Spending on Social Welfare Programs in Rich and Poor States. Final Report.. F. Conclusions

07/01/2004

Our analyses of estimated state effects and site visits to poor states suggest several basic conclusions:

  • Poor states differ from one another in the ways they distribute funds across different program areas. Although state spending on various social programs-after controlling for fiscal capacity, social need, and the other variables included in the 50-state model-tend to be correlated with one another among non-poor states, poor states show a regional divide between those that have small cash assistance programs and devote the great bulk of their social program resources to Medicaid and those that have retained significant cash assistance programs and put fewer resources into Medicaid.
  • Since 2000, spending trends in programs among poor states continued some of the trends evident before 2000 and diverged from others. Spending on Medicaid continued to rise, even during the recession and slightly faster among the poor states than in the nation as a whole. In fact, Medicaid spending rose especially quickly among poor states that traditionally had spent little on Medicaid, thereby reducing some of the regional differences among poor states. Spending on cash assistance generally remained flat among these poor states, though some saw modest increases in cash assistance expenditures while wealthier states continued to see declines in cash assistance spending. Knowing whether non-health social services programs were rising or falling in these six poor states was difficult, but the site visits suggested that many of these non-health social services functions, especially administrative spending, bore the brunt of state budget cuts.
  • These patterns of change might reflect differences in how decisions were made in different program areas. We found, for example, that budget choices about Medicaid in these states were often dominated by strong and active provider institutions-a politics of organized interests, frequently involving the legislature as well as the governor, that was absent in the rest of social welfare system. Spending on health programs was, thus, sensitive to the role of the health industry in the state's economy and the industry's reliance on public programs, and spending growth in Medicaid continued despite the fiscal pressures of the 2001-2002 recession.
  • Cash assistance spending was more directly affected by relatively infrequent changes in policies, set largely by the legislature, and their interactions with the economy. When policies were established, they appeared to reflect ideological viewpoints found among state elected officials.
  • Decisions about non-health social services were less politically salient and, thus, more likely to involve choices by administrators about what programs were of higher priority and more effective. Their choices were strongly affected by short-run budget constraints, such as declines in tax revenues, availability of funding through various grant programs, flexibility administrators had in drawing on these funds as well as governors and state administrators' priorities and judgments in exercising their flexibility.

These different modes of decision-making might help account for some of the findings from the 50-state models of various forms of social welfare spending, though we cannot say so with certainty. Cash assistance, for example, was found to be strongly related to unemployment, a finding which makes sense in light of our conclusion that policies were infrequently changed in this area, except during major periods of reform, as in the early and middle 1990s, and spending changes were usually driven by caseloads. Medicaid spending was negatively related to state population density, a finding that made sense if health providers in rural states were particularly active politically in supporting Medicaid because they constituted a larger part of the economy or they depended more on public funds to sustain themselves. Our conclusions might also help explain the fact that unemployment failed to increase spending on non-health social services and that federal grants to non-social welfare tended to increase spending on such functions. The site visits suggested that overall state revenue levels strongly affected spending on these non-health social services, which were more discretionary in the short-run than other programs. And it was reasonable to assume that these overall revenues were negatively related to unemployment rates and positively related to sources of federal dollars.

More generally, our findings suggest the importance of state and local constituencies in understanding why some programs thrive, even during difficult budgetary conditions, and why others fail to thrive, even when the different programs offer similar fiscal federalism incentives. In these states, constituencies-mostly service providers-were active and strong on health issues, while they were largely absent from state budgetary politics on other social welfare matters, a fact consistent with spending trends among poor states as well as with state differences. If constituencies are, in fact, critical and if they continue to be skewed toward the health industry, low fiscal capacity states might face a long-term squeeze on non-health social services unless social welfare spending can obtain a larger share of the state budget. Given the strong pressures from other program areas outside social welfare, from education, to prisons, to highways and roads, the latter option is unlikely.36 Thus, non-health social services might well continue to constitute a smaller and smaller share of state budgets.

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