Spending on Social Welfare Programs in Rich and Poor States. Final Report.. D. Integrated Analysis Between Econometric Model and Site Visit Data

07/01/2004

We designed our field research in part to help interpret the estimated econometric models and extend the range of factors whose influences might be assessed. At the most general level, the analyses of the econometric data posed and sharpened the questions for the site visits and related analyses of the six states.

First, the site visits were used to weigh the credibility of different explanations of the estimated regression coefficients. For example, the econometric models found that population density exerted positive effects on cash assistance expenditures and negative effects on health-related spending. The site visits suggested hypotheses, consistent with a wide array of quantitative and qualitative data, as to why these differences might occur, at least in poor states.

Second, the econometric models estimated state effects for total as well as different types of social welfare spending. Intercepts estimated for each state,15 these coefficients represented an average level of spending for a particular state after controlling for the effects of all included variables, such as fiscal capacity, unemployment, and poverty. Because these state-effect estimates stripped off the linear effects of economic and demographic variables, they varied greatly among the six poor states and helped sharpen our analyses of institutional and political factors. For example, though Mississippi's spending on medical assistance could not be considered high in an absolute sense, it was sizeable after controlling for the state's fiscal capacity and other significant variables. Thus, the econometric analysis changed the question from why the state's spending on medical assistance was so low to why it was higher than we had expected, given the state's economy and demographics.

Third, the estimated state effects allowed us to examine with greater precision how states varied in the ways they combined, or failed to combine, different types of social welfare expenditures. For example, we found a fundamental division between poor states (i.e., between states that put enormous emphasis on medical assistance and other states whose long-run spending tendencies were more balanced between different functions). We estimated these different configurations, or packages, of spending through the econometric analysis and posed important questions for the site visits.

Fourth, the six state case studies allowed us to assess findings from the econometric analyses in light of state spending changes after fiscal year 2000, the last year for which Census Bureau spending data were available. For example, the models indicated that spending on cash assistance and Medicaid went up during recessions and down during economic booms, other things being equal, while non-health social services showed the opposite pattern. Because the states we studied were, for the most part, experiencing severe fiscal pressures after several years of economic growth, we could draw on quantitative and qualitative data in the case studies to tests these and other expectations.

We also estimated separate econometric models for each of the six states in the field research sample, and we thought these separate estimates would clarify other important differences and similarities among these states. However, with few exceptions, these separate models also turned out to be hard to interpret because of instability, we suspect, due to small degrees of freedom. Thus, we do not present these models in the current report.

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