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Abstract
Using data from the US Department of Housing and Urban Development (HUD) concerning Housing Choice Voucher (HCV, formerly called Section 8) recipients, the authors provide a spatial analysis in Cincinnati, Ohio, USA. ‘Hot spot’ analysis is utilized to detect areas with significant densities of voucher recipients compared with the surrounding environs. Results show that the implementation of Cincinnati's HCV program between 2000 and 2005 in conjunction with public housing transformation has not led to a greater dispersion of voucher recipients and either poverty or racial deconcentration. Many HCV households remain concentrated in hot spots. The implications for US low-income housing policy are discussed.
Notes
1. Housing voucher recipients are required to pay 30% of their monthly adjusted gross income for rent and utilities; the government subsidizes the balance of the costs up to a locally determined maximum, or payment standard. The HCV program is designed to allow families to move anywhere in the United States providing that the family lives in the jurisdiction of the public housing authority (PHA) issuing the voucher when the family applies for assistance. Portability is the mechanism by which Section 8 recipients can move from one PHA jurisdiction to another. The Section 8 Housing Voucher Reform Act (SEVRA) seeks to remove administrative barriers to mobility. SEVRA was passed by the US House of Representatives in July 2007 and is currently being considered by the US Senate (Sard and Fischer Citation2008); the impact of SEVRA on HCV concentration remains to be seen.
2. These transformation policies are grounded in the widely held assumption that public housing is a failure, primarily because it concentrates poverty. By moving residents out and developing alternative housing in which residents of varying income levels reside, it is assumed that poverty will be deconcentrated. However, since by the very definition of ‘mixed-income’ only a relatively small number of relocated public housing residents can actually move back to the new developments, such policies are contingent on providing many (in some cases, the overwhelming majority) of the relocated residents with housing vouchers.
3. The Gautreaux program was a response to a consent decree to a lawsuit filed against the Chicago Housing Authority (CHA) and HUD on behalf of public housing residents in Chicago (Gautreaux v. Chicago Housing Authority 1969).
4. The sites were located in Camden County, New Jersey, Baltimore, Maryland; Lynn, Massachusetts; San Antonio, Texas; Syracuse, New York; Norristown, Pennsylvania; Fairfax County, Virginia; and Cook County, Illinois.
5. Churchill et al.’s case study of the Patterson Park community of Baltimore (2001) relies exclusively on qualitative methods. There are no maps to portray the intensity of voucher clustering in this part of East Baltimore
6. It was beyond the intended scope of this paper to determine whether the HCV program is more controversial in Cincinnati than elsewhere. Churchill et al.’s 2001 study suggests that the program has been controversial in a variety of city and suburban setting across America. Consequently, it is highly unlikely that the level of clustering in the Cincinnati area has been affected by the level of controversy.
7. This paper focuses on Hamilton County the core urban county in the Cincinnati Primary Metropolitan Statistical Area, which contains the bulk of HCV households. The Cincinnati, Ohio Primary Metropolitan Statistical Area (PMSA) (population of 1,168,275 in 2000) consists of 12 counties: four in Ohio (Brown, Clermont, Hamilton, and Warren), six in Kentucky (Boone, Campbell, Gallatin, Grant, Kenton, and Pendleton), and two in Indiana (Dearborn, and Ohio).
8. Memorandum from Valerie A. Lemmie, City Manager, City of Cincinnati Department of Community Development, to Neighborhood and Public Service Committee, 18 October 2004.
9. The dot maps are of limited value because so much information is compressed into such a limited amount of space (Smith Citation2002, Wang and Varady Citation2005).
10. We used 2004 household estimates in the ESRI CommunityInfo database, which calculates the proportion of households that are HCV households. A description of the ESRI CommunityInfo database can be found at http://www.esri.com/industries/university/community_info.html.
11. In the HCV recipient density raster files, any cells with a zero density value were excluded from the analysis.
12. The choice of search distance and density threshold are subjective. We compared several combinations of search distances and density thresholds visually. The current method also does not consider other variables that may affect HCV recipient density, such as population density. This method is sufficient for the purpose of this study, which is to analyse the density change from 2000 and 2005 and to identify areas where more investigation may be conducted.
13. should be used cautiously. We compare the census block groups in which HCV households were located in 2000 and those where they were located in 2005, based on 2000 census block group data dealing with the proportion in poverty and the proportion of Blacks (census data is only available every 10 years). It is possible that some of the block groups that adjoined 2000 high-density HCV areas were themselves undergoing income and racial change. If so, our results may overstate or understate the extent to which HCV households were moving to lower-poverty and lower-minority areas.
14. The manager was unable to explain why a gate was originally included in the development, or why it was approved by the county. The developer may have anticipated a more affluent rent-paying clientele than has been interested in the development in recent years.