TANF Participation Rates: Do Community Conditions Matter?*

Abstract

A general criticism of the 1996 Welfare Reform Act is that it is primarily the result of an urban political agenda, and it may hurt rather than help the rural poor. Under the new welfare system, the rural poor that are most likely to be affected are those who live in socially, economically, and spatially disadvantaged communities. More residents in these communities are likely to need TANF, clients in these communities are least likely to leave TANF by finding employment, and community organizations are likely to have more limited resources to help TANF recipients. The objective of this study is to examine the extent to which variations in community conditions account for differences in TANF participation rates. Using 1997 TANF data from the Mississippi Department of Human Services, we estimated OLS regression models of local TANF participation rates across 100 communities in nonmetro counties. The results indicate that TANF participation rates tend to be higher in communities with high concentrations of African Americans, less faith-based activeness, more employment in retail trade, spatial concentration of the poor, and located in the Delta.

Spatial Context and Poverty: Area-Level Effects and Micro-Level Effects on Household Poverty in the Texas Borderland & Lower Mississippi Delta: United States, 2006

“…There is also widespread consensus that the proportion of the working-age population that is employed is associated with lower poverty in counties (Cotter 2002;Slack and Jensen 2002;Gundersen 2006;Rupasingha and Goetz 2007). Other factors that tend to increase the poverty rate of counties are the percent of families headed by females without a spouse present (Albrecht et al 2000;Goe and Rhea 2000;Lichter et al 2003;Lichter and McLaughlin 1995); a high proportion of the population aged 15 years of age and under (Cotter 2002;Rupasingha and Goetz 2007;Adelman and Jaret 1999); and the nonmetropolitan status of the county (Jensen et al 2003;Jensen and Tienda 1989;O'Hare 1988;Parisi et al 2003;Rank and Hirschl 1988;Rural Sociological Society Task Force on Persistent Rural Poverty 1993;Saenz and Thomas 1991). Factors associated with lower aggregate poverty rates include the percent of the population aged 25 years and over with at least a high-school diploma (Saenz 1997a;Adelman and Jaret 1999;Rupasingha and Goetz 2007;Crowley et al 2006); the net migration rate (Frey and Liaw 2005); and the percent of the population speaking English well (Davila et al 1993;Davila and Mora 2000;Crowly et al 2006).…”

“…For example, certain industrial structures such as high proportions of employment in financial services (Singelmann 1978;Parisi et al 2003;Rupasingha and Goetz 2007) and manufacturing (Brady and Wallace 2001;Cotter 2002;Rupasingha and Goetz 2007) tend to reduce aggregate poverty. There is also widespread consensus that the proportion of the working-age population that is employed is associated with lower poverty in counties (Cotter 2002;Slack and Jensen 2002;Gundersen 2006;Rupasingha and Goetz 2007).…”

Poverty in the Texas borderland and lower Mississippi Delta: A comparative analysis of differences by family type

“…For example, research has shown the percentages of total employment in the manufacturing sector (Cotter 2002;Rupasingha and Goetz 2007) and the finance, insurance, and real estate (FIRE) sector (Parisi et al 2003;Rupasingha and Goetz 2007;Singelmann 1978) are negatively associated with aggregate poverty levels. Jobs in these sectors are generally considered to be more stable and provide employees better compensation than is true of other sectors.…”

Intersectional Perspective and Rural Poverty Research: Benefits, Challenges and Policy Implications

“…For example, in examining how community conditions affect participation rates in the local program Temporary Assistance for Needy Families (TANF) in Mississippi, Parisi et al (2003) found evidence of the processes of underinvestment and discrimination placing individuals from rural areas in the Mississippi Delta region with high populations of BlackBlack at a distinct disadvantage. The authors suggest that these disadvantages are magnified in cases where poor economic conditions, low human capital, minority concentration, high inequality, and low civic engagement occur simultaneously.…”

“…Traditionally, rural poverty research has focused on poverty's connection to human capital, family structure, and local economic conditions (Parisi, McLaughlin, Grice, & Gill, 2003). Over the past two decades, socio-economic concerns, including the effects of globalization on rural populations, and the questions regarding access to financial resources and labor markets, have emerged as the primary focal areas offering insights into the nature of rural poverty (Cobb, 1992;Dewees, Lobao, & Swanson, 2003;Duncan, 1996;Tickamyer & Duncan, 1990).…”