States Facing Significant Fiscal Challenges
- A state’s financial health depends both on its current financial metrics, and the likelihood that its tax base will grow. Some states that are in poor financial health now will probably be able to repair their financial weakness through strong economic growth, attracting new young educated residents, increased real estate values, cutting expenses and/or increasing tax rates.
- However other financially weak states face greater challenges. Their population is relatively old, they are seeing residents migrating out of state and weak growth in property values, state GDP and individual income tax collections. Several of these troubled states already have high state tax burdens, which may make it difficult for them to raise taxes further without accelerating the exodus of businesses and residents.
- State fiscal weakness and multiyear population declines have occurred in the past. Examples of areas which have recovered, as well as steps states can take to recover fiscal health are highlighted in the Federal Reserve Bank of New York's analyses of Puerto Rico’s current fiscal health.
Measuring State Financial Health
In 2015 and 2016 the Mercatus Center at George Mason University measured state financial health: “...through the states’ own audited financial reports. By looking at states’ basic financial statistics on revenues, expenditures, cash, assets, liabilities, and debt, states may be ranked according to how easily they will be able to cover short-term and long-term bills, including pension obligations.
This ranking of the 50 states and Puerto Rico is based on their fiscal solvency in five separate categories:
- Cash solvency. Does a state have enough cash on hand to cover its short-term bills?
- Budget solvency. Can a state cover its fiscal year spending with current revenues, or does it have a budget shortfall?
- Long-run solvency. Can a state meet its long-term spending commitments? Will there be enough money to cushion it from economic shocks or other long-term fiscal risks?
- Service-level solvency. How much “fiscal slack” does a state have to increase spending if citizens demand more services?
- Trust fund solvency. How much debt does a state have? How large are its unfunded pension and healthcare liabilities?”
In addition to these financial measurements, a state’s health can be inferred by its residents behavior. A state that has strong economic growth is likely to see other beneficial patterns like inflows of young and educated residents, rising real estate values due to the increasing demand for housing, and rising levels of individual income. Young educated workers are valuable both because higher incomes are associated with education, and because these workers incomes will grow as they age (while retiree incomes are likely to decline, for example).
Table 1 shows the 10 states with the weakest financial condition based on the Mercatus 2016 study. For context, Puerto Rico has a Mercatus financial score of -3.18. Puerto Rico has seen a significant population decline and defaulted on General Obligation municipal bonds in 2016. No state currently has a Mercatus score as weak as Puerto Rico's, and no state has defaulted on General Obligation bonds since 1933. While that history is comforting, it is also true that states have never had such high levels of unfunded pension and benefit liabilities.
The section of Table 1 in highlighted in brown shows state rankings ranging from 1 to 49 (Alaska is excluded due to its unique characteristics) on the basis of resident age, net migration, home price appreciation, GDP growth (excluding cyclical mining and oil sectors), and IRS income tax collection (both numbers of returns and gross collections). A ranking of 1 is associated with the strongest relative position, while 49 is the weakest position relative to other states. The full table with all 49 states can be found here.
Table 1: Ten States With Lowest Mercatus Financial Health Score
|STATE RANK EXCLUDING ALASKA (49 = Worst, 1=Best)|
|State||Mercatus Financial Score||State Tax (Inc, Sales, Property)||Avg Age ("Worst"=Oldest)||Net Migration 5yr||Home Apprec. 5yr||Net Young Educated Migration 5yr||GDPxMining Growth 5yr||Net Migration 10yr||Net Young Educated Migration 10yr||GDPxMining Growth 10yr||5 Yr Pct Change Num IRS Individ. Returns||5 Yr Pct. Change IRS Gross Tax Collection Individual Returns|
Connecticut and New Jersey show similar problematic characteristics: weak fiscal health combined with a 1) relatively old population, 2) among the highest rates of out migration, confirmed by 3) among the weakest real estate markets, 4) some of the weakest state GDP growth, and 5) relatively poor growth in individual IRS tax filings and gross collections. While Connecticut and New Jersey have historically done well attracting new young, educated residents, that positive attribute has weakened in the last 5 years.
California and, Massachusetts show more encouraging profiles: they attract young educated residents, feature relatively strong state GDP growth, real estate appreciation, and strong growth in individual IRS returns and gross collections.
Recovering Financial Health
States have gone through economic cycles before. A helpful historical perspective is found in Table 2 which is excerpted from a Federal Reserve Bank of New York article on Puerto Rico's declining population. Some states' population declines were caused by commodity “busts” that followed boom periods (e.g., for North Dakota, West Virginia and Pennsylvania).
Table 2: Federal Reserve Table On States That Have Experienced Multiyear Population Declines
The text of the Federal Reserve article cites New York City as an example of successful recovery from a multi-year period of decline:
“New York actually lost more than 10 percent of its population during the 1970s, a decline from about 7.9 million residents to 7.1 million residents. Although the city experienced a weakening of its manufacturing base during this period, its economic troubles also reflected poor fiscal management and deteriorating quality of life. New York City’s large debt burden, outsized spending obligations, and shrinking tax base nearly forced a declaration of bankruptcy in 1975. The city was also viewed by many as unsafe and undesirable.
...Despite its challenges, New York City was able to set the stage for a recovery in part through successful policy. New York State established an Emergency Financial Control Board to help the city balance its budget and restore its credibility to investors. Although the road to solvency was difficult and took time, the city was able to correct its financial problems by the mid-1980s. Moreover, New York City took aggressive action to reduce crime and improve its overall attractiveness. By 2000, New York City’s population had increased to over 8 million people, more than fully reversing the decline that occurred during the 1970s. The city’s recovery was not completely driven by the policy response; New York was fortunate to have unique finance related industries, which boomed in this period. Yet without the right policy, its ability to recover would have been more doubtful.”
Steps that states in poor financial health can take are highlighted in a separate Federal Reserve Bank of New York analysis of the steps Puerto Rico should take:
- Reinvigorate efforts to raise economic growth
- Reform the Commonwealth’s tax system
- Improve the Commonwealth’s financial reporting
- Strengthen performance and harden budget constraints for public-sector corporations
- Adopt a capital budget and a binding balanced-budget rule for the central government
- Adopt a legislative framework requiring multiyear budgeting, specific fiscal targets, and monitoring mechanisms to help ensure that targets are met “
None of these steps are easy and may take decades to have a meaningful impact. However inaction will also cause significant hardship if states become unable to meet current and future financial obligations.
Transparent and reproducible: All of the labeled Figures and Tables can be generated by using the free, publicly-available R program and the R code available in “StateTrajectories.r” on github to analyze the publicly available data obtainable from the links in the article.
 Fin.Score is measure of state financial health including budget deficits, unfunded pension liabilities etc. from Mercatus: https://www.mercatus.org/statefiscalrankings Strong state health is indicated by positive scores and vice-versa: For comparison, Puerto Rico’s score is -3.18
State.Tax includes income, sales and property taxes from: http://taxfoundation.org/article/state-and-local-sales-tax-rates-2016
Age.Rank is state ranking based on average age of state population from youngest (=1) to oldest (=49) ACS Data 2011-2015 IPUMS-USA, University of Minnesota, www.ipums.org. The data is provided freely but is subject to their licensing restrictions.
Migration.5yr is state ranking based on net migration to state from 2011-2015 ACS data (IPUMS-USA, University of Minnesota, www.ipums.org. The data is provided freely but is subject to their licensing restrictions); Rank of 1 means most positive migration to state as percentage of state population
Home.Apprec.5yr is state ranking based on 5 year (period ending Q3, 2016) home price appreciation (1 is state with most appreciation) from BEA: https://www.fhfa.gov/DataTools/Tools/Pages/House-Price-Index-(HPI).aspx
Young.Educ.Migr.5yr is state ranking based on net migration to state of 20 to 34 year olds with a college degree or higher from 2011-2015 ACS data (IPUMS-USA, University of Minnesota, www.ipums.org. The data is provided freely but is subject to their licensing restrictions); Rank of 1 means state has the most young, educated migrating to state as percentage of state population
GDPxMin.5yr is state ranking based on state GDP growth excluding “Mining” (which includes Oil & Gas) from 2010-2014; Rank of 1 means state has most GDP growth of 49 states. Data from BEA: https://www.bea.gov/iTable/iTable.cfm?reqid=70&step=1&isuri=1&acrdn=2#reqid=70&step=1&isuri=1
Migration.10yr is state ranking based on net migration to state from 2006-2015 ACS data (IPUMS-USA, University of Minnesota, www.ipums.org. The data is provided freely but is subject to their licensing restrictions); Rank of 1 means state has most positive migration to state as percentage of state population
Young.Educ.Migr.10yr is state ranking based on net migration to state of 20 to 34 year olds with a college degree or higher from 2006-2015 ACS data (IPUMS-USA, University of Minnesota, www.ipums.org. The data is provided freely but is subject to their licensing restrictions); Rank of 1 means most young, educated migrating to state as percentage of state population
GDPxMin.10yr is state ranking based on state GDP growth excluding “Mining” (which includes Oil & Gas) from 2005-2014; Rank of 1 means most GDP growth. Data from BEA: https://www.bea.gov/iTable/iTable.cfm?reqid=70&step=1&isuri=1&acrdn=2#reqid=70&step=1&isuri=1
Pct.Chg.IRS.Returns.5yr is state ranking based on the percent change in number of individual IRS returns filed from 2010 - 2015; Rank of 1 means state has greatest percent increase in number of returns. Data from: https://www.irs.gov/uac/soi-tax-stats-state-data-by-year
Pct.Chg.IRS.Collect.5yr is state ranking based on the percent change in gross dollars collected from individual IRS returns filed from 2010 - 2015; Rank of 1 means state has greatest percent increase in gross collections. Data from: https://www.irs.gov/uac/soi-tax-stats-state-data-by-year