Spatial variation in poverty-generating processes: Child poverty in the United States

Abstract

This study builds on research demonstrating that sub-regions within the United States have different processes that abet poverty and that child poverty is spatially differentiated. We focus on the social attributes of the local area to assess what the geographic place represents in terms of social characteristics, namely racial/ethnic composition and economic structure, and to resolve apparent inconsistencies in poverty research. Using spatial regime and spatial error regression techniques to analyze county census data, we examine spatial differentiation in the relationships that generate child poverty. Our approach addresses the conceptual and technical aspects of spatial inequality. Results show that local-area processes are at play with implications for more nuanced theoretical models and anti-poverty policies that consider systematic differences in factors contributing to child poverty according to the racial/ethnic and economic contexts.

Where there's smoke: Cigarette use, social acceptability, and spatial approaches to multilevel modeling

“…Given the use of an otherwise comparable model, this difference is suggestive of substantive differences within the United States in whether and how context is related to maternal smoking. Future research could empirically address this additional contextual layer using established approaches for assessing relationship differences that unfold over space (see especially Baller et al 2001; Curtis, Voss and Long 2012; Fotheringham, Brunsdon, and Charlton 2002). This consideration may be particularly important when developing policy recommendations as the relevance of a factor may vary across states or other identifiable contexts.…”

Spatio-temporal dimensions of child poverty in America, 1990–2010

“…The evidence is clear that women also continue to earn less than men in identical jobs (National Commission on Children, 1991), contributing to the economic disadvantage of these households. County-level proportions of female-headed households have long been shown to have a strong positive association with county-level poverty rates (Voss et al, 2006; Curtis et al, 2012). …”

“…Using 2000 Census sample data, Voss et al (2006) applied cross-sectional spatial regression models to examine the relationship between child poverty and socioeconomic characteristics for counties in the U.S. A follow-up analysis explored the importance of regionalism and regional variations in the social and economic processes by which poverty is generated and sustained over time. The study concluded that sub-regions in the U.S. have different poverty-generating processes based on regional differences (Curtis, Voss, & Long, 2012). Subsequent work by Curtis et al (2013) evaluated the relationship between poverty, industrial structure, and racial/ethnic composition for counties in five states in the U.S. Upper Midwest between 1960 and 2000.…”

Explaining Subnational Infant Mortality and Poverty Rates: What Can We Learn from Night-Time Lights?

“…A simple survey of JSTOR articles published in English between the 1990s and the first decade of the 2000s shows that the number of articles with the keyword ''spatial'' in the title or abstract increased 26 % for 128 sociology journals, 108 % for 36 population studies journals, 31 % for 173 economic journals and 38 % for 152 political science journals. Within sociology and demography, spatial modeling has been well advocated Wachter 2005) and used in empirical studies (Curtis et al 2012;Chi et al 2011;Voss et al 2006;Clark 2005;Plane et al 2005;Johnson et al 2005;Hammer et al 2004). Methodological articles stressing the importance of spatial components in estimating parameters or constructing new indexes can also be found in recent literature (Bhati 2005;Elvidge et al 2012;Reardon and O'Sullivan 2004;Savitz and Raudenbush 2009).…”