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It Is Not Always Sunny in San Diego for Housing Choice Voucher (HCV) Holders: The Reproduction of Racial and Socioeconomic Segregation under the Choice Communities Initiative

Journal of Policy Practice and Research volume 2, pages 76–89 (2021)Cite this article

Abstract

This article examines residential mobility patterns of housing choice voucher (HCV) holders in San Diego, CA. It focuses on whether HCV holders moved to higher opportunity ZIP codes following the adoption of the Choice Communities Initiative by the San Diego Housing Commission (SDHC) in 2018. This initiative was designed to incentivize moves to high opportunity ZIP codes using tiered rent subsidies. The analysis is based on a dataset that combines two sources. One includes data obtained from the SDHC measuring: race, ethnicity, gender, household characteristics, rent subsidy levels, and residential mobility for 11,126 HCV recipients. The other includes small area fair market rents (SAFMRs) for ZIP codes in San Diego. Data were analyzed using GIS maps and logistic regression. The results indicate that patterns of racial and socioeconomic segregation have been reinforced in San Diego. Most HCV moves happened within the lowest opportunity ZIP codes, regardless of races. Moves to higher opportunity ZIP codes were impeded due to the inversion of rent subsidies. Rent subsidies were set relatively higher in low opportunity ZIP codes when compared with high opportunity ZIP codes. The findings identify areas where specific policies related to the setting of rent subsidies can be strengthened in order to promote opportunity moves. In a broader context, they highlight the importance of fidelity to programmatic goals in the policy implementation process.

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Data Availability

Data is available upon request.

Notes

  1. Under the rules of the Section 8 certificate program, vouchers could only be used in the municipal boundaries of the PHA that issued them. This constraint led to the clustering of vouchers in geographic areas where poverty concentrated, particularly when vouchers were issued by large PHAs in core cities. The Section 8 voucher demonstration program was designed to encourage the dispersal vouchers metropolitan-wide and deconcentrate poverty.

  2. It is noteworthy that the HCV program is the largest affordable housing program in the United States. In 2020, Congress authorized approximately $24 billion to it. According to HUD’s picture of subsidized households database, the program subsidized approximately 2.56 million households and private rental units in 2019. This represented more than half of all the affordable housing units subsidized by the federal government across the eight programs reported in the database.

  3. These conclusions correspond with parallel research examining housing mobility outcomes outside of the United States (Baker et al., 2016). This highlights the degree to which the embeddedness of neoliberal imperatives in housing policies shapes outcome in a more generalized manner across peripheries in the global context.

  4. In their analysis of the housing mobility policies that grew out of the Mount Laurel affordable housing decisions in New Jersey, Massey et al., (2013) came to similar conclusions about the need for wraparound services in addition to housing mobility counseling.

  5. HUD plans to expand the number of areas mandated to use SAFMRs in 2023, after five years of implementation of the SAFMR rule elapses.

  6. The focus on first year implementation represents a snapshot of HCV holders mobility decisions. In December of 2017, the SDHC notified all HCV holders that the Choice Communities Initiative would begin implementation on January 1, 2018. At that time, the SDHC’s 2018 payment standards were published. Efforts were made to collect 2019, however the SDHC ceased releasing data with unique identifiers for individual HCVs after 2018, which meant that moves for individual HCVs could no longer be tracked after the initial year of the policy’s implementation.

  7. HCV moves were calculated for three years using data provided by the SDHC. The percent of HCV households that moved was constant across all years: 4.9% of HCV households (N = 547) moved between 2015 and 2016, 4.3% of HCV households (N = 537) moved between 2016 and 2017, and 4.4% of HCV households (N = 489) moved between 2017 and 2018.

  8. The percent of movers remaining in the same tier ZIP code was consistent with prior years. Moves in 2016 and 2017 were examined in ZIP codes corresponding to the tiers adopted by the SDHC in 2018. In 2016, 64.8% of movers remained in the same tier. In 2017, 66.8% of movers remained in the same tier.

  9. The percent of movers relocating to a higher or lower tier was also relatively consistent. In 2016, 15.8% of moves relocated to a lower tier ZIP code and 19.4% moved to a higher tier ZIP code. In 2017, 16.7% of moves relocated to a lower tier ZIP code and 16.5% moved to a higher tier ZIP code.

  10. The additive effects of this variable are substantial. For example, Table 1 indicates that there was a 16.05% difference between relative payment standards for two-bedroom apartments in signature communities (96.47% of SAFMRs) and those in choice communities (80.42% of SAFMRs). The model indicates that the odds of such a move would be .883 less likely to occur.

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Acknowledgments

We thank Parisa Ijadi-Maghsoodi for sharing data obtained from the San Diego Housing Commission through a Public Records Act request.

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This article received no research funding.

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  1. University At Buffalo, Buffalo, NY, 14260, USA

    Kelly L. Patterson, Robert Mark Silverman & Chihuangji Wang

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  1. Kelly L. Patterson
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  2. Robert Mark Silverman
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  3. Chihuangji Wang
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Correspondence to Robert Mark Silverman.

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Patterson, K.L., Silverman, R.M. & Wang, C. It Is Not Always Sunny in San Diego for Housing Choice Voucher (HCV) Holders: The Reproduction of Racial and Socioeconomic Segregation under the Choice Communities Initiative. J of Pol Practice & Research 2, 76–89 (2021). https://doi.org/10.1007/s42972-020-00022-x

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Keywords

  • Housing choice vouchers (HCVs)
  • Residential mobility
  • Policy implementation
  • Inequality