Abstract
The changing geography of male same-sex couples over the last decade has important implications for LGBTQ families and communities. While recent scholarship clearly documents that male same-sex couples are becoming more geographically diffuse, less clear is what locational factors drive this change. Some explanations center on the increased cost of housing in established “gayborhoods.” Others point to increasing social acceptance of same-sex couples opening up new residential opportunities. This paper explores these explanations in a spatial regression model that uses neighborhood attributes to predict change in the neighborhood concentration of male same-sex couples, while also accounting for spatial spillover effects from neighboring areas. Data come from the 2009–2013 and 2014–2018 American Community Surveys for four metropolitan areas: New York, Chicago, Atlanta, and San Francisco. Results suggest that gentrification of gayborhoods is generally associated with declining concentrations of male same-sex couples in these areas. But across the four metropolitan areas, there are notable differences in whether same-sex concentrations are more sensitive to housing values, rental costs, or the supply of affordable housing units. Outside of gayborhoods, increasing housing costs are generally associated with increasing same-sex concentrations. These findings add nuance to our understanding of gentrification’s impacts on same-sex couples and affirm that housing affordability is a key concern among same-sex populations. We discuss the theoretical and methodological challenges of continued study in this area.
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Notes
See Hwang and Sampson (2014) for an example of another study that observed gentrification over a similarly short time span.
Researchers can re-allocate same-sex partners between the “married” and “unmarried partner” categories if they use non-aggregated, household-level data like those released by IPUMS. However, such data are only released at higher levels of geography, not census tracts.
There are also well-documented errors in the enumeration of same-sex partners resulting from the miscoding of sex by the respondent on their census form (Black et al. 2007; Gates and Steinberger 2009). The Census Bureau released “preferred” estimates to correct for these errors, but the preferred estimates refer only to married same-sex partners. Errors in the enumeration of unmarried partners, the primary data we utilize in our analysis, are not as much of a concern (DiBennardo and Gates 2014; O’Connell and Feliz 2011).
Within our MSAs, same-sex marriage became legal in New York in 2011, California in 2013, Illinois in 2014, and Georgia in 2015.
Based on the authors’ calculations from the 2013 and 2018 files of IPUMS USA, percentages are calculated as the ratio of married same-sex couples nationwide to all same-sex couples nationwide (i.e., married and unmarried partners combined), multiplied by 100.
Unmarried same-sex partners are tabulated in the ACS in table number B11009.
We conducted supplementary analysis where the dependent variable was change in the number of male same-sex households rather than the tract percentage point change. The results mirrored our reported results. The number of male same-sex partners (after adjusting for county same-sex marriage rates) decreased on average by 22, 18, 32, and 13 households in gayborhoods in New York, Chicago, Atlanta, and San Francisco, respectively, and increased on average by 7.8, 4.0, 2.7, and 21.1 households in other tracts in New York, Chicago, Atlanta, and San Francisco, respectively. These results suggest that whether reported as a number or as a percentage of the population, the concentration of male same-sex couples decreased in gayborhoods while increasing in other tracts over the study time period in all four MSAs. Regression results are substantively similar whether we use the number or the percentage of tract male same-sex households as the dependent variable.
We also conducted supplementary analysis where the dependent variable was the relative percentage change in the concentration of male same-sex couple households rather than the percentage point change. We find results that are substantively similar to our reported results, except for gayborhoods. Because the relative percentage change essentially controls for starting values of same-sex concentrations, which is also the criteria we use to define gayborhoods, using relative change as our dependent variable obscures differences between gayborhoods and other neighborhoods.
Measured with Moran’s I, the spatial autocorrelation of tract percent male same-sex couples in 2010 was 0.19 in New York, 0.22 in Chicago, 0.29 in Atlanta, and 0.58 in San Francisco. All are statistically significantly above zero.
We also explored include a spatial error term, but did find it to be statistically significant or to improve model fit.
In New York, higher rent is associated with increases in male same-sex concentrations outside of gayborhoods (\(\beta\) = 0.1536; see Table 4).
In San Francisco, housing cost measures are not significantly associated with male same-sex concentrations outside of gayborhoods (see Table 4).
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Acknowledgements
The authors thank Veronica Newton, Daniel Pasciuti, Jun Zhao, two anonymous reviewers, and the editor for their helpful feedback.
Funding
This study was supported by a Research Initiation Grant from the Office of the Vice President for Research at Georgia State University. Partial support for this research also came from a Eunice Kennedy Shriver National Institute of Child Health and Human Development research infrastructure grant, P2C HD042828, to the Center for Studies in Demography & Ecology at the University of Washington.
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Spring, A., Charleston, K. Gentrification and the Shifting Geography of Male Same-Sex Couples. Popul Res Policy Rev 40, 1163–1194 (2021). https://doi.org/10.1007/s11113-020-09625-4
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DOI: https://doi.org/10.1007/s11113-020-09625-4