The Lewin Group and the Nelson A. Rockefeller Institute of Government
U.S. Department of Health and Human Services
Assistant Secretary for Planning and Evaluation
June 30, 2004
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How does a states fiscal capacity affect its spending on social welfare programs? Do poor states (i.e., states with low fiscal capacity as measured by per capita personal income) differ from richer states in how much they spend on social welfare programs or how they allocate expenditures across cash assistance, Medicaid, and social services for low-income populations? And how do economic downturns and recent changes in federal policy affect state social welfare spending?
To address these questions, the Office of the Assistant Secretary for Planning and Evaluation (ASPE) of the U.S. Department of Health and Human Services (HHS) sponsored a study of the relationship between state fiscal capacity and social welfare spending in the U.S. from the late 1970s through the early 2000s. The study was conducted by the Lewin Group and the Nelson A. Rockefeller Institute of Government of the State University of New York. Our research included econometric analyses of more than two decades of state social welfare spending and case studies of six states with low-fiscal capacities and high needs for social welfare services. This brief presents key findings from the research. More information on the econometric models and the poor-state analyses may be found in the projects final report.
For the purposes of the study, we defined social welfare spending as programs that supported lower-income households, typically, though not exclusively, programs with means tests. These programs included health initiatives such as Medicaid and state child health insurance programs (SCHIP); cash assistance programs such as Aid to Families with Dependent Children (AFDC) or cash payments under AFDCs replacement, Temporary Assistance for Needy Families (TANF); and a wide variety of other service programs providing child care, foster care, low-income energy assistance, services to the homeless and those funded by the Social Services Block Grant (SSBG). Because the study was designed to understand the effects of state fiscal capacity on social welfare spending, we included in the analyses only spending that went through the budgets of state and local governments. Direct expenditures by the federal government such as the federal Earned Income Tax Credit (EITC), Food Stamp Program (FSP) benefits, and the federal portion of Supplemental Security Income (SSI) for poor elderly and disabled people were excluded from direct examination.
Although the study used spending data on specific programs, such as Medicaid and TANF, at several points in the analysis, most of the quantitative research in the project was based on state and local spending data collected annually by the U.S. Census Bureau (Census Bureau) since 1977. One of the largest expenditure categories in the Census of Governments (Census) data was termed public welfare expenditures, amounting to $233 billion in fiscal year (FY) 2000. To determine whether fiscal capacity affected different types of social welfare spending in different ways, the study organized the 10 subcategories under public welfare expenditures into three basic types of spending:
Because some Medicaid dollars flowed to public hospitals and such hospitals serviced many low-income families, we also analyzed a Census category called Public Hospitals at several points in the study, though the analyses were usually done separately. Exhibit 1 details these categories, showing the spending levels in many of the subcategories for FY 2000 (the most recent data available). Health care expenditures constituted the largest part of total spending on social welfare, with Medicaid and Public Hospitals being the largest and second largest categories of spending. States spent a total of $230.2 billion on these two functions in 2000. Non-health Social Services made up the third largest category ($58 billion), and Cash Assistance came in fourth ($20.7 billion).
|Spending Category||Detailed Item in Census Data||FY 2000 $
Federal Categorical Assistance
|17.7||Includes AFDC or TANF cash assistance; federal Supplemental
Security Income (SSI) when it passes through state accounts; and state SSI
Note: The only federal SSI funds that pass through state accounts are retroactive federal payments reimbursing the state for payments made to individuals under state supplement programs; the total amounts are small
Other Cash Assistance
|Includes cash assistance programs not under federal categorical programs (e.g., general assistance, refugee assistance, home relief, and emergency relief)|
Vendor Payments for Medical Care
|155.0||Includes payments made directly to private vendors for medical assistance and hospital and health care (payments consist mostly of Medicaid/SCHIP)|
|Non-health Social Services||E75
Vendor Payments for Other Purposes
|2.1||Includes payments made directly to private vendors for services and commodities other than medical, hospital, and health care|
|E77, F77, G77
|1.2||Includes payments for provision, construction, and maintenance of nursing homes and welfare institutions owned and operated by a government for the benefit of needy persons|
|E79, F79, G79
Other Public Welfare
|54.4||Includes operational payments for public employees in the sphere of public welfare; and payments for welfare programs such as child care, child welfare, adoption assistance, foster care, low-income energy assistance and weatherization, social services to the physically disabled, SSBG-funded programs, welfare-related community action programs, and temporary shelters and other services for the homeless|
|Public Hospitals||E36, F36, G36
Own Hospitals (except federal veterans)
|75.2||Includes payments for hospital facilities providing in-patient medical care and institutions primarily for the care and treatment of the disabled that are directly administered by a government as well as direct payments for acquisition or construction of hospitals|
|Non-social Welfare||All Other Spending||1,309.0||Includes primarily elementary and secondary education, higher education, highways and public mass transit, police protection, financial administration, housing and community development, utilities (water supply and electric power), and sewerage|
We measured state fiscal capacity using states real per capita personal income. Per capita personal income relates in many ways to the resources that state and local governments may tax to pay for social welfare as well as non-social welfare spending and the availability of such resources might affect overall levels of spending. We considered and compared other measures of fiscal capacity, but real per capita personal income was strongly correlated with other indicators, and it had the virtue of being available annually throughout the time period our analyses covered.
To compare changes in spending patterns for rich and poor states over time, we classified all of the states plus the District of Columbia into four quartiles with respect to their fiscal capacity, as measured by real per capita income averaged over the 24-year period. Exhibit 2 displays, in map form, the states in each of the quartiles, from the richest states in Quartile 1 to the poorest in Quartile 4.
States by Fiscal Capacity Quartile,
Measured by Average Real Per Capita Personal Income, 19772000
|Selected Characteristics||Quartile 1||Quartile 2||Quartile 3||Quartile 4|
|Mean per capita personal income, 19772000 (2000 dollars)||$24,794||$21,387||$19,242||$17,058|
|Mean percentage of people under federal poverty level, 19772000||11.0||11.0||13.2||17.1|
|Median population density (population per square mile), 19772000||338||89||57||52|
The map shows that the poorest states come from two areas of the country. One group of states in Quartile 4 includes several southern states. Another group of poor states is located in the West, from New Mexico to Montana and South Dakota. We chose states for the case studies in part to represent this regional variation. West Virginia and South Carolina were selected among the eastern states; Mississippi and Louisiana were selected among the states in the central South; and New Mexico and Arizona were selected among the western states. As we note below, regional differences among the poor states were correlated with major differences in how they allocated funding among different social welfare programs.
Exhibit 2 also displays information about the states in these different quartiles, including average real per capita income, poverty rates, and population density. States in different quartiles differed in income; low-fiscal capacity states also had higher poverty rates and lower population densities (i.e., they were generally more rural).
Study findings emerged from several methods and data sources, including analyses of spending trends, econometric models of state spending on different types of social welfare functions, and the case studies of the six poor states (Arizona, Louisiana, Mississippi, New Mexico, South Carolina, and West Virginia). Five of the six case study states were in the fourth, or poorest, quartile. The sixth state (Arizona) was at the bottom of the third quartile. All had high social needs as measured by poverty and unemployment rates. The states also showed important differences in geography and recent changes in fiscal capacity and need. The case studies relied on discussions with public officials, administrative data on program spending and caseloads, and state budgets, reports, policy information, and other public documents.
The studys major findings are as follows:
Poor states spent less per capita than rich states did on social welfare programs. As the chart at the top of Exhibit 3 shows, when averaged over the entire period of 1977 to 2000, per capita spending on social welfare was positively correlated with state fiscal capacity. The wealthiest 13 states (Quartile 1) spent an average of $639 per capita on social welfare programs over this time period, after expenditures were adjusted for inflation. The poorest 12 states (Quartile 4) spent only $408 per capita.
This $231 difference resulted largely from differences in states spending of their own tax revenues. Federal grants did not reduce absolute spending differences between rich and poor states. Average federal grants to the wealthiest states were $371, higher than the average grants to the other three quartiles, including the poorest states, which received an average of $339. However, because poor states spent less money overall on social welfare, that $339 constituted a large proportion (83 percent) of their total spending on such programs. By contrast, the $371 per capita from federal sources spent by the richest quartile of states made up a much smaller share (58 percent) of their total social welfare budgets. That is, more federal money went to rich states than to poor states, but poor states relied more heavily on the federal government to support their social programs.
Per Capita Spending on Social Welfare and Non-social Welfare Functions,
The chart at the bottom of Exhibit 3 shows that state fiscal capacity was also positively correlated with state spending on non-social welfare functions. The differences across quartiles again were due to how much states spent of their own revenues. However, federal spending played a smaller role in this component of state budgets. Although federal spending averaged over two-thirds (69 percent) of state spending on social welfare functions, federal grants typically made up only about one-eighth (13 percent) of total state spending on non-social welfare functions.
The studys econometric models generally confirmed the importance of state fiscal capacity for spending on social welfare. State fiscal capacity was related to overall spending on social welfare even after controlling for other variables, such as social need (measured by per capita unemployment and poverty), federal grants per capita, population density, year effects, and long-run state effects.(1) State fiscal capacity was even more strongly related to spending on non-social welfare functions after controlling for these other factors, perhaps because states relied more on their own-source revenues in supporting non-social welfare functions.
When we broke total social welfare spending down into more specific categories, the relationships between state fiscal capacity and state spending varied greatly. As the chart at the top of Exhibit 4 demonstrates, states of lower fiscal capacity showed consistently lower levels of per capita spending on cash assistance and non-health social services when compared to wealthier states. Spending on health-related functions showed a weaker relationship to fiscal capacity than spending on non-health functions. Levels of spending on Medicaid were highest for the richest quartile of states, and spending levels were lower for Quartiles 2 through 4. Yet Medicaid spending showed no differences among Quartiles 2, 3, and 4, indicating a weaker relationship to fiscal capacity than found for cash assistance and non-health services. In the case of payments to public hospitals, the relationship was the inverse of what was found for social welfare spending. The poorest states spent the most per capita on public hospitals.
Spending Per Capita and Per Poor Person on Different Types of Social Welfare Functions,
Averages for Fiscal Capacity Quartiles, 19772000
Because most social programs targeted low-income people, per capita spending levels failed to capture differences in the degree to which states met social needs. To understand spending from that perspective, we compared state spending per poor person. Differences between rich and poor states were more consistent, as shown in the chart at the bottom of Exhibit 4. Disparities between the top and bottom quartiles were even greater for spending on cash assistance and non-health social services, while spending on Medicaid and public hospitals showed positive though weaker relationships to fiscal capacity. For example, the poorest states spent only one-fourth the amount that the richest states spent on cash assistance, while the ratio of spending on Medicaid in poor to rich states was about one-half.
As Exhibit 5 shows, Medicaid spending grew rapidly among all states in the late 1980s and early 1990s, even after controlling for the high rates of inflation in health care services. But the strongest growth occurred among the poorest states, those in Quartile 4, probably a consequence in part of federal Medicaid expansions in eligible populations, services, and special funding for health care providers during those years. In the middle and late 1990s, Medicaid spending growth slowed or even stalled among the wealthier states not surprisingly, given the strong economy and possible downward pressures on Medicaid caseloads exerted by welfare reforms. But the poorest states continued to show increases in spending even in the late 1990s. By 2000, differences between the richest and poorest states in per capita spending on Medicaid had narrowed substantially.
Changes in Average Per Capita Spending on Medicaid,
by State Fiscal Capacity, 19772000
Changes in real per capita spending on cash assistance varied even more across states, as Exhibit 6 illustrates. In the wealthier states of Quartiles 1 and 2, spending on cash assistance either declined slowly or remained static until the late 1980s, when spending began to grow. Spending then declined in the middle and late 1990s as caseloads dropped due to welfare reform and economic growth. Richer states thus reaped substantial fiscal savings in late 1990s from reductions in spending on cash assistance.
Changes in Average Per Capita Spending on Cash Assistance,
by State Fiscal Capacity, 19772000
(adjusted with GDP price deflator)
By contrast, spending on cash assistance was already low in poor states, so even large caseload declines in the late 1990s yielded small fiscal savings. State fiscal capacity became less correlated with spending on cash assistance programs at the end of the 1990s when compared to the early 1990s and before. In contrast to the upward convergence of states with respect to spending on Medicaid, states of different fiscal capacities converged downward in their spending on cash assistance after the early 1990s.
Spending on non-health social services programs, by contrast, showed growing divergence among states of different fiscal capacities, as Exhibit 7 shows. All quartiles gradually increased their spending on non-health social services between 1977 and 2000. But growth was faster among the wealthiest states, especially during the late 1990s, while spending growth on services in the poorest states (Quartile 4) lagged behind.
Changes in Average Per Capita Spending on Non-health Social Services Programs,
by State Fiscal Capacity, 19772000
(adjusted with GDP price deflator)
These different trends produced enormous changes in the composition of social welfare expenditures and in the relationship between state fiscal capacity and how states allocated their dollars across social welfare functions. Exhibit 8 shows these shifts by tracking the percentage of total public welfare spending for different program functions in the wealthiest and the poorest quartiles (Quartiles 1 and 4) during the years 1980, 1990, and 2000. Over these two decades, Medicaid came to absorb a much larger share of the budgets of both rich and poor states. Cash assistance spending shrank as percentage of total social welfare spending in all states, though most precipitously in rich states, thereby reducing differences between rich and poor states.
Average Percentage of Total Public Welfare Spending on Different Functions,
by State Fiscal Capacity (Quartiles 1 and 4), 1980, 1990, and 2000
One striking change was the growing disparity between rich and poor states in their spending on non-health social services. In 1980, poor states spent a slightly larger percentage of their social welfare budgets on such programs than did rich states. By 2000, poor states were spending a much smaller percentage of their social welfare budgets on non-health services. Most of the remainder of their social welfare budgets nearly three out of every four dollars was devoted to Medicaid.
Based on estimations of econometric models of state spending on different social programs in all states from 1977 to 2000, we found different types of programs to be influenced by different state characteristics. State fiscal capacity was positively related to Medicaid spending (i.e., rich states spent more than poor states, other things equal). We also found that Medicaid expenditures were positively related to unemployment. Medicaid spending responded strongly to federal grants for social welfare, perhaps reflecting the attractiveness to the states in matching federal Medicaid dollars. The regression equations also indicated that Medicaid spending was higher in states with lower population densities.
Unlike Medicaid, cash assistance spending was negatively related to state fiscal capacity.(2) Spending on cash assistance, however, was significantly and positively related to unemployment and federal grants. Thus, like Medicaid, cash assistance spending rose with unemployment, other things equal; and, though less strongly as Medicaid, cash assistance spending was encouraged by federal spending. Unlike Medicaid, however, cash assistance expenditures were higher among states with high population densities than among rural states.
Non-health social services mostly services such as child care, child welfare, and energy assistance, programs serving the homeless, and a wide variety of others responded to a different set of factors. State fiscal capacity and federal grants for non-social welfare programs strongly affected spending on these diverse services; also, spending was higher in low population density states. Spending on non-health social services was not sensitive to unemployment, like other program areas. In fact, a negative, albeit insignificant, relationship occurred between unemployment and service spending, other things equal. A negative, though significant, relationship also appeared between such spending and the percentage of people in poverty. These relationships suggest that a states total economic resources were critical in understanding spending for non-health social services.
In sum, the multivariate econometric analyses suggested the following:
By estimating regression equations for states of different fiscal capacities (i.e., for each of the four quartiles), we found that our general model of spending fit wealthy states more closely than poor states. In other words, poor states showed weaker relationships between the independent variables in the equations and all types of social welfare spending. For example, fiscal capacity, federal grants, unemployment, and population density were all significantly related to spending on cash assistance for the rich states in Quartile 1. Yet, only population density showed a significant relationship to cash assistance spending for the poor states in Quartile 4. Also, unemployment was positively and significantly related to Medicaid spending among Quartile 1 states, but the same coefficient was insignificant when the regression was estimated for Quartile 4 states. Similar differences in the degree of fit were found in equations for non-health social services, payments to public hospitals, and non-social welfare services.
But we found important exceptions. For Medicaid, federal spending for social welfare was at least as important for poor states in affecting state spending as it was for wealthier states. Population density was also important in many of the equations for poor states. Finally, our analyses of state effects revealed that poor states showed long-run differences in the ways they allocated their social welfare budgets, especially between cash assistance and health care programs, including Medicaid and payments to public hospitals. For example, poor western states showed higher levels of spending on cash assistance programs than did poor southern states, and they also showed lower levels of per capita spending on Medicaid. Poor states thus seemed to undergo smaller short-run changes in their spending patterns but did vary from one another based on relatively stable attributes, such as population density, region, and demographic composition of the states population.
When we examined what happened in the six poor states after 2000 and through 2003, when the case studies were completed we found that the trends identified between 1977 and 2000 generally continued. Per capita Medicaid spending increased in most states between federal FYs 2000 and 2003, and the growth was greater among the six poor states in our sample than for all states. Using administrative data from the federal agency responsible for Medicaid, we found, as the graph at the top of Exhibit 9 shows, that the average nominal growth in spending among the six poor states between 2000 and 2003 was slightly higher than the average growth in Medicaid spending for all states.
Per Capita Spending on Medicaid and TANF Basic Assistance,
Averages for the Six Poor States and for All States
Per capita spending on Medicaid, 19972003.
Per capita spending on TANF basic assistance, 19982002
Some of this growth was due to the fact that some of the poor states (notably New Mexico and Arizona) that had spent relatively little on Medicaid in the late 1990s greatly expanded their programs in the early 2000s. The most striking change occurred in Arizona. State voters overrode years of legislative opposition to Medicaid expansion in 2000 by enacting a citizens initiative, Proposition 204, that greatly expanded Medicaid coverage to include households up to 100 percent of the federal poverty level. Enrollment grew from 575,000 in January 2001 to 902,500 in January 2003. Louisiana also expanded eligibility for children and aged and disabled people in FY 2003, and it increased eligibility among pregnant women to include all those under 200 percent of the federal poverty level. Other major factors driving up Medicaid costs and noted by our respondents included expansions in enrollments due to the weakened economy and SCHIP outreach efforts and the substantial increases in prescription drug costs.
In recent years, TANF basic assistance constituted an important part of the cash assistance component of the Census data. Spending on this assistance continued to drop among all states between federal FYs 2000 and 2002, with an average decline of 13 percent, as the graph at the bottom of Exhibit 9 shows. However, as was also true before 2000, no average decline occurred among poor states in cash assistance spending. Mean cash assistance expenditures remained comparatively static among these states, as before 2000.
The econometric analyses indicated that non-health social services were most likely to show a cyclical effect (i.e., be vulnerable to cuts when government revenues declined). Our case studies confirmed that the greatest pressures on spending in the poor states were imposed on non-health social services and expenses. Administrative expenditures were often severely curtailed during the recent state fiscal crises. South Carolinas department of social services saw a 26 percent reduction in staff between FYs 2001 and 2003. Arizona reduced its human service workforce despite substantial increases in Medicaid and cash assistance caseloads. Administrative cutbacks were greater among poor states than among others. For example, TANF administrative costs per capita declined by 22 percent among the six states between FYs 2000 and 2002, while the average decline for all states was only 5 percent.
Legislatures often cut state spending on child welfare programs, including staffing and payments for protective services, foster care, and adoption. However, the effects of some of these cuts were sometimes mitigated by the greater use of federal TANF dollars to support such programs. A number of programs deemed less critical to basic agency goals were cut or eliminated, including parenting and fatherhood programs, employment services, job development positions, and pregnancy prevention programs. Some discretionary cuts in child care were imposed. However, because most of these states put small amounts of state money into their child care programs, only the two states that had put larger sums of TANF or state money into their subsidy programs in the 1990s (Arizona and Louisiana) made major reductions in their child care spending.
The case studies of the six poor states revealed important differences in the processes affecting spending on different social welfare functions. Cash assistance spending in low fiscal capacity states was largely determined by policies established through state legislation. These policies were changed infrequently in the six case study states. A flurry of policymaking around AFDC waivers and TANF cash assistance occurred in these and many other states in the middle and late 1990s. By 2003, however, TANF and its policies drew little attention from legislators in these six states and changes in earned income disregards, maximum benefits, time limits, and sanction policies had changed little since the late 1990s. For example, maximum benefit levels for AFDC and TANF assistance had changed only once or twice in most of the six states during the last 20 years. Debates over these policies also seemed more ideologically and racially charged than most other social policy questions.
Our site visits indicated that Medicaid spending processes were vastly different. Federal mandates, considerations of federal match rates, and active participation of organized provider groups that served as advocates for various parts of the program often dominated Medicaid spending. Perhaps because of the involvement of such groups, Medicaid was also a more politically salient program area. Unlike welfare, even the post-reform versions, health programs regularly engaged the attention of elected officials, including legislators, governors, and top administrators.
Among the six poor states in our sample, organized providers were especially strong in the four rural and southern states where Medicaid played a major role in the health care industry and local economy. In these states, hospitals and other health institutions played a large economic role; nursing home residents were more likely to rely on Medicaid; and a greater proportion of births, often more than half, were paid for by Medicaid. Also, most health institutions in these states relied on Medicaid, making it more of a universalistic program, in contrast to the situation in wealthy states, where some institutions depended heavily on Medicaid, while many did not.
Attractive federal match rates were often noted in debates over Medicaid budgets in poor states, especially during periods of budgetary stress. By themselves, however, match rates appeared to constitute insufficient conditions for understanding levels of support for Medicaid in poor states because equally strong match rates had been available under AFDC and were still available under child welfare programs, though with much less expansive effects. However, the combination of attractive match rates, federal minimum requirements, and strong constituencies seemed critical and meant that, even in poor and conservative states, medical assistance programs could enjoy substantial support.
Other factors might have bolstered support for Medicaid. In most of the states, the agencies that administered Medicaid were separated from those that administered welfare and non-health social services, and that separation insulated health programs from the often negative views about social service agencies held among legislators.
Our case studies indicated that, for the most part, non-health service programs elicited less political interest. These programs did not evoke the ideological divisions affecting cash assistance programs. Nor did they elicit participation of major provider groups in these low-fiscal capacity states. As a result, decisions in poor states about what programs to support in this diverse category of non-health social services were often delegated to and controlled by state administrators rather than legislators and governors. Choices regarding non-health services were more likely to reflect a sort of technocratic politics. Decisions were often made on the basis of state administrators assessments about the relative merits of different programs and their centrality in achieving major goals.
However, though administrators had some control over which programs grew and which were cut, they had little control over general fiscal constraints, and these changing constraints often dominated recent budgetary processes for this group of programs. Since the last recession, legislatures and governors typically instructed social service agencies in the six case study states how much they must cut from their total budgets, not precisely where to reduce services. Administrators often made cuts based on judgments about what services were critical to major agency goals, what programs were successful in terms of performance standards, what programs were needed to create or maintain a coherent package of benefits or services, what programs involved high stakes (e.g., life or death issues), and how and whether programs can be administered with fewer staff.
This study sought to understand how state fiscal capacity affected spending on social welfare programs. It found that low fiscal capacity states spent less on social welfare programs than did high fiscal capacity states and that these differences were greater for cash assistance and non-health social services than for health-related programs.
We also found that the level and composition of social welfare spending changed enormously in the last two and a half decades. Medicaid spending grew much faster than overall social welfare expenditures, particularly since the late 1980s. Cash assistance spending was more volatile rising in the early 1990s and falling in the late 1990s though the general tendency was down. Non-health social services grew more steadily throughout the period. These trends produced a major shift in the basic structure of state social welfare budgets, away from cash assistance and toward health care services. At the same time, a major realignment occurred in the relationship between the composition of social welfare services and state fiscal capacity. Per capita expenditures on Medicaid and cash assistance by rich and poor states converged, especially since the middle 1990s. By contrast, per capita spending on non-health social services diverged, with rich states spending much more than poor states on these programs.
These shifting patterns of spending are partly understandable in light of our findings that different social programs respond to different factors and that states of different fiscal capacity vary in their responsiveness to the same variables. Unemployment, for example, changes the mix of expenditures, as higher unemployment increases Medicaid spending and fails to boost non-health social services. Increases in state per capita personal income tend to push up Medicaid and non-health social services while showing an inconsistent effect on cash assistance.
Our case studies also suggested that different institutional processes characterize different program areas. Although these findings are limited to these six poor states, they also indicate the possibility of dramatically different dynamics across program areas. The greater role of ideology and demographic characteristics in decisions affecting cash assistance expenditures; the importance of federal match rates, minimum requirements, and organized providers in Medicaid politics; and the significance of overall state resources and flexibility in non-health social services all suggest that the mix of social welfare programs is likely to continue to change.
(1) State effects are separate intercepts estimated in the regression models for each of the 50 states (plus the District of Columbia). They may be viewed as average differences in state spending over the entire period (1977-2000), after controlling for the linear effects of the included variables, such as fiscal capacity and unemployment. State effects may, for example, be the result of differences in state political cultures, which were not directly measured in this study. Year effects are dummy or binary variables representing each year of the time series. A year effect indicates an average difference in spending across all states compared to some baseline year. A significant year effect may result from a national policy change or some other factor operating on all states but not fully measured by the independent variables included in the regression.
(2) However, when the equations were estimated for each fiscal capacity quartile, only the wealthiest quartile (Quartile 1) showed a negative and significant relationship.
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Human Services Policy (HSP)
Assistant Secretary for Planning and Evaluation (ASPE)
U.S. Department of Health and Human Services (HHS)
Last revised: 06/10/08