Fertility falls first as a number in the news and arrives last as something you can feel in the economy. But the later a variable arrives, the longer it tends to stay once it does. South Korea’s ultra-low fertility is no longer a “problem” to be solved; it is becoming a “condition” of the next economic order.

When prices rise, we feel it immediately. When interest rates rise, we confirm it in next month’s loan payment. But fertility is different. Even when the number falls, it is quiet at first. It makes headlines, yet daily life seems unchanged. The point is that this quiet does not mean “there is no problem”; it means the shock is still in transit. Demography is a slow-moving variable. But once it moves, it moves for a long time. That is why the real fear of a society with falling fertility is not an immediate panic, but an order that changes starting a few years later. South Korea is a place where that change in order can appear especially fast.

The Winter 2026 issue of the Journal of Economic Perspectives begins by framing fertility decline not as “a problem of a particular region,” but as “a global baseline trend.” The focus here shifts away from debates about diagnosing causes and toward judging persistence: whether lowered fertility is likely to rise again, or whether a low state is more likely to endure. The numbers are laid down forcefully from the outset. The global average fertility level has fallen from about five children in the 1950s to the low twos today, and roughly two-thirds of humanity now live in countries where “two adults, on average, have fewer than two children.” In other words, we are already living in a zone that struggles to sustain population size without net immigration—and that zone has become standard.

A crucial distinction enters here. “Today’s annual fertility rate” and “the number of children a cohort has over a lifetime” are not the same number. What statistics commonly call the total fertility rate is typically a “period” measure, constructed by aggregating age-specific fertility patterns in a single year.

By contrast, the force that reshapes a population at the generational level is ultimately measured by a “cohort” metric—namely, the number of children a particular birth cohort actually has over its lifetime. The reason to hold onto this distinction is simple. Period measures are shaken by timing. If births did not happen “less,” but happened “later,” then fertility can look as if it fell for a while and then rose again later.

For example, if a society shifts toward having the first child at age 34 and the second at age 38, the period total fertility rate may fall for some time and then jump again at some point. But that rebound does not mean that the number of children per family increased; it may be an illusion created by delayed births being recorded all at once.

So the lens moves to cohorts. The observation offered here is cold. In places where fertility fell on a lifetime basis, there are hardly any cases where it later returned in a large way. Even if there are occasional flickers of rebound, over the long run it is far more common for the lowered trajectory to persist. Even major swings like a baby boom are treated not as an exception to the long-term trend, but as a temporary fluctuation.

When people explain low fertility, the scene that commonly comes to mind is “rising childlessness.” But a more detailed dissection enters here. Lower cohort fertility is produced by the overlap of two forces. First, the share of people who never have children over a lifetime increases. Second, even among those who do have children, second and third births decline. And the second force often accounts for a larger share than many expect.

The evidence is presented in the shape of the data. If you gather only the groups whose cohort fertility has fallen below the replacement level (2.1), the share of childlessness does tend to rise. But even at the same level of cohort fertility, childlessness varies widely. In some places, childlessness exceeds 25 percent; in others, it remains below 5 percent. In other words, there is a broad range where “an increase in people who do not have children” alone is insufficient to explain low fertility.

The more decisive scene appears when you look at “parents only.” Excluding the childless, there are many cohorts in which the average number of births among those who do have children falls below 2.1. Put differently, in many cases the structure is already in place in which fertility does not recover to replacement even if childlessness disappears. This is the moment when the essence of low fertility expands from “more people are not having children” to “even those who do have children are having fewer.” At this point, low fertility shifts from a “problem of choice” to a “redefinition of family size.” When the default shape of the family changes, the surface area that policy must touch suddenly becomes much larger.

This is also where it becomes clearer why pro-natalist policy is always controversial. Policy research often captures changes that respond over a short horizon. When parental leave, cash benefits, or childcare support is introduced, a signal can appear that births increase in a particular year. But whether that increase carries through to “more children over a lifetime” is a separate question. Because annual measures are sensitive to timing, if policy causes births to be “pulled forward,” short-term figures can rise. But if births subsequently fall by a similar amount, lifetime totals may not change much.

An extreme example appears here: Romania’s “Decree 770.” In 1966, when a coercive policy banning abortion and effectively blocking contraception was implemented, a sharp rebound appeared in the very next year, with the period total fertility rate jumping by nearly twofold. If you look only at annual indicators, the conclusion that “policy raised fertility” becomes far too easy.

But over time, people adapt. Fertility then falls again quickly, and whether “the number of children became persistently higher” on a cohort (lifetime) basis becomes far more unclear. The point is this. Sharp short-run swings in fertility can lead to an overestimation of policy power, and the force that changes the long-run demographic path may be far more gradual or limited than that.

This perspective delivers a simple but heavy message for South Korea. If long-run forecasts are moved by nothing more than “fertility went up or down a little right now,” the same debate will repeat. If you do not distinguish when births occurred (timing) from how many births ultimately occurred (total quantity), both policy and business will keep falling for the illusion.

The impact of fertility decline usually does not arrive all at once. It travels. So what matters is both “how severe it is” and “in what sequence it arrives.”

The first thing to move is “household decisions.” Marriage is delayed, the first birth is delayed, and the second becomes harder. Here, policy struggles to produce immediate results, because people change decisions not primarily by “cash support” but by “the structure of life.” Stable housing, predictable jobs, time and relationships that can share childcare burdens, and above all the conviction that “having a child will not collapse my life” are required. Without that conviction, fertility falls not as a rebound but as an accumulation of delay.

Next comes the labor market. What appears before an obvious change in the unemployment rate is a shift in how firms hire. The moment fewer new entrants appear, firms shift strategy from “recruiting” to “retaining.” Competition for skilled workers begins, wage gaps widen, and investment in automation and digital transformation accelerates. Manufacturing tends to automate quickly, but services depend heavily on people. So the demographic shock can be felt as something that cuts growth while pushing up service prices and care costs. The sentence “prices rise because fertility is low” sounds awkward, but the sentence “service prices rise because there are fewer people” is entirely plausible.

Last comes public finance and asset markets. From here, “the whole society’s bill” is opened. Healthcare, care, and pensions are items that automatically grow over time. At the same time, if the working-age population shrinks, the denominator that must finance those costs shrinks. So even if the same policies are maintained, the burden rate rises. What matters at this stage is not merely the size of welfare, but trust. People begin to doubt whether “the money I paid can sustain the system in the future,” and from that moment savings, investment, and housing choices change. This is where fertility becomes linked to asset markets: why house prices weaken in some regions, why they become more expensive in others, why long-term interest rates become more sensitive—under many of those questions, demography begins to sit at the bottom.

South Korea’s fertility level is low, but what is even more frightening is the speed of change. If demographic structure changes gradually, society has time to adapt. But if it changes quickly, the result is not adaptation but collision. Labor-market institutions, the link between education and employment, housing structure, the care system, and the design of pensions and healthcare begin to fall behind the times all at once. And institutions that fall behind ultimately survive by “shifting costs onto individuals.” While individuals endure, childbearing is delayed further and falls further. Structure affects decisions, and decisions reinforce structure—a feedback loop is formed.

The core point is here. If low fertility is treated only as a matter of culture or campaigning, solutions keep sliding into emotion. By contrast, if you separate the cohort-based “total quantity” from the period-based “timing,” what is difficult to change reveals itself first. And that revelation becomes strategy. It becomes possible to redraw the economic sequence not as a forecast that wishes for rebound, but as preparation that assumes persistence.

Demographic shock arrives late. So if the economy looks fine right now, people easily relax. But once the shock arrives, it stays for a long time. And then it is hard to reverse. Policies that raise fertility sharply in the short run are rare. In the end, the more realistic competition may shift from “how much did fertility rise” to “who adapts better in a world where low fertility persists.”

For South Korea to be competitive here, productivity, immigration, care, housing, the labor market, and fiscal sustainability cannot move separately. The era of solving everything with one fertility number has already passed, and the era of designing a system that does not collapse even with low fertility has arrived. That design belongs more to painful adjustment than to flashy slogans. But demography is a variable with few options. The narrower the range of choices, the more precise the operation must be.

Going forward, low fertility moves beyond being a recurring headline and becomes a basic condition of macroeconomics. Growth forecasts, fiscal forecasts, real estate and regional forecasts, industrial policy, and labor policy all diverge depending on demographic assumptions. And those demographic assumptions are more likely to start not from “it will rebound next year,” but from “a low state may persist.”

In sum, the question posed by South Korea’s ultra-low fertility is not only “what should be done to make people have more children.” It is also “do we know the sequence in which the economy is shaken when low fertility persists for a long time.” The shock seeps into the labor market first, then moves into public finance and asset markets. And the speed of that movement can be especially fast in South Korea. Demography is a quiet variable, but it is never a small one. It begins quietly and changes structure.

Journal of Economic Perspectives, 2026-02-04, “The Likelihood of Persistently Low Global Fertility”, Michael Geruso; Dean Spears