Family Homelessness: An Investigation of Structural Effects

Abstract

Homelessness has often been attributed to personal deficits rather than to socioeconomic (structural) conditions. This study uses a unique dataset or panel containing the number of people in family units in emergency shelters in Missouri by county during five matched summer and winter dates (1993–2001). This panel contains a nearly complete enumeration of emergency shelter populations within central city, suburban, smaller metropolitan, and rural counties in Missouri on these dates. Structural effects on homelessness are assessed using generalized estimating equations. During winter and summer dates, the number of people in families in emergency shelters is positively related to unemployment rates and inversely related to general relief. Economic activity as measured by taxable sales is inversely related to family emergency shelter populations in the summer but not in the winter. Results are consistent with beliefs that family homelessness is a consequence of poor economic conditions and insufficient social welfare support.

KEYWORDS:

• Homelessness
• structural effects
• families
• generalized estimating equations
• Missouri

Notes

Note. *One-tailed test; otherwise all tests are reported as two-tailed.

Note. *One-tailed test; otherwise all tests are reported as two-tailed.

1. A family is defined in the MASW censuses as having at least one parent or guardian and one child younger than 18, or a homeless pregnant woman, or a homeless person in the process of securing legal custody of a person. The number of individuals in family units came from the MASW censuses and is recorded by shelter by county. The number of people and their familial status were among those questions answered from shelter records. The county population used in this study is the mean of the 1990 and 2000 U. S. censuses.

2. The coldest day, January 1 through March 31, statewide, was ascertained ex post from National Weather Center records. Shelter directors indicated that occupancies during the summer were higher on Mondays. Four of the census Mondays were the last in June; the first Monday in July was used in 1993.

3. FMRs are generally set one time per year though there were two years in this study in which rents were set twice. FMRs are based on the preceding U. S. decennial census, adjusted with information from the American Housing Surveys (AHS) and random digit dialing (RDD) telephone surveys. FMRs are generally set at the fortieth percentile rent drawn from the distribution of rents of all recent movers. Newly built housing (less than 2 years old), public housing and substandard housing are excluded. FMRs include all utilities except telephone. Starting in January 2, 2001, 39 areas had their FMRs increased to the fiftieth percentile to “promote residential choice, help families move closer to areas of job growth, and deconcentrate poverty” (U. S. Department of Housing and Urban Development, 2003b, p. 60084). The St. Louis and Kansas City metropolitan areas were included among the 39 areas whose FMRs were increased to the fiftieth percentile.

4. The number of shelter beds in a county, as with the number of people in families in a shelter, is taken from shelter records for the MASW censuses.

5. Martha Burt, principal research associate in the Urban Institute's Center on Labor, Human Services and Population, reviewed our initial test results that showed no relationship between the dependent variable and the income maintenance independent variables (personal communication, November 12, 2004). She suggested that Food Stamps, Family Assistance, and SSI would be invariant at the county level and might mask possible relationships with General Relief. Further tests revealed a high degree of correlation among the income maintenance variables. We therefore included only General Relief in this analysis.

6. GEE was described by Liang and Zeger (1986) for use with correlated cross-sectional longitudinal data sets.

7. Owing to the availability of socioeconomic and demographic data, the county is the unit of analysis. Observations of shelters are aggregated by county.