing and voting underexplored, it would also carry implications for policy considerations and future research. Like redistricting, if housing policies and plans are significantly associated with shifts in population composition, they could potentially serve as a systematic way to reshape a population and thereby affect voting outcomes in the medium to long term. Such a study could provide the evidence to add new considerations to such policies such as how they will affect the population not only economically but in composition and decision-making. Further research could address this more specifically by exploring areas of the country where these policies are adopted on a much wider scale and addressing the intentions of the politicians that champion and employ them.
Hometown: Stafford, Virginia
Department: Government
Advisor: Paul Manna
All William & Mary Honors Fellowships fundraising supports the Charles Center Honors Fellowships Fund. Direct support for individual undergraduate research projects is distributed by the Roy R. Charles Center for Academic Excellence.
No updates for this campaign.
Donors
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1956 | 1 | $100 |
1978 | 1 | $250 |
1979 | 1 | $50 |
2018 | 2 | $50 |
2019 | 4 | $85 |
2020 | 2 | $60 |
2021 | 1 | $100 |
2022 | 1 | $10 |
2023 | 1 | $10 |









