«Mixed Messages on Mixed incoMes Volume 15, Number 2 • 2013 U.S. Department of Housing and Urban Development | Office of Policy Development and ...»
Reducing barriers to employment is one reason the HCVP policies shifted to enable easier mobility for voucher holders. In other words, higher employment levels are more likely if the voucher holder can move closer to job opportunities without losing housing assistance. Given this reasoning, it is possible that movers would be employed more often than nonmovers. To investigate this possibility, a logistic regression model was specified with employed or not as the dependent variable and the same set of independent variables used in the previous analysis. The results from this regression are shown in exhibit 6.
The analysis indicates that movers are no more likely to be employed than nonmovers. As suggested in the MTO analysis, it may be that movers are relatively recently moved and experiencing an adjustment period before finding employment. It may also be that the move was related to considerations other than employment. Six variables in the model have statistically significant coefficients. As a voucher holder’s age increases, he or she is less likely to be employed. Being foreign born, being married, having a child present, and graduating from high school are all positively associated with being employed. As expected, having a higher income is associated with having a job. Living in the
The value is 1 minus the exponentiation of the coefficient for “lives in central city” [1 - exp (- 0.300)].
I conducted an alternative regression to assess if movers with children experienced better school quality than nonmovers with and without children. The results were not statistically significant.
compare the poverty rate and school quality before and after moves. Also, to determine if employment status before and after a move were associated, I conducted a chi-square analysis. Exhibit 8 contains the results of these analyses.
Movers did experience improvements in their neighborhood poverty rate and in school quality.
Although the t-statistic is significant, however, the magnitude of the improvement is rather small (a less than 1-percent reduction in the neighborhood poverty rate and about a 7-point increase on the API index). The results for employment before and after moves are very discouraging. Before moving, 73.0 percent of the voucher holders worked; after moving, that number dropped to 52.2 percent. Also, only 15 voucher holders who moved went from unemployed before moving to employed after moving. The results from this sample clearly provide no evidence that voucher holders move for employment opportunities.
Research and Policy Implications Taken as a whole, the literature provides a mixed narrative on mobility, and the results from this study do not change the story. The lack of differences for neighborhood poverty level, employment, and school quality outcomes between HCVP movers and nonmovers may mean that mobility is not based on these outcomes and that our assumptions about the reasons for mobility are inaccurate or incomplete. Understanding the reasons for voucher holders’ moves in the regular HCVP is an important step in assessing voucher holders’ needs and improving program goals. Researchers need to better understand voucher holders’ decisions about residential location and the tradeoffs they make during their housing search. With this knowledge, researchers can better design studies, not only to evaluate a range of standard outcomes, as done for MTO, but also to assess the degree to which voucher holders achieve their desired outcomes in the HCVP.
One result from the multivariate models that is consistent across outcomes was location in the central city. It is clear that voucher holders living in the central city, at least in Orange County, experienced a cluster of negative outcomes compared with the outcomes of voucher holders living outside the central city. This result suggests that future research on the HCVP should include analyses of the effect of moving within and out of central cities, including relatively smaller central cities and central cities in suburban environments such as Orange County.
Voucher holders’ locational choices in Orange County and elsewhere may be constrained to a few relatively similar neighborhoods. In other words, moving would not change outcomes dramatically.
Such an interpretation about the lack of differences between HCVP movers and nonmovers is consistent with the results comparing mover-only outcomes before and after their residential relocation.
Although neighborhood poverty rate and school quality improved, the improvements were quite minimal. As such, it is reasonable to suggest that these marginal changes likely have no discernible positive effects on the lives of voucher holders or their children. The burden for HCVP administrators is to work on opening up new neighborhoods that offer more opportunities to voucher holders, although doing so is a tall order for LHAs that have struggled in the past convincing landlords to accept voucher recipients.
Mobility may be a mechanism for low-income people to achieve better neighborhoods and access new opportunities. Programmatic and structural changes are necessary, however, for mobility to have a good chance at achieving certain outcomes in the HCVP. Moreover, we cannot expect rapid change from mobility out of low-income neighborhoods. Generations of disadvantage created intergenerational poverty, and it will take generations of advantage to change the status quo.
Acknowledgments The author thanks the staff and voucher holders of the Santa Ana Housing Authority and the Orange County Housing Authority for their contributions to this study. The research was made possible through funding from the U.S. Department of Housing and Urban Development. The author is solely responsible for the accuracy of her statements and interpretations, which do not necessarily reflect the views of the U.S. government.
Author Victoria Basolo is an associate professor in the Department of Planning, Policy, and Design at the University of California, Irvine.
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