Two states had more than $200 billion in public pension debt: California ($265 billion in unfunded pension liabilities) and Illinois ($201 billion).

Two other states reported more than $90 billion in unfunded pension liabilities: Texas ($92.2 billion) and New Jersey ($92 billion).

Unfunded liabilities exceeded $60 billion in two additional states: Pennsylvania ($67 billion) and Ohio ($61 billion).

Fourteen states have more than $30 billion in unfunded liabilities, including Massachusetts ($44 billion), Florida ($44 billion), New York ($45 billion), Kentucky ($40 billion), Connecticut ($37 billion), Michigan ($36 billion), Georgia, ($33 billion), and Maryland ($31 billion).

Tennessee, Washington, and South Dakota are the only three states that did not report any aggregate unfunded pension liabilities at the end of 2024, according to Reason Foundation’s pension report.

With $15,804 in pension debt per person, Illinois has the highest unfunded pension liabilities per capita, according to the Reason Foundation report.

Connecticut has the second-most public pension debt per capita at $10,151.

Six other states have public pension debt exceeding $8,000 per person: Alaska ($9,990), Hawaii ($9,784), New Jersey ($9,688), Mississippi ($9,033), New Mexico ($8,641), and Kentucky ($8,626).

California and Massachusetts have more than $6,000 in pension debt per resident.

Thirty-five states have at least $2,000 in public pension debt per capita, and 45 have at least $1,000 per person.

In the aggregate, state and local pension plans had $1.48 trillion in debt. Reason Foundation finds that the median funded ratio of all U.S. public pension plans was 79% at the end of 2024. This means governments have 79 cents for every dollar of pension benefits already promised to public workers and retirees.

With its public pension systems just 52% funded, Illinois has the worst funded ratio in the nation.

The other states with funding below 60% are Kentucky (54%), New Jersey (55%), Mississippi (56%), and Connecticut (59.5%).

State with public pension systems with funded ratios below 70% are South Carolina (62%), Hawaii (63%), Rhode Island (65%), New Mexico (66%), Pennsylvania (66%), Massachusetts (66%), Vermont (67%), New Hampshire (69%), and Colorado (70%).

Just three states had fully funded public pension systems at the end of 2024: Tennessee (104% funded), Washington (102%), and South Dakota (100%) and another six states were over 90% funded.

For detailed information about public pension plans’ unfunded liabilities, asset allocation, contribution rates, stress testing, and more, please visit Reason Foundation’s full Annual Pension Solvency and Performance Report.

The report ranks public pension systems from best to worst across five core dimensions: funded status, investment performance, contribution rate adequacy, asset allocation risk, and probability of meeting assumed returns.

Reason Foundation extracted these values from publicly available audited financial reports. Despite a thorough review, data collection at this scale can lead to discrepancies. Please alert us if you identify any errors. Reason Foundation’s pension team provides tailored technical assistance and resources to address the specific needs of states, counties, and cities. So please don’t hesitate to contact us at pensionhelpdesk@reason.org.

The post Study: Illinois, Connecticut, Alaska, Hawaii, New Jersey and Mississippi have the most per capita pension debt appeared first on Reason Foundation.

Reason Foundation finds that 18 public pension plans now have over $20 billion in debt each, nine systems have more than $30 billion, and one, CalPERS, has over $100 billion in unfunded liabilities. At $166 billion in debt, the California Public Employees Retirement Fund, the largest public pension system in the country, had the most pension debt in the nation at the end of 2024, the most recent year with complete data available.

The next five public pension systems with the most unfunded liabilities are all teachers’ retirement plans: the Illinois Teachers Retirement System ($83 billion in unfunded liabilities), the Texas Teacher Retirement System ($63 billion), the Pennsylvania Public School Employees’ Retirement System ($43 billion), the New Jersey Teachers’ Pension and Annuity Fund ($41 billion), and the California State Teachers Retirement System ($40 billion).

The three other public pension systems with over $30 billion in unfunded liabilities are the Florida Retirement System ($39 billion), the New Jersey Public Employees Retirement System ($31 billion), and the Illinois State Employees Retirement System ($30 billion).

In the aggregate, the nation’s public pension systems reduced their unfunded liabilities from $1.62 trillion in 2023 to $1.48 trillion in 2024, a 9% decrease. But three public pension systems saw their debt grow by more than $1 billion in 2024. Unfunded liabilities grew by over $500 million in another five additional plans.

With a $1.54 billion increase in unfunded liabilities, the Maryland Teachers’ Retirement System saw the largest growth in public pension debt in the nation from 2023 to 2024. The system now has $14.56 billion in debt.

Unfunded liabilities also increased by over $1 billion in 2024 in the Massachusetts Teachers’ Retirement System ($1.17 billion increase in debt) and the Illinois Teachers’ Retirement System ($1.01 billion).

From 2023 to 2024, public pension debt increased by over $500 billion in another five plans: the Maryland State Employees’ Retirement System ($735 million increase in unfunded liabilities), the Alameda County Employees’ Retirement Association ($678 million), the Illinois State University Retirement System ($628 million), the New Mexico Public Employees Retirement Association ($601 million), and the Indiana Public Employees Retirement Fund ($502 million).

The 2024 fiscal year was strong for most investors and the stock market, but some public pension plans lagged behind. Failing to meet investment expectations increases public pension debt and taxpayers’ costs. The median investment return for public retirement systems in 2024 was 9.88%, according to Reason Foundation’s Annual Pension Solvency and Performance Report.

The Fire Fighters’ Relief and Retirement Fund of Austin, Texas, earned just a 4.7% return in 2024. It was the only pension system in the nation that earned less than a 5% return in 2024. The fund’s debt increased from $297.5 million to $349.5 million in 2024.

Five other public pension plans failed earn a 6% returns in 2024: the Kansas City Public School Retirement System (5.2%), the Educational Employees’ Supplementary Retirement System of Fairfax County (5.68%), Oregon Public Employees Retirement System(5.8%), Omaha City Employees Retirement System (5.92%), and the South Dakota Retirement System (5.98%).

At the other end of the spectrum, Reason Foundation finds that 11 public pension plans earned investment returns of over 15% in 2024, and five plans produced returns exceeding 20%.


The Miami General Employees and Sanitation Employees Plan earned a 24% return rate in 2024, the highest in the nation.

The Michigan Legislative Retirement System (23.94% return), the Alabama Judicial Retirement Fund (22.21%), the Alabama Employees’ Retirement System (ERS) (21.2%), and the Alabama Teachers’ Retirement System (21.1%) also produced returns of over 20% for 2024.

For detailed information about public pension plans’ unfunded liabilities, asset allocation, contribution rates, stress testing, and more, please visit Reason Foundation’s full Annual Pension Solvency and Performance Report.

The report ranks public pension systems from best to worst across five core dimensions: funded status, investment performance, contribution rate adequacy, asset allocation risk, and probability of meeting assumed returns.

These values were extracted from publicly available audited financial reports. Despite a thorough review, data collection at this scale can lead to discrepancies. Please alert us if you identify any errors. Reason Foundation’s pension team provides tailored technical assistance and resources to address the specific needs of states, counties, and cities. So please don’t hesitate to contact us at pensionhelpdesk@reason.org.

The post The public pension plans with the most debt, best and worst investment return rates appeared first on Reason Foundation.

Interest payments on the national debt are also climbing. In May, Moody’s downgraded the U.S. credit rating from AAA to Aa1. 

Still, the political will to address the national debt and federal budget deficits does not exist in meaningful numbers on either side of the political aisle. To get a clearer picture of why the national debt matters to taxpayers and future generations, how we got here, who holds this debt, and what would need to be done to rein it in, Reason Foundation built Debtor Nation.

Why the national debt matters

• The national debt is expensive: Debt incurs high interest costs, diverting taxpayer funds from productive uses to pay interest to bondholders.
• Debt burdens economic growth: Interest payments on the national debt consume a rising portion of the national budget and gross domestic product (GDP). This borrowing stifles economic growth by absorbing capital from the private sector, making borrowing more expensive for taxpayers and businesses.
• Debt imposes unfair costs on future generations: Future taxpayers are on the hook to pay for today’s deficits. They must accept either higher taxes, inflation, or reduced government services.
• The debt is becoming unaffordable: The current debt and projected reliance on debt increases the risk of higher borrowing costs, insolvency, and default.

How we got here 

• The annual U.S. debt-to-GDP ratio reached 120% in 2024, exceeding levels last seen immediately following World War II.
• Federal expenditures consistently outpace revenue, driving continued debt growth. Given that federal receipts bounce between 15% and 20% of GDP, spending more than 20% of GDP is simply not sustainable in the long term.
• Federal debt growth transcends party lines, driven by major events and policy decisions across presidential administrations and congresses.

Who holds the federal debt? 

• The federal debt is divided between intragovernmental holdings (primarily the Social Security Trust Fund) and debt held by the public.
• Public debt holders include domestic investors, foreign entities, and the Federal Reserve, which has significantly increased its holdings in recent years.
• Foreign ownership of U.S. debt represents a substantial portion, raising opportunities and potential economic stability risks.

Where does the federal government spend money? 

• Mandatory spending, including Social Security and Medicare, accounts for a significant portion of federal outlays, exceeding 65% of total annual expenditures.
• Interest payments on the national debt have reached historic levels, creating additional budget pressure.
• At $908 billion, defense spending remains the largest discretionary budget item, dwarfing other discretionary spending categories.

Conclusion 

You can view the full Debtor Nation data visualization tool here. The tool includes more insights into our national debt, along with a calculator that shows exactly what changes the federal government would need to make to help us climb out of the situation the national debt has put taxpayers and future generations in. 

The post Debtor Nation 2025 appeared first on Reason Foundation.

The Case for Connecticut’s Fiscal Guardrails: How to Protect Public Pensions and Taxpayers examines how they have improved Connecticut’s creditworthiness, making it less expensive for the state to borrow money to finance necessary projects. Moreover, the guardrails have reversed decades of pension underfunding, reducing the risk that Connecticut will face tax increases to make the pensions’ minimum liability payments during a recession.  

The interactive Reason Foundation-Yankee Institute CT Pensions Dashboard explores various economic scenarios for reducing the state’s public pension debt. The study and dashboard are built upon dual pension models of the State Employee Retirement System, SERS, and the State Teacher Retirement System, STRS. The models account for the assumed rates of investment returns, payroll growth rates, cost-of-living adjustment provisions, and mortality assumptions, among dozens of other variables.

Connecticut Pensions Dashboard

The post How Connecticut pensions can save $7 billion in interest costs over the next 30 years appeared first on Reason Foundation.

The table below is a snapshot of the forecasted 2023 unfunded accrued liabilities and funded ratios, organized by state, using a 7% return assumption for 2023. The table also presents the projected unfunded liabilities and funded ratios for each state under 5% and 9% investment return scenarios to give a range of potential investment return outcomes. 

Assuming a 7% return for the 2023 fiscal year, on a funded ratio basis, the state with the best pension funding is Washington, which sits at around 107% funded and has a surplus of $8 billion. New York is the other state project to have a surplus ($8.7 billion) at the end of 2023.

The other 48 states are projected to have public pension debt after their 2023 fiscal years. California has the largest amount of unfunded public pension liabilities, estimated at $245 billion after the 2023 fiscal year. Illinois and New Jersey are also forecast to have over $100 billion in unfunded liabilities at the end of 2023, followed by Texas with over $88 billion in public pension debt.

In terms of funded rations, a pension plan’s assets as a percentage of its liabilities, the lowest-funded state is Kentucky. Its public pensions are just 47% funded, with unfunded liabilities of $44 billion. New Jersey is the other state with a funded ratio under 50%, meaning it has less than half of the funding needed to pay for promised pension benefits.

In aggregate, state pension plans have reported mostly steady growth in unfunded obligations since the Great Recession of 2007-2009. In 2020, 2022, and now 2023, total state pension debt amounts were around the current level of $1.3 trillion, the highest total state pension debt ever seen. 

Funded ratios have improved gradually over that time—but very slowly. State pension plans' funded ratios hit a low of 63.5% funded in 2009 and are projected to be 76% funded after their 2023 fiscal years. This means that after 15 years of trying to recover from massive financial losses suffered in 2008 and 2009, state pension plans can only pay 76 cents of every dollar of retirement promises already made to teachers, police officers, firefighters, and other public workers. 

Only a few state-run pensions have reported their investment returns for the 2023 fiscal year. The 2023 investment returns that have been publicly released suggest a mixed set of results hovering above and below the nationwide average investment return assumption of 7%. 

Of the plans reporting investment results as of this writing, the best investment returns are from the Louisiana State Employees' Retirement System, with an 11.7% return for 2023, and the Oklahoma Public Employees Retirement System, with a 10.9% return for 2023. 

The lowest, or worst, investment returns reported so far are from the Indiana Public Retirement System, with a 2.2% investment return for 2023, and the Oklahoma Police Pension and Retirement System, with a 2.9% return for 2023. 

The State Pension Tracker dashboard allows users to select an investment return rate for 2023 to display how that result would affect public pension funding at a national, state, and plan-specific level.

The tool gives a valuable historical perspective on the funding progress of 118 state-run pension systems. As states gradually report their 2023 investment returns and eventually report their realized unfunded liabilities throughout the year, the dashboard will update to reflect these developments, making the State Pension Tracker a valuable source for fast, accurate, and up-to-date pension analysis.

Public pension funding is deeply influenced by annual investment returns, given that pensions are funded through employer and employee contributions and the investments made using those contributions. Investment returns are inherently volatile. They can fluctuate based on a wide range of economic factors, including market trends, inflation rates, and broader economic health. In years with substantial investment returns, pension funds can see their funded statuses improve, reducing the pressure on employers and governments to make up for any shortfalls through increased contributions. Conversely, in years with poor investment performance, the funded ratio can decline along with rising unfunded liabilities. 

Therefore, achieving consistent and positive investment returns is crucial for pension funds' long-term health and stability. Pension plan administrators aim to mitigate risks through diverse investment portfolios and asset allocation strategies that can weather market fluctuations and generate steady returns. However, the continued growth of unfunded liabilities has necessitated urgent and sustained interventions such as increased contributions, adjustments to benefit structures, and potentially, going forward, the exploration of more conservative investment expectations to mitigate future risks and ensure that pension promises made to public workers are kept.

Click here or on the dashboard preview below to explore the full State Pension Tracker.

For any questions about the State Pension Tracker or this analysis, please email Zachary Christensen at zachary.christensen@reason.org.

The post Forecast: State pension debt totals $1.3 trillion at the end of 2023 appeared first on Reason Foundation.

In 2006, Alaska’s two pension systems—the Teachers’ Retirement System (TRS) for teachers and Public Employees’ Retirement System (PERS) for all other public safety and government employees—were closed to new hires due to significant funding and cost issues. As part of that reform, all new and future hires were to be enrolled in a defined contribution (DC) plan. Even with no new entrants earning benefits in the closed plan, Alaska’s unfunded pension liabilities for current and retired public employees have grown to a combined $6.7 billion.

The argument being made today for reopening the defined benefit plan for existing and new workers is that the defined benefit plan supposedly provides a better benefit. Therefore, some claim it would improve Alaska’s ability to attract and retain teachers, public safety, and other government workers. However, an in-depth analysis that evaluates these two Alaska plans under several career situations shows that the defined benefit plan is not optimal for most workers. 

To foster informed decision-making in the legislative process, Reason Foundation’s Pension Integrity Project has developed a dynamic interactive analysis that compares Alaska’s DB and DC benefits under multiple variations of common situations, and we confirmed the validity of our analysis with the Alaska Department of Administration’s Division of Retirement and Benefits. 

A comprehensive comparison of the closed defined benefit plan, the DB proposed in Senate Bill 88 (currently being considered in the state legislature), and the existing defined contribution plan suggests that the DC plan is the optimal benefit for most new hires.

Any comparison between DB and DC benefits must first answer the question, ‘For whom?’ Both types of retirement benefits are subject to several factors that can vary significantly from person to person. The age a worker begins employment (or entry age) and the rules for when they can start drawing retirement benefits (requirements that differ between public safety, teachers, and other employment types) are major considerations. The investment returns on savings, annuity payout rates, and assumed wage increases also impact the value of benefits.

The dynamic benefit analysis of Alaska’s plans shows the annual retirement benefit (or annuity) that a retiree could expect after a range of years of service. To show how these benefits will compare over common situations and assumptions, all factors listed above can be adjusted and visualized for all years of service until full retirement eligibility is achieved.

Generally, the value of the defined contribution annuity will exceed that of the legacy defined benefit plan for many years of service. In most cases, the value of the DB benefits will surpass that of the DC plan only in later years of service, a situation that retention data suggests is much less common:

• According to assumptions used by PERS and TRS, about 50% of new public safety members and 70% of new teachers and other members leave within 10 years; and 
• About 60% of new public safety members and 77%-to-85% of new teachers and other members leave within 20 years (assuming an entry age of 25). 

This analysis shows that while a select group of workers could enjoy an improved benefit by reopening the defined benefit plan, the vast majority of Alaska’s public employees would be better served in the existing defined contribution plan.

Notes on Methodology

• To calculate the annual annuity for defined contribution plans, the analysis applies the assumed return to the required contribution amounts for the average starting salary of $80,435 for public safety members, $59,581 for teachers, and $57,949 for other members. 
• In situations where a member would fulfill the requirements for full pension benefits (based on either age or years of service), the analysis assumes the member would also use existing DC savings to purchase an annuity at that point. This can come after just 20 years of service for public safety members and teachers, which (depending on entry age) can mean beginning guaranteed benefits through annuities at an unusually early age, thus generating a significant reduction in annual benefits. This assumption can be toggled off in the tool with the “DC Annuitization at 60: Off” button.
• The annuity payout rate is the interest rate used to convert the DC balance into an annuity. We assume a life expectancy of 85 for the annuitization calculation.
• To calculate the annual annuity generated by the defined benefit plan, the analysis applies the selected variables to the plan’s existing benefit calculation.

The post Comparing Alaska’s defined benefit and defined contribution retirement plans appeared first on Reason Foundation.

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​​But cryptocurrencies are also exceptionally volatile over much shorter periods of time. ​Day-to-day price fluctuations of cryptocurrencies eclipse those of traditional currencies, stocks, and precious metals, and do so consistently across assets and time periods. This phenomenon is not entirely driven by the longer-term ups and downs reported in headlines. Bitcoin, Ethereum, and other cryptocurrencies frequently exhibit daily price drops during bull markets and increases during bear markets far in excess of traditional assets. The interactive chart below provides one way to visualize this day-to-day volatility—the daily percentage increase or decrease in price in U.S. dollars from the previous day. 

This interactive tool allows the reader to investigate the phenomenon of day-to-day volatility for different cryptocurrencies, traditional assets, and time periods. During the period 2018–2022, Bitcoin’s average daily change (​​measured as the absolute value of the percentage change from the previous day) was 2.87%, versus the Euro (0.34%), pound (0.43%), and yen (0.35%). Other major cryptocurrencies, such as Ethereum (3.76%), Ripple (4.04%), and Dogecoin (4.55%), exceed Bitcoin’s already-high fluctuations. 

The table below presents this statistic for each asset or index tracked by the data tool. 

Why is the day-to-day volatility of cryptocurrencies important? 

Despite much public discussion about cryptocurrencies as speculative investments or world-changing technology, their success ultimately hinges on widespread adoption as currencies—including as a medium of exchange. Day-to-day volatility creates exchange rate risk over short periods of time. This creates problems for a currency’s usefulness as a medium of exchange if one or both parties to the transaction need to quickly move their money into a different currency. Either the buyer or seller, or both, must take this exchange rate risk, increasing the transaction cost and, ultimately, the price. 

To date, the use of cryptocurrencies as a medium of exchange has taken off in only a small number of market niches, most notably dark net markets where mostly illicit goods are for sale. A 2018 article reported that Bitcoin’s high short-term volatility was adding to the cost and lowering the number of transactions on such platforms. 

There are likely multiple causes for the unusually high volatility of cryptocurrencies. While more widespread adoption may be part of the solution, other likely causes are structural and follow directly from the way cryptocurrencies are designed. Large banks and other financial firms hold huge reserves of traditional currencies, and stocks have market makers, both serving to smooth out short-term volatility and make exchange markets more liquid. Bitcoin, on the other hand, eschews large central intermediaries by design.   

Solutions lie in further entrepreneurial innovation, and that process is already well underway. Bitcoin’s ​​Lightning Network is designed to facilitate faster transactions at a larger scale. Stablecoins, pegged in value to fiat currencies like the dollar or other assets, eliminate high day-to-day volatility by design. They can be used to keep money in the crypto ecosystem—protected from short-term fluctuations and, in theory, easier and faster than traditional fiat currencies--to exchange with Bitcoin or Ethereum. However, their relative novelty opens the door for long-tail risk as well as fraud. 

These and other avenues carry some promise to address day-to-day volatility and make cryptocurrencies more viable for everyday use. But innovation must continue. The Lightning Network and Stablecoins both introduce the scope for large financial intermediaries and dependence on the fiat system that crypto pioneers sought precisely to avoid. Furthermore, the much larger number of people not yet sold on crypto may see these as further complications to already convoluted and risky alternatives to fiat. 

The crypto community must turn away from ​​voices such as Bitcoin maximalists that say the perfect solution is already in hand, and keep innovating and experimenting.  ​Regulators ​could do great harm by making rules that ossify this still-developing technology or cut off as-yet unrealized solutions that only a market process of discovery can deliver. 

We hope that the interactive tool provided here, which offers an intuitive way to visualize the phenomenon of day-to-day volatility in cryptocurrencies, will play a part in opening the conversation and potential for fresh ideas. 

Methodology 

We selected the top 10 cryptocurrencies by market capitalization from CoinMarketCap in addition to FTX’s FTT token. The top 10 cryptocurrencies include seven traditional cryptocurrencies and three stablecoins. We did not include the latter, which track the day-to-day volatility of fiat currencies by design, in the interactive chart, but do report their average daily changes in the summary table. Daily price and exchange rate data are sourced from Yahoo Finance via the R library quantmod. The only modification to the original source data occurred for the Ruble to Dollar data (RUBUSD=X). On Jan. 1, 2016, the original value appears to be off by a factor of 100, this value is divided by 100. Additionally, on June 13, 2022, and July 18, 2022, the adjusted close is outside of the bounds of the high and low—and inconsistent with historical data on the close price from The Wall Street Journal. These two values were replaced with the open price from the following day.

Daily percent change values are calculated from the percent change from the previous trading day’s adjusted close price. Our comparison of daily changes across different types of currencies and assets presents a challenge because different assets trade according to different schedules. Stocks trade on exchanges with daily opening and closing times and close on weekends and certain holidays. Traditional foreign exchange markets stay open around the clock, Monday through Friday, but close on weekends, and this is further complicated by time zones and different holidays globally. Cryptocurrencies trade continually.  

There is subjectivity inherent in addressing this issue. We chose to limit our analysis to the trading days of our traditional stock indices (S&P 500 & Russell 2000), which align with New York Stock Exchange trading days, and use reported adjusted close as the price. While this eliminates a small amount of data from the sample for cryptocurrencies, we conducted robustness checks and confirmed this does not drive our results about persistent differences in day-to-day percent changes. 

The post Examining day-to-day crypto volatility and why it’s important appeared first on Reason Foundation.

Government pension plans depend on annual investment results to help generate the funding needed to pay for the retirement benefits that have been promised to teachers, public safety, and other public workers. Since investment returns contribute to long-term public pension solvency trends, interested parties keep a close eye on the annual return results of these pension funds to see how they are performing compared to their own assumed rates of return. 

Reason Foundation’s list of public pension investment return results includes all major state pension plans that have reported their 2022 fiscal year results as of this writing.

The distribution of 2022 investment returns shows a significant range of results across all of the state pension plans reporting results at this time.

The Oklahoma Public Employees Retirement System reported a -14.5% return for its 2022 fiscal year, which is the lowest return rate among the public pension plans reporting results.

The New York State and Local Retirement System (NYSLRS) and the New York Police and Fire Retirement System (PFRS) reported 9.5% returns—the highest return rate in the nation for fiscal 2022, although their results are mostly attributed to plans’ 2022 fiscal year ending in March 2022, before the largest market losses in the 2022 calendar year.

Overall, the median investment return result for state pension systems in 2022 is -5.2%, which is far below the median long-term assumed rate of return for 2022 of 7% for the plans included in this list. With return results for the 2022 fiscal year so far below pension plans’ return assumptions, most state pension plans will see growth in their unfunded liabilities and a worsening of their reported funding levels.

With each public pension plan achieving different investment returns, the funding impact will also be different for each pension system.

Methodology

'Estimated Investment Gain/(Loss)' is calculated by taking the plan's FY 2020-21 Market Value of Assets and multiplying it by the difference between '2022 Return' and 'Assumed Rate of Return.' Estimated values are meant to approximate total amounts of investment loss that plans would fully & directly recognize this year due to FY 2021-22 return deviating from the assumption (i.e., not accounting for the smoothing mechanism). Investment returns shown are Net of Fees, if not stated otherwise. ‘Deviation from Assumed Rate of Return’ shows the difference between ‘2022 Return’ and ‘Assumed Rate of Return.' Positive returns are highlighted in light blue, and negative in orange. The distribution of the 2022 investment returns chart is based on the `normalized` probability density function, with all probabilities (i.e., all points on a line graph) summing up to 100%. 

The post The 2022 fiscal year investment results for state pension plans  appeared first on Reason Foundation.

The primary responsibilities of the legal system are to promote public safety and to provide for justice. Pressure to raise revenue, at best, undermines and, at worst, directly conflicts with those responsibilities. When incentives are misaligned, police departments and court systems become more concerned with taxation by citation than carrying out their core functions. Such conflicts of interest can undermine the legitimacy of the criminal justice system. 

Using data from the Census Bureau’s Annual Survey of State and Local Government Finances, Reason Foundation created this data visualization tool to shed some light on the amount of revenue generated through fines and fees in 2020, the most recent year for which data is available.

In 2020, local governments across the United States collected just under $9 billion in fines and fees. Local governments in three states—New York ($1.4 billion), California ($1.26 billion), and Texas ($1.17 billion)—collected well over a third of the $9 billion in fines and fees in 2020.

Local governments in New York, California, Texas, Illinois, Florida, Georgia, Ohio, New Jersey, Washington, and Pennsylvania** collected the most fines and fees in 2020. In all, 20 states saw their local governments bring in more than $100 million in fines and fees in 2020.

On a per capita basis, local governments in New York, Illinois, Texas, and Georgia collected more than $35 per resident in fines and fees in 2020. In contrast, local governments in New Hampshire, Connecticut, Maine, Nebraska, and Kentucky* collected less than $3 in fines and fees revenue per resident in 2020.

Local governments use fines and fees as a significant source of revenue

In 2019, local fines and fees revenue accounted for less than 2% of pre-pandemic state general revenue in all 50 states. The year 2017 is the most recent year for which comprehensive local revenue data are available. In 2017, 28,159 U.S. cities, townships, and counties reported a total of $4,975,608,000 in revenue from fines and fees after excluding jurisdictions without sufficient data (see data and methodology notes below). In most places, fines and fees accounted for less than 5% of general revenue.

However, a sizable minority of jurisdictions in the United States appear to be highly dependent on criminal justice and court-related fines and fees. At least 482 local governments derived 10% or more of their general revenue from fines and fees in 2017.

In fact, in 176 local U.S. jurisdictions, the money from fines and fees accounted for 20% or more of that government's total general revenue in 2017.**

Going further, there were 42 municipalities where fines, fees, and forfeits made up 50% or more of the general revenue.

Rural areas with relatively small populations tend to be the most dependent on fines and fees. Along major roadways, so-called speed-trap towns appear common. Due to data limitations, these numbers understate the scope and scale of the revenue generated by local fines and fees in many states.

U.S. cities, townships, and counties getting more than 5% of their revenue from fines and fees in 2017

For more information, please see Reason Foundation's recently released policy brief, "Fines and fees: Consequences and opportunities for reform."

Recommendations for reform

Fines and fees have turned many courts into revenue centers for state and local governments. While most governments do not derive a significant portion of their general revenues from fines and fees, some are almost entirely dependent on them. Nonetheless, fines and fees are not a reliable source of revenue.

Moreover, using fines and fees to directly fund courts, law enforcement agencies, or other government activities can result in undesirable conflicts of interest. In addition to these fiscal considerations, fines and fees have devastating consequences on low-income individuals, racial minority groups, and juveniles and their families.

The following policy recommendations address the primary fiscal considerations associated with fines and fees, ensure accountability, and promote fairness within the justice system.

Eliminate user fees and poverty penalties

User fees effectively transfer costs away from taxpayers and onto individual users of government services. While user fees are appropriate and desirable in many contexts, they do not make sense in the justice system. The rule of law benefits all members of society, and the users of courts—particularly defendants—are often those who are least likely to be able to pay for their operations. Funding law enforcement and court systems through user fees make access to justice regressive—costing the poor far more relative to their income or wealth than the middle class or wealthy. That is fundamentally unjust. Funding the legal system through user fees also reduces the opportunity for lawmakers to weigh funding priorities, rein in excess, and ensure that the system is funded appropriately.

Poverty penalties, including interest fees, late fees, payment plan fees, and collection fees are particularly regressive. These fees punish individuals for their financial status rather than their crimes, and this undermines the objective of fairness within the justice system. Moreover, such punitive financial penalties may hinder the ability of former offenders to reintegrate, contributing to high recidivism rates.

Fully fund courts from state budgets

Eliminating user fees in the justice system may require states to assume greater responsibility in funding their court systems. Allocating funds from general revenues would protect against potential conflicts of interest. The particular structure of court systems in each state may complicate this process, especially in states without unified court systems. This obstacle is worth overcoming to ensure that courts are adequately and equitably funded.

Develop standardized tools to determine the ability to pay and scale fines accordingly

Determination of a defendant's ability to pay fines should not be left solely to the subjective assessment of an individual judge. This can result in wildly different outcomes for otherwise comparable defendants. Establishing standard practices would ensure that individuals are treated equally under the law. Scaling fines according to an individual's ability to pay would also reduce the administrative costs associated with pursuing uncollectable debts.

Affidavits, bench cards, or ability-to-pay calculators may be used to standardize ability-to-pay determinations. Income-based fines, or day fines, could also be used to scale penalties according to an individual's financial status. There is room for experimentation among the states in this area. Still, state law should clarify the factors that are considered when determining an individual's ability to pay. Defendants should be made aware of these factors and what documentation they will be expected to provide.

Provide alternatives to monetary sanctions

Indigent defendants should be able to receive alternatives to monetary sanctions. Community service is one possible alternative to fines but it may prove overly burdensome for some. For example, community service may conflict with work schedules or family obligations. Such conflicts should be avoided, as maintaining employment and social ties are critical to reducing the risk of recidivism. Courts should be able to consider a range of alternatives, including waivers, job training, and drug or mental health treatment. Incarceration should never be considered an alternative to monetary sanctions, and fees should never be charged for alternatives to monetary sanctions.

Eliminate all fines and fees in juvenile cases

The objective of the juvenile justice system should be to rehabilitate young offenders and avoid future escalation in their criminality. Fines are a purely punitive measure and do not serve any rehabilitative function. They do, however, place undue financial burdens on youth and their families. Juveniles should be considered indigent by default, and their families should not be held responsible for any monetary sanctions they incur.

End driver's license suspensions for failure to pay

Driver's license suspensions are an inefficient and counterproductive penalty for failure to pay fines and fees. There are significant administrative costs associated with the enforcement of suspensions. Driver's license suspensions also inhibit the ability of individuals to secure and maintain employment necessary to fulfill their legal financial obligations.

Collect and publish data on court debt and collection practices

Data on fines and fees is needed for transparency, accountability, and fiscal responsibility. Without sufficient information, lawmakers, advocates, and other stakeholders are less able to understand the problems related to fines and fees and identify possible policy reforms.

Currently, most states do not adequately track the imposition and collection of fines and fees. When information is available, it is often dispersed among local governments, individual courts, and private collections firms. This practice not only undermines the ability of lawmakers to make informed policy and budgetary decisions but also contributes to the broader perception that the justice system is unfair and unaccountable. Enabling citizens to access information related to fines and fees would help restore the justice system's legitimacy and allow them to hold their lawmakers more accountable.

At a minimum, states should collect and publish information related to fines and fees, including:

• The monetary amount of fines and fees levied annually;
• The revenue generated by fines and fees;
• How fines and fees revenue is allocated;
• And the costs associated with the collection of the fines and fees.

*Correction: A previous version of this post misstated Kentucky's fines and fees data as $31 per capita rather than $2.50 per capita.

**Correction: A previous version of this data incorrectly displayed data for Jamestown, South Carolina, where Jamestown, Pennsylvania, is located. Jamestown, Pennsylvania, should not have appeared on the map, "U.S. cities, townships, and counties getting more than 5% of their revenue from fines and fees in 2017," above, which shows municipalities that get more than 5% of their general revenue from fines and fees. As reported by the Census Bureau, Jamestown, Pennsylvania, collected approximately $2,000 in fines and forfeits revenue in 2017, which accounted for less than 5% of the town's general revenue that year.

The correct data for Jamestown, South Carolina, is as follows:
Fines and Forfeits: $105,000
Percent of revenue: 64.4%
General Revenue: $163,000
Per Capita: $1,313

This error was made in the GPS settings of the "U.S. cities, townships, and counties getting more than 5% of their revenue from fines and fees in 2017" above, but the error was not made in any state-level calculations.

Notes on data and methodology

In general, there is a severe lack of data regarding the revenue generated from fines and fees. This lack of data can make it difficult for policymakers to assess the scale of the problem and the potential impacts of reform. In the absence of data, perceived reliance on fines and fees revenues to fund court systems and other government activities can present a significant obstacle to reform.

The Annual Survey of State and Local Finances includes a line item for "Fines and Forfeits." According to the Census Bureau's classification manual, Fines and Forfeits includes revenue from:

• Penalties imposed for violations of the law
• Civil penalties (e.g., for violating court orders)
• Court fees, if levied upon conviction of a crime or violation
• Court-ordered restitution to crime victims where the government actually collects the monies
• Forfeits of deposits held for performance guarantees or against loss or damage (such as forfeited bail and collateral)

The Census Bureau's survey of state and local government finances has been administered annually since 1957. A census is conducted every five years (years ending in '2' and '7'). In the intervening years, a sample of state and local governments is used to collect data. A new sample is selected every five years (years ending in '4' and '9'). Even in census years, many values are imputed rather than being collected directly.

In our analysis of individual local governments, we excluded any city, county, or township whose "fines and forfeits" value was imputed. We also excluded any jurisdiction that reported zero general revenues or for whom more than 50% of line items were imputed. As a result of those data filters, approximately 8,330 cities, townships, and counties were excluded from our analysis.

The post Local governments collected $9 billion in fines and fees in 2020 appeared first on Reason Foundation.

At the end of the second quarter of 2022, the $30.6 trillion debt of the United States federal government was 1.2 times larger than the annual economic output of the country. The U.S. is now reaching federal debt levels, as a share of gross domestic product (GDP), that we have not seen since the end of World War II.

Federal spending is increasingly untethered from fiscal realities. From 1965 to 2022, the federal government ran an annual budget deficit in 52 of the 57 years.

The annual federal budget deficits during and following the Great Recession of 2007-2009 were dwarfed by the recent federal deficits of 2020 and 2021, however, when annual budget deficits were $3.1 and $2.8 trillion respectively. The COVID-19 pandemic and accompanying lockdowns and policies sparked the largest spending bills in American history, including the $2.2 trillion CARES Act signed by then-President Donald Trump in March 2020. A year later, in March 2021, President Joe Biden signed the $1.9 trillion American Rescue Plan Act.

After accounting for inflation, the national debt jumped by almost $5 trillion in less than two years—rising from $25.9 trillion in the first quarter of 2020 to $30.6 trillion at the end of the second quarter of 2022. To get a sense of the magnitude of the growth of the debt, the current debt of more than $30 trillion translates to each American individual owing $91,814 based on the U.S. Bureau of Economic Analysis (BEA) estimate of 333 million Americans. This is an increase in the national debt of nearly $14,000 per person just since the first quarter of 2020.

While the increase in the national debt during the pandemic has been particularly shocking, it is consistent with a decades-long, bipartisan trend of deficit spending where government expenditures consistently exceed government receipt of money. When tax revenue is insufficient to cover government spending, the government must issue U.S. Treasury bonds, shorter-term obligations like bills and notes, or other debt instruments. 

Federal Debt Holders

The federal debt is often classified into two buckets: intragovernmental holdings and debt held by the public.

Intragovernmental Debt

Intragovernmental holdings are government debt held by government agencies. As of September 8, 2022, intragovernmental holdings totaled $6.6 trillion, which is 21.4% of the total outstanding public debt. The largest share of this intragovernmental debt is held by the Social Security Trust Fund (46%).

Debt Held by the Public

Debt held by the public can be broken down into debt held by the U.S. public, foreign entities, or the U.S. Federal Reserve. The U.S. public is a broad category that encompasses domestic non-federal investors. It includes state and local governments, private pension funds and insurance companies, banks, and other investors. Foreign entities include the governments and central banks of other countries and private international investors. 

In recent years, even relative to the first two groups of debt holders, the U.S. Federal Reserve has greatly increased its holding of government debt. The Federal Reserve buys the debt with newly created reserves, but these purchases raise the risk of inflation by monetizing the debt. Since new reserves can increase the nation’s supply of money, they can lead to higher prices as more dollars chase the same volume of goods and services. The Federal Reserve asserts, “Federal Reserve purchases of Treasury securities from the public are not a means of financing the federal deficit.” But Federal Reserve asset purchases are traditionally a means of circulating newly printed bills. While new tools like interest on monetary reserves can mitigate the impact of such expansion, the dramatic increase of Federal Reserve debt purchases (which include mortgage debt and corporate bonds as well as Treasurys) is a serious concern.

Given the persistence of federal deficit spending, if demand for U.S. debt does not keep pace with debt accumulation, the risk of debt monetization via Federal Reserve purchases rises further.

Foreign Holders of U.S. Debt

Demand for U.S. debt has increased because the dollar is the de facto reserve currency of the world. The Bretton Woods system, which pegged other currencies to the U.S. dollar which was redeemable for gold, effectively ended after President Richard Nixon suspended dollar-to-gold convertibility. Since that point, the nations belonging to the Organization of the Petroleum Exporting Countries (OPEC) have principally denominated oil sales in U.S. dollars, therefore boosting demand for America’s debt.

The United States heavily relies on foreign buyers for debt financing, which can potentially be a liability if or when international conflicts arise. Russia held $139 billion in U.S. debt in 2013. After the Russian annexation of Crimea in 2014, the U.S. responded with aggressive sanctions and threats to remove Russia from the Society for Worldwide Interbank Financial Telecommunication (SWIFT) system. In response, Russia’s central bank began divesting from U.S. Treasurys. Today the West is once again sanctioning Russia after its invasion of Ukraine.

Historically, many countries have relied on the safety and stability of U.S. Treasurys. Western sanctions on Russia are a reminder that this “risk-free” asset is not risk-free for those failing to align with American foreign policy. The mid-March reporting that Saudi Arabia may begin pricing Chinese oil sales in yuan is an indication that U.S. financial dominance is not completely unchallengeable. Yuan-denominated oil sales could further erode Chinese demand for our debt, which has declined in recent years.

Today, China and Japan account for nearly one-third of all foreign holdings of U.S. debt. Given America’s friction with China and the population decline experienced in Japan, it is not a certainty that these two countries will indefinitely continue to sweep up large volumes of additional U.S. debt.  

Ultimately, the United States government must understand that we do not have an unlimited capacity for financing our deficit spending. This will become even more difficult as we pay out the rapidly growing liabilities for programs like Social Security and Medicare.

Other Long-Term Federal Financial Obligations

Organizations incur long-term financial obligations in forms other than bonds and the U.S. federal government is no exception. Some common types of financial obligations include pension and retiree health care costs for veterans, civilian federal employees, and the general public (through Social Security and Medicare benefit commitments). Looking at the federal government's balance sheet as of 2021, public holdings of U.S. Treasury securities make up less than one-quarter of total federal liabilities. Unfunded entitlements, like Medicare and Social Security, account for the most at 59% of obligations.

Overall federal obligations have now surpassed $300,000 per American. While substantial in their own right, the debt obligations of state and local governments across the country are dwarfed by the various categories of federal debt.

Conclusion

Unfortunately, the United States does not seem positioned for economic expansion like it was the last time the debt-to-gross domestic product (GDP) ratio was this high during the post-World War II era. Following WWII, debt was reined in by brief periods of inflation and several decades of exceptional economic growth.

In the first two quarters of 2022, the U.S. economy experienced negative growth. With weak or negative economic growth expected, and no significant restriction on federal spending in sight, the debt-to-GDP ratio will continue to rise.

Jeffrey Rogers Hummel, Professor Emeritus in the Economics Department at San Jose State University, was consulted on the “Federal Reserve Assets as Percentage of Publicly Held Debt” chart.

Data & Methodology

• Federal Spending Versus Receipts: 
  • Overall data is from the U.S. Department of Commerce’s Bureau of Economic Analysis (BEA) National Income and Product Accounts data, specifically Table 3.2 (Government Current Receipts and Expenditures, which is reported quarterly). 
    • Spending data is from “Current Expenditures” on lines 24 and 44. 
    • Revenue data is from “Current Receipts” on lines 1 and 41. 
    • The inflation-adjusted data series are adjusted according to Q2 2022 dollars using the U.S. GDP implicit price deflator (FRED: GDPDEF) sourced from BEA.
    • The percent of GDP data series are calculated using quarterly Gross Domestic Product data (FRED: GDP) sourced from BEA.

• National Debt: Data are sourced from the U.S. Department of the Treasury—titled “Federal Debt: Total Public Debt” (FRED: GFDEBTN).
  • The debt data are inflation-adjusted to Q2 2022 dollars with the U.S. GDP implicit price deflator (FRED: GDPDEF) sourced from the U.S. Department of Commerce’s Bureau of Economic Analysis (BEA).
  • Per capita figures are derived from the above data and divided by U.S. population (FRED: B230RC0Q173SBEA) data sourced from BEA.
  • The percent of GDP data series are calculated using quarterly Gross Domestic Product data (FRED: GDP) sourced from BEA.

• Who Holds the Federal Debt: Data is sourced from the U.S. Department of Treasury.
  • Federal Reserve Banks: Public debt securities held by Federal Reserve banks. Data are sourced from Treasury (FRED: FDHBFRBN). The data are reported and presented at the quarterly level.
  • Foreign Entities: Federal debt held by foreign investors. Data are sourced from Treasury (FRED: FDHBFIN).
  • U.S. Public: Calculated by subtracting debt held by “Federal Reserve Banks” (FRED: FDHBFRBN) and “Foreign Entities” (FRED: FDHBFIN) from a FRED data stream, from Treasury, called “Federal Debt Held by the Public” source from Treasury (FRED: FYGFDPUN).
  • Agencies & Trusts: Federal debt held by agencies and trusts. Data are sourced from Treasury (FRED: FDHBATN).
  • All data series above are inflation-adjusted to Q2 2022 dollars with the U.S. GDP implicit price deflator (FRED: GDPDEF).
  • The percent of GDP data series are calculated using quarterly Gross Domestic Product data (FRED: GDP) sourced from BEA.

• Federal Reserve Assets
  • Total Federal Reserve Assets: The Federal Reserve has a balance sheet that contains both assets and liabilities. Notes in circulation, bank reserves, and other liabilities. On the asset side of the ledger, the Federal Reserve has securities that include things like: U.S. Treasurys, mortgage-backed securities, loans to banks or other institutions, and liquidity swaps with central banks from other countries. Total Federal Reserve assets as a percentage of publicly held debt are calculated by dividing reserve bank credit (FRED: RSBKCRNS) by total public debt outstanding (Treasury: tot_pub_debt_out_amt).
  • Total Treasury Deposits at the Federal Reserve: When the U.S. Treasury issues public debt and deposits the proceeds at the Federal Reserve this is considered a treasury deposit. This figure as a percentage of publicly held debt is calculated by taking reserve bank credit (FRED: RSBKCRNS) and backing out three other data streams (FRED: WTREGEN; FRED: WLRRAL; and FRED: WORAL) and dividing by total public debt outstanding When the Fed borrows from the private sector, it does through what is referred to as reverse repurchase agreements. That amount is calculated by backing out of reserve bank credit in two data streams (FRED: WREPODEL and FRED: WREPOFOR). The overall total of these two forms of Fed borrowing as a percentage of publicly held debt is the sum of the five data streams divided by total public debt outstanding.
    
• Biggest Foreign Holders: Data is retrieved from the US Treasury Department’s Major Foreign Holders of U.S. Treasury Securities historic tables, which due to aggregations below certain thresholds may result in missing data for certain years for some countries. Data are adjusted to 2021 dollars with the US GDP implicit price deflator (FRED: A191RD3A086NBEA).

• Beyond Publicly Held Debt
  • Federal: Data for these series are taken from the Financial Reports of the United States Government for the years 2000 through present published by the U.S. Treasury Department. 
    • The data is inflation-adjusted to 2021 dollars with the US GDP implicit price deflator (FRED: A191RD3A086NBEA). 
    • Per capita figures are derived from the above data and divided by U.S. population (FRED: B230RC0A052NBEA) data sourced from BEA. 
    • The percent of GDP data series are calculated using annual Gross Domestic Product data (FRED: GDPA) sourced from BEA.
  • State & Local: The bonded debt data come from the U.S. Census Bureau’s Survey of state and Local Government Finance (2020 and 2021 levels are extrapolated). 
    • Pension Debt: Data are sourced from the Board of Governors of the Federal Reserve System (FRED: BOGZ1FL223073045Q). Excluded here are state and local retiree healthcare liabilities for which time series data are not available. Reason Foundation has estimated that these liabilities totaled $1.2 billion in 2019. 
    • The data is inflation-adjusted to 2021 dollars with the US GDP implicit price deflator (FRED: A191RD3A086NBEA). 
    • Per capita figures are derived from the above data and divided by U.S. population (FRED: B230RC0A052NBEA) data sourced from BEA.
    • The percent of GDP data series are calculated using annual Gross Domestic Product data (FRED: GDPA) sourced from BEA.

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The interactive map below shows the funded ratios for state-managed public pension systems from 2001 to 2022. A funded ratio is calculated by dividing the value of a pension plan’s assets by the projected amount needed to cover the retirement benefits already promised to workers. The funded ratio values for 2022 are projections based on a -6% investment return. 

Year-to-year changes in investment returns and funded ratios tend to grab attention, but longer-range trends give a better perspective of the overall health of public pension systems.

In 2001, only one state, West Virginia, had an aggregated funded ratio of less than 60%. By the end of 2021, four states—Illinois, Kentucky, New Jersey, and Connecticut—had aggregate funded ratios below 60%.

If investment returns are -6% or worse in the 2022 fiscal year, Reason Foundation’s analysis shows South Carolina would be the fifth state with a funded ratio below 60%. 

Over the same period, 2001 to 2021, the number of states with state-managed pensions with funded ratios above 90% fell from 33 to 20. If all plans return a -6% investment return assumption for 2022, Reason Foundation projects the number of states that have funded levels above 90% would shrink from 20 to six.  The six states with funded levels that would still be above 90% after -6% returns for 2022: Delaware, Nebraska, New York, South Dakota, Washington, and Wisconsin. 

Importantly, the -6% investment return assumption for the 2022 fiscal year used in this map may be too optimistic for some public pension plans. The S&P 500 lost 12% of its value over the 2022 fiscal year from July 1, 2021, to June 30, 2022. Vanguard’s VBIAX, which mimics a typical 60/40 stock-bond portfolio, was down 15% for the fiscal 2022 year ending in June 30, 2022. Thus, given the condition of financial markets this year, the public pension plans with fiscal years that ended in June 2022 are likely to report negative returns for the 2022 fiscal year.  

Another useful long-term trend to look at are the unfunded liabilities of state-run pension plans. Whereas a pension system’s funded ratio takes the ratio of assets to liabilities, unfunded liabilities are the actual difference between the pension plan’s assets and liabilities. Unfunded liabilities can be conceptualized as the pension benefits already promised to workers that are not currently funded by the plan. Again, the values for the 2022 unfunded liabilities map are a projection using an investment return of -6%. 

The five states with the largest unfunded liabilities are California, Illinois, New Jersey, Pennsylvania, and Texas. In fiscal year 2021, the unfunded liabilities of those states totaled $434 billion and would jump to $620 billion in 2022 with a -6% return.  

For more information on the unfunded liabilities and funded ratios of state-run pensions, please visit Reason’s 2022 Public Pension Forecaster.

Notes

ⁱ The state-funded ratios in this map were generated by aggregating (for state-managed plans) the market value of plan assets and actuarially accrued liabilities. Prior to 2002, Montana and North Carolina reported data every two years, therefore for 2001 figures from 2002 are used. Figures for Washington state do not include Plan 1, an older plan that is not as well funded.

ⁱⁱ The discount rate applied to plan liabilities will impact the funded ratio of a plan. Therefore, the map above can be best thought of as a snapshot of state-funded ratios based on plan assumptions by year. Overly optimistic assumptions about a pension plan’s investment returns will result in artificially high-funded states. Conversely, pulling assumptions downward, while prudent, will result in a worse-looking funded ratio over the short term.

ⁱⁱⁱ In addition to projections for fiscal 2022, some public pension plans in 29 states have yet to report their complete fiscal 2021 figures and therefore include a projection estimate for 2021 as well. Thus, 2021 projections were used for at least one plan in the following states: Alabama, Alaska, Arkansas, California, Colorado, Georgia, Hawaii, Illinois, Kansas, Louisiana, Massachusetts, Michigan, Missouri, Nebraska, New Hampshire, New Jersey, New York, North Carolina, Ohio, Oregon, Pennsylvania, Texas, Tennessee, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.

The post Projecting the funded ratios of state-managed pension plans appeared first on Reason Foundation.

Based on a -6% return for fiscal 2022, the aggregate unfunded liability of state-run public pension plans will be $1.3 trillion, up from $783 billion in 2021, the Pension Integrity Project finds. With a -6% return in 2022, the aggregate funded ratio for these state pension plans would fall from 85% funded in 2021 to 75% funded in 2022. 

The 2022 Public Pension Forecaster below allows you to preview changes in public pension system funding measurements for major state-run pension plans. It allows you to select any potential 2022 investment return rate to see how the returns would impact the unfunded liabilities and funded status of these state pension plans on a market value of assets basis.

The nation’s largest public pension system, the California Public Employees’ Retirement System (CalPERS), provides a good example of how much one bad year of investment returns can significantly impact unfunded liabilities, public employees, and taxpayers.

If CalPERS’ investment returns come in at -6% for 2022, the system’s unfunded liabilities will increase from $101 billion in 2021 to $159 billion in 2022, a debt that would equal $4,057 for every Californian. Its funded ratio will drop from 82.5% in 2021 to 73.6% in 2022, meaning state employers will have less than three-quarters of the assets needed to pay for pensions already promised to workers. 

Similarly, the Teacher Retirement System of Texas (TRS) reported $26 billion in unfunded liabilities in 2021. If TRS posts annual returns of -6% for the fiscal year 2022, its unfunded liabilities will jump to $40 billion, and its funded ratio will drop to 83.4%. The unfunded liability per capita is estimated to be $1,338. 

The table below displays the estimated unfunded liabilities and the funded ratios for each state if their public pension systems report -6% or -12% returns for 2022. 

Estimated Changes to State Pension Unfunded Liabilties, Funded Ratios

The first three quarters of the 2022 fiscal year clocked in at 0%, 3.2%, and -3.4% for public pensions, according to Milliman. The S&P 500 is down more than 20% since January, suggesting that the fourth quarter results will be more bad news for pension investments.

Considering the average pension plan bases its ability to fund promised benefits on averaging 7% annual investment returns over the long term, plan managers are preparing for significant growth in unfunded liabilities, and a major step back in funding from 2021. 

The significant levels of volatility and funding challenges pension plans are experiencing right now support the Pension Integrity Project’s position last year that most state and local government pensions are still in need of reform, despite the strong investment returns and funding improvements in 2021. Unfortunately, many observers mistook a single good year of returns—granted a historic one—as a sign of stabilization in what was a bumpy couple of decades for public pension funding. On the contrary, this year’s returns, as well as the growing signs of a possible recession, lend credence to the belief that public pension systems should lower their return expectations and view investment markets as less predictable and more volatile. 

State pension plans, in aggregate, have struggled to reduce unfunded liabilities to below $1 trillion ever since the Great Recession, seeing this number climb to nearly $1.4 trillion in 2020. Great results from 2021 seemed to finally break this barrier, with the year’s historically positive investment returns reducing state pension debt to about $783 billion. Now, state-run pension plans will again see unfunded liabilities jump back over $1 trillion, assuming final 2022 results end up at or below 0%. 

It is important not to read too much into one year of investment results when it comes to long-term investing. But during this time of economic volatility, policymakers and stakeholders should recognize that many of the problems that kept public pension systems significantly underfunded for multiple decades still exist. And many pension plans are nearly as vulnerable to financial shocks as they were in the past.

Going forward, state and local leaders should continue to seek out ways to address and minimize these risks, making their public retirement systems more resilient to an uncertain future. 

Webinar on using the 2022 Public Pension Forecaster:

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A Horizon Actuarial Services report released in Aug. 2021 surveyed firms like JPMorgan, BlackRock, and BNY Mellon to find that long-term investment returns are expected to decrease across the main asset classes that public pension plans invest in. The Horizon report states:

“Over the last five years, expected returns have declined for all but a few asset classes. The steepest declines have been for fixed income investments such as US corporate bonds and Treasuries, where return expectations have fallen more than 100 basis points since 2019. These declines were driven by recent monetary and fiscal policy interventions, and may have significant implications for multiemployer pension plans.”

Some public pension plans have made the prudent decision to reduce their investment return assumptions in light of this cautionary market outlook. Notably, the New York Common Retirement Fund lowered its assumed rate of return 90 basis points, which takes the assumed rate of return from 6.8% to 5.9%. This 5.9% expected return fits between Horizon’s 10- and 20-Year forecasts of 5.38% and 6.25%.

To get a better sense of the investment outlook for state pension plans, we created a tool that runs a simulation of the investment performance of a hypothetical public pension portfolio over 30 years. It displays the growth of $1 in assets; a distribution of the compound annual growth rate for those 30 years; and the simulation estimated probability of hitting several return assumptions.

The tool utilizes assumptions on asset returns, volatilities, and correlations pulled from BlackRock, BNY Mellon, Horizon Actuarial Services, JPMorgan, and Research Affiliates to simulate portfolio returns. Specifically, the model uses a Monte Carlo simulation with 10,000 simulations of the portfolio over 30 years. Users can select which capital market assumptions they want to run the model with. Additionally, users can select between the national average pension asset allocation, a 60/40 stock-bond portfolio, or a custom portfolio. Step-by-step directions on how to use the tool can be found below.

It is important to note that while this tool uses the latest assumptions from reputable financial advisors, they are still mere speculations on market performance. Additionally, while this approach for portfolio simulation is commonly used in the financial industry, it does not account for the time-variant nature of asset correlations. In times of financial stress, for example, assets can be more tightly correlated than they are in normal market conditions—aggravating portfolio losses. This was true during the Great Recession from December 2007 to June 2009 and could be true in a future crisis as well.

How to Use the Tool

1. To run the portfolio simulation with the preloaded settings, simply hit the “Run Simulation” button in the top right.
2. To modify the inputs, select the “Control Panel” button in the top left.
3. The user can modify both the asset returns, volatilities, and correlations by firm (both Horizon’s 10-year and 20-year assumptions are included) via the “Capital Market Assumptions” dropdown.
4. Asset allocation can be switched between the national average for state pension plans or a 60/40 stock-bond split. Additionally, asset allocation can be customized via the “Custom” button. Note that the portfolio must equal 100% to run the simulation.
5. Once selections are completed, click “Run Simulation” to see the results.

Outputs

1. Assets: Displays the 25^th percentile to 75^th percentile (middle 50 percent of the data) of asset growth for $1 for the 10,000 simulations over 30 years.
2. Distribution: Displays the distribution of compound annual growth rates for the 10,000 simulations over 30 years. Opposed to the arithmetic return, the compound annual growth rate (or geometric return) better represents the long-run growth of an asset. Also displayed are two lines: (1) the median simulation return and (2) where 7% return sits in the distribution which is often used as the assumed rate of return for public pension plans.
3. Return Probability: Displays the probability of the portfolio reaching various assumed rates of return given the results of the 10,000 simulations.

The post Modeling how public pension investments may perform over the next 30 years appeared first on Reason Foundation.

This analysis reveals that most state pension plans saw significant drops in funding in the early and late 2000s, followed by a minor rally during the largest bull market run of our nation’s history. In the last five years, the average has remained in the lower 70 percent range.

Fortunately, a strong year of returns in FY 2021 will result in a significant bounce to the funding status of nearly all plans. Still, twenty years ago, state pension plans were nearly 100 percent funded in aggregate, and most plans are still working to overcome funding shortfalls that arose over a decade ago during the Great Recession. This year’s funded ratio increase does not change the trends plans have experienced for the last two decades and such history should inform plan assumptions going forward.

The graphic below shows each state’s public pension funded ratio (total reported actuarial assets compared to liabilities for all plans aggregated by state) from 2001 to 2020.

Methodology: Displayed funded ratios are the quotient of the actuarial value of assets (AVA) and actuarial accrued liabilities (AAL) of state-managed plans. The discount rate is a weighted average of state-managed plans’ discount rates with AAL as the weight.  Source: Data primarily come from Public Plans Data and is supplemented by Pension Integrity Project analysis of annual financial reports.

One of the largest reasons funded ratios have declined over time is investment returns coming in below plan expectations and insufficient annual contributions from states. For years, most pension plans have held too high assumed rates of investment returns that have led to underfunding. Despite excellent returns this year, a number of plans have taken prudent steps to lower their assumed rate of return in 2021.

A pension plan’s discount rate is also highly influential on a plan’s funded ratio and if the rate is too high it will hide the true extent of the state’s public pension liabilities. As some public pension plans have prudently adjusted their discount rates down to realistic levels, they have also revealed the true cost of fully funding their public pension systems. This affects funded ratios by revealing a higher pension liability. The second chart of this tool shows the change in each state’s discount rate between 2001 and 2020.

The post State pension plan funded ratios in 2020 appeared first on Reason Foundation.

We recommend viewing this interactive chart on a desktop for the best user experience. If you are having trouble viewing the chart and interactive options on your device, please find a mobile-friendly version here. 

The post Investment return results for state pension plans appeared first on Reason Foundation.

A single year, or even several years, of above-average investment returns would be welcome news for public pension plans. But, a year or two of great returns will not resuscitate the public pension plans at risk of financial insolvency. Public pension plans with growing debt are in need of structural reforms that protect taxpayers, employees and retirees. A key component of these reforms is setting realistic assumptions about future investment returns.

For the last 20 years, state and local pension plans’ assumed rates of return have been far too optimistic. The distributions of average (geometric mean) assumed investment returns and actual returns from 2001 to 2020 demonstrate this. The figure below shows the distribution of the average assumed investment return rate versus actual investment returns for 200 of the largest state and local pension plans in the United States. The median assumed rate of return over the last 20 years was 7.7 percent per year, the median actual rate of investment return for these public pension plans was 5.7 percent.

This two percent difference helps to explain the nearly 30 percent drop in the average pension plan funded ratio over the same period. In recent years, many pension plans lowered their assumed rates of return. As visualized below, the distribution of state and local pension plan assumed rates of return (blue) are moving closer to the distribution for the 20-year average (orange). 

Although progress has been made there is still a significant gap between the assumptions for investment returns and actual returns from the last two decades. For public pension plans, falling short of investment return expectation, even by a small percentage, can add millions to billions in pension debt over time.

In short, state and local governments are betting that the next few decades will not be like the last two. Policymakers should continue to lower overly optimistic assumed rates of return. By doing so, they can reduce the risk of future growth in unfunded pension liabilities, protecting taxpayers and government workers.

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Funded ratios are used to display the dollars a pension plan has saved compared to the amount the plan will need to fulfill pension promises already made to public workers and retirees.

The interactive tool below shows each state’s public pension funded ratio and how it compares to the aggregated national funded ratio (total assets compared to liabilities for all plans run by each state) from 2001 to 2019. For example, California’s funded ratio is currently 71.6 percent, which means the state has roughly 71 cents saved for every dollar of pension benefits it owes. 

This analysis reveals that most state pension plans saw significant drops in funding in the early and late 2000s, followed by a minor rally during the largest bull market run-up in our nation’s history. In the last five years, the average seems to have leveled at around 72 percent. Initial analysis of 2020 data shows that state aggregated funded ratios remain roughly unchanged from 2019 at 72 percent. 

There are many reasons funded ratios have declined and stagnated. The largest of these are investment returns coming in below plan expectations and insufficient annual contributions.

Another factor that should be considered when comparing pension funding between states is how they have adjusted their discount rates, which is how plans calculate the present value of promised benefits. A discount rate is highly influential on a plan’s funded ratio and if the rate is too high—meaning it reflects an unrealistic expectation on long-term investment returns—it will hide the true extent of the state’s public pension liabilities.

As some public pension plans have prudently adjusted their discount rates down to realistic levels, they have also revealed the true cost of fully funding their public pension systems. This affects funded ratios by revealing a higher pension liability. The second chart of this tool shows the change in each state’s discount rate between 2001 and 2019. 

The post How State Pension Funding Ratios Have Declined Over Time appeared first on Reason Foundation.