State and Local Governments' Fiscal Outlook: 2019 Update
Released: 2019-12-19T00:00:00

Letter

State and Local Governments Will Need to Make Policy Changes to Achieve Fiscal Balance

Our simulations suggest that the sector will likely continue to face a difference between revenues and expenditures during the next 50 years, as measured by its operating balance. We simulated the state and local government sector’s operating balance—a measure of the sector’s ability to cover its current expenditures out of current revenues—to understand the sector’s long-term fiscal outlook based on historical revenue patterns and other assumptions. Because a great majority of states and many local governments are required to balance or nearly balance their operating budgets, the operating balance illustrates the magnitude of fiscal pressures they face. Expenditures and revenues are both simulated to increase as a percentage of gross domestic product (GDP) during the simulation period. However, expenditures are generally expected to grow at a faster rate than revenues, resulting in a declining operating balance (see figure 1).

One way of measuring the long-term fiscal challenges faced by the state and local government sector is through an indicator known as the “fiscal gap.” The fiscal gap is an estimate of annual changes in expenditures and in revenues our simulations suggest would be needed to maintain the operating balance equal to zero during the 50-year simulation period. The sector could close the fiscal gap through an increase in revenues, a reduction in expenditures, or a combination of the two of sufficient magnitude. Our simulations suggest that the fiscal gap is about 3.6 percent of GDP over the next 50 years.

The sector will need to take actions in annually reducing its expenditures or raising revenues, to achieve fiscal balance. Assuming no change in simulated expenditures, the sector would need to take actions equivalent to increasing its total revenues by 4.2 percent each year to achieve fiscal balance. Alternatively, assuming no change in its simulated revenues, the sector would need to take actions equivalent to decreasing its noninterest expenditures by an amount equal to 3.2 percent of its total expenditures each year. Total expenditure reductions required by the sector are 20.7 percent each year, which includes interest payments on debt that are simulated to be 17.4 percent of annual spending. To eliminate the fiscal gap, the sector would most likely take actions that include a combination of expenditure reductions and revenue increases.

Health Care Cost Growth and Other Factors Contribute to the State and Local Sector’s Fiscal Imbalance

States’ Spending on Medicaid is a Key Driver of Long-Term Expenditures

Our simulations suggest that growth in the sector’s overall expenditures is largely driven by health care expenditures. Medicaid will likely constitute a growing expenditure for state and local governments. In 2018, Medicaid spending was 2.9 percent of GDP compared to 0.85 percent of GDP for other kinds of health care spending such as non-Medicaid social benefit payments and employee health benefit contributions. At the end of our simulations, Medicaid is simulated to be 4.6 percent of GDP and the other kinds of health care spending are 1.3 percent of GDP. After 2029, Medicaid spending in our simulations is derived from Centers for Medicare & Medicaid Services’ (CMS) projections. On average, Medicaid expenditures are expected to rise by 1 percentage point more than GDP each year over the simulation period. Breaking this down, Medicaid expenditures per capita are expected to increase, on average, about 0.6 percent faster than GDP per capita—referred to as excess cost growth.

Excess Cost Growth The extent to which health care costs per capita outpace gross domestic product (GDP) growth per person.

As shown in figure 4, health care expenditures are simulated to increase from about 3.94 percent of GDP in 2019 to 5.9 percent of GDP in 2068. In comparison, nonhealth, noninterest expenditures, which include all other operational expenditures other than debt interest payments, will decrease as a share of GDP by 2.74 percentage points over the simulation period. Per capita, national health expenditures, which make up part of the health care expenditures in the figure below, are expected to grow on average 0.8 percent faster than GDP each year during the simulation period, according to CMS.

Employee Compensation Decreases as a Share of the Sector’s Expenditures during the Simulation Period

Employee compensation is the largest expenditure for the state and local government sector. It declines from 6.8 percent of GDP in 2018 to 6.1 percent of GDP in 2068. All spending components, including employee compensation, are simulated to increase in actual dollar amounts during our simulation period. Of the spending components included in employee compensation, only health benefits for employees and retirees increase as a share of employee compensation. In contrast, wages and salaries, pension contributions, and other forms of compensation decrease as a share of employee compensation (see figure 5). These percentages reflect a simulated decrease in state and local government employees’ compensation as a share of GDP.

Our simulations suggest that spending on health benefits for state and local government employees and retirees is likely to rise, on average, by 0.9 percentage points more than GDP each year. Similar to the growth in Medicaid spending, growth in spending for these health benefits is due to an increase in the simulated number of employees and retirees enrolled as well as an increase in the simulated amount of health benefits for each employee and retiree. According to our simulations, if employee and retiree health benefits follow trends in overall national health spending, they will likely make up an increasingly larger share of total employee compensation going forward.

Our simulations suggest that annual contributions to state and local government employee pension plans will need to remain at their historical 10-year average of 12.9 percent of wages and salaries for state and local governments to meet their long-term pension obligations. Prior to the last decade, from 1999 to 2008 the state and local government sector averaged about an 8 percent contribution rate, which was lower than what our current simulations show is necessary for meeting pension obligations. State and local government contributions to employee pension plans are simulated to decline as a share of GDP, as are wages and salaries of state and local government employees.

Growth in Federal Medicaid Grants Drives Revenues

Our simulations suggest that federal grants will increase slightly as a share of GDP. The largest grant receipts are for Medicaid which will likely grow more quickly than other types of federal grants making up an increasing share of revenues in the future (see figure 6). The increase in Medicaid expenditures simulated during this period will likely put increasing pressure on both federal and state governments. As a matching formula grant program, the simulated increase in federal Medicaid grants implies an expected increase in Medicaid expenditures that will be shared by state governments. Federal investment grants (i.e., grants intended to finance capital infrastructure investments) and other federal grants unrelated to Medicaid (i.e., grants intended to finance education, social services, housing, and community investment) are simulated to decline as a share of GDP.

Further, our simulations suggest that if historical relationships between state and local governments’ tax revenues and tax bases persist, total tax revenues for the state and local government sector will increase from 8.7 percent of GDP in 2019 to 9.1 percent of GDP by the end of the simulation period. As shown in figure 7, the different components of total tax revenues are simulated to remain fairly consistent or slightly increase. The simulations suggest that personal income tax revenues will increase as a share of GDP by about 0.5 percentage points during the simulation period. Sales tax is expected to decrease by approximately 0.2 percentage points and property taxes are simulated to slightly increase as a share of GDP through 2068 from 2.73 percent to 2.86 percent.

Economic Growth and Other Factors Could Affect the Sector’s Fiscal Outlook

Sensitivity Analysis An analysis using alternative assumptions of one variable to determine the uncertainty, or sensitivity, of another variable.

Several factors, or key model variables, could affect the state and local government sector’s long-term fiscal outlook, including economic growth, health care excess cost growth, and the rate of return on pension assets. To see how the outlook changes in response to them, we developed sensitivity analyses—simulations that use alternative assumptions about their growth. For each of these key variables we use a baseline assumption, a higher-than-baseline assumption, and a lower-than- baseline assumption. We determined that these alternative assumptions highlighted the operating balance’s sensitivity to changes, shifting the future fiscal outcomes for the sector.

Economic Growth

Future trends in GDP growth could affect the state and local government sector’s fiscal outlook. In our simulations, GDP growth is based on the most recent data from the Congressional Budget Office (CBO) and the Board of Trustees of the Federal Old-Age and Survivors Insurance and Federal Disability Insurance Trust Funds (OASDI Trustees) which project real GDP (adjusted for inflation) to grow by 1.9 percent per year on average from 2018 through 2029, and by 2 percent per year on average after 2029. Using these projections, our simulations suggest that maintaining current policies would cause the sector’s operating balance to become increasingly negative. Using the OASDI Trustees’ alternative assumptions of real GDP growth at a faster rate—2.7 percent—suggests that the operating balance, while remaining negative, would have an improved outlook compared to the baseline.

While growth in revenue and health care spending is largely tied to GDP in our simulations, spending for other components is tied to inflation and population growth and grows more slowly than GDP. As such, increases in GDP growth improve the sector’s outlook. Our simulations, using the OASDI Trustees’ alternative assumptions also show that if GDP were to grow at a slower rate—1.4 percent—the difference between revenues and expenditures would expand, resulting in an increasingly negative operating balance (see figure 8).

Excess cost growth in health care is another key determinant of the sector’s fiscal balance. In our simulations Medicaid spending per capita grows about 1.8 percent faster than GDP per capita on average for the period from 2020 through 2029. Medicaid spending per capita grows about 0.6 percent faster on average from the period from 2030 through 2068. Other health expenditures per capita grow about 0.8 percent faster than GDP per capita for the period from 2019 through 2068. Using these projections, our simulations suggest that maintaining current policies will cause the sector’s expenditures to exceed its revenues and this difference will become increasingly negative during the next several decades.

The simulations developed assuming zero excess cost growth in Medicaid and national health expenditures suggest that spending would be lower as a share of GDP. The difference between revenues and expenditures would be significantly less negative than the baseline simulations around the middle of the simulation period before stabilizing, but remain negative over the simulation period. In the scenario using the alternative projections from CMS where excess cost growth rises faster— 0.6 percent on average for Medicaid for the period from 2030 through 2068 and 0.9 percent for national health expenditures for the period between 2019 through 2068—our simulations show that the difference between revenues and expenditures would persist for the remainder of the simulation period (see figure 9).

The rate of return on pension assets could also affect the state and local government sector’s fiscal outlook. Based on an inflation-adjusted rate of return on pension assets of 5 percent, our simulations suggest that state and local governments would need to make pension contributions equivalent to about 13 percent of employees’ wages and salaries to meet their long-term pension obligations. The simulations we developed using a higher rate of return—7.5 percent—suggest that pension contributions would be about 3 percent of state and local government employees’ wages and salaries to meet pension obligations. Under this scenario, spending would need to be a lower share of GDP and the sector’s outlook would improve. The difference between revenues and expenditures would briefly narrow early on before becoming increasingly negative through the remainder of the simulation period.

Alternatively, we estimated that if the rate of return on pension assets is relatively low—2.5 percent—required pension contributions would need to be about 24 percent of state and local government employees’ wages and salaries. Under this scenario our simulations show that spending would be a higher share of GDP and the sector’s outlook would worsen as the sector’s negative operating balance would continue to grow larger (see figure 10).

This report was prepared under the direction of Michelle A. Sager, Director, Strategic Issues, who can be reached at 202-512-6806 or sagerm@gao.gov, and Oliver M. Richard, Director, Center for Economics, who can be reached at 202-512-8424 or richardo@gao.gov if there are any questions. GAO staff who made key contributions are listed in appendix II.

Appendix I: Objectives, Scope, and Methodology

Data

This update of the state and local government fiscal model used aggregate data on the state and local government sector and national data on other variables from the following sources: the Agency for Healthcare Research and Quality, Bloomberg, the Board of Governors of the Federal Reserve System, the Board of Trustees of the Federal Old- Age, Survivors, and Disability Insurance Program (OASDI Trustees), BEA, the Bureau of Labor Statistics, the Census Bureau, the Centers for Medicare & Medicaid Services (CMS), the Congressional Budget Office (CBO), and the Social Security Administration. These data sources are generally the same data sources we used for our prior update. We used annual observations on historical data through 2018 where available.

Objectives and Methodology

This report updates GAO’s state and local fiscal model to simulate the fiscal outlook for the state and local government sector. This includes identifying the factors that are likely to contribute to the state and local sector’s fiscal imbalance. The level of receipts and expenditures for the state and local government sector as a whole in future years is based on current and historical spending and revenue patterns. We used Table 3.3 of the National Income and Product Accounts (NIPA)—State and Local Government Current Receipts and Expenditures—prepared by BEA as an organizing framework for developing our model, and we simulated state and local government receipts and expenditures using methods similar to those we have used in prior updates. Our simulations of real U.S. gross domestic product (GDP) were consistent with the growth path developed by CBO for the period from 2019 through 2029 and by the OASDI Trustees for the period thereafter. Our simulations of U.S. population was consistent with the growth path developed by the OASDI Trustees, and our simulations of excess cost growth for national health expenditures and for Medicaid were consistent with CMS projections, all for the entire simulation period. Our simulations of other variables, such as the GDP price index, personal income, and 3-month U.S. Department of the Treasury (Treasury) rates, were consistent with the growth paths for these variables developed by CBO for as much of the simulation period as possible. Otherwise, we developed our own assumptions about the likely future growth path of the variables in our model. In general, we assumed that current policies remain in place and that all levels of government continue to provide services at current per capita levels. A detailed description of the model is in appendix I of GAO, State and Local Governments’ Fiscal Outlook: 2018 Update, GAO-19-208SP (Washington, D.C.: December 2018). We describe below where we updated equations or added equations to the model. Otherwise our approach is the same as the approach we used in that update.

State and Local Government Sector Receipts

We simulated the future growth paths of the following types of state and local government revenues: current tax receipts, contributions to government social insurance, income on financial assets, current transfer receipts, the surplus from government enterprises, and capital transfer receipts. We also simulated the future growth path of state and local government long-term debt issuance. We updated some of the equations we used to simulate tax receipts(see table 1). We also added equations to simulate current transfers from the rest of the world to state and local governments, disaster-related insurance benefits to state and local governments, and other capital transfers to state and local governments, which we had not included in prior updates. The equations we used to simulate the other types of receipts are the same as the equations we used in GAO-19-208SP.

We simulated the future growth paths of the following types of state and local government expenditures: consumption expenditures, current transfer payments, interest paid on outstanding state and local government debt, subsidies, capital outlays, and consumption of fixed assets (depreciation). We also simulated the future growth path of the state and local government sector’s net social insurance fund balance. We updated some of the equations we used to simulate the interest paid on outstanding state and local government debt (see table 1 above). We also added equations to simulate current transfer payments to the rest of the world, which we had not included in prior updates. Otherwise, the approach we used to simulate expenditures is the same as the approach we used in GAO-19-208SP.

State and Local Government Sector Fiscal Balance

Our main indicator of the sector’s fiscal balance is its operating balance net of funds for capital expenditures (henceforth, operating balance), which is a measure of the sector’s ability to cover its current expenditures out of current receipts. Operating balance is defined as total receipts minus (1) capital outlays not financed by long-term debt issuance, (2) current expenditures less depreciation, (3) current surplus of state and local government enterprises, and (4) net social insurance fund balance.

We also estimated the annual changes in spending and in receipts that our simulations suggest would be needed to maintain the operating balance equal to zero during the 50-year simulation period, which we refer to as the “fiscal gap.” As discussed above, our baseline simulations assume that current policies remain in place and that all levels of government continue to provide services at current per capita levels. We then simulated the change in total expenditures needed to maintain the operating balance equal to zero. To estimate the annual change in spending needed to maintain balance we calculated the present value of that change as a percentage of the present value of baseline total expenditures and as a percentage of the present value of U.S. GDP, all for a 50-year period. We also calculated the interest and non-interest expenditure components of the change in total expenditures needed to maintain balance. We used a similar approach to estimate the annual change in total receipts needed to maintain balance.

Sensitivity Analysis

We assessed the sensitivity of our baseline results to alternative projections of real U.S. GDP growth, health care excess cost growth, and the real rate of return on state and local government pension fund assets. Following the same approach we used in GAO-19-208SP, for each of these variables, we selected an alternative projection associated with faster growth or rate of return and one associated with slower growth or rate of return.

Real U.S. GDP. For our baseline simulations, we used CBO projections of real GDP for the period from 2019 through 2029 and the OASDI Trustees’ intermediate projections of real U.S. GDP growth for the years thereafter. For our sensitivity analysis, we used the OASDI Trustees’ high-cost and low-cost projections.

Health care excess cost growth. For our baseline simulations, we used CMS’s baseline projection of national health expenditures excess cost growth and we estimated Medicaid excess cost growth based on CMS’s baseline projections. For our sensitivity analysis, we used CMS’s alternative projection of national health expenditures excess cost growth and we estimated Medicaid excess cost growth based on CMS’s alternative projections. As another alternative, we simulated the model assuming both zero excess cost growth for national health expenditures and Medicaid. Our simulations used CBO’s projection of federal spending on Medicaid, CHIP, and exchange subsidies as a fraction of GDP to simulate certain variables related to state and local government spending on Medicaid and other health spending. This projection incorporates excess cost growth for the period from 2019 through 2029 but assumes zero excess cost growth starting in 2030, so we could only vary Medicaid excess cost growth in the alternative simulations for 2030 and later.

Real rate of return on state and local government pension assets. For our baseline simulations, we assumed a 5 percent real rate of return on state and local government pension assets. For our sensitivity analysis, we used 2.5 percent and 7.5 percent.

Table 2 shows the growth rates or rates of return associated with the baseline and alternative projections of each variable for the simulation period.

We simulated the model changing either real U.S. GDP growth, health care excess cost growth, or the real rate of return on pension assets, leaving the other variables fixed at their baseline values. Thus, our sensitivity analysis is in the spirit of a partial equilibrium comparative statics analysis that sheds light on how each of the individual variables may affect the state and local government sector’s fiscal outlook. However, these variables are likely to be correlated, so future changes in one would likely be associated with changes in others.

Caveats and limitations

Our approach has a number of limitations and the results should be interpreted with caution. First, the state and local fiscal model is not designed for certain types of analyses. The simulations are not intended to provide precise predictions. Even though we know that these governments regularly make changes in tax laws and expenditures, the model essentially holds current policies in place and analyzes the fiscal future for the sector as if those policies were maintained because it would be highly speculative to make any assumptions about future policy adjustments.

In addition, fiscal outcomes related to the sector’s financial position and solvency may not reflect all aspects of the sector’s “health.” Other indicators include economic indicators that go beyond the sector’s financial position to include economic growth, income, or distributional equity, as well as indicators of the quality of services provided by the sector, including education, health care, infrastructure, and other public goods and services.

Finally, our unit of analysis is the state and local government sector as a whole, so our results provide an assessment of the sector’s fiscal outlook. However, individual state and local governments likely exhibit significant heterogeneity in their expenditure and revenue patterns and their fiscal outlooks will likely differ from the sector as a whole. Nevertheless, it is informative to assess the overall fiscal outlook because doing so reveals the outlook for state and local governments as a sector. In addition, aggregate data on the sector is available on a more timely basis than data for individual state and local governments, allowing for a better assessment of the sector’s current fiscal outlook. Our results for the sector also provide a baseline from which to view the experiences of individual state and local governments. Finally, assessing the fiscal outlook of the sector as a whole can help mitigate the tendency to extrapolate from the most visible, but potentially not representative, experiences of individual states or localities.

Appendix II: GAO Contacts and Staff Acknowledgments

GAO Contacts

Acknowledgments

In addition to the contact named above, Peter Del Toro, Courtney LaFountain, Melissa Wolf (Assistant Directors), Silvia Symber (Analyst-in- Charge), Shelby Clark, Amalia Konstas, Dylan Stagner, Frank Todisco, Walter Vance, and Alicia White made significant contributions to this report.

Related GAO Products

State and Local Governments’ Fiscal Outlook: December 2018 Update, GAO-19-208SP. Washington, D.C.: Dec. 12, 2018.

State and Local Governments’ Fiscal Outlook: December 2016 Update, GAO-17-213SP. Washington, D.C.: Dec. 8, 2016.

State and Local Governments’ Fiscal Outlook: December 2015 Update, GAO-16-260SP. Washington, D.C.: Dec. 16, 2015.

State and Local Governments’ Fiscal Outlook: December 2014 Update, GAO-15-224SP. Washington, D.C.: Dec. 17, 2014.

State and Local Governments’ Fiscal Outlook: April 2013 Update, GAO-13-546SP. Washington, D.C.: Apr. 29, 2013.

State and Local Governments’ Fiscal Outlook: April 2012 Update, GAO-12-523SP. Washington, D.C.: Apr. 5, 2012.

State and Local Government Pension Plans: Economic Downturn Spurs Efforts to Address Costs and Sustainability, GAO-12-322. Washington, D.C.: Mar. 2, 2012.

State and Local Governments’ Fiscal Outlook: April 2011 Update, GAO-11-495SP. Washington, D.C.: Apr. 6, 2011.

State and Local Governments: Knowledge of Past Recessions Can Inform Future Federal Fiscal Assistance, GAO-11-401. Washington, D.C.: Mar. 31, 2011.

State and Local Governments: Fiscal Pressures Could Have Implications for Future Delivery of Intergovernmental Programs, GAO-10-899. Washington, D.C.: July 30, 2010.

State and Local Governments’ Fiscal Outlook: March 2010 Update, GAO-10-358. Washington, D.C.: Mar. 2, 2010.

Update of State and Local Government Fiscal Pressures, GAO-09-320R. Washington, D.C.: Jan. 26, 2009.

State and Local Fiscal Challenges: Rising Health Care Costs Drive Long- term and Immediate Pressures, GAO-09-210T. Washington, D.C.: Nov. 19, 2008.

State and Local Governments: Growing Fiscal Challenges Will Emerge during the Next 10 Years, GAO-08-317. Washington, D.C.: Jan. 22, 2008.

Our Nation’s Long-Term Fiscal Challenge: State and Local Governments Will Likely Face Persistent Fiscal Challenges in the Next Decade, GAO-07-1113CG. Washington, D.C.: July 18, 2007.

State and Local Governments: Persistent Fiscal Challenges Will Likely Emerge within the Next Decade, GAO-07-1080SP. Washington, D.C.: July 18, 2007.