Content by Keyword: Poverty and Measurement

We found a different type of decision-making in TANF cash assistance programs. Medicaid was a high visibility program that sometimes commanded the attention of governors and often drew the attention of legislators and organized lobbyists, but TANF cash assistance programs drew attention only sporadically from legislators and from few others outsid

The site visits indicated that decisions about Medicaid were more likely than other social program areas to involve active and highly organized constituencies, especially service providers, and to engage the attention of elected officials, including legislators and sometimes governors and their staff or top appointees. Medicaid budgets and policie

These six states varied in their spending patterns, both before and after FY 2000, though we found that some regional differences in spending patterns of poor states before 2000 have declined in strength in recent years. For the most part, spending trends evident among the poor states before 2000 continued after that year: medical assistance expan

Because Medicaid spending was not cut substantially in these states and, in fact, continued to grow in most states and because spending on cash assistance programs remained essentially flat, offering few opportunities for savings, fiscal pressures during state budget crises fell mostly on non-health social services programs. This outcome was espec

Spending on cash assistance has declined sharply in most states over the last several years, especially since the implementation of welfare reform (Boyd et al., 2003). As noted above, the declines in cash assistance spending through 2000 were steep for wealthy states but smaller for poor states.

The site visits largely indicated that the spending trends and state differences found before 2000 continued even through the recession. Perhaps the clearest example was the continued growth of Medicaid in these states. In most of the six poor states, the growth in spending on Medicaid before 2000-indicated by increases in the Census Bureau's Vend

At the time of our site visits, all six states were experiencing difficult fiscal problems. Yet these problems varied between rich and poor states as well as among these six states. The crisis was driven largely by a sharp drop in revenues in 2001 and 2002 (Boyd 2003). The declines were greatest among the comparatively wealthy states in the Northe

Although we have no Census data after 2000, we can draw from the site visits and administrative spending data on selected programs to determine whether these six poor states continued or departed from prior trends and differences. Subsection IVB examines recent changes in spending among the six states and finds, for the most part, that the state t

The division among the poor states we noted in section III was also found among the six poor states selected for site visits. Exhibit IV-1 shows the estimated state effects for cash assistance, Medicaid, non-health social services, public hospitals, and non-social welfare. Again, these state effect scores were scaled to equal zero for the mean sta

The econometric models support the claim that state fiscal capacity exerts positive effects on total spending for social programs as well as spending for major components of social welfare budgets, such as cash assistance, medical assistance, and other public welfare programs. However, the models raise two sets of new questions:

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 h

i) Effects of Fiscal Capacity

One result of the 50-state model was the estimation of unexplained variance in spending across different states. These state effects were estimated intercepts or constant terms for each of the states in the econometric models. They may be interpreted as general dispositions of states-averaged across the entire period, 1977-2000-to support certain

To confirm that the effects estimated for the unemployment per capita variable were truly state labor market effects and to get a better sense of how spending changed in response to unemployment changes alone, we estimated simple linear relationships between spending per capita in each category and the state unemployment rate with and without per

When we repeated the regressions separately by quartile, poverty continued to exert consistently negative signs only for the richest states (Quartile 1) and generally had more positive signs for the other quartiles. However, the only statistically significant and positive effects of the poverty variable occurred for cash assistance in quartiles 2

When we estimated the regression separately for each quartile, the signs of the effects of federal grants reverse or the coefficients are estimated with less statistical significance for the poorest states (Quartile 4), indicating weak grant income effects for those states, as shown in Exhibit III-11.

From Exhibit III-11, we can see that when the states are separated by quartiles based on average per capita personal income, differences across quartiles in the estimated effects emerge. For example, for cash assistance and non-health social services, the effect of personal income for the richer states (Quartiles 1 and 2) is statistically signific

Exhibit III-11 shows results for the same regression model estimated separately for each of the 4 quartiles defined by mean real per capita personal income. Below, we summarize the general findings from this analysis by quartile and spending category for the explanatory variables of greatest interest: (1) fiscal capacity, (2) federal grants, (3) n

Exhibit III-10 displays the regression results for the five regressions with dependent variables defined as respective categories of per capita state and local spending (CA - cash assistance, M - Medicaid, NSS - non-health social services, PH - public hospitals, and non-social welfare - NW) for all states. 21 Below the estimated coefficients, t-s

Using conventional ordinary least squares, we estimated the 50-state econometric model on pooled time series and cross-section data on state and local spending for the 24 years from 1977 to 2000. We conducted standard tests for auto-correlation of residuals, which sometimes constitutes an issue for time series analysis. 19