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The 2010s may have seen the slowest population growth in U.S. history, census data show

William H. Frey Brookings Institution

Date Posted:: January 9, 2020
Is Database:: Database

US population growth in the 2010s was the slowest in history, with a 0.48% increase from 2018 to 2019, the lowest annual rate since 1918.

The 2010s marked the slowest population growth in U.S. history, with a mere 0.48% increase from 2018 to 2019, the lowest annual rate since 1918. This decade-long stagnation was characterized by fewer births, more deaths, and uneven immigration patterns. Immigration fell to 595,000, the lowest since the 1980s, while natural increase dropped below 1m. The aging population contributed to a decline of 1.14m in the under-18 demographic. Regional disparities emerged, with higher growth in the Mountain West and Southeast, low growth in the Midwest and Northeast, and population loss in four states. California faced potential congressional seat loss due to declining growth. These trends reflect broader demographic shifts, including lower fertility rates and an aging population, with projections indicating higher growth rates for those over 65 compared to youth.

"... The nation’s population growth from 2018 to 2019 grew by a mere 0.48%, according to newly released Census Bureau estimates. This is the lowest annual growth rate since 1918, and caps off a decade that should show the slowest 10-year population growth since the first census was taken in 1790....The decade’s patterns reveal a nation with unprecedented growth stagnation, an absolute decline in its under-18 youth population, higher growth for states in the Mountain West and Southeast, low growth in the Midwest and Northeast, and population loss in four states. Moreover, declining growth in California could lead to its first-ever loss of a congressional seat... The 2010s was a decade of fewer births, more deaths, and uneven immigration. (download Table A) The 2018-19 period had an exceptionally low growth rate of 0.48%, with immigration declining to 595,000 people—the lowest level since the 1980s—and a drop in natural increase to below 1,000,000. (download Table B) While immigration may have been unusually low due to recent federal restrictions which led to a decline in the noncitizen foreign-born, relatively low natural increase levels are likely to persist due to the aging of the population. One symptom of the aging population is the decade-wide loss in young people under age 18. Between 2010 and 2019, the nation sustained an absolute decline of 1.14 million youth. Some of this change can be attributed to lower fertility rates and the aging into adulthood of the last of the millennial population, though census projections show older populations—especially those over age 65—will display far higher rates of growth than youth.."

The 2010s may have seen the slowest population growth in U.S. history, census data show: Extended Excerpt Image 1

William H. Frey, "The 2010s may have seen the slowest population growth in U.S. history, census data show," Brookings Institution, January 2, 2020, https://www.brookings.edu/research/population-change-and-the-projected-change-in-congressional-representation/

Falling Fertility: The Changing Value of Freedom, Fulfillment, and Family

Raquel Fernández, Inés Berniell and Milagros Onofri National Bureau of Economic Research

Date Posted:: September 2, 2026
Is Database:: Database

Fernández et al. cast doubt on Goldin’s hypothesis that men’s limited willingness to share domestic responsibilities is central to fertility decline, pointing instead to the erosion of the belief that children are necessary for a fulfilling life.

Figure 1 documents how fertility outcomes and attitudes changed over the decade. Intended fertility fell in every GGS country, from 28 to 21% on average (Figure 1a). The ideal number of children fell in 17 of the 22 ISSP countries, from 2.42 to 2.31 on average (Figure 1b). [Children] became more likely to be seen as constraining parental freedom and less likely to be seen as conferring status (Figure 1c). Gender roles became less traditional, and the division of household work became more equal [Figures 1i]. Despite this greater sharing of chores and care, work–family conflict rose sharply. The decade saw changes that might have been expected to make the burden of children lighter, at least for women. Simultaneously, however, children became less attractive and, above all, less necessary: the belief that a fulfilled life requires children lost more ground than any attitude we measure [Table 2, Part II, Panel B].

Terra Incognita: The Economics of a Shrinking World

Jesús Fernández-Villaverde and Patrick Norrick University of Pennsylvania

Date Posted:: August 14, 2026
Is Database:: Database
Is Important:: Important

The UN appears to systematically overestimate births; e.g. 33 of 37 countries with high-quality statistics registered fewer births in 2024 than the UN had forecast. Fernández-Villaverde and Norrick infer humanity is below replacement fertility in 2026.

In Table A1 we compare the World Population Prospects (WPP) estimates of births in 2022-2023 with the official numbers reported by several countries. [A2 shows the full sample with the deviations.] As of 2026, humanity is likely to be below the replacement fertility level: we are having fewer births than we need to keep population constant in the long run. This astonishing fact does not mean that population has stopped growing. Because of momentum effects (the large cohorts of women born two or three decades ago are having their children now, and their own parents have not died yet), world population will keep growing for another 30 years or so. But unless trends change, it will peak at roughly 9 billion around 2056 and then start falling, first slowly, then fast.

Takeaways by Macro Roundup^® AI

Global fertility has fallen below replacement level as of 2026, ending humanity’s ability to sustain long-run population stability without a reversal in trends.
Population momentum—driven by large cohorts of women now in peak childbearing years—will sustain growth for roughly 30 more years before world population peaks at approximately 9 billion around 2056 and begins declining.

Americans Are Done With Being Put in Racial Boxes

Justin Fox Bloomberg

Date Posted:: July 21, 2026
Is Database:: Database
Is Important:: Important

Less than half of Americans < 29 years old are non-Hispanic whites. As of 2020, 33.8mm Americans – 10.2% of the population – identify as being of two or more races, largely driven by intermarriage between whites and either Hispanics or Asian Americans.

The increase in immigration from Asia and Latin America since the 1960s has been the chief driver of the rise in diversity and decline in the non-Hispanic White share of the population. But those immigrants have been doing what generations of immigrants before them did and, well, becoming Americans. Marriages across racial and ethnic lines are much more prevalent among Hispanic and Asian Americans than Black or non-Hispanic White Americans, while intermarriage rates have been rising steadily for the latter two groups, too. As a result, a growing share of Americans just isn’t going to fit neatly into any single racial or ethnic category that the US government can come up with.

Takeaways by Macro Roundup^® AI

Post-1960s immigration from Asia and Latin America is the primary driver of rising U.S. demographic diversity and the declining non-Hispanic White population share.
Intermarriage rates among Hispanic and Asian Americans exceed those of Black and non-Hispanic White Americans, expanding a multiracial population that no single government racial category can accurately capture.

The Pig In The Python: US Decennial Labor Flows And Economic Opportunity, 1910–2040

Steven Ruggles Proceedings of the National Academy of Sciences

Date Posted:: July 14, 2026
Is Database:: Database
Is Important:: Important

Accounting for both inflows and the overhang of previous labor market entrants, Ruggles predicts a labor shortage such that “Americans born in the 2020s might be the first cohort in a half century that earns significantly more than their parents did.”

Figure 3A highlights the influx of workers that occurred between 1960 and 1980, as the large baby-boom cohort entered the labor force, female labor-force participation expanded, and immigration rose [see Figure 2 for a detailed breakdown]. It was difficult for the economy to absorb all the new workers, and wages for young people declined sharply after peaking in 1973. Figure 3A does not, however, provide a valid measure of labor-market competition because the baby boomers and newly employed women and immigrants did not suddenly vanish after they entered the labor force; they kept working and occupying jobs until they eventually retired decades later. The glut of workers entering the labor force in the 1970s would continue to stifle demand for new workers until their eventual exit from the labor force, a process that is still in progress. The index of employment competition shown in Figure 3B is [a better] measure of relative cohort size than 3A. It represents the cumulative net labor-market entries over the previous five decades as a % of the working-age population in the current decade. As shown in Figure 1C, we are already seeing signs of an uptick in the wages of young workers, and as the demographic shortage accelerates we may finally see real wages of the young exceed the levels of the early 1970s.

Takeaways by Macro Roundup^® AI

Baby-boom labor-force entry during 1960–1980 suppressed young-worker wages, which declined sharply after peaking in 1973, reducing economic opportunity for new.
Cumulative labor-market entries over five decades as a % of working-age population drives employment competition that persists decades after initial.
Female labor-force participation expansion and immigration during 1960–1980 created a sustained worker glut that stifled demand for new employment until.

Baby Busts and Growth Booms: Demographic Change and the Macroeconomy

Daron Acemoglu, David Autor, Keelan Beirne and Andrew Scott National Bureau of Economic Research

Date Posted:: July 7, 2026
Is Database:: Database
Is Important:: Important

Cross-country evidence from 1950 to 2020 shows that a 1pp lower birth rate is associated with 22 log points (~25%) higher GDP per worker 40 years later and 29 log points (~44%) after 60 years, likely driven by labor-saving technical change.

Figure 3 traces out how GDP per worker evolves following a 1pp increase in birth rates at t−20. Since cohorts born at t−20 (e.g., 1970) do not enter the working-age population until t = 0 (e.g., 1990), we should observe no response before t = 0; [indeed] the estimated coefficients are ~0 and statistically insignificant before t = 0. Beginning at t = 0, however, higher birth rates are associated with lower GDP per worker, and the negative effects grow progressively larger over time. For example, a 1pp lower birth rate at t−20 is associated with 22 log points higher GDP per worker at t+20 and 29 log points higher by t+40. The latter corresponds to roughly 0.73 percentage points faster annual growth over the 40-year interval. We find that lower birth rates are associated with more labor-saving patents and a growing share of high-tech industries across countries and US commuting zones [Figure 11]. They are also predictive of higher TFP growth across countries and US industries and increased patenting in ICT and broader automation technology classes. Using cross-country variation in WWII-era military and civilian deaths, we present suggestive evidence that the positive growth effects of falling birth rates are primarily driven by the scarcity of younger workers rather than by reductions in population per se [Figure 14]. [Editor’s note: the paper does not grapple with the fiscal consequences of an aging population.]

What Demographic Prediction Can and Cannot Achieve

Samuele Lo Piano, Marta Kuc-Czarnecka, Roger Pielke, and Andrea Saltelli Social Science Research Network

Date Posted:: May 29, 2026
Is Database:: Database

Simulation of the decision chain yielding projections of world population in 2050 that range from 6 to 14B suggests most of the variance in demographic forecasts arises not from parameter uncertainty or data randomness but from model choice.

We explore demographic predictions by propagating all plausible choices that can be made during the analysis through the modelling process. This approach involves navigating the so-called ’garden of forking paths’—mimicking in silico what would happen if multiple investigators were to examine the same problem. For this, we now abandon [the Chinese government mathematician] Song Jian’s ‘historic’ model and turn to models currently in use: the Cohort-Component and UN WPP models, the Lee-Carter model and the Lotka-Volterra model. Note that in standard use, these tools are used in isolation, see e.g. the FAO’s How to Feed the World in 2050, resting on a single UN WPP population trajectory shielding the reader from the compounding effect of their uncertainty. Unsurprisingly, the exercise capturing the modelling of the modelling process for global population projections to 2050 and 2075 reveals distinct characteristics regarding the sensitivity and projection outcomes of the different models. Once abandoned the straitjacket of Song’s approach, uncertainty is free to manifest itself. The overall uncertainty distributions of the projected populations show a wide range of possible outcomes, reflecting the inherent uncertainties in demographic projections.

Takeaways by Macro Roundup^® AI

Model choice accounts for 98% of output variance in 2050 global population projections, driving divergent forecasts ranging from 4–25 billion.
Song Jian’s optimization model converges to 700 million people by 2080 across all parameter variations (670–700 million range), demonstrating structural.
Global fertility declined from 5 children per woman in 1950 to 2.1 currently, with no rebound in countries where rates.

US population growth in the 2010s was the slowest in history, with a 0.48% increase from 2018 to 2019, the lowest annual rate since 1918.

Fernández et al. cast doubt on Goldin’s hypothesis that men’s limited willingness to share domestic responsibilities is central to fertility decline, pointing instead to the erosion of the belief that children are necessary for a fulfilling life.

Does freedom from family obligations now outweigh the fulfillment children provide?

Related Articles:

The UN appears to systematically overestimate births; e.g. 33 of 37 countries with high-quality statistics registered fewer births in 2024 than the UN had forecast. Fernández-Villaverde and Norrick infer humanity is below replacement fertility in 2026.

Will declining birth rates eventually shrink the global economy?

Takeaways by Macro Roundup® AI

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Less than half of Americans < 29 years old are non-Hispanic whites. As of 2020, 33.8mm Americans – 10.2% of the population – identify as being of two or more races, largely driven by intermarriage between whites and either Hispanics or Asian Americans.

Is the traditional racial classification system becoming obsolete?

Takeaways by Macro Roundup® AI

Related Articles:

Accounting for both inflows and the overhang of previous labor market entrants, Ruggles predicts a labor shortage such that “Americans born in the 2020s might be the first cohort in a half century that earns significantly more than their parents did.”

Does a one-time labor surge create permanent wage pressure?

Takeaways by Macro Roundup® AI

Related Articles:

Cross-country evidence from 1950 to 2020 shows that a 1pp lower birth rate is associated with 22 log points (~25%) higher GDP per worker 40 years later and 29 log points (~44%) after 60 years, likely driven by labor-saving technical change.

Related Articles:

Simulation of the decision chain yielding projections of world population in 2050 that range from 6 to 14B suggests most of the variance in demographic forecasts arises not from parameter uncertainty or data randomness but from model choice.

How much do demographic models actually predict versus explore?

Takeaways by Macro Roundup® AI

Related Articles:

Takeaways by Macro Roundup^® AI

Takeaways by Macro Roundup^® AI

Takeaways by Macro Roundup^® AI

Takeaways by Macro Roundup^® AI