16 Unemployment rates per capita are lower than unemployment rates usually reported. The former rate is the number of unemployed divided by the total population in the state, while the latter is the number of unemployed divided by the number of persons seeking jobs.
17 Social welfare spending in this analysis includes no spending on public hospitals.
18 The Non-health Social Services category includes support activities, such as operational payments for administrative workers; payments for child care, foster care, low-income energy assistance, and social services for the physically disabled programs; Social Services Block Grant-funded programs; and temporary shelters and services for the homeless. The category also includes direct payments to private vendors for non-health services and commodities and for the provision, construction, and maintenance of governmentally owned and operated welfare institutions and nursing homes.
19 The Durbin Watson statistics indicated some autocorrelation but insufficient, in our opinion, to adjust the analysis.
20 The model structures are described in Appendix A. Generally, we estimated three generic models with sub-models within each model. In Model 1D, we introduced need variables into the structure for Model 1C. Model 1D is the model described in the body of this report. Models 2 and 3 experimented with specifications that explicitly introduced price effects of federal grants using the method McGuire (1978) recommended. . For reasons related to both the lack of appropriate data to estimate price effects, econometric difficulties related to the same variable appearing on both sides of the equations, and the model statistical results being weak and inconsistent (including many "wrong" signs), we focus primarily on Model 1. Although no explicit grant price effects occur in Model 1, we expect the combination of state and year dummies to pick up much of the variation of grant price effects across states and over time.
21 For definitions of these variables in terms of Census categories, see Exhibit II-1 and the accompanying discussion.
22 The relationship between fiscal capacity and spending on cash assistance seems to be more complex, however. When the equations were estimated for each fiscal capacity quartile, only the wealthiest quartile (Quartile 1) showed a significant and negative relationship. Also, when we examined the estimated state effects from the cash assistance equation, we found the state effects were positively correlated with our four quartiles of states, quartiles that reflected long-run differences in state fiscal capacity. One possible interpretation of these inconsistencies was that our indicator of fiscal capacity-per capita personal income-had two counteracting effects on cash assistance: one long-run effect and one short-run effect. Higher state income in the long run might have encouraged states to adopt more generous cash assistance policies (in terms of higher maximum benefits and need standards, greater earnings disregards, and less stringent asset limits). However, in the short run, increases in per capita income during economic downturns would have decreased welfare rolls as recipients left voluntarily for jobs or became disqualified because their incomes were too high. This latter dynamic (the wage effect) might have been particularly strong among richer states because they tended to have more generous benefit policies, and their cash assistance rolls were thus more likely to include large numbers of working families, whose income fluctuations exerted a greater, countercyclical effect on state spending. (Maximum benefit levels, one indicator of the relative generosity of cash assistance policies, averaged $575 for a three-person family in 2000 for the states in Quartile 1 (the wealthiest). The median maximum benefit levels for Quartiles 2, 3, and 4 were $429, $292, and $277 respectively.)
23 For example, the means of the variables are cash assistance ($82), Medicaid ($151), non-health social services ($125), public hospitals ($115), and other non-social welfare ($3,422). The small relative value for cash assistance spending leads to the odd result that the coefficient on PCPI for cash assistance spending is close to zero but nonetheless statistically significant because its standard error is also extremely small.
24 We should note, however, that the non-social welfare federal grants (i.e., intergovernmental revenue) include federal grants for the public hospital category of spending because the Census classifies public hospital spending as spending for non-social welfare. Census data do not permit disaggregating federal grants in more detail than the broad categories of federal grants for social welfare spending and other federal grants.
25 It should be noted, however, that the effect is negative in quartile 1 for cash assistance. This mirrors the negative impact of personal income on cash assistance found in the overall regression, as reported in Exhibit III-10.
26 The large positive effect might also reflect the increase in federal spending for Medicaid in response to increases in state matching funds. McGuire (1978) reviews the arguments why federal grants can be viewed as exogenous in a model such as this one. However, his major assumption is that the federal government acts through its grants to induce a target level of state spending, implying that if state matching funds increase, no resultant change in federal spending would occur as a result because the state behavior was anticipated. This assumption might prove untrue in practice, and reverse causality effects might occur.
27 One possibility is that in the poorest states, less movement on and off cash assistance occurs as the state of the economy improves or worsens.
28 A pro-cyclical effect means spending moves in the general direction of the economy. When the economy improves, so does spending and vice versa. Conversely, an anti-cyclical effect occurs when spending moves contrary to the direction of the economy.
29 For more on state effects, see footnote 7 in subsection II.B.1.
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