For decades, the fertility debate has focused on graying workforces and a shrinking pool of young workers. Those pressures are real, but there is another challenge unfolding that concerns how demographic busts impact long-lived capital investment often financed with municipal debt. 

Here is what America’s demographic future looks like: 

• National growth is now immigration-dependent. The Congressional Budget Office’s most recent projections (January 2026) have the population growing from 349 million in 2026 to roughly 364 million by 2056, but only because of immigration. Deaths are projected to exceed births nationally starting in 2030, and the total fertility rate is projected to stay near 1.6, well below the 2.1 rate needed for a generation to replace itself. 

• Immigration is slowing sharply. Census Bureau population estimates released in January 2026 show national population growth fell to 0.5 percent between July 2024 and July 2025, the slowest pace since 2021, driven by a historic decline in net international migration, from 2.7 million to 1.3 million in a single year. 

• The trends are uneven by place. The Institute for Family Studies’ 2026 State of Fertility Report puts California’s rate at 1.42 children per woman and Massachusetts at 1.35, among the lowest in the country, while Utah, Idaho, and South Dakota remain comparatively high. West Virginia, one of only three states to lose population between 2010 and 2020, shrank another 4.3 percent between 2015 and 2025, with deaths outnumbering births by nearly 8,000 in the most recent year alone. 

These change where public infrastructure should be built and how the long-term debt that finances it should be evaluated. 

Municipal Debt Risk 

Long-lived capital is frequently allocated based on population assumptions that later prove too optimistic. Investors who buy municipal debt, and the rating agencies that grade these bonds, are increasingly at risk from shifting or falling populations. The stakes are not abstract: the municipal bond market holds about $4 trillion outstanding, and individual investors, directly or through funds, hold close to 70 percent of it, more than any other class of buyer. 

S&P Global defines its own rating outlook as reflecting expectations over a short window of six months to two years, and Moody’s Investors Service uses a similar timeframe. Moody’s economy factor compares five-year historical GDP growth to the national rate, a trailing measure rather than a forward-looking one. None of these timelines match the 20-to-40-year maturity of the debt being rated. 

Moody’s methodology explicitly acknowledges this limitation, stating that as the forward horizon lengthens, the utility of precise estimates typically diminishes.  

Yet the demographic forecasting required here is not difficult. Every child who will attend public school over the next eighteen years is already alive today. National Center for Education Statistics (NCES) enrollment projections built on these existing cohorts have a mean absolute error of about 2.5 percent even 10 years out, making them far more reliable than most forward-looking metrics built into credit scorecards. 

School buildings, highway corridors, water mains, and utility grids are long-lived assets financed by municipal bonds running 20 to 40 years. Without considering demographic trends, rating agencies are not fully capturing a material risk.

Where People Live 

How populations shift and congregate over time is another risk. Both agencies build regional comparison machinery into other parts of their scorecards. Moody’s adjusts local household income for regional cost of living, and S&P runs standard peer comparisons that explicitly reoriented its 2024 methodology toward broader regional indicators. Population trends, however, receive no such treatment. 

Demographics sit entirely outside the scored framework as an unweighted qualitative judgment call. As a result, a significant drop in population from the time municipal debt was initially issued might be overlooked so long as the near-term population baseline is stable at a lower level. 

Fitch’s state government criteria go further: they permit comparing an issuer’s demographic trend to national levels over five-, 10-, and 20-year windows, longer than Moody’s or S&P look. But Fitch doesn’t assign that demographic comparison any standard weight either, so it ends up just as informal and unscored as the population judgment calls at Moody’s and S&P. 

	Moody’s	S&P Global	Fitch
Framework	U.S. Cities and Counties Methodology (2024)	Methodology For Rating U.S. Governments (2024)	U.S. Public Finance Rating Criteria (2024)
Scored factors	Economy 30%, Financial Performance 30%, Leverage 30%, Institutional Framework 10%	Economy 20%, Financial Performance 20%, Reserves 20%, Liquidity Management 20%, Debt and Liabilities 20%	No standard weighting; qualitative key rating drivers
What “economy” measures	Resident income vs. regional cost of living, full value per capita, five-year GDP growth vs. national rate	Gross state/county product and per capita income vs. national benchmarks	Revenue/economic growth vs. U.S. performance, using five-, 10-, and 20-year CAGRs (per state criteria; city/county criteria not independently confirmed)
Regional benchmarking	Yes income adjusted to metro-area cost of living	Yes standard peer comparison; 2024 update added broader regional indicators	Yes issuer vs. national trends, longest horizon of the three
Population trend	Not scored; qualitative “other considerations” only	Not scored; no regional or peer benchmark applied	Named as a permitted comparison, but unweighted like the other two
Rating outlook horizon	~12–18 months	Defined as six months to two years	Not standardized to a fixed window

Table 1. What Moody’s, S&P, and Fitch score, and what they don’t: our synthesis of published criteria, not verbatim agency language. Sources: Moody’s U.S. Cities and Counties Methodology (2024); S&P Global Ratings, Methodology For Rating U.S. Governments (2024); Fitch Ratings, U.S. Public Finance State Governments and Territories Rating Criteria (2024). 

Demographic Stress Test 

Demography deserves to be a model input. There are implications when it is not.  Between June 2024 and June 2025, S&P’s negative outlook revisions for K-12 school districts rose 40 percent, concentrated in states including Indiana, Pennsylvania, Texas, and Wisconsin. In January 2026, Moody’s downgraded Berryessa Union School District in California, citing a three-year enrollment decline of 1.9 percent, but the proximate trigger was depleted cash reserves; enrollment shows up only as a secondary pressure once the erosion is already visible in the budget. Washington’s K-12 sector saw 24 downgrades and zero upgrades over the past year, with declining enrollment and lagging state funding both cited as causes. In each case, population loss enters the rating only after it has already drained the fund balance it should have been scored against from the outset. 

A real demographic stress test would close both gaps at once. It requires cohort-based accounting for the eighteen years in which the relevant population is already alive, paired with scenario-based testing for the assumption-dependent years beyond that horizon. 

This resembles the stress-testing approach bank examiners use to evaluate mortgage concentration risks. These stress tests must be scaled to specific locations, using the same regional benchmarks Moody’s and S&P apply to local income today. Left uncorrected, the current framework risks the same costly failure twice: severe infrastructure shortages where people are arriving, and deeply stranded capital where they have already left.