It is well documented that children living in low-income households fare worse on nearly all dimensions of well-being compared to children living in higher income households.  For example, these children have poorer health and lower educational achievement.  Less is known, however, about which factors explain variation in the well-being of poor and low-income children.  In other words, looking only at children at the bottom of the income ladder, why do some fare better than others? 

As part of a larger project examining multiple determinants of the well-being of low-income children, this paper explores the relationships between program participation (e.g., TANF, Food Stamps/SNAP, Medicaid, housing assistance, energy assistance, and free school meals) and children’s educational well-being (e.g., participation in extracurricular activities, attitude towards school, has repeated a grade, and has been expelled) and physical well-being (e.g., health status and visited a doctor and dentist in the past year).  Data come from the 2004 and 2008 Panels of the Survey of Income and Program Participation (SIPP). 

Program participation may improve child well-being in that it increases the likelihood that children have access to basic necessities such as food and housing.  However, some suggest that program participation promotes dependency and single-parenthood and discourages employment – which generally have detrimental effects on child development and well-being.

The study sample includes children aged 5 to 17 living with a biological parent whose average family income levels fall below 130 percent of the poverty threshold.  Core and topical module data are merged from Waves 1-3 of the 2004 SIPP Panel and Waves 2-4 of the 2008 SIPP Panel.  SIPP data are well suited for this analysis because they provide longitudinal information on key independent variables (i.e., program participation) and control variables (i.e., socio-demographic characteristics and family structure), and the topical module data provide in-depth child well-being measures.

The dependent variables are all dummy coded.  Logistic regression models assess the strength and direction of the relationships between program participation and the numerous child well-being measures, which I expect to be mixed.  For example, I hypothesize that programs providing in-kind benefits (e.g., Food Stamps or Medicaid) will be associated with better child well-being, while cash assistance programs (e.g., TANF) will be associated with poorer child well-being.  All analyses are weighted to be nationally representative and adjusted to correct for SIPP’s complex sampling design.

This project is intended to increase knowledge about childhood poverty.  While much emphasis is placed on moving children out of poverty, this is often not a viable outcome.  An alternate way to think about the problem of childhood poverty is to create avenues for improving the well-being of low-income children in the absence of increasing family income levels.