We examine the predictors of state spending on Temporary Assistance for Needy Families (TANF) cash assistance, which has fallen dramatically since the passage of welfare reform in 1996. Over the 2000s, states allocating 33% or more of their TANF expenditures toward cash assistance are more likely to have higher minimum wages and are more liberal, though with fewer Black residents—both overall and on the TANF caseload. Our preferred empirical specifications suggest a negative link between state basic assistance expenditures—which we use as a measure of cash assistance—and the proportion of Black residents on the state’s TANF caseload. These findings contribute to a longstanding body of research examining the political economy of racial disparities within the welfare system and support further investigation into the mechanisms driving these observed associations. Upon considering the Kerner Commission’s call to reinvest in economically disadvantaged communities, it is important to consider how reform proposals modeled off of TANF may extend to new domains of the American social safety net. Our findings, as well as those of others within the welfare research literature, recommend a closer look at whether and how race operates within systems of devolved authority.

Rural homelessness in the United States is an understudied phenomenon. Among those studies which do address the issue, there exists no uniform or consistent definition for rural homelessness. In this review of the literature, we look at rural homelessness and consolidate the literature into four main groups based on the definitions currently in use. We recommend a comprehensive definition for rural homelessness that looks at this phenomenon on a spectrum of needs, populations, and periodicity. We further recommend that current homeless count methodology be improved by using a more detailed survey of homeless situations, not only in the rural United States, but in urban areas as well.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in ABSTRACTUsing unique longitudinal administrative tax panel data for the District of Columbia (DC), we assess the combined effect of the DC supplemental earned income tax credit (EITC) and the federal EITC on poverty and income dynamics within Washington, DC, from 2001 to 2011. The EITC in DC merits investigation, as the DC supplement to the federal credit is the largest in the nation. The supplemental DC EITC was enacted in 2000, and has been expanded from 10 percent of the federal credit in 2001 to 40 percent as of 2009. To implement the study, we estimate least squares models with 0/1 dependent variables to estimate the likelihood of net-EITC income above poverty and near-poverty thresholds. We also estimate the likelihood of earnings growth and income stabilization from the EITC. To identify the effect of the EITC, we exploit variation in the EITC subsidy rate from 2008 to 2009, when an additional EITC bracket of 45 percent was added for workers with three or more dependent children, up from 40 percent in the previous year for workers with two or more children. We also estimate a model examining the impact of city-level changes to the EITC. The structure and richness of our data enable us to control for tax filer fixed effects, an important innovation from many previous EITC studies. Overall, we find that the combined EITC raises the likelihood of net-EITC income above poverty and near poverty by as much as 9 percent, with the largest consistent effects accruing to single-parent families. JEL Classification Codes: I32, I38, H24, J38

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in ABSTRACTUsing unique longitudinal administrative tax panel data for the District of Columbia (DC), we assess the combined effect of the DC supplemental earned income tax credit (EITC) and the federal EITC on poverty and income dynamics within Washington, DC, from 2001 to 2011. The EITC in DC merits investigation, as the DC supplement to the federal credit is the largest in the nation. The supplemental DC EITC was enacted in 2000, and has been expanded from 10 percent of the federal credit in 2001 to 40 percent as of 2009. To implement the study, we estimate least squares models with 0/1 dependent variables to estimate the likelihood of net-EITC income above poverty and near-poverty thresholds. We also estimate the likelihood of earnings growth and income stabilization from the EITC. To identify the effect of the EITC, we exploit variation in the EITC subsidy rate from 2008 to 2009, when an additional EITC bracket of 45 percent was added for workers with three or more dependent children, up from 40 percent in the previous year for workers with two or more children. We also estimate a model examining the impact of city-level changes to the EITC. The structure and richness of our data enable us to control for tax filer fixed effects, an important innovation from many previous EITC studies. Overall, we find that the combined EITC raises the likelihood of net-EITC income above poverty and near poverty by as much as 9 percent, with the largest consistent effects accruing to single-parent families. JEL Classification Codes: I32, I38, H24, J38

Objectives: To estimate the impact of county-level income, access to food, availability of health resources, socioeconomic factors, and state political ideology on population obesity and mental health in US counties. Design: We compiled a county-level data set from the US Census, County Health Rankings, USDA Food Environment Atlas, the American Community Survey, and the State Ideology Database. We specify 2 multivariable regression models for county-level obesity rate and per capita poor mental health days and control for rurality, food access, income, availability of health care resources, state political ideology, and socioeconomic characteristics. Results: We find that higher food access reduces obesity in counties; an increase in per capita full-service restaurants by 1 unit is associated with reduction in obesity rate by 1.24 points and an increase in per capita grocery stores reduces poor mental health days by 0.14. We also find that counties in liberal-leaning states tend to have lower obesity rates. Access to primary care providers (increase in primary care physicians by 1 is associated with decline in obesity rate by 1.18 points and poor mental health days by 0.11 days), and recreational facilities (increase in recreational facilities per 1000 by 1 is associated with reduction in obesity rate by 3.16 points and poor mental health days by 0.47 days) reduces obesity rates and poor mental health days. Median income is associated with decrease in obesity rate and poor mental health days. Increase in median household income by 1% is associated with reduction in obesity rate 4.75% and reduction in poor mental health days by 1.39 days. Conclusions: We find that access to food and health care at county level and state ideology through policy making affects health outcomes. Our analysis indicates that counties can improve access to food and health care by investing in these services thereby improving county-level health outcomes and save dollars in the process.