Abstract
The term “gentrification” carries conflicting popular connotations, conjuring images of both revitalization and displacement. Despite a rich critical literature from urban social scientists, gentrification as it relates to rural housing and rural development is a similarly conflicted term. With the frequent conflation of rural gentrification and economic improvement, researchers and policy-makers alike need more nuanced techniques for identifying how the process distributes costs and benefits across households. This paper operationalizes rural gentrification as a specific demographic pattern of household migration, termed the “Rural Gentrification Score,” and maps its footprint between 1980 and 2000 in 25 US states. It then uses census data to better understand the impacts of rural gentrification on home values in rural counties, interrogating the popular notion that homeowners benefit from gentrification. Using comparative analyses, two related hypotheses about rural gentrification and inequality are explored: (1) that gentrified rural counties were susceptible to greater home value segregation and (2) that over time gentrification’s spread culminated in greater homogeneity of home values. Results support each of these hypotheses and point to nuances in the relationship between population turnover, inequality, and socioeconomic context. Most notably the findings highlight a spatial and temporal pattern of widening wealth inequality in gentrifying rural counties.
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Notes
“Non-metropolitan” and “metropolitan” refer to county level designations from the US Office of Management and Budget. They are used interchangeably with “rural” and “urban” in this paper, but should not be confused with US census designations of urban and rural calculated at the census block level.
While rural gentrification is measured for all rural counties in the contiguous 48 states, the analytical component excludes states where demographic traits preclude straightforward comparisons across counties.
This was the most comprehensive migration data available until 1991, when the IRS began making its filings data available. With the elimination of the US Census long form questionnaire, approximations of these data are now available from the American Community Survey for 2010, although the comparability to past years datasets is unclear.
La Paz, Arizona; Broomfield, Colorado; Cibola, New Mexico.
Because CGI calculations are impacted by the number of bins in which the Census Bureau reports home values, interpretation of changes in gentrification counties between years should be made with caution. The 1970 Census presents home values in fewer bins than later census years, which Watson suggests produces more conservative segregation measures. This means that the uniform increase in segregation seen in this study’s 1980 census may be partially attributable to the change in bin numbers. This does not impact comparison of apparent rates of change between different counties.
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Appendix: Assessing the RGS
Appendix: Assessing the RGS
In the rural demography literature, in-migrants’ urban origins are an often overlooked distinction when assessing impacts of rural population growth. Newcomers from cities can catalyze different types of change than those from other rural counties. The RGS is designed to ascertain these differences. Moreover, in accounting for population turnover, the RGS is a more nuanced indicator of changes to housing markets than net migration rates, for example.
Evidence of gentrification’s unique implications for inequality is apparent in the RGS’s relationship to home values and housing costs. Across all rural counties and decades, the RGS is more strongly correlated with counties’ median home values and rents than are net migration rates (Table 4). This echoes research conducted in urban real estate markets which finds that home prices are a function not only of the demand for local property, but of the process of population turnover that creates enclaves of particularly high value homes (Watson 2009).
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Golding, S.A. Gentrification and Segregated Wealth in Rural America: Home Value Sorting in Destination Counties. Popul Res Policy Rev 35, 127–146 (2016). https://doi.org/10.1007/s11113-015-9374-9
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DOI: https://doi.org/10.1007/s11113-015-9374-9