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Turbulent Times: NH's State Budget, 2008 to 2013

Executive Summary

Date: May 1st, 2013

This paper has several aims: to outline the major changes in New Hampshire’s state budgets made over the course of the Great Recession; to put those changes in a broader historical context; and to help policy makers understand the potential impact of these changes, with a specific focus on New Hampshire’s health and human service programs and state aid to cities and towns.

Over the past three decades, many of the particulars of state spending in New Hampshire have remained remarkably consistent, in terms of annual increases in spending and the distribution of spending across state agencies. But the past five years have seen a sharp shift in those patterns. Actual state spending in 2012 was only slightly higher than in 2008, despite the fact that many of the costs of state government increased over that period. In addition, the recession increased demand for many state services in those years.

Among our findings:

1. Spending reductions since the beginning of the recession have disproportionately focused on a small share of state programs. The 9.2 percent decline in budgeted appropriations in the FY2012-2013 state budget was not spread evenly across state government. The vast majority of those cuts came in a small handful of programs and agencies: the public university and community college systems; payments to hospitals; and the state retirement system.

2. Almost two-thirds of the spending reductions in health and human services came as cuts to provider payments, rather than program changes. Between 2008 and 2012, the New Hampshire Department of Health and Human Services (DHHS) budget decreased by roughly $480 million. Slightly more than 60 percent of that represented reimbursement rate reductions, with half of that resulting from changes in reimbursements to the state’s hospitals.

3. Human service caseloads and services continued to grow across the study period. The number of individuals receiving services from DHHS increased by more than 5.4 percent each year from 2008 to 2012. Food stamp and nutritional supplements grew the most quickly, at 15.1 percent. Medicaid enrollment increased by 5.2 percent per year, led by increases in growth in developmental services recipients. Financial supports saw the steepest cuts, declining by 10 percent.

4. The impact on service caseloads of several programs needs more careful analysis. Data on the effect of three of the largest changes to the DHHS budget (excluding provider reimbursement changes) – changes in the Children in Need of Service process, restructuring of transitional housing services, and the removal of the rental subsidy for housing assistance – are not available. Thus, a thorough analysis of the impact of these changes on program recipients is not possible at this time.

5. In addition to the direct health impacts of changes in DHHS, there are indirect impacts as well. Local expenditures on health and welfare have declined relative to inflation and population growth, which may have a potential impact on health and well-being associated with changes in the state’s contribution to local budgets. Reductions in municipal aid and local revenues appear to have contributed to a shift in appropriations from health and welfare to other local programs.

Recommendations for review

For budget makers and others trying to understand how the budgetary changes have shaped New Hampshire’s various health and human service programs, this analysis suggests three potential areas for review. First, the non-profit community has seen significant reductions in reimbursement rates. Little comprehensive data is available to show how these changes have impacted the non-profits and the services they provide. 

Second, this analysis suggests that while the number of individuals receiving services through the medical safety net programs continued to grow over the time period, the financial safety net may have faced significant reductions.  How these spending reductions impacted individuals is not clear. However, the combination of declines in financial support, supportive housing, and local welfare expenditures suggest that further analysis may be warranted to help policy makers understand the implications of budgetary changes.    

Finally, this paper also raises questions about how state policymakers should evaluate and assess budgetary changes in the future. Since the state budget is complex network of connected systems, understanding the impact of any spending change requires analysis across a broad range of policies. What changes in the way the state gathers and reports data would improve efforts to assess those changes across programs and in terms of the people affected, rather than simply in dollar amounts increased or decreased? How can that information by used by policymakers during the biennial budget-writing process? If policymakers are interested in restoring funding for services that have previously been cut, how will they determine which spending increases would result in the most value to the state? We hope this work will provoke a discussion around these questions.

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