Housing insecurity is the uncertainty felt by individuals and households about the stability, safety, adequacy, or affordability of their home and neighborhood (Raymond et al. 2018, Cox et al. 2019). Households can be insecure for many reasons, from overcrowding and illness to job loss and neighborhood change. This white paper focuses on mobile and manufactured housing (MH), which has unique characteristics that can make its residents more vulnerable to housing insecurity than those who live in site-built housing for cultural, historical, and legal reasons. Fortunately, factory-built housing is not inherently vulnerable; indeed, MH is potentially less costly to construct, install and purchase, and more energy efficient than site-built housing (Burch et al. 1993; Baechler & Hadley 2002). MH offers a high quality of life at low cost that allows residents to raise healthy families or “age in place.”
To address this “MH gap,” we develop a novel approach for (i) identifying populations of MH households most vulnerable to housing insecurity and (ii) mapping these populations to better understand their geographies. To do so, the white paper analyzes census microdata from nearly 2,000 MH households in Pima County. This process revealed two MH households profiles whose constellation of vulnerability factors suggest they are more likely to be vulnerable to housing insecurity. These profiles are (i) fixed-income seniors (FIS) and (ii) low-income households living in older homes (LIO). After using qualitative data from interviews with 72 Pima County MH residents and other techniques, to confirm these results, the profiles were converted into MH-specific vulnerability indices and mapped (see Figure 0).
Key findings and contributions:
- The most vulnerable profile groups of MH residents in Pima County / Metro Tucson are Fixed-Income Seniors (FIS) and the Low-Income, Old MH (LIO) households.
- The identification and mapping of these profiles will help policy makers and social service providers better direct their resources to close the MH gap.
- To address the unique characteristics of MH, a method for creating MH-specific vulnerability indices is developed. While in this white paper depth with respect to housing type, and geography are prioritized, the method is applicable to other cities and scales, and all housing types.
- Qualitative methods are combined quantitative analyses (logistic principal components analysis) to select among possible statistical models.
- The most geographically widespread MH vulnerability profile in Tucson is Low-Income Older MH (LIO).
- Vulnerability profiles rarely spatially overlap: FIS and LIO vulnerability profiles only overlap in five census block groups.
Mobile and manufactured housing is arguably Tucson’s most important and largest source of unsubsidized affordable housing. However, it is also the nexus of vulnerabilities that can make its residents housing insecure. This white paper aims to help policy makers and housing advocates to recognize MH’s value and importance despite the ways in which it has been marginalized – by creating a tool that distinguishes the MH subpopulations most vulnerable to housing insecurity from the MH population as a whole. Using principal components
analysis, we were able to identify MH-specific profiles of vulnerability, and then produce mappable indices corresponding to these profiles. This novel approach achieves two broad goals.
- 1) It avoids reinforcing perceptions of MH as an inherently inferior form of housing, and instead recognizes that MH can be both good and bad housing for highly differentiated populations – like any other housing type. Many vulnerability indices use MH as an indicator of vulnerability – suggesting that factory-built housing is a proxy for vulnerability and/or homogeneously correlated with vulnerability. This elision of the complex relationship between MH and vulnerability highlights some of the limitations of broader, more generalized, vulnerability indices.
- 2) The white paper provides insights that are tailored to specific populations with unique needs. This will allow local policy makers, service providers and researchers, to better serve and understand the needs of vulnerable groups. Given the non-traditional characteristics of MH and the current lack of a widely accepted evaluation tool for housing insecurity, the ability to zero in on specific populations is particularly valuable.
The methods developed in this white paper will allow future researchers to ask questions about how MH vulnerability has changed over time, varies by socioeconomic status and other household characteristics, and use inferential techniques to better determine its causes and the potential effects of policy interventions.