Patterns of Multiple Instability Among Low-Income Families with Children

Background: Prior research shows that income, family ,and residential instability can all have lasting adverse impacts, and the lingering effects of the Great Recession and cuts to public assistance programs compound the risk of experiencing instability for low-income families in particular. However, prior studies have primarily focused only on a single domain like economic or family instability and have ignored the complexity of multiple instabilities experienced by low-income families. This limited view of instability may limit our ability to craft policies to effectively support these families. This study addresses this knowledge gap by examining patterns of multiple instability among low-income families. We have two specific aims: (1) to identify distinct patterns of income, family, and residential instability among low-income families, experienced both independently and in conjunction with one another; (2) to compare these patterns of instability with respect to sociodemographic and other background characteristics.

Methods: We use nationally representative data from the 2008 Panel of the Survey of Income and Program Participation (SIPP). Our sample includes low-income (less than 200% of poverty) families with children. We adopt a number of innovative measurement approaches for capturing instability. First, unlike much previous research, we specifically measure: income instability, allowing for both positive instability (>=25% increase in income above the average for all periods) and negative instability (>=25% decrease in income); family instability, measuring both the addition of a spouse or the loss of a spouse; and residential instability, indicated by a recent move. Second, we use the longitudinal nature of the SIPP to observe instability at six points over a two-year period, whereas much previous research has focused only on the presence of any instability between two time points. For the analysis, we use sequence and cluster analysis to identify distinct patterns of instability over time. Together, these innovations allow us to create a more complete picture of the nature of instability among low-income households, an important first step to adapting the social safety net to be more responsive to household needs.

Results: Findings indicate that roughly 75% of families experienced a negative income shock in one of the six waves. Experiences of family (5.6%) and residential instability (4.3%) were less common and typically experienced only once, rendering separate sequence and cluster analyses of limited utility for these outcomes. Analyses of income instability identified five distinct clusters, including families with little-to-no instability (~30% of sample) and families with early negative income shocks followed by later positive income shocks (~20%). Analyses of all three types of inequality in conjunction identified six clusters, e.g., families with instability across most periods (~ 13% of the sample), families with limited-to-no instability (~43%), and families with increasing instability over time (~7%).  Comparisons of the income and multiple instability clusters indicated significant differences with respect to ethnicity, marital status, and education level. 

Implications: Study findings underscore the potential value of adopting a more nuanced understanding of instability experienced by low-income households both in future research and in developing policy and programmatic interventions.