• The desire gap is the opportunity. People already want more children than they’re having. The job isn’t persuasion; exposure to kids alone increases fertility ideals, it’s building environments where existing desires can be acted on. Moralizing about young men needing to shape up or young women not having the right values doesn’t close the gap and won’t close the gap.

• Build the coalition and infrastructure subnationally Local governments can move completed family sizes; national governments control entry into parenthood. Stop waiting for national reform. Build working ecosystems at the municipal and provincial level now, capture the gains available there, and assemble the political coalition of places that have actually delivered.

• This is a product/service delivery problem, not a culture war Every place that sustained above-average fertility built an integrated system, held it across administrations, and made it visible in everyday life. They didn’t change anyone’s values. They built an environment where existing values could be executed on. Integration and constancy of purpose are the product. Everything else is downstream.

The mothers in Nagi who arrive with plans for one child and leave with plans for two aren’t being persuaded of anything. They wanted more children before they got there. The previous environment didn’t let them have them. Nagi did. The wanting was already there. The system finally caught up to it.

Hold that in mind. It’s the shape of the argument.

When Steve Jobs walked on stage in January 2007 and introduced the iPhone, he wasn’t selling a device. He was selling a proposition: that the Mac would still work with it, that the App Store would be stocked next year, and that whatever Apple announced in 2012 would still run on the thing you bought in 2007. And then there was always “one more thing.” The phrase was pure theater, but it worked because there was always actually one more thing, and the one more thing always connected to every other thing he’d already shown. The showmanship and the system were the same act. But the showmanship only sold because underneath it was an obsessively integrated system. Hardware talked to software talked to services talked to retail, and every seam was somebody’s job. The phone was worth more because the App Store was stocked. The App Store was worth more because the phone was in your pocket. The Mac was worth more because both synced to it. None of the components did much alone; together they produced something that felt like magic to the customer, and the magic was real because the machinery underneath it was real. People who didn’t know they wanted a smartphone discovered they wanted one because the environment made smartphones feel like a thing to have, and concentration of early adopters changed what the next wave of customers could imagine.

Apple is the one widely understood case of what an ecosystem does. The ecosystem isn’t the Mac, the App Store, the iPhone, or the repair network. It’s the way each piece makes the others more valuable. It requires both: the razzle & the dazzle that makes people want to enter the system, and the tick-tick-tick of a system that actually delivers once they’re inside.

Fertility policy has almost no equivalent. It has components: baby bonuses, parental leave, childcare subsidies, housing grants. Most countries spend real money on some of them. The aggregate numbers keep falling. But here’s the thing: the components mostly work. Korean baby bonuses produce babies. German parental leave reforms produce conceptions. Italian childcare expansions, above a threshold, produce births. Evaluated individually, the programs do what they’re designed to do, with some doing much better than others. Evaluated as a system, they produce the world’s lowest fertility rates. The reason is that nobody designed the system.

A baby bonus that lands in a city with affordable family housing, available childcare, and neighbors who used the same bonus last year is not the same intervention as a baby bonus that lands in a city without those things. Same check. Same amount. Completely different product. The check didn’t change. The environment it landed in changed everything about what the check could do. That’s the alchemy, and it’s the same alchemy Apple was selling: the pieces make each other work, and the felt experience of the pieces working together is the thing that actually shifts decisions.

But alchemy that works has machinery underneath it. The baby bonus lands right because someone built the housing, someone staffed the childcare, someone made sure the programs talked to each other instead of each department optimizing its own line item while the family fell through the gaps between them. The central government runs cash transfers. The province runs its own programs. The city runs still others, with funding from local taxes. No one is responsible for whether they cohere. Each layer optimizes its own components. The family doesn’t experience the components. The family experiences the gaps.

On top of this, the whole arrangement has to survive an election, and a new mayor/governor/president/PM, and a budget cycle, and the moralist on the op-ed page who thinks the problem is that young people have the wrong values (oftentimes the right accusing women, the center/left accusing men, and sometimes the inverse), and the minister who wants to announce something visible before the next vote rather than sustain something invisible that compounds over fifteen years. The alchemy requires the machinery. The machinery requires the politics. A few places have figured out how to hold all three within the layer they control, and the difference shows up in fertility numbers that sit two to five times apart under identical national laws.

Same country, same laws, five times the children. Why?

Two young Korean women, same age, same income, same education, same national fertility policy. One lives in Yeonggwang County. One lives in Busan’s Jung District. Yeonggwang’s fertility rate is 1.71. Busan Jung’s is 0.32. Economic models don’t predict this. Cultural models don’t predict it. Ideological and religious models don’t predict it. What’s the variable nobody is measuring?

In 2009, a research group put childless women in fMRI scanners and showed them photographs of infant faces. The women’s reward circuitry (the nucleus accumbens, the part of the brain that fires when someone you love walks into the room or when you eat a perfect peach) lit up before they consciously processed the image. Later work using EEG clocked the response at roughly 140 milliseconds. The women didn’t decide to find the babies cute. The brain had already responded by the time the deciding part woke up. The response was graded: more infantile features produced stronger responses, in women who had never been pregnant, who weren’t thinking about pregnancy, who in some cases didn’t want to be pregnant. Something in them was keeping score of how many babies they had encountered. They didn’t know they were keeping score.

The women didn’t decide (she did, but you get the point). That’s the part I keep coming back to. The empathy response is decision-making before the deliberation, the part that runs on perception before the reasoning wakes up. It’s hard to build policy around a 140-millisecond response. It’s also hard to build policy while pretending it isn’t happening.

And the 140-millisecond response doesn’t stop at desire. It reaches all the way into marriage. In Japan, somewhere between 30 and 39 percent of never-married adults in their 20s and 30s say they are uncertain whether they want children. Not opposed; uncertain. brought my attention to Fumiya Uchikoshi and colleagues at Harvard, Princeton, Tokyo, and Gakushuin’s paper. They tracked what those uncertain adults did over the following years, in a paper published this year in Population and Development Review. Controlling for whether they wanted to marry (which in conventional models would be the variable doing the work), they found that uncertainty about fertility cuts the annual marriage transition rate by 30 to 50 percent. People who don’t know whether they want children marry later, or don’t marry.

The arrow runs the other way. Marriage doesn’t cause children; the prospect of children causes marriage. They call it child-driven marriage, and the reframes where the causation you assumed was backward tend to be where the actual leverage lives.

So the woman in Yeonggwang and the woman in Busan aren’t just in different policy environments. They’re in different neurological environments. The woman in Yeonggwang walks past children in playgrounds, parents pushing strollers, neighbors visibly managing two and three kids. Her brain is accumulating 140-millisecond responses before she deliberates anything, and the accumulation shapes her fertility desires, and the desires shape whether and when she marries. The woman in Busan walks past convenience stores and study cafés. Same brain. Same circuitry. Different inputs. The variable nobody is measuring is the density of the environment the circuitry is responding to.

What if TFR isn’t really one number?

The density is measurable, but the measurement most people use throws the signal away. When Stephen Shaw decomposed the Total Fertility Rate across 314 million mothers in 33 countries, he found that what looks like one number is actually two numbers multiplied together, and the two don’t move together. He checked it three ways (breakpoint co-occurrence, wavelet coherence, mutual information) and confirmed statistical independence. The share of women who become mothers at all (call it TMR, the Total Maternal Rate) drops in sharp shocks and doesn’t recover between them. The average family size among mothers (CPM, Children per Mother) stays roughly flat for decades. TFR averages them together and throws away 49% of the information in the process. A single TFR value of 1.5 corresponds, on average, to thirteen distinct combinations of the two underlying numbers. The thing every fertility paper for sixty years has been measuring is half a measurement, and the half that’s missing is the half that tells a mayor what to do.

Here’s the simplest way to hold it: TFR is an average of two different decisions made by two different people at two different life stages. The 27-year-old deciding whether to become a mother at all is deciding TMR. The 33-year-old mother of one deciding whether to have a second is deciding CPM. Policies that work for one often don’t work for the other. Forces that move one often don’t move the other. Sixty years of policy has been optimizing against an aggregate that hid both failure modes.

Shaw’s shock pattern has the right time signature for an environmental mechanism, with a wrinkle the smooth-decline reading misses. TMR doesn’t drift downward; it drops in discrete shocks and ratchets down. Italy, Japan, and the UK all show sharp TMR falls around 1974. The US shows the same shock pattern in 1971 and again in 2008. Shaw’s prefecture-level analysis of Japan is the cleanest single piece of evidence: TMR fell in all 47 Japanese prefectures simultaneously between 1974 and 1975, with a probability under the null of less than 0.0001, as improbable as flipping a coin 47 times and getting heads every time. The breakpoint cluster in monthly birth data begins in October 1974 and peaks in November, which, accounting for conception and gestation, lines up almost exactly with the Japanese Oil Shock of October 1973. CPM stayed roughly flat across the same period. The shock altered who became a mother at all. It barely touched how many children mothers ended up having.

This gives the transmission mechanism its time signature. A shock (economic crisis, labor-market upheaval) disrupts fertility-desire formation in the cohort experiencing it. That cohort’s lowered birth rate depletes the next decade’s ambient infant exposure. The empathy channel runs at lower amplitude on the following cohort. Their fertility desires form against a thinner environment. Their TMR ratchets down again at the next shock and doesn’t recover between shocks because the environment never refills. CPM stays stable because it’s a different decision, made by people already inside parenthood, responding to local rather than national conditions. The smoothness of the aggregate decline was an artifact of TFR aggregation.

Put Shaw’s ratchet together with Uchikoshi’s child-driven marriage, and East Asia’s marriage collapse stops being mysterious. Atoh’s work and recent estimates by Tan, Cui, and Uchikoshi attribute 40 to 70 percent of TFR decline in Japan, Korea, Taiwan, and Singapore to falling marriage rates. The conventional reading is that fewer people are marrying, so fewer children are born. The better reading is that an earlier generation’s TMR shock depleted the ambient infant environment of the next cohort, which produced uncertain fertility desires in unmarried young adults, which depressed their marriage rates, which produced still fewer children (the next TMR step down), which further depleted the environment for the cohort after that. The marriage collapse is downstream of a fertility-desire collapse, which is downstream of a depleted environment, which is downstream of TMR shocks the previous generation absorbed and never recovered from. The trap closes itself.

Is the whole problem just economics?

None of this is to say the empathy channel is the only thing going on. Rising education costs, women’s labor-market opportunities, contraception, the genuine economic burden of raising children: all do real work in the fertility decline. Galiani and Sosa are explicit that the empathy channel is one mechanism among several, additive to economic pressures rather than replacing them. Shaw is similarly careful that his shock-and-ratchet pattern shows association rather than definitive causation. What the combination makes visible, and what sixty years of TFR-anchored policy never had to confront, is that one of the actual drivers of the decline has an environmental leverage point that fiscal instruments cannot reach. The economic factors still matter. They are not the whole picture, and the part they don’t cover is the part where felt environment compounds over generations.

TMR and CPM respond to different forces and require different interventions. In most developed countries both have been declining, meaning the aggregate decline reflects two different decisions made by different people at different life stages. The 27-year-old deciding whether to enter parenthood at all is a different customer from the 33-year-old mother of one deciding whether to have a second. Any policy portfolio that works has to work for both, and most don’t. Most serve the existing-parent customer through benefits that escalate with each child. The prospective-parent customer, who doesn’t yet have a child to trigger any of them, is served by cash she hasn’t yet decided to earn.

Who can actually reach any of this?

The two customers’ frictions live at different scales, and this matters for what work can be done now. The split is rough. Most frictions sit at one layer, but individual frictions cross between them. TMR’s binding constraints are mostly national, and Shaw’s shock pattern shows why: TMR moves with national-scale disruptions that hit cohorts simultaneously, and the disruptions ratchet rather than reverse. Whether a 25-year-old can form the fertility desires that drive her marriage decision depends on whether she has stable employment, whether her education will complete on a reasonable timeline, whether her labor market will penalize her 66 percent in maternal earnings, whether her employer will force her to sign an illegal contract promising to resign if she becomes pregnant. No mayor can fix any of these. CPM’s frictions are mostly local, consistent with Shaw’s finding that CPM stays flat across periods of national turbulence; it’s not insulated from the national environment, but it’s tracking something more local. Whether a mother of one has a second depends on whether local childcare works, whether her neighborhood contains other families managing two or three children in ways that shift what a livable family size feels like. A mayor can absolutely reach these.

Housing is the clearest friction that refuses the split. A young couple that wants to marry and start a family can’t if there’s nowhere in the city they can afford a family-sized unit. That’s a TMR friction, and the lever is overwhelmingly municipal: zoning, parking minimums, permitting timelines, all decided at the city and sometimes state level. The federal government has essentially no direct authority over what gets built where. Housing is also a CPM friction at the same layer (the mother of one in a two-bedroom can’t have a second if the three-bedroom doesn’t exist because zoning prevents it from being built) and it’s the substrate the empathy channel runs on (a neighborhood of family-sized units near transit puts families in walkable range of each other; a neighborhood of studios above retail doesn’t). Three jobs, one lever, one layer. The political coalition for this already exists in YIMBY organizing across the English-speaking world, which has proven that cross-ideological housing coalitions are buildable at the municipal and state level in a way that almost no other pronatalist intervention can claim. Pronatalists who aren’t already in that coalition should be.

The local cases below do most of their measurable work on CPM (higher concentrations of families with children raising completed family sizes among residents who were going to become mothers somewhere) while also producing TMR effect through two channels: concentration raising ambient infant exposure for residents who weren’t already fertility-minded, and housing-stock decisions directly enabling household formation for couples who currently can’t start one. But the bulk of the TMR problem is national and isn’t being reached by any of the local work.

Yeonggwang. What the young couple sees walking through their county is most of this argument in concrete form. Children in the playgrounds, parents pushing strollers, neighbors who took the same marriage incentive the county offers, used the same baby care package, claimed the same child-raising subsidy. Six consecutive years as Korea’s highest fertility rate, more than double the national average, in a rural county with no subway, no university, and no tech industry. Busan Jung-gu, three hundred kilometers away under the same national framework, has none of the visible design and none of the children. Same country, same laws, more than five times the children per woman in Yeonggwang. Section I returns to what Yeonggwang actually does.

A skeptical reader will say: much of this is selection. Fertility-minded families move to Yeonggwang. Haenam County, also in South Jeolla, once held Korea’s top TFR and then lost it. (Section I returns to Haenam as the anti-case.) The critique is real and applies in varying degrees to most cases below. It’s also less damaging than it looks once the chain is in hand. Families moving into Yeonggwang aren’t reshuffling a fixed stock of fertility; they’re concentrating in a place where they are visible to each other and to everyone else who lives there. Concentration does CPM work directly, by raising completed family sizes among residents who were going to become mothers somewhere, and it does some TMR work indirectly, by raising infant exposure for residents who weren’t already fertility-minded and letting the empathy channel run on them before the child-driven marriage mechanism shifts their decisions. Concentration is one of the channels through which production happens.

What the local cases are showing

Don’t people already want more children?

The Nagi pattern, wanting already present and the system finally catching up, is the shape of the problem almost everywhere. Korean women, surveyed across multiple cohorts, say their ideal is between 1.8 and 2.16 children. They produce 0.72. Italian women say their ideal is around 2; under “ideal living conditions” they say 2.3. They produce 1.18. Across 27 EU member states, 87% of women say two or more children is their personal ideal, and a third of women aged 40 to 54 report having fewer children than they wanted. The desired-actual gap is enormous and it is not closing on its own. People want children. The system isn’t delivering on the wants people already have.

This is the first-order claim, and it belongs in front of every other one. Most of the available fertility recovery in the next decade lives inside this gap. Closing the gap doesn’t require convincing anyone of anything. It requires building the environment in which the children people already say they want become plannable. Cash transfers, ecosystems, and moral exhortations all bid for the same job. They are not equally good at it, and the reasons they differ matter.

What makes this more than a one-time transfer is what happens after the gap closes. Children produced by gap closure don’t just exist. They occupy the environment: playgrounds, sidewalks, train platforms, supermarket aisles. The 22-year-old commuter who hasn’t formed a family preference yet now lives in a denser child environment than her older sister did. Her brain is keeping score in 140-millisecond increments, before she consciously deliberates anything at all. By the time she’s deciding, she’s deciding on top of accumulated unconscious priors that were shaped by the previous round’s gap closure. Her ideal number of children, when she’s surveyed, will be slightly higher than her sister’s was at the same age, because the environment that formed it was slightly denser.

This is what Sebastian Galiani and Raul Sosa formalize as the empathy channel in their April 2026 NBER paper. Each child in an environment generates a positive externality on the desired fertility of surrounding adults, mediated by the reward circuitry that fires before conscious processing. Konrad Lorenz identified the underlying baby schema in 1943; Glocker and colleagues confirmed in 2009 that infant faces with high baby-schema intensity activate the nucleus accumbens in women who have never been pregnant. Kringelbach’s group established that the response runs within roughly 140 milliseconds. Ruth Feldman’s research showed that oxytocin tracks infant contact regardless of whose child it is, in fathers and alloparents and unrelated adults. The channel is dormant when fertility is high, where additional infants barely move the signal, and steeply active when fertility is low, where each additional infant (or its absence) shifts the operating point. Galiani and Sosa calibrate the channel at between 3 and 33% of the fertility decline, with 13.4% at baseline.

The implication is that gap closure compounds. Closing the desired-actual gap for the current cohort puts more children into the environment, which lifts desired fertility in the cohort behind them, which means the next round of gap closure operates on higher desires, which puts still more children into the environment. The same loop ran in reverse for fifty years and produced the trap. Fewer children meant less exposure meant lower desired fertility meant fewer children. The local ecosystems that work are running the loop forward.

This is the difference between a cash transfer and an ecosystem, and it explains why Korea’s modest cash-transfer gains don’t compound. Cash arrives at the moment of birth in a household already inside parenthood. It does some gap-closure work for that household, but it doesn’t densify the environment in concentrated, visible ways. The 22-year-old commuter sees nothing she didn’t see before. The next cohort’s desired fertility is unmoved. Each year’s transfers do roughly the same work as the previous year’s, and the base doesn’t grow. Local ecosystems concentrate. Yeonggwang’s higher fertility produces a denser child environment, which lifts desires in residents who weren’t already family-oriented, which produces still more children, which densifies the environment further. Same gap-closure intent. Very different long-run trajectory.

Whose preferences have to change?

Two recent thought leaders clarify why the frame matters by getting it wrong. Helen Andrews, on the right, argues that the “girlboss lifestyle would not exist if it were not massively subsidized” and treats the removal of women’s economic options as the implicit pronatalist program. Something that doesn’t match the research on the topic, especially with a greater correlation of income and CPM.

Matthew Yglesias, from the center-left, identifies that the binding constraint on marriage formation is on the male side (educated women marry at higher rates than working-class women, and the men who aren’t getting college degrees are the weak link). He then concludes that “someone needs to tell them to either stay in school or else take some other conscientiousness-demonstrating path.”

At time of Ygelsasis’s writing, the unemployment rate for college graduated young men and non college grades are at the same, alongside the fact that post 2008. Men saw persistently higher unemployment rates than women. On top of that, learn to plumb is a dismal failure as blue collar job market collapse.

Tell who, with what mechanism, through what institution, on what timeline that matches the demographic clock. The prescription doesn’t survive contact with the question of who would deliver it.

I find both arguments frustrating (well, disgusting and repulsive) in similar ways. Both are about whose preferences need to change. The data says preferences don’t need to change for the first-order gain. The preferences are already there, in the form of a desired-actual gap that no amount of moralizing will close, as if moralizing haven’t been tried. Andrews wants women to revise downward what they want from their lives so they will accept what the current system delivers. Yglesias wants working-class men to revise upward what they expect of themselves so they will become deliverable to women whose preferences would then be met, regardless of current economic realities.

Neither asks what environment would let the preferences people currently hold actually be executed on, or what the same environment would do to the next cohort’s preferences as a compounding effect. Andrews is comfortable making women bear the cost of a transition she isn’t responsible for designing. Yglesias is comfortable making working-class men bear the diagnosis without offering them anything that resembles a path. Both treat the people whose lives are at stake as objects to be hectored or modified, rather than as people responding rationally to an environment that someone built and someone could rebuild.

Research like Han and Uchikoshi that Yglesias gestures at without naming deserves direct treatment, because the talk about economics being the reason why men are the binding constraint. Among Korean men aged 25 to 29, the share neither working nor seeking work nearly tripled between the mid-1990s and the early 2020s, from roughly 10% to 30%; in the same Japanese age group, the rate barely moved.

The study attributes about a third of Korea’s fertility decline in this age group to that rise. Male economic inactivity is a national-scale TMR friction that excludes the inactive from the marriage market almost entirely, and no mayor can fix it. Naming it doesn’t change who can act on it. It does change what a thinkpiece is supposed to do.

Where can we see the chain working?

Sarah Hrdy’s cooperative-breeding research adds the historical dimension: girls in traditional societies arrived at first pregnancy with hands-on experience caring for younger siblings and neighbors’ children, which exposed the neurobiological systems that generate maternal desire to the stimulus they evolved for. Modern societies dismantled that apprenticeship by age-segregating residential life and privatizing childcare. Local ecosystems that concentrate children in visible public space are partly rebuilding what age segregation took apart.

The population-level test is clean. A quasi-experimental study of Italian municipal childcare expansion found that municipalities starting with childcare coverage above 20 percent and expanding further showed measurable fertility gains over four years. Municipalities starting below 10 percent and expanding just as aggressively showed nothing. The authors attribute this to a minimum cultural threshold for using educational services; below it, expansion doesn’t register as a meaningful option for couples making family decisions. The shape is exactly what the compounding loop predicts. Visibility has to cross a threshold before additional supply registers in decisions, because what registers isn’t the supply but the normalization of using it. Same population, same selection, different births.

How do you build an ecosystem in a rural county?

Yeonggwang. What the young couple sees walking through their county is most of this argument in concrete form. Six consecutive years as Korea’s highest fertility rate, reaching 1.71 in 2024 against a national 0.75, in a rural county of 52,000 people with no subway, no university, and no tech industry. What Yeonggwang has is a dedicated Population and Jobs Policy Office (인구일자리정책실) established in 2019 as the first such department at Korea’s basic-local-government level, and more than 80 lifecycle support programs running across marriage, pregnancy, birth, childcare, and youth retention. The county frames itself as a saenghwal-miljakhyeong dolbom dosi, a “life-embedded care city,” and uses the older Korean phrase “from cradle to grave” (요람에서 무덤까지) to describe the setup: every child is enrolled in the support network from birth and the services follow them through school, marriage, and eventually their own children.

The individual programs are unremarkable as components. A ₩5 million marriage grant, rent-interest support for newlyweds, a ₩30 million transportation card for expecting mothers, neonatal support scaling from ₩5 million for a first child up to ₩35 million for a sixth, fertility-treatment subsidies, and a monthly birth allowance of ₩200,000 payable for 216 months until age 18 (₩43.2 million in total). More unusual is the father’s parental leave subsidy (아빠 육아휴직 장려금), which pays men who take leave and which the county frames as a tool for both gender equality and paternal bonding. Most unusual is the adjacent infrastructure: e-mobility manufacturing at Daema Industrial Complex, Hanbit Nuclear Power Plant employment, and Neulpum Village young-professional housing that makes Yeonggwang a place a young person can both move to and stay. Marriages jumped 40 percent between 2023 and 2024 (from 177 to 248), which will feed the TMR of the next cohort. Mayor Jang Se-il describes the sequence directly: youth support, marriage, birth, child-rearing, in that order, as the chain the county is trying to operate on. The design is the ecosystem. The specific programs are the visible pieces.

Sejong, Korea’s purpose-built administrative capital established in 2012, operates on a different principle. Sejong held Korea’s highest TFR at the metropolitan level for seven consecutive years starting 2015, peaking at 1.89 and still at 1.03 in 2024 even as the national figure fell to 0.75. Sejong didn’t layer subsidies. It assembled three things at once: stable public-sector employment as central ministries relocated from Seoul, relatively affordable new housing (a local policy choice enabled by Sejong’s being built without legacy zoning politics), and public kindergartens accounting for 93 percent of early-childhood provision against a national figure closer to a quarter. The housing did TMR work directly: it was what let young government workers form households. The childcare did CPM work: it was what let those households have second children. The employment anchored both. Concentration raised infant exposure for everyone else who lived there. The empathy channel activated. Fertility desires formed.

Lee Sang-rim, a demographer at the Korea Institute for Health and Social Affairs, puts the principle directly:

“We need to approach fertility from the perspective of the youth life course, independence, employment, housing, family formation, child-rearing, rather than through fertility-boosting subsidy programs.”

When the first three work, the fourth and fifth can happen. Sejong’s advantage is narrowing as neighboring Daejeon competes for the same newlyweds with its own ₩300,000-per-month subsidy, which illustrates how fragile municipal success is when the national framework doesn’t recognize and protect what works.

When does a train-station daycare beat a cash bonus?

Nagareyama, a Tokyo commuter town that elected Yoshiharu Izaki mayor in 2003, ran a formal SWOT analysis of the city before taking office, picked dual-employed households with children as the target customer, and built infrastructure around them. The headline intervention was train-station childcare: at Nagareyama-Otakanomori and Minami-Nagareyama stations, parents drop children between 7 and 9 a.m., staff bus them to participating daycares across the city, and the buses return them by 6 p.m., at 100 yen per day. The logistical problem it solved was real. The less obvious thing it did was put parents and children together in the most visible public space in the city twice a day, for years. Nagareyama reached a fertility rate of 1.50 in 2022 against a national 1.26, and was Japan’s fastest-growing city for six consecutive years.

Matsudo runs a similar model with different instruments. The city has won or placed in the top three of Nikkei’s dual-career-friendly cities ranking every year since 2018, and has achieved 10 consecutive years of zero waitlist by building 121 small-scale childcare facilities positioned at all 23 train stations in the city. Matsudo treats the commuter-parent as the customer: every station has childcare within walking distance of the fare gates. The insight travels within a prefecture willing to organize around it.

Akashi, in Hyogo Prefecture, demonstrates what happens when a city government chooses what it is. Mayor Fusaho Izumi raised the child-policy budget from 125 billion yen to 297 billion yen while the overall budget stayed flat, and tripled the staff on child policy, recruited lawyers and welfare specialists onto the municipal payroll, consolidated kindergartens and libraries under a new Children’s Future Department, and moved authority over preschool policy from the school board to the mayor’s office. The visible “five free things” for children rested on organizational restructuring that took years and that no one outside city hall noticed. The reorganization was the intervention; the free services were its downstream expression. Akashi hit a TFR of 1.7 in 2018 against a national 1.42 and ran nine consecutive years of population growth. Critics point out that much of the gain is in-migration from Hyogo municipalities that didn’t match the policy. Right, and it matters less than they think. In-migration concentrates families in an environment where they’re visible to Akashi’s existing residents, and concentration activates the chain.

Two smaller cases extend the pattern. Hinode-machi in western Tokyo produced the largest TFR improvement of any Japanese municipality in Nikkei’s survey, +0.57 from 1.02 to 1.59, through coupons and allowances. Furubira-cho in Hokkaido raised its TFR by 0.47 to 1.62 on a retention logic its mayor stated plainly: “Childcare support has a defensive aspect against out-migration. It’s worth the cost.”

What happens when you get the numbers without the ecosystem?

Haenam County, in the same South Jeolla province as Yeonggwang, is the story of success that wasn’t. Haenam held Korea’s top TFR for seven years running, peaking at 2.46 in 2015. In 2017 it became the only Korean region to exceed 2.00 since Korean below-replacement fertility set in. The county received a Presidential Award on Population Day in 2016. It was the global poster child for municipal fertility success, until it wasn’t. By 2022, Haenam’s TFR had fallen to 1.04. Annual births fell from 839 in 2015 to 295 in 2021. The Korean press coined a term for what had happened: 먹튀 출산, “eat-and-run birth.”

There’s something bleak about a town winning a Presidential Award for something it wasn’t actually doing. Neighboring counties started offering bigger cash subsidies. Fertility-minded families moved for the subsidies, collected them, and moved on. The design Haenam had was transactional, not ecological. There was nothing to stay for after the cash arrived. A 2023 analysis by the Korea Institute for Health and Social Affairs showed the deeper mechanism: Haenam’s “high fertility” years corresponded to a low share of women aged 15 to 49 in the population (28 to 35 percent), compared to 44 to 54 percent in genuinely growing high-fertility places like Jinju, Asan, and Dangjin. Haenam had a small denominator that cash could inflate temporarily. It did not have an ecosystem that shifted desires in the next cohort. When the cash moved elsewhere, so did the numbers.

Is there a single variable that matters most?

Kasuga, a Fukuoka commuter town of roughly 115,000, is the exemplar of the scale-of-commitment principle. Kasuga allocates approximately 41 percent of its municipal budget to child welfare spending (児童福祉費), roughly triple what comparable Japanese municipalities allocate. The town positions itself as family-friendly for Hakata-area commuters, operates six train stations connecting to Fukuoka’s center, and pushed its child-focused investment at a level that a recent analysis of all 1,741 Japanese municipalities by Kawasaki and Morimoto identified as the single most powerful municipal-level predictor of desired birth rates, with a coefficient of 0.47 that dwarfs density, transit access, income, facility counts, and commute patterns. The point isn’t that every municipality should allocate 41 percent. The point is that the share of the budget going to children is the most consequential variable any municipality controls, and most municipalities don’t know this because nobody has told them.

Can a province do what a country can’t?

Bolzano, Trentino, and Vorarlberg sustain fertility meaningfully above their national averages over decades at the provincial scale, and they do it through three different designs.

Bolzano (Alto Adige / Südtirol) is the consumer-facing brand. Italy’s national fertility has fallen to 1.13 in 2025; Bolzano holds 1.55 and is the only Italian province whose fertility rate actually rose between 2024 and 2025. The province runs an 8.7-billion-euro annual budget, with roughly 200 million euros going to family policies specifically, split across direct transfers, the 0-to-3 childcare network, and employer incentives for work-family conciliation. The visible elements are the Family+ card giving retail discounts to families with three or more children, retailer partnerships, trilingual welcome backpacks for newborns, and the Tagesmütter system of certified home-based childcare that covers rural valleys where centralized daycare would be uneconomic.

The institutional elements are more load-bearing than the visible ones. A single unified Department for Family has coordinated the work since 2013, an Agency for the Family acts as the policy interface with municipalities and employers, a Consulta per la Famiglia of 19 members shapes direction, and every municipality and district community has a family-referent in its executive council. This is the organizations-don’t-optimize-separately principle in action: the province broke down the barriers between departments that would otherwise each run their own family program badly. The housing component is equally important and usually overlooked: Bolzano builds more housing per capita than Milan or Rome (roughly 0.22 square meters per capita in 2022 against 0.14 in Milan, and 0.31 against 0.11 pre-Covid), which means a young couple can actually find a family-sized apartment. And the Audit certification for family-friendly workplaces now covers 55 certified companies, bringing the employer into the ecosystem rather than leaving the conciliation problem to households alone.

Trentino, just south, runs a more institutional setup. Provincial Law No. 1 of 2011 established an integrated family system with a dedicated agency run by Luciano Malfer since its founding. The province runs a Family Audit certification for employers, a “Comune Amico della Famiglia” designation for municipalities, a network of Distretti Famiglia (family districts), and 93.4 percent municipal coverage of early-childhood services. Regional TFR for Trentino-Alto Adige combined is 1.39 against the national 1.18, with Trentino’s own number somewhat below Bolzano’s but well above the Italian baseline. The contrast with Bolzano is instructive: Bolzano does consumer-facing branding backed by services; Trentino does institutional structure backed by a provincial statute. Different instruments, same outcome.

Vorarlberg, Austria’s westernmost Land, runs a third model with almost no centralized brand. Vorarlberg’s 2023 TFR was 1.50 against Austria’s 1.32. The province offers a Familienpass that every Vorarlberg family automatically receives, good for discounts at over 200 partner businesses and reduced public transit fares, renewing automatically until children turn 18. On top of this sit the familieplus program recognizing family-friendly municipalities, and Vorarlberg lässt kein Kind zurück (”Vorarlberg leaves no child behind”), a comprehensive child-welfare framework coordinating federal and provincial supports. Municipalities administer most services; the province provides the shared infrastructure; the brand is almost invisible compared to Bolzano’s. This matters because Vorarlberg demonstrates that the specific visibility design is substitutable. What isn’t substitutable is sustained institutional commitment to families as the unit around which other provincial decisions orient themselves. (Vorarlberg’s trajectory is fragile: the regional family association reports a 9.4 percent birth-rate decline between 2021 and 2023, reflecting Austria-wide housing and cost-of-living pressures. Even strong provincial ecosystems don’t insulate against national-scale shocks.)

Malfer puts the shared principle in his own words:

“Money isn’t what counts. In these policies the winning card is a management model that conceives of the family as a resource for society.”

The management model is the product. Everything visible downstream is just the management model becoming visible. Michela Morandini, Bolzano’s director of Social Cohesion, Family, Elderly, and Cooperatives, says the same thing from the other province:

“There is broad consensus across all local parties on maintaining these policies, which have lasted for years and are not continually changed like national ones.”

A family pulling out the Family+ card today has reasonable confidence it will mean the same thing in ten years. That confidence is the product. The card is its visible manifestation.

What does twenty years of commitment actually buy?

Nagi, a rural town of roughly 5,700 people in Okayama Prefecture, is the closer on commitment. Nagi’s TFR climbed from 1.41 in 2005 to 2.81 in 2014, then to a peak of 2.95 in 2019, which the town built and sustained for more than two decades through ordinary interventions any municipality could copy: cuts to its own council seats and staff to free up child-policy budget, volunteer aiiku-iin delivering personal gifts to newborn families, and a suite of supports sustained long enough that residents learned to plan around them. Eighty-five percent of Nagi’s child-rearing households have two or more children; 48 percent have three or more. That’s a CPM distribution: completed family sizes shifted upward by an environment that made second and third children plannable.

A young couple in Nagi believes the support will still be there in five years because it has been there for twenty. That belief is part of the product, and it can’t be manufactured through a single visible intervention. It’s the cumulative output of a town that kept doing the same thing long enough that the doing became part of what the town is. Call it constancy of purpose. Institutions that change direction every administration cannot build the trust that lets families plan around them, which is the failure mode every municipality trying the visible interventions without the underlying commitment eventually demonstrates: a mayor announces, the press covers, fertility ticks up, the next administration arrives with different priorities, the budget tightens, the program disappears. The customer base that had started to believe the city was committing learns that institutional commitments cannot be trusted.

What the municipal cases share isn’t generosity. None of them spent dramatically more than comparable places. What they share is the alchemy and the machinery held together long enough that the compounding started, and the politics to keep it running across administrations. Visibility shapes desires, which shape marriage decisions, which shape fertility. Each link is now empirically established.

Why the national conversation is stuck

What if the French exception isn’t fading evenly?

France is the case Shaw’s framework reframes most sharply. The conventional reading is that France’s century-long fertility exception is fading: French fertility is closer to European averages than a decade ago and falling. The decomposition says something more specific. Between 2013 and 2023, France’s CPM remained stable between 2.3 and 2.4 children, while TMR fell from 85.0% to 72.8%.

French mothers are still having French-sized families. What’s collapsing is entry into motherhood at all. This matters because French policy has been organized for a century around the CPM side: generous family allowances that scale with parity, school and childcare systems that make two and three children manageable for existing mothers, tax incentives (the quotient familial) that lower the marginal cost of additional children inside a family. These instruments still work for the population they reach, which is why CPM held flat through a decade when most of Europe saw it slipping. None of them do anything for the 27-year-old who hasn’t started. Whether she enters motherhood depends on whether she can form a household, whether the labor market will penalize her for doing it, whether the housing she can afford has room for a child.

The CPM-supporting ecosystem, the part that works locally on existing parents, is doing roughly what it always did. The TMR-supporting national conditions are deteriorating. The French exception isn’t fading in some general sense; it’s fading in one component while the other holds, and the failing component is the one that sits before any local ecosystem can reach.

This is the diagnostic payoff of the decomposition. A country can spend more, sustain the spending longer, build the most institutionally continuous family policy in the developed world, and still watch the aggregate number slip, because the aggregate hides which half is slipping. If you can’t see that France’s TMR is falling while its CPM is stable, you can’t see that French policy needs a different kind of intervention now than the one it has historically delivered well.

Why do cash transfers keep hitting ceilings?

Poland’s 500+ program raised fertility from 1.29 to 1.45 within two years through a near-universal cash transfer; Polish fertility has since fallen back. Germany’s 2007 parental allowance reform produced a measurable increase concentrated among highly educated women, but current German fertility is where it was before. Targeted components can move TMR for the segment they target. They don’t compound without an ecosystem around them. said it in 2020 with more directness than most pro-natal literature allows:

“Any pro-natal policy agenda will have to be about more than just a child tax credit. It’s vital that policymakers also think about how they can remove obstacles to marriage, facilitate access to decent housing, and accelerate completion of education, all vital elements in the modern economic life cycle leading up to childbearing.”

Cash at the moment of childbirth arrives after most of the consequential choices have been made.

What does x% percent of a national budget buy when the system is broken?

Korea is the anti-case, and Korea’s decline is heavily TMR. Korean marital fertility has been stable; the collapse is in whether people marry at all, which means the binding constraints are all the national conditions shaping whether young Koreans form fertility desires in the decade before marriage. The country spends roughly 6 percent of its government budget on fertility policy and has the world’s lowest national rate, which is what spending looks like when it’s flowing through a system that doesn’t work.

Korean policies, evaluated rigorously, have measurable effects in their domains. Kim’s analysis of Korea’s regional baby bonus variation finds Korean TFR would have been 4.7 percent lower without the transfers, equivalent to roughly 562,000 fewer children over the lifecycle of the 2015 female cohort, with elasticities from 0.34 to 0.58 depending on birth order. The same program dropped the third-child sex ratio from a counterfactual 124.7 boys per 100 girls to 105.3, cash reshaping a deeply embedded cultural preference. A 2011 reform expanding childcare leave subsidies for higher-earning mothers produced a 2.3 to 2.5 percentage point increase in conception rates with no significant effect on employment. These are real findings. Korean policies work in the places where they can reach; they do modest CPM work on families who were already going to have at least one child. What they don’t do is reach the TMR frictions producing the aggregate decline, because those frictions sit before any component-level policy can touch them. No marriage bonus reaches a 25-year-old whose employer will force her to sign an illegal contract promising to resign if she becomes pregnant, whose housing is unaffordable on non-regular employment, whose education ran six years past the age her mother was when she married, and whose ten-year earnings penalty for motherhood is seven times what a Swedish mother faces.

The vertical fragmentation makes this worse. Korea runs national cash transfers, metropolitan housing rules, ward-level childcare allocation, and a private hagwon market that none of those layers regulates. Each layer optimizes its own component. Nobody is responsible for whether they fit together for the family trying to use them. The principle that organizations fail when departments optimize separately applies equally across levels of government. The central, provincial, and municipal layers are running independent strategies on the same families.

The Korea Institute of Public Administration said substantively the same thing in 2023: current regional support policy “lacks long-term performance indicators and performance management systems; insufficient project identification and evaluation systems for the regional extinction response mission; and insufficient awareness and capacity at the local government level”. The country’s successful municipal outliers get no structural recognition: as National Assembly member Lee Gae-ho noted in August 2025, Yeonggwang has produced six consecutive years of top-ranking fertility and measurable net in-migration, yet “actual fiscal support is lacking” because the central government has no incentive system that rewards municipalities that succeed. The center can’t see what its own municipalities have built, which means it can’t amplify what works or replicate it elsewhere.

The scale of the TMR frictions deserves naming because the numbers are staggering. Korean workers put in 1,865 hours a year against 1,431 in Sweden. Raising a child to 18 costs $275,000, or 7.8 times GDP per capita, against 4.1 times in the US. Eighty percent of Korean children attend a hagwon, and Koreans spent $19 billion on shadow education in 2023. None of this is reachable by any subsidy a mayor can offer. This is what the environment looks like when the chain has been running in the wrong direction for a generation. The TMR shocks that drove the chain into this position arrived discretely and ratcheted down. Each ratchet depleted the next cohort’s exposure environment further.

Doesn’t Korea’s recent rebound change the picture?

Korean TFR rose slightly in 2024 and 2025: 0.72 in 2023, 0.75 in 2024, an estimated 0.80 in 2025, the first sustained increase in a decade. The rebound is structural timing. The echo-boom generation born in the early 1990s is entering peak childbearing age, and pandemic-deferred marriages are happening with the usual two-year lag before births. None of the structural conditions has changed. The aggregate moved without the environment moving, which is exactly the failure mode the decomposition was built to expose: TFR can rise on cohort timing while the underlying ratchet stays where it was, and the next cohort will discover the gain didn’t compound.

National-scale policy is mostly stuck. Multiple ministries with separate budgets, short electoral cycles, slow demographic feedback, and structural reforms that are politically contentious in ways component-level programs aren’t. France stayed the course for a century because institutional continuity held, and even France is now showing the TMR component slipping while the CPM component holds, which is what slipping looks like before the aggregate number tells you it’s slipping. Korea and Germany and Italy haven’t, and there’s no credible mechanism in their current political economies for them to start.

The local work is the infrastructure

What can’t a mayor reach?

The bulk of the fertility problem in most developed countries is TMR (fewer young adults entering the parenthood pathway at all), and the bulk of TMR’s binding constraints are national. No mayor can reach them. Housing is the major exception, and its politics are moving. Most of the others are not. Energy policy shapes the real cost of running a household and therefore the economics of forming one. Industrial policy determines whether the labor market absorbs young men at stable wages, which determines whether they become marriageable on the timeline their biology and their desires suggest. Education finance shapes both the direct cost of raising a child and the timeline on which a young adult finishes training and enters the family-formation window.

Each of these deserves careful work, close attention to political economy, and mapping of the coalitions that could move them. None of it exists yet in the form pronatalists need. Someone has to do it. This essay is not that essay. This essay is about what to do in the meantime. Shaw's ratchet pattern makes the stakes legible: the 1970s oil shock didn't just raise prices, it triggered the economic disruption that stamped an entire cohort's TMR down permanently and never let it recover. Energy and industrial policy are pronatalist policy, whether pronatalists treat them that way or not. That essay still needs writing.

The claim here is that while the national conversation remains stuck, useful subnational work should proceed now. The municipal and provincial cases do most of the achievable work on CPM (completed family sizes among women who were going to become mothers), direct TMR work on the frictions local authority can reach (housing the main one), and additional TMR work through local concentration raising ambient infant exposure for residents who weren’t already fertility-minded. None of this solves the national TMR problem. But together these build the infrastructure national TMR reform will need to land on if and when it arrives, and they’re the work doable inside the political constraints mayors and provincial administrators actually face.

What are mayors actually doing when they succeed?

A mayor building Nagareyama’s station childcare or Akashi’s Children’s Future Department isn’t building a scale model of what a prime minister should do. She’s doing two things at once: building CPM infrastructure, and working around the missing vertical coherence her national government won’t supply. The mayor can’t make the central government cohere with the city, but she can at least make the city cohere with itself. Akashi consolidated kindergartens and libraries under a new Children’s Future Department and moved preschool authority from the school board to the mayor’s office. Trentino passed Provincial Law No. 1 of 2011 to put a single agency in charge. Nagi cut its own council seats to free up child-policy budget. These are vertical integration moves inside the layer the actor controls.

The empathy channel runs in an environment. Environments are built locally, by entities small enough to act and sustained enough to hold. A country with no local ecosystems is a country where, even if national TMR reform eventually arrives, the young mothers it produces stop at one child because the local environment doesn’t make a second or third livable. A country with a hundred Nagareyamas is a country where national TMR reform, when it comes, has CPM infrastructure to land on. The local work complements national reform; it doesn’t substitute for it.

Yeonggwang and Sejong and Nagareyama and Akashi and the Alpine provinces aren’t demonstrations of what Korea or Italy or Japan should do at the center. They show what mayors and provincial administrators can do now, inside the political constraints they face. Every one of these places shifted ambient exposure, then desires, then marriage and fertility decisions, at the scale where they had authority to act. The aggregate numbers for their countries didn’t move much, because most other cities and provinces didn’t do the same thing and because the national TMR frictions continued to depress entry to parenthood across the full cohort. Building the ecosystem in your jurisdiction makes the national number movable when the center eventually turns, and captures the CPM gains available at your scale regardless of what the center does.

The Uchikoshi findings sharpen this in a specific way, and Shaw’s decomposition sharpens it further. If fertility desires shape marriage decisions rather than the other way around, and if marriage decisions drive fertility in East Asia, then the TMR leverage point is the environment shaping fertility desires in unmarried young adults. The bulk of that environment is national. But some of it is local: the ambient infant exposure a 25-year-old experiences in her actual neighborhood is a municipal-scale variable, and local ecosystems that sustain high exposure do activate the empathy channel for residents who weren’t already fertility-minded. This is the TMR work local ecosystems can do. It’s real but limited. What it isn’t limited on is CPM: the same local environments that produce some TMR activation are also the environments where existing mothers decide whether to have second and third children, and that decision is almost entirely a local question. National cash transfers, by contrast, deliver modest CPM effects and essentially no TMR effects because they don’t touch the binding national constraints that shape young adults’ fertility-desires environment. Uchikoshi’s own policy conclusion lands here, where the operational decision gets made: “policy efforts that increase fertility desires among young people contemplating family formation by reducing uncertainty around childbearing may also contribute to higher fertility via their positive effect on marriage.” Reducing uncertainty around childbearing is exactly what a local ecosystem does. It makes the environment clear enough that a young adult can see what her thirty-five-year-old self might plausibly live, and the empathy channel takes care of the rest.

One caveat. Some fraction of the fertility-desires shift is autonomous, genuine preference change that ecosystems cannot reach. A 25-year-old who has thought it through and concluded she doesn’t want a life that includes children isn’t going to be empathy-channeled back into wanting one. That fraction exists, and the ecosystem argument makes no claim on it. What the ecosystem argument claims is the fraction shaped by environment, which Shaw’s reading of the Fertility Gap puts at the center of the problem: the gap between desired and actual fertility stems less from mothers having fewer children than desired, and more from a growing share of women who hope to become parents but ultimately remain childless. That’s a TMR phenomenon, women who wanted to become mothers and didn’t, and it’s exactly the territory where ecosystems do work, because the fraction of TMR loss attributable to depleted environment rather than autonomous preference change is large, and it’s largest in places where the ratchet has been running longest.

So what should pronatalists actually do?

The pronatalist response to national policy stagnation shouldn’t be despair. It should be aggression at every layer below national, because that’s where the work that compounds is actually getting done. I am still going to write essays on why energy and industrial policy is pronatalist policy and vice versa at the end of the day, because no pronatalist policy is immune from oil shocks, as Shaw’s paper makes perfectly clear. Pronatalists need to think about this stuff, but we are still limited by the political economy.

Build the ecosystem where you have authority. Capture the CPM gains available at your scale. Start with housing, the YIMBY coalition already exists, the municipal authority is real, and the intervention does TMR, CPM, and empathy-channel work simultaneously.

The local work also builds the political capital and institutional expertise that pronatalists will need for national reform. A country with a hundred Akashis has a bench. A country with zero has a press release.

Jobs didn’t convince anyone they wanted a phone. He built the system, and the system delivered, and the delivering changed what the next wave of people could imagine wanting. The demographic version is harder and slower, but it’s the same thing: alchemy on top, machinery underneath, and the politics to keep both running long enough that the compounding kicks in. The jurisdictions that have figured out how to hold all three together are municipalities and provinces. The countries that end the next four decades with that infrastructure in place will be in a different position from the countries that don’t.

A 2025 college graduate applies to forty jobs, hears back from three, gets ghosted after two rounds of interviews with each. Her LinkedIn feed tells her why: AI is coming for entry-level work. Dario Amodei predicts half of entry-level white-collar roles will vanish by 2030. Jack Dorsey fires 40 percent of Block’s workforce and says intelligence tools have changed what it means to run a company. She starts to wonder if her degree was a mistake.

Marc Andreessen, on the 20VC podcast last week, told her she is being lied to. Most large companies are overstaffed by 25 to 75 percent thanks to pandemic-era hiring binges, he said, and AI is “the silver bullet excuse” to clean house without admitting the real reason. “AI literally until December was not actually good enough to do any of the jobs that they’re actually cutting. It just can’t have been AI.”

He is mostly right. The evidence we lay out below supports him. But his version has a convenient blind spot.

If these companies are so bloated, where are the good products? Microsoft has over 220,000 employees, yet Windows 11 shipped with a Start menu that broke basic workflows, an ad-infested lock screen, and a Settings app that still cannot do half of what the Control Panel could in 2009. Google has 180,000-plus people and has been trying to fix Google Assistant for a decade. Apple spent years and roughly 165,000 employees on a Vision Pro that sold to almost nobody. These are not organizations with 50 to 75 percent surplus headcount. They are organizations where management layers, internal politics, and misallocation have made it hard to ship anything well. The people are not unnecessary. The structure wastes them.

There is also something Andreessen will not say, because it implicates his own industry. If cost of capital were still near zero, as it was from 2009 to 2022, Andreessen Horowitz would be writing bigger checks into more portfolio companies, each hiring aggressively to chase growth before profitability. Venture capital ran on that model for over a decade: fund companies, tell them to hire fast, grow into the valuation later. The people now called “bloat” were, three years ago, called “scaling.” What changed was the federal funds rate. When capital is expensive, every investor suddenly discovers their portfolio companies have too many people. Andreessen is diagnosing a symptom and calling it a disease.

Meanwhile the graduate’s problem is real, and it is worse than either narrative acknowledges. The share of unemployed Americans who are new workforce entrants hit a 37-year high in 2025, peaking at 13.3 percent in July, exceeding anything recorded during the Great Recession. It settled to 10.6 percent by February 2026, still worse than the worst of 2008-09. The New York Fed reports that the underemployment rate for recent college graduates climbed to 42.5 percent by the fourth quarter of 2025, meaning almost half the people who just spent four years and six figures on a degree are working jobs that never required one. Finance and information services, the traditional on-ramps for college graduates, have been shedding an average of 9,000 jobs per month since 2023. Before the pandemic, those same industries were adding 44,000 jobs per month.

She is right that the ladder is broken. She is wrong about what broke it. And Andreessen, for all his bluster, is wrong about why.

It is not AI. But it is not simply a correction of pandemic overhiring, either. The true culprits run deeper: a job ladder that has lost half its rungs over four decades, rising employer concentration, the quiet spread of noncompete agreements into low-wage work, and the sharpest monetary tightening cycle in forty years, now about to be compounded by an oil shock that will freeze what little entry-level hiring remains. The wrong diagnosis leads to the wrong treatment, and young workers cannot afford the delay.

Forty-Years of Collapse

To understand what is happening to the graduate, we need to go back much further than ChatGPT. Four decades further.

Labor economists have used the metaphor of the job ladder for so long that we sometimes forget it describes a real mechanism. The job ladder is not a metaphor for ambition. It is the institutional infrastructure through which labor markets allocate talent and distribute gains. A young worker enters the labor market and takes a job at a firm that may not pay particularly well. Over the next several years, she receives offers from competing employers. Some pay more. She accepts the better ones and moves up. Robert Topel and Michael Ward documented in 1992 that the average American worker has seven employers in the first ten years. That churn is not dysfunction. It is the mechanism by which wages grow. About 60 percent of the wage growth in the first decade of a career comes not from raises within a firm but from moving between firms toward better-paying employers.

That is how it is supposed to work. A March 2026 working paper from Niklas Engbom, Aniket Baksy, and Daniele Caratelli shows how badly it has broken down. Using Current Population Survey microdata from 1982 to 2023 and a job-ladder model calibrated to match the data, they estimate that employed workers today are roughly half as likely to receive a better-paying outside offer as they were in the 1980s. Net upward job mobility, their summary measure of ladder strength, fell by 51 percent between the early 1980s and the 2010s.

Half the rungs are gone.

The consequences for wages are severe. After more than doubling between 1940 and 1970, real hourly earnings in the United States have increased by only about 25 percent since 1980. If you hold the demographic composition of the workforce constant at its 1980s level, stripping out the effect of the shift toward older and more educated workers, real wage growth since 1980 is close to zero. Engbom, Baksy, and Caratelli estimate that the decline in the job ladder accounts for about one-third of that slowdown, reducing annual real wage growth by 0.68 percentage points. Over four decades, that compounds into a very large number.

Only about one-third of the wage effect is mechanical, meaning workers climb the ladder less often and therefore end up at lower-paying firms. The remaining two-thirds arises because firms choose to pay less when they face less competition for workers. We tend to think of the job market as a place where employers set wages and workers accept or decline. The Engbom paper shows that a large share of what determines wages is not the employer’s productivity or the worker’s skill but the threat of departure. When that threat recedes, as the Nobel laureate Peter Diamond predicted, firms converge toward offering the minimum workers will accept. The ladder is the invisible discipline that makes the whole system pay what it should. And the discipline has been quietly collapsing for forty years.

The decline is broad-based. Men and women, white and nonwhite workers, college graduates and non-graduates all saw large drops in upward mobility. But the decline is especially pronounced for young workers, whose net upward mobility fell from 1.286 in the 1980s to 0.482 in the 2010s. Women experienced a larger decline than men. Nonwhite workers fell from 1.099 to 0.423. There is no demographic group for which the ladder is working as it once did.

The graduate applying to forty jobs in 2025 would recognize the symptoms even without seeing the data. A Rezi.ai analysis of job postings found that 35 percent of positions labeled “entry-level” now require three or more years of experience. Entry-level roles requiring zero to two years have dropped by 29 percentage points. This “experience inflation” is what the collapsed ladder looks like from the ground. When firms face no competitive pressure to invest in developing junior talent, they redefine entry-level to mean mid-career. The label stays. The opportunity vanishes.

Engbom, Baksy, and Caratelli rule out several plausible alternative explanations. The decline is not driven by lower matching efficiency: job-finding from nonemployment has declined only modestly over forty years, while job-finding from employment has fallen sharply. If the matching technology or labor demand were the problem, both rates would have moved together. The decline is not driven by house lock-in: renters experienced larger declines in on-the-job search efficiency than homeowners. It is not driven by dual-career constraints: single-career households experienced larger declines than dual-career households. This is not a story about workers who stopped climbing. It is a story about an economy that pulled the ladder away.

Who Pulled the Ladder Away

Two forces show up consistently in the cross-state evidence: rising employer concentration and the proliferation of noncompete agreements.

States where employer concentration increased more between the 1980s and 2010s experienced larger declines in upward job mobility. States where a higher share of workers report being bound by noncompete agreements show the same pattern. A back-of-the-envelope calculation by Engbom, Baksy, and Caratelli implies that rising concentration and noncompete use together may account for roughly 60 percent of the national decline in the efficiency of on-the-job search.

The concentration story is about arithmetic. Fewer employers in a labor market means fewer competing offers for employed workers. Fewer competing offers means less pressure on wages. You can see the same mechanism in industry after industry. In oil and gas, as documented in a previous article, roughly $200 billion in mergers since late 2023 has consolidated half of the Permian Basin’s most productive formation under two companies. ExxonMobil acquired Pioneer for $60 billion, Chevron acquired Hess for $53 billion, and Diamondback merged with Endeavor for $26 billion. The wildcatter ecosystem that once converted price signals into production and employment, chaotically and wastefully but at enormous scale, was replaced by capital-disciplined giants that return cash to shareholders regardless of what prices do. The labor market consequences follow: fewer firms competing for workers, less upward mobility, lower wage pressure.

The same dynamic, less dramatic but more pervasive, operates across the broader economy. It does not require conspiracy. It requires only that the number of independent employers shrinks and that the remaining employers face less competitive pressure to bid for workers.

The noncompete story is more galling. Legal experts describe the period from 1990 to roughly 2010 as the golden age of noncompete enforcement in America. What started as a tool for protecting senior executives’ trade secrets metastasized into a blanket restriction applied to hourly workers, sandwich shop employees, pet cremation technicians. An estimated 30 million Americans, nearly one in five workers, are bound by a noncompete agreement. These agreements directly suppress the mechanism through which the job ladder operates: they prevent employed workers from accepting better offers.

The FTC, under the Biden administration, attempted a nationwide ban. The estimated effects were large and specific: $400 to $488 billion in increased wages over the next decade, $524 per worker per year in additional earnings, 8,500 new businesses annually, and 17,000 to 29,000 additional patents per year. The rule was struck down in federal court. The Trump administration formally vacated it in September 2025. The FTC has shifted to case-by-case enforcement, including a February 2026 consent order against a pet cremation company that had imposed blanket noncompetes on 1,780 employees, including hourly laborers and drivers. The bipartisan Workforce Mobility Act, reintroduced in June 2025 by Senators Murphy, Young, Cramer, and Kaine, would ban most noncompetes nationwide. It has been referred to committee. No further action has been taken. Over 150 bills have been introduced in more than 35 states, creating a patchwork that varies by jurisdiction. The patchwork is the opposite of the clear nationwide signal that would restore competitive dynamics.

The graduate scrolling LinkedIn is not competing against chatbots. She is competing against four decades of eroded mobility, in a labor market where the companies that might hire her face less pressure to do so than at any point since the data began. We all spent two years worrying that AI will trap young workers in obsolete careers, if they every get a career in the first place. Meanwhile, noncompete agreements have been legally trapping workers in underpaying jobs for decades, and we barely noticed.

AI Alibi

So if the ladder was already broken, why does everyone keep blaming AI?

Partly because there is a credible-looking academic case. Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen’s 2025 working paper, aptly titled “Canaries in the Coal Mine,” finds a 16 percent relative decline in employment for early-career workers ages 22 to 25 in the most AI-exposed occupations since the public release of ChatGPT in November 2022. Brynjolfsson himself reiterated the finding at a Stanford panel in March 2026: about a 20 percent decline for entry-level software developers, about 15 percent for call center workers. Mid-career people are doing fine. Senior people are doing well. The narrative has cultural momentum. A Harvard survey found that 44 percent of young Americans believe AI will reduce job opportunities, while only 14 percent expect it to create more.

Let’s take this argument seriously. But taking it seriously means subjecting it to scrutiny.

The central weakness is the timeline. The “Canaries” paper documents an employment inflection point beginning in November 2022, immediately following ChatGPT’s public launch. By June 2023, roughly half of the total observed decline had already materialized. For this to be an AI story, we need to believe that within six months of a consumer chatbot’s release, firms across the economy decided that AI could replace junior staff, built the necessary enterprise infrastructure, redesigned complex workflows, ensured data security and regulatory compliance, and executed staffing changes at national scale.

That did not happen.

The OpenAI API, a prerequisite for building any custom application, only launched on March 1, 2023. ChatGPT Enterprise, which offered the data privacy guarantees that corporations require before touching sensitive operations, launched on August 28, 2023. The generative AI models available in late 2022 and early 2023 fabricated information freely enough that the term “hallucination” entered common use. U.S. Census data shows that fewer than 10 percent of large businesses were even planning to use AI in the next six months as late as the fourth quarter of 2023. By the third quarter of 2025, actual adoption among large businesses had only climbed to 12 percent. The tools that would have been necessary for the displacement story to work did not exist during the period the displacement supposedly occurred.

What did exist was a hiring freeze, and it started before the chatbot arrived. An analysis of job postings data from Lightcast, published by Zanna Iscenko and Fabien Curto Millet of Google’s economics team in their January 2026 paper for the Economic Innovation Group, shows that vacancies for the highest AI-exposure quintile of occupations peaked in March and April of 2022 and declined sharply throughout the rest of the year, a full six months before ChatGPT launched. The decline in employment levels starting in November 2022 is the predictable, lagged consequence of that earlier hiring freeze: when you stop bringing in new graduates, routine attrition is no longer offset by new hires, and the headcount of 22-to-25-year-olds mechanically shrinks.

Iscenko and Curto Millet illustrate this with a simple thought experiment. Take a hypothetical occupation that starts with an equal number of workers at each age from 22 to 65 and impose a complete hiring freeze but zero layoffs for one year. When you study this occupation a year later, entry-level employment for the 22-to-25 age band has shrunk by 25 percent. Employment for every other age group has not changed at all. The statistical pattern perfectly mimics targeted AI displacement. It is not AI displacement. It is arithmetic.

The job postings data also contradicts the AI story on its own terms. Within occupations most exposed to AI, postings for junior roles have not declined faster than postings for senior roles. Both fell roughly in parallel from their spring 2022 peak, with junior postings actually stabilizing faster. If AI were selectively automating entry-level tasks, the divergence between junior and senior postings would be the first place you would see it. It is not there.

Why, then, did AI-exposed occupations get hit harder than others? Because “AI exposure” and “interest rate sensitivity” overlap almost completely. Occupations in the top quintile of AI exposure are overwhelmingly concentrated in information, finance and insurance, and professional and technical services. Approximately 38 percent of workers in the most AI-exposed quintile are in these sectors, compared with less than 2 percent in the least-exposed quintile. These are the sectors most sensitive to capital costs and economic uncertainty. When the Federal Reserve began its most aggressive tightening cycle in forty years in March 2022, the timing lined up exactly with the decline in job postings across these sectors. Research by Zens, Böck, and Zörner has found that workers in tasks rated as easily automated are also disproportionately affected by conventional monetary policy shocks. The correlation is confound, not coincidence.

And the same differential pattern appears in the hiring slowdown of early 2020, when generative AI could not even theoretically be the explanation. If the same occupations decline relative to others during every downturn, AI is not required to explain the pattern. Monetary policy and sector sensitivity are sufficient.

The finding is not isolated. Gimbel, Kinder, Kendall, and Lee find no discernible break in aggregate U.S. employment trends since ChatGPT. Humlum and Vestergaard, using extremely detailed Danish microdata, find that AI’s impact on individual earnings and hours is “precise zeros,” with workplaces adopting AI showing no shifts in job creation or destruction. They do find a decline in early-career employment, but their difference-in-differences analysis shows AI is not driving it. A Yale Budget Lab report described the notion of AI roiling the job market as “largely speculative.” The Vanguard finding is the sharpest of all: their December 2025 economic outlook reports that the roughly 140 occupations most exposed to AI automation are actually outperforming the rest of the labor market in both job growth and real wage increases since the second quarter of 2023. If AI were displacing workers, these occupations would be the worst place to look for a job. They are not.

AI may yet reshape entry-level work in ways we cannot currently measure. But the claim that it has already done so at scale is not supported by the evidence. So why do companies keep saying it?

Because it works. The practice has acquired a name: AI washing. Of the 1.2 million job cuts U.S. companies announced in 2025, nearly twice 2024’s total, AI was cited in only about 55,000, or 4.5 percent, according to the research firm Challenger, Gray and Christmas. A January 2026 Forrester report found that “many companies announcing A.I.-related layoffs do not have mature, vetted A.I. applications ready to fill those roles,” describing the trend as companies attributing financially motivated cuts to future AI implementation that does not yet exist. Nearly 60 percent of hiring managers surveyed by Resume.org said they emphasize AI’s role in reducing hiring or cutting jobs specifically because it is viewed more favorably than admitting to financial constraints.

The cases are specific enough to be embarrassing. Amazon’s CEO Andy Jassy initially linked the company’s rounds of layoffs to AI and generative tools, then walked it back, saying the cuts were “not really AI-driven, not right now at least.” Jack Dorsey’s Block fired over 4,000 employees in February 2026 citing AI, but the company’s own filings show it had grown from 5,477 employees in 2020 to over 10,000 by 2025 during a pandemic-era hiring spree. The cuts brought headcount roughly back to where it was before the over-expansion. Meta reportedly planned to cut 20 percent of its workforce not because AI does those workers’ jobs, but to pay for the servers that run AI. As Bloomberg Opinion put it in March 2026: “Don’t blame AI for poor management decisions.”

The most telling datapoint is the simplest. Since March 2025, New York State has given employers the option to cite “technological innovation or automation” in the legally required WARN Act layoff notices they file before mass reductions. Of the 160 companies that filed notices since then, including Amazon and Goldman Sachs, companies that freely cite AI efficiencies in their investor communications, not one checked the box attributing layoffs to AI. When it matters legally, the AI explanation disappears.

Why would executives do this? Peter Cohan, a management professor at Babson College, told Built In that AI is “the least bad reason companies can use” for layoffs. Blaming tariffs risks political retaliation. Blaming revenue shortfalls spooks investors. Blaming pandemic over-hiring is an admission of strategic failure. Blaming AI sounds forward-looking and market-friendly. Shares go up.

The reputational cost, as Mercer’s Global Talent Trends 2026 report documents, falls on workers: employee concerns about AI-related job loss jumped from 28 percent in 2024 to 40 percent in 2026, and 62 percent of employees feel their leaders underestimate the emotional impact of AI on the workforce. When companies AI-wash their layoffs, they corrode the trust needed for workers to engage productively with AI tools. The wrong diagnosis does active damage.

The companies that ghosted our graduate after two rounds of interviews are, in many cases, the same ones citing AI efficiencies in their earnings calls. Not every company is following that script. In February 2026, IBM announced it was tripling entry-level hiring, including for software developers and other roles “we’re being told AI can do.” IBM’s chief human resources officer, Nickle LaMoreaux, explained the logic at the Leading with AI Summit: the entry-level jobs of two to three years ago can largely be performed by AI, so IBM rewrote the job descriptions. Junior developers now spend less time on routine coding and more time working directly with customers and building new products. The entry-level job description changed. The entry-level job survived. Her warning to competitors who are cutting instead was equally direct: companies that forego entry-level hiring will have to poach mid-level employees from competitors at a 30 percent premium, people who don’t know the internal culture and take longer to get up to speed. Axios called it a “narrative violation.”

The Oil Shock Will Finish What the Fed Started

That is the structural story: a ladder that has been losing rungs for four decades, weakened by concentration and noncompetes, with AI taking the blame for damage it did not cause. Now comes the cyclical crisis that will make all of it worse.

The proximate cause of the entry-level hiring collapse of 2022 to 2025 was the Federal Reserve’s tightening cycle, which began in March 2022, the exact month when job postings in those same rate-sensitive sectors began falling. The tightening was necessary. Inflation was running well above target. But the distributional consequences were predictable: the sectors where young, college-educated workers concentrate are the sectors most exposed to rising capital costs. As John Haltiwanger, Henry Hyatt, and Erika McEntarfer demonstrated in their 2018 research, the job ladder is highly procyclical, and more so for younger workers. When the economy tightens, hiring stops, workers stop quitting, and entry points to the market disappear.

Indeed’s Hiring Lab describes the current environment as “low-fire, low-hire.” Employers are not expanding but not cutting either. Comfortable for incumbents. Devastating for anyone trying to get a first foothold. ZipRecruiter data shows that employee turnover dropped from 177 percent in 2023 to just 50 percent in 2025. Workers are clinging to positions. Vacancy chains are frozen. The people who suffer most from a frozen market are, by definition, the people who don’t yet have a place in it.

There were, as of early 2026, cautious signals of a thaw. ZipRecruiter found that 63 percent of businesses plan to increase hiring, with emphasis on entry-level roles. Some forecasters saw rate cuts on the horizon.

Then the Strait of Hormuz closed.

On February 28, 2026, the war between the United States, Israel, and Iran began. Within 48 hours, tanker traffic through the Strait, which carries roughly 20 percent of the world’s seaborne oil, had collapsed by 81 percent. Seven of twelve major marine insurance clubs cancelled war risk coverage. Brent crude surged above $82, with JPMorgan warning of $120 and Deutsche Bank modeling a full closure at $200. European diesel futures jumped 23 percent in a single day.

We laid out in detail what this oil shock means for energy markets, inflation, interest rates, and fertility. What matters here is the implication for an entry-level labor market already hanging by a thread.

The transmission runs through a short chain. Higher oil prices feed into broader inflation. The SF Fed found in December 2025 that two-year Treasury yields now respond more than three times as strongly to oil supply news as they did before 2021. Markets are already pricing in no rate cuts this year and possibly further hikes. Each increment of tightening falls hardest on the sectors already hemorrhaging entry-level positions. An oil-driven inflation spike does not create new jobs for graduates anywhere in the economy. It guarantees that the interest rate environment remains hostile for the sectors that would otherwise absorb them.

In a prior era, an oil shock at least had a compensating mechanism. High prices meant pain at the pump, but they also meant a drilling boom in West Texas, the Gulf Coast, and the Intermountain West. Young men without college degrees could earn $80,000 to $120,000 on a rig crew. That income supported marriages, mortgages, and children. Between 2010 and 2014, Houston alone added 457,500 jobs.

That industry no longer exists. As we documented, capital discipline and consolidation have produced an oil sector that converts high prices into share buybacks rather than employment. The U.S. rig count fell from 750 in December 2022 to 550 by late February 2026, while production held near record levels. The total upstream workforce has shrunk by 252,000 from its peak while producing substantially more energy. Petroleum engineering degrees have collapsed 76 percent from their 2017 peak. When EOG Resources held its fourth-quarter earnings call the day before the Iran strikes, it committed to returning 90 to 100 percent of free cash flow to shareholders and keeping production flat. Scott Sheffield, formerly of Pioneer Natural Resources, said it as plainly as anyone: “Whether it’s $150 oil, $200 oil, or $100 oil, we’re not going to change our growth plans.”

So: the oil shock raises inflation, which delays rate cuts or forces hikes, which prolongs the hiring freeze, which extends the entry-level drought. The sectors that would historically have absorbed displaced workers are either structurally configured not to expand (energy) or exposed to diesel and input cost increases (construction, manufacturing). And the broader uncertainty, compounded by tariff escalation and immigration policy changes, ensures that employer risk aversion persists.

The graduate entering the labor market in the spring of 2026 faces a convergence with no close parallel in the postwar period. A ladder weakened over four decades. A tightening cycle that has frozen what remains. An oil shock extending the freeze. And a public conversation that remains fixated on a chatbot.

Compounding (Economic) Scars

If this were merely a matter of waiting a few years for conditions to improve, none of what follows would matter much. It is not.

The research on labor market scarring says that what happens to our graduate in the next two years will follow her for decades. Till von Wachter’s 2020 survey of the evidence in the Journal of Economic Perspectives documents what happens to young workers who enter the labor market during a recession. For a typical downturn, where unemployment rises by 4 to 5 percentage points, college graduates experience an initial earnings reduction of about 10 percent that takes 10 to 15 years to fade. High school graduates fare roughly twice as badly. Nonwhite entrants experience larger earnings losses, mostly driven by reductions in weeks worked in the first four years.

Schwandt and von Wachter (2019) study puts the cumulative cost in dollar terms: among all labor market entrants, entering during a large recession reduces the present discounted value of earnings over the first ten years by 9 percent, rising to 13 percent for those without a high school diploma and 11 percent for nonwhite workers. These losses amount to three-quarters of mean annual earnings for the average entrant over the first decade.

The effects go past paychecks. Adverse labor market entry persistently increases alcohol consumption, leads to higher obesity and more smoking in middle age. College graduates who entered during the 1980s recession showed higher rates of heart attacks decades later. By their late 30s, according to Schwandt and von Wachter (2020), unlucky entrants start dying at higher rates than their luckier peers, a gap driven by heart disease, liver disease, lung cancer, and drug overdoses. The gap keeps widening through their 40s.

We keep calling this a labor market problem. By their late 30s it is a mortality problem.

Unlucky cohorts have fewer children, divorce more often, and are more likely to live alone in middle age. Criminal activity rises for at least 15 years after entry, especially for men and high school dropouts. Self-esteem erodes. None of this is temporary. A young worker entering a weak labor market in the 1980s could still recover, because the structural machinery of upward mobility remained intact. Today that machinery is broken.

And the safety net was never designed for people at the start of their careers. Unemployment insurance, job search assistance, and retraining all require work history that new entrants, by definition, do not have.

The effects on family formation deserve particular emphasis, not least because they have downstream consequences that last generations. Drawing on Stephen Shaw’s 2025 analysis of 314 million mothers across 33 higher-income countries, that economic shocks suppress entry into motherhood rather than reducing family size among women who are already mothers. The oil shock of 1973 drove simultaneous declines in the Total Maternal Rate across all 47 Japanese prefectures. The 2008 financial crisis drove a sustained decline in U.S. first births that continued well after the economy recovered. Hungary’s TFR collapsed from 1.59 to 1.39 between 2021 and 2024 as the energy crisis erased a decade of pronatalist policy gains. Czechia’s fell from 1.83 to 1.37, the lowest since records began in 1806.

The mechanism runs through male employment. When young men cannot find stable work, marriages do not form, and first births do not happen.

A 2025 study in the Chinese Sociological Review found that approximately a third of Korea’s fertility decline in the 25-to-29 age group traces to a near-tripling of male economic inactivity. The collapsing job ladder is the slow-motion version of the same mechanism. And each successive shock operates on a lower baseline, which means the same-sized disruption does more damage.

When the graduate expresses cynicism about the economy’s capacity to reward her effort, that cynicism is rational. She is responding to an economy that has, in measurable and documented ways, stopped rewarding effort as reliably as it once did.

The Ladder Is the Point

We are drawn to dramatic explanations because they are legible and because they absolve us of responsibility. If a machine took your job, no human decision is to blame. Andreessen’s version is only slightly better: if pandemic overhiring is the culprit, the correction is mechanical and self-resolving. Neither account requires anyone to do anything differently.

But the evidence assembled here points to something less cinematic and more damning: policy choices, market structures, and institutional failures that have systematically weakened the mechanism through which young workers build careers and economies distribute prosperity. Consolidation eliminated competitive ecosystems and noncompetes legally prevented workers from climbing. Concentration reduced the pressure that made firms pay well. The Fed’s tightening cycle froze what remained of the ladder, and the oil shock will extend the freeze.

If the diagnosis is wrong, the prescription will be wrong too. If you believe AI is displacing entry-level workers, you prescribe AI literacy training, prompt engineering curricula, reskilling programs oriented around technology adoption. These may be useful in their own right. But they do not address a collapsing job ladder, rising employer concentration, or noncompete agreements that legally prevent workers from accepting better offers. Prescribing AI training to address a structural labor market crisis is like prescribing swimming lessons to someone who is living in a drought blighted area.

The structural diagnosis implies different interventions. On employer concentration, antitrust enforcement oriented not only around consumer prices but around labor market competition and the ability of workers to receive competing offers. On noncompete agreements, finishing what the FTC started. The estimated $524 per worker per year in additional earnings from a nationwide ban is not a theoretical exercise. Oregon’s 2008 ban on noncompetes for hourly workers raised job-to-job mobility by 12 to 18 percent. The mechanism works. On social insurance, programs that do not condition eligibility on prior work history, which new entrants by definition lack. On the oil shock, recognizing that monetary tightening in response to a supply-side price spike is, as Bernanke and Blanchard’s own research has shown, the wrong tool for the problem.

None of these are mysteries. The Workforce Mobility Act has bipartisan sponsors. It is stalled in committee. The evidence on labor market concentration has been accumulating for a decade. The scarring research has been published and replicated. The bill is written. The papers are cited. The data is not ambiguous.

And nothing is moving.

That is the part that is hard to write about calmly. Not the structural decline, which at least has the dignity of being a long process driven by large forces. The part that is hard to sit with is the gap between what we know and what we are doing about it. We know that the job ladder is broken. We know what broke it. We know what the scarring research predicts for the cohort entering the labor market right now. We have interventions with bipartisan support, proven track records, and detailed cost-benefit analyses gathering dust in committee.

The graduate we started with is not an abstraction. She is one of millions people who finished college in 2025 (not just in the US) and walked into the worst entry-level market in four decades. The scarring literature says that what happens to her in the next two years will shape her earnings, her health, her family, and her life expectancy for decades. That should bother us more than it does.

• Remote work raises fertility among employed, partnered adults. Davis et al. (2026) estimate WFH accounts for ~291,000 U.S. births per year.

• Return-to-office is functionally anti-natalist policy beloved by “pronatalists”. A drop from 42% to 30% WFH among women implies ~100,000 fewer births per year.

• WFH delivers more fertility impact than the entire U.S. early childhood spending apparatus, at zero taxpayer cost.

• The loudest “pronatalists” (Musk, Andreessen) spent two years killing workplace flexibility while funding nearly a billion in elite fertility tech.

• The 2026 Strait of Hormuz crisis forced Asian governments to mandate remote work for fuel savings, accidentally reviving the arrangement corporate America just buried.

• One or two hybrid days per week capture nearly all the fertility upside. Companies are going after hybrid like they did with full WFH regardless

By early 2026, the return-to-office movement had won. Not gracefully (Amazon could not even find enough desks for the 350,000 corporate employees it ordered back five days a week) but decisively. JPMorgan Chase ended remote work in April 2025. Dell, AT&T, TikTok, Truist, and the Washington Post followed with five-day mandates. Instagram’s Adam Mosseri told staff a five-day office presence was needed for a “winning culture.” Microsoft began requiring Puget Sound employees three days minimum in February 2026. A KPMG survey found 83 percent of CEOs expected full return to office within three years; a ResumeBuilder survey reported nearly half of all companies demanded four or more in-office days by 2026, with 28 percent phasing out remote work entirely. Some companies used the mandates as quiet layoffs, hoping workers who valued flexibility would self-select out rather than commute.

And the workers complied. By December 2025, only 40 percent of employees said they would quit over a mandatory return-to-office notice, down from 91 percent who said the same in January. The job market had tightened: 2025 produced just 584,000 total job gains, the weakest outside a recession since 2003. The leverage belonged to employers, and employers wanted bodies in chairs.

The pandemic experiment was over. Remote work was being consigned to a brief, strange interlude, a concession to extraordinary circumstances that would not recur. The implicit premise of every return-to-office memo was clear enough: the exogenous global shock that created mass remote work was a one-time event. COVID-19 was the exception. Normalcy was the rule.

After all, what were the odds of another global shock that would force millions of workers home overnight?

In March 2026, the Strait of Hormuz closed, and the question answered itself.

We will not rehearse the geopolitics; the reader is more than aware. What bears noting is how governments responded. Thailand ordered all non-frontline public-sector employees home, set air conditioning to 26 degrees, told workers to take the stairs, and replaced travel with online meetings. The Philippines moved to a four-day government workweek. Pakistan’s Prime Minister mandated remote work for half of all government employees and shifted universities online. Vietnam urged all employers to allow remote work and encouraged citizens to ride bicycles. Bangladesh closed universities, stationed troops at oil depots, and turned off Eid-al-Fitr light displays. Nepal filled cooking gas cylinders only halfway to stretch supply.

These governments did not mandate remote work because they had read a working paper about fertility. They did it to keep the lights on. But in doing so, they resurrected the very arrangement that corporate America had just buried, and that a growing body of research now links to higher birth rates.

I want to be clear-eyed about what comes next. The commodity shock that forced these mandates will itself devastate birth rates by destroying the employment and economic prospects of young people, especially young men, across the region. No workplace policy can stand against that kind of destruction. But as we argue below, the remote work mandates these governments stumbled into are among the most effective interventions available for raising children per mother among those with the means to form families. And the loudest pronatalists in American life, the ones who claim declining birth rates are civilization’s gravest threat, are the same people who just spent two years dismantling it: Elon Musk, who has fathered at least fourteen children and called declining birth rates “a much bigger risk to civilization than global warming,” told tech workers on CNBC to “get off the goddamn moral high horse with the work-from-home bulls***.” Marc Andreessen, whose Techno-Optimist Manifesto declares “our planet is dramatically underpopulated,”testified before his local town council that he was “immensely against multifamily housing development.” The network around them (Thiel, Altman, Armstrong, Buterin) has poured some $800 million into fertility technology while the companies in their orbit dismantle the workplace flexibility that actually raises fertility.

Here is the core of our argument. A growing literature (Lu et al. 2025, using U.S. census data; Wang and Dong 2024, running experiments in Singapore; Bailey et al. 2023, on the COVID baby bump; Chong and Noguchi 2024, on Japanese pregnancy odds) converges on the same finding: remote work raises fertility. The latest and most comprehensive contribution is Davis, Aksoy, Barrero, Bloom, Cranney, Dolls, and Zarate (2026), drawing on original survey data from 38 countries and the U.S. Current Population Survey. The effect operates on what we call the intensive margin: more children per mother, among people already positioned to have families. It cannot solve the deeper economic preconditions for family formation. But the magnitudes are striking, the evidence is no longer tentative, and the policy it identifies is precisely the one that self-described pronatalists just finished destroying.

The evidence

Davis et al. (2026) draw on two original surveys. The Global Survey of Working Arrangements (G-SWA) covers 38 countries; its fourth wave, fielded November 2024 to February 2025, includes a new fertility module. The U.S. Survey of Working Arrangements and Attitudes (SWAA) is a monthly survey yielding 89,886 respondents aged 20–45 from 135,949 total usable observations (December 2022 to December 2025). Both samples are carefully constructed: respondents in the bottom 5 percent of completion times and the 17 percent who fail attention checks are dropped, and the SWAA data are reweighted via raking to match the Current Population Survey on age, sex, education, partner status, region, and employment.

The authors consider three fertility measures: realized fertility from 2023 to early 2025 (including children in gestation), planned future fertility, and lifetime fertility (children to date plus plans). The headline findings are large and consistent. When both partners work from home at least one day per week, estimated lifetime fertility is greater by 0.32 children per woman in the 38-country sample (14.3 percent of mean fertility) and 0.45 in U.S. data (17.5 percent of mean fertility). For realized fertility since 2023, women who work from home had 0.037 more children in the G-SWA (25 percent of sample mean) and 0.091 more in the SWAA (33 percent of sample mean). Planned fertility is also significantly higher. These patterns hold across all specifications, for men and women separately, with controls for age, education, marital status, pre-2023 children, own and partner employment status, and country or state fixed effects.

A complementary analysis using the Current Population Survey (approximately 137,000 respondents ages 30–45, 2023–2025) reinforces the findings by linking fertility not to individual WFH status but to occupation-level WFH shares, the fraction of job postings advertising remote work in one’s occupation, as classified by Hansen et al. (2026) using an LLM applied to half a billion postings with 99 percent accuracy. A one-standard-deviation increase in own-occupation WFH share raises one-year fertility by 7.3 percent of mean for women; adding partner’s occupation, the total effect reaches 14 percent. The results also hold in 2017–2019 data, before anyone could have chosen occupations with foreknowledge of pandemic-era WFH opportunities. Since nearly nine in ten people aged 30–45 stay in the same occupation year to year, reverse causation is implausible. Davis et al. also note a “missing intercept” problem: their cross-sectional estimates cannot capture aggregate effects of WFH prevalence on fertility norms, so the true effects are likely larger.

Davis et al. is not the first study to establish this link. It is the most comprehensive. Lu et al. (2025) find that the COVID WFH shock raised fertility, especially through higher-order births, second and third children, not first. Wang and Dong (2024) demonstrate a causal effect of flexible work on fertility intentions in a Singaporean experiment. Chong and Noguchi (2024) report increased pregnancy odds for Japanese women in high-WFH occupations. Bailey et al. (2023) show relative birth-rate gains among college-educated American women in 2021, the group that saw the largest WFH expansion. What Davis et al. adds is scale (38 countries, 135,000+ U.S. respondents), household-level analysis capturing partner effects, and a concrete national-level quantification: WFH accounts for an estimated 291,000 U.S. births per year, 8.1 percent of total fertility, as of 2024. Since U.S. WFH rates are now three to four times pre-pandemic levels, this implies roughly 200,000 extra births relative to a no-pandemic-WFH counterfactual. By comparison, Olivetti and Petrongolo (2017) find that U.S. government spending on early childhood care and education (0.4 percent of GDP) contributes an estimated 0.08 children per woman. The WFH contribution is 0.13. Remote work is delivering more fertility impact than the entire early childhood spending apparatus, at zero cost to taxpayers.

The debate is no longer about whether the relationship exists. It is about magnitude and mechanisms.

Two margins, two different forces

Before we go further, we need to draw a distinction that much of the fertility debate elides.

Birth rates reflect two things: how many people become parents (the extensive margin) and how many children those parents have (the intensive margin). These respond to different forces. Entry into parenthood is overwhelmingly driven by economics: stable employment, a partner with stable employment, a reasonable expectation of affording housing and children. When commodity shocks or recessions destroy the prospects of young adults, and especially young men, whose earnings remain disproportionately important to household formation decisions across cultures, fewer people form families. If young men in Bangkok or Karachi cannot find work, they do not marry, and births do not happen.

WFH affects the second margin. The Davis et al. results are conditional on age, education, employment status, partner’s employment, and marital status. The women and men in their regressions overwhelmingly have jobs and partners. For this population, remote work eases the time and coordination costs of combining employment with child rearing. It shifts the calculus from two children to three, or from “not yet” to “now.” The Lu et al. (2025) finding that the COVID WFH shock raised fertility mainly through higher-order births, not first births, reinforces this reading. Remote work is not making new parents. It is giving existing parents room for one more child.

This distinction is essential for everything that follows.

Return-to-office as anti-natalist policy that Elon Musk loves

If WFH raises fertility by these magnitudes, the corporate return-to-office wave is, functionally, an anti-fertility policy. Andy Jassy did not set out to reduce birth rates. But eliminating remote work for 350,000 employees in prime childbearing years removes a feature that workers value at roughly 5 percent of earnings, that parents value even more, and that is associated with significantly higher realized and planned fertility. Intentions are beside the point.

The distributional dimension sharpens the concern. WFH concentrates among college-educated, professional workers, precisely the groups with the lowest fertility and the most to gain from flexibility. Bailey et al. (2023) found that college-educated American women saw relative birth-rate gains in 2021, the group with the greatest WFH expansion. Davis et al. reveal a gendered pattern: women’s fertility is negatively associated with paid employment in their 38-country data, but this penalty is largely offset when the woman works from home. Return-to-office mandates restore the full penalty. And when companies use those mandates for indirect headcount reduction (as Resume Builder’s Stacie Haller notes, leaders are often aware that flexible workers will leave rather than comply) the workers who self-select out are disproportionately parents, the people managing school schedules and sick days and the thousand logistical demands of family life.

A rough estimate: if the U.S. WFH share among women drops from approximately 42 percent to 30 percent, the Davis et al. framework implies about 100,000 fewer births per year. These are births lost on the intensive margin, not fewer parents, but parents who lose the flexibility that made an additional child feasible. That is illustrative, not definitive. But the order of magnitude is sobering: a fertility reduction imposed by corporate fiat that exceeds the effect of many countries’ entire pro-natal policy apparatus.

The 2026 energy crisis: a cruel and clarifying test

The crisis-driven WFH mandates are analytically interesting for reasons Davis et al. could not have anticipated; their paper predates the conflict. The mandates are exogenous to fertility concerns (no country adopted remote work for fuel conservation to raise birth rates), they are massive in scale (millions of workers moved to remote arrangements within days), and they overlap geographically with the world’s lowest-fertility nations. Japan, with a TFR of 1.23, had the lowest WFH share in the Davis et al. sample at 21 percent. South Korea, with the world’s lowest TFR at 0.75, stood at 27 percent. Davis et al. estimate that raising WFH to the U.S./UK/Canada average of 45.3 percent would yield 31,800 extra births per year in Japan and 10,500 in South Korea. This is also not the first time it has happened: after Russia’s invasion of Ukraine disrupted European energy supplies in 2022, Germany encouraged remote work to reduce consumption, and a Freshfields analysis found it could cut national gas use by 5 percent. Crisis-driven WFH expansions are becoming a recurring geopolitical feature, not a pandemic anomaly.

But we must be honest about the savage arithmetic of commodity shocks. The same crisis forcing Asian governments to mandate remote work is simultaneously annihilating the conditions under which young people form families. Oil above $100 a barrel in import-dependent economies means surging costs for fuel, food, transport, and electricity; inflation eroding real wages; firms cutting back. South Korea, which imports 70 percent of its oil from the Middle East, has seen its Kospi index post some of the steepest market declines this month. The Economist Intelligence Unit projects elevated energy prices will raise inflation and lower growth across the region. Agriculture faces its own disruption: Gulf fertilizer supplies have been cut, Thai rice exports to the Middle East have stalled, Indian farmers are dumping supply at lower prices. When young men cannot find stable work, household formation collapses and births do not happen, regardless of whether office workers have been told to stay home on Fridays. The crisis-hit countries will almost certainly see birth rates fall, not rise, in 2026 and 2027.

The tragedy is that the crisis simultaneously expands WFH (good for the intensive margin) and contracts the economic foundations of family formation (catastrophic for the extensive margin). The net effect will be negative. But the longer-run story may be different. The oil crisis is temporary. The WFH habits it creates need not be. East Asian countries have spent billions on conventional pronatalist policies (cash bonuses, parental leave, childcare subsidies) with limited results. If crisis-induced remote work practices outlast the crisis, as they did after COVID-19, permanently higher WFH rates and the accompanying fertility gains could follow. We should not pretend that WFH can solve the fertility crisis in societies where the binding constraint is the economic destruction of young men’s prospects. If the shock lingers, it will do more damage to birth rates in one year than a decade of WFH expansion could repair. But on the intensive margin, the gains are real.

Even there, WFH is not a panacea. Kim et al. (2024) argue that status-driven competition in child education is a key driver of East Asian fertility collapse: parents locked in a positional arms race over schooling, spending enormous sums and time to secure marginal advantages. WFH makes it easier to drive a child to tutoring. It does not make the arms race less exhausting. Davis et al. acknowledge that these status externalities “could mute the potential impact of expanded WFH opportunities.” Fair enough. But status competition suppresses desired family size, while workplace inflexibility suppresses the ability to achieve even a reduced desired family size. WFH addresses only the latter. In East Asia, that may mean a lower ceiling on WFH-induced gains than in North America or Europe. But at TFRs below 1.0 in South Korea, every fraction of a child per woman matters.

Pronatalist paradox

I described the pronatalist contradictions above: Musk’s simultaneous championing of birth rates and disparagement of remote work, Andreessen’s planet-is-underpopulated manifesto paired with opposition to housing construction, $800 million in fertility technology from a network that is dismantling the zero-cost workplace policy that outperforms government early childhood spending. We do not need to redescribe the figures. We still need to diagnose the analytical failure.

The return-to-office case is that in-person collaboration fosters mentorship, company culture benefits from proximity, young workers gain from office exposure, and there are productivity costs to fully remote work. The research is shaky on all those points, and company culture is more affected by layoffs. Let’s take them at their word. Hybrid arrangements of one or two days a week capture a lot of the fertility upside while preserving the in-person collaboration that return-to-office advocates prize. Companies are still eliminating hybrid arrangements, let alone remote work.

The deeper problem is the distinction between techno-pronatalism and real world pronatalism. Techno-pronatalism (IVF, genetic screening, embryo selection, artificial wombs) is expensive, selective, and accessible primarily to elites. Real world pronatalism (workplace flexibility, affordable family size housing, child bonuses, etc) is (relatively) cheap, universal, and available to everyone. As the Heritage Foundation’s Emma Waters has noted, Silicon Valley pronatalists “tend to promote, in practice if not in speech, a selective pronatalism: more babies of a certain kind.” The WFH-fertility evidence is emphatically not selective; it operates across education groups, occupations, and countries.

And the pronatalists are not merely failing to support the intensive margin. They are attacking the extensive margin as well. Opposition to housing construction raises the cost of family formation. The use of return-to-office mandates as covert layoffs pushes parents out of employment. The tightening job market of 2025, to which tech layoffs contributed, made it harder for young adults to establish the economic footing that precedes family formation. They are undermining the workplace flexibility that raises children per mother while doing nothing to strengthen the economic foundations that determine who becomes a parent. That is not a contradiction in emphasis. It is incoherent.

What should be done

Davis et al. observe that “for societies faced with undesirably low birth rates, WFH can thus yield societal benefits that go beyond any direct benefits to employees and employers.”

Governments should stop discouraging remote work, especally if they received poor advice from certain “industry leaders”. The public sector is the obvious starting point: because the government is a large employer across many occupations, its workplace practices set private-sector norms.

For crisis-hit Asian economies, the immediate priority is economic stabilization: protecting employment, containing inflation, keeping young men in the labor force. No WFH policy substitutes for those preconditions. But once the crisis recedes, the governments that mandated remote work for fuel conservation should study making some version permanent. Japan and South Korea have low WFH rates, extremely low fertility, and have exhausted most conventional pronatalist options. Hybrid work incentives could complement existing policies at minimal fiscal cost; the Davis et al. estimates imply 31,800 extra births per year in Japan and 10,500 in South Korea if WFH rates reached the U.S./UK/Canada benchmark.

Employers should understand what the evidence implies for talent. Workers value WFH at roughly 5 percent of earnings; parents value it more. Firms offering hybrid arrangements will attract and retain workers with stable families and the lower turnover that follows. Davis et al. caution that “policy interventions that push for a one-size-fits-all approach to working arrangements are likely to yield unhappier workers and lower productivity.” The goal is expanding options, not mandating remote work universally. But expanding options is precisely what the return-to-office movement is not doing.

Beating Dead Horses

By early 2026, the return-to-office movement had declared victory. Then the Strait of Hormuz closed, and governments from Bangkok to Islamabad ordered workers home, not to build culture, but to save fuel. The arrangement corporate America had just buried was resurrected in days.

I am not romanticize what is happening in Asia. Again, commodity shocks will devastate birth rates by destroying the employment prospects of young people, especially young men. The binding constraint on fertility in crisis-hit Asia is whether young men can find work and young couples can afford a home, not whether they commute.

But for those who are still employed, partnered adults who do form families, the question of how many children they have are shaped by the logistics of combining paid work with child rearing. On this margin, the evidence is clear: the ability to work from home even one day a week is associated with 0.32 more children per woman across 38 countries, and 0.45 more in the United States, amounting to 291,000 births per year that would not otherwise occur.

Meanwhile, in Palo Alto, the play pretend pronatalist tech executive who tweets about civilizational collapse from declining birth rates is ordering his employees back five days a week. He has invested millions in artificial wombs and embryo selection. He has not invested a penny in the workplace flexibility that produces, at no cost to anyone, hundreds of thousands of additional births per year, not by creating new parents, but by giving existing parents room for one more child.

The CEOs said the pandemic was a one-time event. They asked what could possibly force remote work back. Now they have their answer, and it arrived not from Silicon Valley but from the Strait of Hormuz. The fertility intervention that works is not a moonshot. It is the ability to work from home at least one or two days a week. Now the question is whether the people who claim to care most about birth rates will read it before the next shock forces their hand again.

Key facts

• 61% of young unmarried Japanese adults knew nothing about any of the 17 family benefits their government already provides. Telling them what existed raised strong marital intentions by 25% (Gong and Wang 2021).

• Across 216 European regions, a 1% increase in government quality is associated with an ~8% increase in fertility (Giannantoni and Rodriguez-Pose 2025).

• Fun Fact! Akashi City paid for their pronatalist programs, at first, with budget cuts in other areas, and later on with tax revenue from new residents moving in AND more births.

Here is a partial list of things a local government can do to raise birthrates at little or no cost: publish a single clear guide to every family benefit the city already offers. Enforce the familial status protections that have been federal law since 1988. Switch parking requirements from per-bedroom to per-unit so developers stop paying a penalty for building three-bedroom apartments. Announce the locations and timelines of planned daycare centers before they open, not after. Shorten permitting review for small residential projects from twelve months to 90 days. Audit the benefit application process and ask whether a 25-year-old first-time parent could complete it without help.

None of these require new legislation. None require new revenue. And the evidence we review here says they matter more than the expensive programs cities typically reach for first.

We want to make an argument that will sound, at first, like we are telling local officials to do nothing. We are not. We are telling them to do the thing that matters as more of a prerequisite/corequisite and costs the least, before they do the things will cost a lot of money.

The lowest cost investment (in the long term) a city can make to support family formation is not a new subsidy, a new program, or a new department. It is making the existing institutional machinery work as designed: delivering services reliably, communicating intentions clearly, and earning the trust of households deciding whether this is a place where they can raise a child. You will need to spend money in the mid-to-long term. Right now we are talking about the lowest hanging (and cheapest) fruit to a very complex and expensive phenomenon.

The same insight, two directions

Quality Theorist Joseph Juran argued that organizations waste 20-40% of their total effort on rework and correcting failures that should never have occurred. Quality is free, because the money is already being spent on failure. A government office that takes 45 days to process a childcare application is not saving money. It is spending money on confusion and abandoned applications while telling every household that encounters the process: this system does not work.

Rory Sutherland arrived at the same place from the demand side. The UK government spent £6 billion shaving 40 minutes off the London-to-Paris Eurostar. Sutherland’s counter-proposal: for a fraction of that cost, improve the onboard experience so passengers would ask the trains to slow down. People do not evaluate a service by its technical specifications. They evaluate it by how it feels to use.

These are not identical claims. Juran is talking about process efficiency; Sutherland about subjective experience. But they reinforce each other. Fixing how your system operates is not separate from fixing how your system is perceived. Treating them as two different departments is how cities end up with announcements nobody believes and services nobody knows about.

Akashi’s former mayor Fusaho Izumi understood this intuitively. In 2016, before introducing free nursery school for second children, he opened a children’s complex in front of Akashi Station: a play space, a library with four times the floor area, drop-in childcare, family counselors, a parenting hotline. He had evicted the pachinko parlors and consumer loan offices to build it (one sued; the case went to Japan’s Supreme Court; Izumi won). His logic, explained in multiple Japanese-language interviews: parents will not trust any sort of subsidy unless they can see the system it is embedded in. The library, the play space, the counselors were the trust infrastructure that made later financial benefits credible.

Why does this matter for fertility? Because having a child is not a transaction. It is a decades-long bet on the institutional environment. Will the schools function? Will the clinic be there at 2 a.m.? Will the childcare subsidy actually arrive?

The evidence

In a national survey experiment published in Demography, Gong and Wang (20212) found that 61% of young unmarried Japanese adults knew nothing about any of the 17 family benefits their government provides. Zero out of seventeen. After the treatment group was shown what the policies were, strong marital intentions rose by 25%. No new spending occurred. The effect was largest among highly educated women and both low- and highly educated men, the groups facing the highest perceived costs of marriage under traditional gender norms. The information changed what people thought the costs were.

Okamoto (2026) modeled Japan’s demographic trajectory in a dynamic lifecycle simulation and found that merely announcing a childcare subsidy reform one to five years before it takes effect increases the long-run stabilized population by up to 7.6%. Even granting the usual caveats about models, the logic is hard to dismiss: if households plan ahead, credible information changes outcomes independently of the policy itself. The marginal cost of a public announcement is, to a first approximation, zero.

Across 216 regions in 18 European countries, Giannantoni and Rodriguez-Pose (2025) found that a 1% increase in regional government quality is associated with an approximately 8% increase in fertility. The European Quality of Government Index is built not from spending data but from citizen surveys about perceptions and experiences of public services: healthcare, education, administration, corruption. Institutional quality and female employment were the two most consequential predictors. The contrast is stark at the regional level. Stockholm’s female employment rate is 81%; Campania’s is 27.7%. Italian regions like Sardegna (fertility rate: 1.09) do not lack family benefit programs. The money goes in; the experienced quality does not come out.

On that note, there is another finding from the same European data deserves particular attention. Temporary contract and gig work actually discourages childbearing. You cannot offer someone flexibility and insecurity in the same instrument and expect them to take a twenty-year bet on it.

Supporting evidence from the Japanese municipal data: municipalities where residents work locally show higher desired birth rates (0.19 SD). Car commuters outperform train commuters, not on speed but on flexibility for unexpected daycare pickups. Community festivals correlate with higher desired rates (0.13), likely through the informal childcare networks they sustain. Tokunoshima Town maintains Japan’s highest actual fertility rate at 2.25 largely through organic social support rather than formal programs.

A caveat: the Gong and Wang experiment measures stated intentions, not births, and the cross-sectional studies cannot rule out unmeasured confounders. But the pattern is consistent across three continents, five independent research teams, and radically different institutional contexts. At some point, convergent evidence earns the benefit of the doubt.

What cities can do Monday morning

The honest answer to “what should we do?” is simpler than you want it to be. Improve how your government operates and how it communicates.

This sounds circular. A city with weak institutions is not good at strengthening its own institutions. But the circularity breaks when you think of institutional capacity not as comprehensive reform but as a sequence of visible wins, each building credibility for the next. Some of you are going to go “I just don’t think the government can reform at any level”. Drawing on American History, former Treasury Secretary John Snyder, facing a corrupt IRS in the late 1940s, started by automating one calculation on one tax form in one office in Cincinnati. When that worked, other offices tried it. When those succeeded, he reworked the forms. When Congress saw results, they approved the structural reforms he could not have gotten on day one. We still have a lot of these super effective reform programs (or at least the documents and books). has documented this stuff, especially on how WW2-era Bureau of the Budget’s work simplification program applied these same methods across federal management. The approach is Juran’s and Deming’s, and it was built for government before it was exported to industry.

Nagareyama’s Mayor Yoshiharu Izaki did the same thing in a municipal context. His first moves in 2003 were not about children at all. On day one he halted a ¥1 billion over-budget recreational facility under construction. He required three competitive bids for all contracts above ¥1.3 million; previously, everything under ¥150 million had been sole-sourced. That single change cut the cost of equivalent projects by 40%. He compressed the city plan from 600 pages across four volumes to one volume. He froze new hiring for three years. None of this was family policy; it was operational triage that created the fiscal room for everything that followed.

We have spent several thousand words arguing against new programs and are now going to recommend four specific actions. Three are not new programs: enforcement of existing law, removal of existing regulations, and better planning of services already being provided. Only the fourth is genuinely new, designed as the smallest viable version of itself.

1. Enforce family protections already on the books.

In the US, we have the Fair Housing Act which prohibited familial status discrimination since 1988. Familial status complaints were the fourth most common type filed with HUD in 2021, roughly 7% of all complaints. A California property management company recently paid $3 million to settle charges for prohibiting children from playing outdoors. Landlords still deny leases because a child would share a bedroom.

Audit your complaint pipeline, and not just for housing. Routine testing, especially for fair housing. Publicize protections in plain language. Housing alone, attorneys report that much of this discrimination is not invidious; landlords assume children will be noisy or that siblings cannot share a room. Laws are most likely there. Someone has to turn it on.

2. Deregulate housing. Fully, if you can. Selectively, if you must.

My first-best recommendation is straightforward: abolish parking minimums, eliminate single-family-only zoning, liberalize floor area ratios, allow single-stair residential buildings up to six stories, and cut permitting timelines to 90 days for projects under 50 units. Let people build housing. The evidence that restrictive land use regulation constrains housing supply, raises costs, and drives families to the exurbs is overwhelming and does not need rehearsing here.

I recognize that full liberalization is politically difficult in most cities, especially in America and the UK. For cities that cannot get there in one move, a narrower version still helps: target the regulations that specifically penalize family-sized units.

Per-bedroom parking means every additional bedroom triggers additional land cost. Developers respond rationally: they build studios. The share of new apartments with three or more bedrooms has fallen from 7–11% in the 1990s to 5% today.* Switching to per-unit parking removes this penalty at zero cost. An FAR exemption for three-plus bedroom units expands the option set. Allowing single-stair buildings up to four stories opens the floor space a third bedroom would occupy. None require spending. All remove barriers. And each builds the political credibility for the next, larger reform.

3. Plan and communicate family-friendly amenity infrastructure, in sequence, with advance notice (or like Nagareyama advertise what you do have).

Choi et al. (2026) identified distance thresholds: public daycare within 400 meters, clinics within 200 meters, elementary schools within 820 meters. When your city sites a daycare it is already going to build, the decision should use distance-to-residential-concentration data, not merely coverage ratios. Planning with walkable distance costs no more. It requires a different map.

If your municipality will open three daycare centers over five years, announce the locations and timeline now. The announcement costs nothing.

Just to reference previous cases (I promise I will bring in a lot of fresh cases in future articles). Yeonggwang County in South Korea (population 53,000, no subway, no university, no tech industry) has sustained the highest total fertility rate in the country for six consecutive years, reaching 2.54 in 2019 and holding at 1.71 in 2024, more than double the national average. It began with the smallest necessary infrastructure: in 2015, recruiting a delivery-capable obstetrics clinic and establishing a public postpartum care center, eliminating ninety-minute “expedition births.” That first win funded the second. In 2018 the county created a dedicated population policy department, a national first among basic local governments, which enabled lifecycle programs with 94 support items documented in a single guide distributed to every resident.* Each phase was bigger than the last.

Akashi city in Japan hit 1.65 against a national 1.3 by reallocating budget from public works to child welfare. Izumi classified every municipal program into four categories: must, better-to-do-than-not, optional, and don’t. He halted public housing construction (the city had enough) and cut the sewer plan from ¥60 billion to ¥15 billion.** No new revenue. Freed budget went to children’s medical care first (the cheapest and most visible benefit), then the station-front children’s complex, then free nursery for second children, then free school lunches. Each phase was funded by the population growth the previous phase attracted; by 2019, Izumi had paid off ¥10 billion in city debt and grown reserves from ¥7 billion to ¥10 billion.**

Nagareyama reached 1.50 by solving one specific problem first: commuter parents could not physically get children to scattered nurseries and still make the train. The city built station-based transit childcare at two stations. Parents drop children off by 7 a.m.; dedicated buses collect up to 100 children per morning and distribute them to nurseries across the city. The process reverses by 6 p.m., with extension to 8 p.m. Cost to parents: ¥100/day.

4. Build a local partnership to ramp up family-sized apartment development.

The family-sized apartment market has a structural information failure that operational improvements alone cannot fix.

Developers are not building family-sized units despite strong demand because the industry’s financial assumptions are wrong. Stone and Fijan (2025) document the gap: studios have vacancy rates of ~8% versus 4-5% for three-bedrooms, higher rent-to-income ratios (32% vs. 25-26%), and shorter tenure (23.5 vs. 29.2 months). When these differentials are incorporated, effective rental returns on three-bedroom units are 29-50% higher than on studios. But the industry prices buildings using flat vacancy assumptions across unit types. A survey of over 6,000 Americans found bedroom count is by far the most important apartment feature for people considering children, more influential than 600-900 additional square feet or $1,500 in monthly rent.

The city’s role: publish vacancy and turnover data developers can cite in investor presentations. Convene a working group with developers, lenders, and municipal agencies responsible for childcare siting, benefit awareness, and permitting. Offer pre-approved design templates and expedited permitting. Start with one developer, one project, one neighborhood. Prove the pro forma works with accurate data. Fill it. Document the results.

Why cities get this wrong

Juran distinguished between the “breakthrough” mentality and the “control” mentality. Organizations love breakthroughs: new programs, new departments, press conferences. They are bored by control, the steady maintenance of existing processes at high quality. Fixing the online portal so parents can find benefits that already exist does not make the evening news. Yet the evidence here says the portal fix matters more.

There is also a tolerance problem. Every case in this article has a period where the inputs are happening but the outputs have not appeared. Akashi’s Izumi put it bluntly: “For the first five or six years, nobody evaluated what we were doing. It was a tough period.” Nagareyama’s Izaki lost his first mayoral election in 1999 and spent four years holding town meetings before winning on his second attempt.* Most governments abandon a strategy during the silent years. The ones that succeed are the ones that don’t.

Cities also organize as if operations and communications are separate functions. One department processes claims; a different office talks about policy; neither thinks about the other. Announcements without follow-through, delivery without visibility.

When you do spend: budget priorities and local targeting

Everything above is about making existing systems work before spending new money. But eventually you will spend, and when you do, two findings should govern how.

Across all 1,741 Japanese municipalities, Kawasaki and Morimoto (2025) found that the share of the municipal budget allocated to child welfare is the single most powerful predictor of desired birth rates. The coefficient (0.47) dwarfs density, transit access, income, facility counts, and commute patterns. Kasuga Town in Fukuoka allocates roughly 41% of its budget to child welfare, triple the comparable average. Tokyo and Osaka show large fertility penalties (-0.26 standard deviations); Nagoya, equally dense and wealthy, shows none. The difference is budget priorities. The urban fertility penalty is not structural fate but an institutional decision.

How much to allocate is the first question. Where to aim it is the second. Lee (2024) analyzed all 229 South Korean municipalities and found that the same national childbirth benefit produced significant positive effects in Jeolla and Gangwon provinces and zero measurable effect in Seoul’s 25 districts. Survey evidence showed that Jeolla and Gangwon had the highest demand for economic support around childbirth; cash addressed their actual constraint. In Seoul the binding constraint is housing cost or career interruption risk, which creates an incredible amount of leakage. The money did not fail, and cash benefits have a long and rich history of working against tailwinds. Cash benefits work best on a national level, and it’s your job on the local level to address constraints before giving local benefits.

The foundation before the edifice

Across every evidence base in this article, institutional quality, communication, and budget priorities predict fertility better than spending levels or program generosity. And Yeonggwang, Akashi, and Nagareyama demonstrate what happens when a municipality builds the operational infrastructure first and uses each success to justify the next: outcomes that diverge from national averages by a factor of two or more.

You will need to spend the money sooner or later, most likely sooner. But the return on that spending is determined by the operational quality of the system through which it flows.

If you run a city and you don’t know where to start, pick up Juran or Deming. Try out Work Simplification (we have an online copy right here!). Walk through your own processes. Find out what your city offers families, and find out whether families know it exists. Fix one thing residents will notice, and fix it completely. Then fix the next thing, and make it bigger. The operation is the message. Start there.

On February 28, 2026, war between the United States, Israel, and Iran effectively shut the Strait of Hormuz. Brent crude surged past $82 intraday; Barclays warned of $100, JPMorgan modeled $120, Deutsche Bank’s worst case reached $200. By Monday, South Korea’s KOSPI had suffered its steepest single-day plunge in history, eclipsing the post-9/11 crash. An economy that grew just 1% in 2025 absorbed another blow at precisely the moment the Bank of Korea had projected a fragile recovery to 2%.

Almost nobody (or at least on Substack besides myself) is discussing what this shock will do to births.

The pattern is by pretty familiar for long time readers: 1973, 2008, 2022. Each energy & economic shock collapsed total maternity rates (% of women who become mothers) across affected economies while CPM barely moved. The most expensive pronatalist programs in Europe could not withstand two years of energy-driven inflation. Hungary’s TFR, raised from 1.23 to 1.59 over a decade, collapsed to 1.39 by 2024. The Czech Republic’s fell from 1.83 to 1.37, the lowest since records began in 1806.

South Korea enters the 2026 shock from the lowest baseline on Earth. Its TFR stands at 0.72 nationally, 0.55 in Seoul. More than half of Korean women are projected to remain childless. The government has spent upward of $280 billion on pronatalist policy since 2006: subsidized housing, paid parental leave, cash bonuses for newborns, government-sponsored dating events. The TFR continued to fall. One study found that 74% of baby bonus disbursements went to births that would have occurred anyway. (Just to clarify: that’s still a 1/3rd increase, but money alone isn’t enough!)

And at these levels, every shock cuts deeper. A 5-point TMR decline from 90% leaves 85% entering motherhood. The same decline from 48% leaves 43%.

Countries cannot control energy shocks. They can control the physical structure of their cities: how far the daycare is, how long the commute takes, whether a clinic is walkable when a toddler spikes a fever at midnight. These spatial relationships are not linear. They exhibit thresholds and cliffs that most pronatalist policy ignores entirely.

A recent study by Choi, Lee, Jung, and Sohn (2026), published in Cities, maps these thresholds across Seoul. Daycare within 400 meters (1/4 of a mile) is associated with higher births; the effect vanishes beyond. Commuting past 65 minutes turns sharply negative. Neighborhood clinics within 200 meters (1/8th of a mile) are positive. Large hospitals within 1.5 kilometers (~1 mile) are negative.

What the study says

Method in brief

Most prior studies of residential environments and fertility rely on density-based indicators (hospitals per 1,000 residents, daycare centers per district). These capture quantity but miss physical accessibility. An area might have high hospital density on paper, but if the hospitals cluster in one corner of the district, residents on the other side face long travel times and effectively low access.

The deeper problem is the assumption that these relationships are linear. They aren’t. Tamefuji (2010) found that maternal employment drops sharply beyond 15 minutes from childcare, not gradually, but at a cliff. Chen et al. (2022) documented similar distance-decay patterns for subway access, with the premium confined to roughly 500 meters to 1.2 kilometers. Smith Jr. et al. (2013) found the relationship can reverse entirely: excessive hospital proximity suppresses fertility through noise and congestion. The terrain is cliffs, plateaus, and reversals. Linear models can’t map it.

The Choi et al. study adopts an N-minute city framework, evaluating accessibility by travel time rather than facility counts, across five functional categories: working, supplying, caring, learning, and enjoying. Its unit of analysis is the 250m × 250m grid cell, a resolution that aligns with actual walkable distances and mitigates the Modifiable Areal Unit Problem inherent in irregular administrative boundaries. Birth counts, available only at the administrative level, are distributed to grid cells proportionally based on women aged 20–39 (who account for 92.8% of Korean births). Independent variables measure network distance along actual road paths to the nearest facility in each category, with sociodemographic controls including age diversity, elderly ratio, young adult ratio, marriages, and average monthly income.

Among models tested, XGBoost achieved an R² of 0.8578, substantially outperforming linear regression at 0.7827. SHAP was applied for interpretability: feature importance rankings, summary plots for effect direction, and dependence plots for threshold identification. Geographically Weighted Regression then captures how relationships shift across Seoul’s geography. Together, these tools reveal that relationships are non-linear, where the inflection points fall, and how they vary across space.

Shorter Commutes Means Higher Children Per Mother

Commuting time exhibits the clearest threshold in the entire analysis. SHAP values are positive in the 50–65 minute range, then turn sharply negative beyond 65 minutes. Not a gradual decline. A cliff, a point at which the daily time budget for parenting appears to become unviable. The GWR results add texture: the negative association is most pronounced in Seoul’s southwestern districts (Gangseo, Yeongdeungpo, Dongjak) and the steep-topography areas of Changsin-dong, where transit bottlenecks compound the commuting burden. For the 46% of Korean households that are dual-income, every minute beyond 65 is a fertility disincentive that no cash subsidy can easily offset.

People Love Living Near Trains

Subway proximity reveals a different problem. Within 220 meters of a station, SHAP values are positive: extreme convenience supports work-family balance. Between 220 meters and 1 kilometer, values turn negative. Beyond 1 kilometer, the effect converges to zero.

The mechanism is housing prices. Transit-adjacent areas in Seoul command steep premiums. Young families, newly married, carrying education debt, facing the enormous costs of private tutoring, are precisely the households priced out of the 220m-to-1km zone. For them, the housing premium overwhelms the commuting benefit. That’s a spatial equity problem masquerading as a transportation one.

Daycare, clinics, and the hospital paradox

Public daycare shows the sharpest single threshold: SHAP values strongly positive within 400 meters, dropping off sharply beyond. The GWR confirms this effect is especially pronounced near central business districts (Seoul Station, Gwanghwamun) where dense office complexes make walkable childcare a critical lifeline.

The policy implication cuts against current practice. Childcare policy in Seoul has focused on quantity: more facilities, more slots. The data say placement matters at least as much. A daycare center 600 meters away, however well-staffed, falls outside the threshold. For a parent rushing between a morning shift and evening pickup, those extra 200 meters are the difference between a schedule that works and one that doesn’t. But here’s the equity problem: areas where daycare, clinics, and schools cluster within walkable thresholds tend to overlap with higher-income neighborhoods. The 400-meter radius doesn’t just correlate with higher fertility. It correlates with higher housing prices, which price out the young families who would benefit most.

Neighborhood clinics tell a similar story at finer scale: positive SHAP values within 200 meters, diminishing toward zero beyond 400 meters. Infants and toddlers visit clinics an average of 6.5 times per year, two to three times the frequency of other age groups. A walkable clinic isn’t a luxury for these families. It’s a near-daily necessity.

Large hospitals present the opposite pattern, and it is one of the study’s most striking findings. SHAP values are negative within 1.5 kilometers, positive between 1.5 and 3.5 kilometers, declining again beyond. The GWR confirms this around major institutions: Seoul National University Hospital, the National Medical Center, Korea University Anam Hospital. The mechanism is straightforward: sirens, congestion, transient populations erode the residential tranquility families seek. Different scales of healthcare infrastructure relate differently to residential life.

Education, leisure, and null findings

Elementary schools within 820 meters and private academies within 200 meters is associated with higher fertility. A notable GWR finding: educational infrastructure shows largely insignificant spatial variation across Seoul, implying that schools have reached spatial saturation. Fertility effects come not from regional disparities in supply but from whether individual cells fall within the walkable thresholds. The relevant planning unit is the neighborhood, not the district.

Cultural facilities within 780 meters are associated with lower fertility. This isn’t counterintuitive once you consider where cultural facilities cluster in Seoul: intense commercial zones where noise, congestion, and nightlife dominate. In Hongdae and Hyehwa, youth-oriented entertainment districts, fertility rises with distance from the cultural core. These aren’t family amenities. They’re signals of an environment oriented toward childless urban lifestyles.

Parks showed no consistent directional trend. Restaurants and grocery stores had no significant effect. The study’s authors think it’s likely because South Korea’s advanced food delivery infrastructure (72.5% usage, reaching 84–87% among twentysomethings and thirtysomethings) has decoupled food access from physical proximity.

Sociodemographic patterns

The sociodemographic controls largely confirmed expected patterns. Income shows positive SHAP values above approximately 3.27 million KRW, close to the national average wage of 3.64 million KRW, consistent with risk theory: economic insecurity leads people to delay or forgo childbirth. Areas with greater age diversity (entropy index above 0.94) show higher fertility, consistent with research on intergenerational childcare support networks. Marriage is the single most powerful predictor of birth counts, unsurprising given that only 2% of Korean births occur outside marriage, compared to the OECD average of 40%. The study appropriately conducted a secondary SHAP analysis excluding marriage to reveal the residential environment’s independent contribution.

“Family-friendly” is a luxury good

This is where the analysis becomes most consequential.

The thresholds identified above (400 meters for daycare, 200 meters for clinics, 820 meters for schools, under 65 minutes for commuting) are not distributed equally across Seoul. Areas that meet them are desirable. Desirable neighborhoods command higher prices. Higher prices push out young families. The infrastructure gap between neighborhoods that meet these thresholds and those that don’t isn’t just inconvenient. It’s a mechanism driving housing price differentiation, and through that, reproductive inequality.

In a city where the price-to-income ratio stands at 13.9 years, where average apartment prices have surpassed $1 million, where 82.6% of young people rent, this cycle is the operating reality for millions. A “fertility-friendly environment” has become a commodity accessible only to those who can already afford it.

The $280 billion in pronatalist spending has targeted reducing the private costs of children for individual families. Almost none has been directed at ensuring that the public infrastructure associated with higher fertility (walkable daycare, accessible clinics, manageable commutes) is equitably distributed across income levels and neighborhoods. The money targeted the wrong margin.

What this means for urban policy

The study recommendations below is grounded in an empirically identified threshold.

Childcare placement over quantity. The current approach increases facility counts per district. The evidence argues for a different standard: ensure every residential area falls within 400 meters of a public daycare center. Walkable distance, not per-capita ratio. This almost certainly requires more facilities in underserved neighborhoods rather than additional slots in areas already within the threshold.

The 65-minute commuting constraint. Land-use and transit planning should treat this as a hard ceiling for residential zones targeted at young families. This means integrating childcare and affordable housing into transit-accessible nodes, not merely building transit lines and hoping families benefit. The subway paradox underscores the point: access to transit is necessary but not sufficient. It must be paired with affordability measures that prevent young families from being priced out of the very zones where the commuting benefit exists.

Differentiated healthcare proximity. Neighborhood clinics should be sited within 200 meters of residential concentrations. Large hospitals require buffer planning, a recognition that their negative externalities within 1.5 kilometers may discourage family formation. Not an argument against hospitals. An argument for understanding that institutional scale matters for residential environments.

Threshold-based school placement. Educational infrastructure is spatially saturated in Seoul; fertility effects are driven by micro-level proximity, not district-level supply. Future placement should ensure individual neighborhoods fall within 820 meters of an elementary school and 200 meters of supplementary educational facilities.

Caveats

This study identifies associations, not causal effects. Families with children may sort into neighborhoods with better infrastructure, rather than better infrastructure causing higher fertility. Disentangling selection from treatment would require longitudinal data tracking neighborhoods before and after infrastructure changes, data not yet available at this spatial resolution. The dasymetric mapping used to distribute births to grid cells improves on raw administrative data but inevitably introduces estimation error. And the nearest-neighbor metric assumes residents use only the closest facility; a neighborhood with three daycare centers within 600 meters might offer more effective accessibility than one center at 350 meters. Future research using Two-Step Floating Catchment Area methods could capture these dynamics.

Several features of the Korean context (the 2% non-marital birth rate, the dominance of private academies, the delivery infrastructure that decouples food access from proximity) limit direct generalizability. But the structural dynamics (threshold effects in walkable accessibility, the tension between transit proximity and housing affordability, disamenity effects of large-scale institutions) are likely to operate in any high-density city where young families face time poverty and financial constraint. The specific numbers will differ. The logic should travel.

Getting the questions right

South Korea (or most countries) cannot close the Strait of Hormuz. It cannot control oil prices or global inflation. What it can control is whether the physical environment makes parenthood logistically survivable for households on the fence.

Every threshold in this study is a policy lever. Every one is currently left to the market, which prices young families out of the neighborhoods where the thresholds are met and traps them in neighborhoods where they aren’t. The evidence from Seoul tells us where to start. The evidence from 1973, 2008, 2022, and now 2026 tells us we are running out of time.

Key points

• The fertility gap between Korea and Japan comes down to one age group. Korea’s TFR fell 51% from 2000 to 2023 versus Japan’s 12%, and nearly all that divergence traces to women aged 25–29. Korean births in this group collapsed 87%; Japan’s fell 35%. Other age brackets looked similar in both countries.

• Male economic inactivity is the key. Among Korean men 25–29, the share neither working nor seeking work nearly tripled, from ~10% in the mid-1990s to 30% by the early 2020s. In Japan it barely moved. The study attributes about a third of Korea’s fertility decline in this age group to that rise.

• Male inactivity and female employment suppress fertility different ways by birth order. For first births, predictors are male inactivity and unemployment; female labor force participation isn’t significant. For second-plus births, female participation becomes strongly negative (−0.811, p<0.001), alongside male inactivity, but male unemployment drops out. This pattern is consistent with research showing that workplace inflexibility and childcare burdens make it difficult for working mothers to have additional children.

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If you’ve read anything about South Korea’s collapsing birth rate in the past few years, you’ve almost certainly encountered the 4B movement. The name comes from four Korean words beginning with bi (meaning “no”): no marriage, no childbirth, no dating, no sex with men. It emerged from Korean feminist circles around 2017 to 2019, born of fury over gender-based violence, digital sex crimes, and a society where the word “feminist” is treated as a slur. Western media ran with it.

The narrative has been adopted with equal enthusiasm by people who agree on almost nothing else. First Things, the conservative religious journal, declared flatly that the movement is “both a consequence of South Korea’s fertility crisis and a cause.” From the other direction, progressive commentators frame 4B as effective resistance, a successful “birth strike” that has brought the patriarchal Korean state to its knees. One widely shared article in The International Affairs Review stated, without qualification, that the decline in Korea’s fertility rate “results from the 4B Movement.”

Here is what everyone discussing 4B seems to have missed: the movement has approximately 3,400 members on Naver, South Korea’s largest online platform, and claimed about 4,000 at its peak in 2019. As Ju Hui Judy Han, a gender studies scholar at UCLA, has noted, the vast majority of Korean feminists do not subscribe to 4B’s tenets, and the movement has actually lost momentum in recent years. More importantly, the timeline doesn’t work. South Korea’s birth rate fell below the replacement level of 2.1 in 1983. It crossed the “lowest-low” threshold of 1.3 in 2001. It dropped below 1.0 in 2018. The 4B movement emerged, at the earliest, in 2016 or 2017. The fertility collapse was well underway for decades before the first Korean feminist typed bihon into a Twitter post. Attributing Korea’s demographic crisis to 4B is like attributing a house fire to someone who showed up after the roof had already caved in and took a photograph.

So what is driving it?

A recent study by Sinn Won Han of Yonsei University and Fumiya Uchikoshi of Harvard, published in the Chinese Sociological Review, offers an answer that cuts against both framings. The mechanism is not ideological refusal or a "birth strike." It is more consequential: a large and growing share of young Korean men have become detached from the labor force entirely, limiting the options of women who do want to marry. Male employment (Korea, Japan, America, and almost everywhere) is effectively a prerequisite for marriage, and marriage is effectively a prerequisite for childbearing, that detachment cascades into a demographic crisis.

The story is not about women who won’t marry. It’s about men who can’t.

The natural experiment that nobody noticed

Japan and South Korea are, to a first approximation, the same country when it comes to the structural conditions that suppress fertility. Both have punishing work hours and expensive urban housing. Both are gripped by an education arms race in which parents pour enormous sums into private tutoring. Both maintain dual labor markets that punish women who step off the career track to raise children. And both have been grappling with low fertility for decades.

And yet. Korea’s total fertility rate has plummeted to 0.72 births per woman. Japan’s sits at 1.20. Between 2000 and 2023, Korea’s TFR fell by 51%. Japan’s fell by 12%.

If the standard explanations (gender inequality, housing costs, education expenditures, family-unfriendly workplaces) were sufficient, these two countries should look roughly the same. They don’t. And 4B cannot explain the gap either, since Japan has no comparable movement and its fertility has been far more stable.

Where the divergence lives

Han and Uchikoshi begin by decomposing the fertility decline by age group. The entire Korea-Japan divergence is concentrated in one demographic: women aged 25 to 29. In Korea, the birth rate for this age group collapsed from 150 live births per 1,000 women in 2000 to just 20 in 2023, an 87% decline. In Japan, the same age group fell 35% over the same period, from 100 to 65 births per 1,000.

Every other age bracket tells a broadly similar story in both countries. The 30 to 34 age group in Korea saw a temporary increase between 2005 and 2012 as some women who delayed childbearing had children a few years later, but that recuperation stalled and reversed. What initially looked like postponement has increasingly become abandonment.

If we want to explain the Korea-Japan divergence, we need to explain what changed for people in their late twenties.

Watching the wrong gauge

Most research on labor markets and fertility tracks the unemployment rate. Han and Uchikoshi argue it is the wrong indicator, at least for Korea. Unemployment among Korean men aged 25 to 29 has spiked during recessions (1997, 2008) but recovered each time. It has not trended dramatically upward.

The economic inactivity rate tells a different story. Inactivity captures individuals who are neither employed nor actively seeking work. Among Korean men aged 25 to 29, the rate has nearly tripled over three decades, rising from roughly 10% in the mid-1990s to 30% by the early 2020s. Among Japanese men in the same age group, the rate has barely moved: from 3.6% in 1995 to 5.5% in 2022.

This divergence has opened up steadily and structurally, not in response to any single recession. Unemployment is cyclical. Inactivity is secular. If you’re only watching unemployment, you’re watching a gauge that oscillates around a roughly stable mean while the real pressure builds somewhere your instruments aren’t pointed.

What economic inactivity looks like

Korea’s inactivity is different from what the term typically connotes in Western Europe, where it tends to reflect welfare dependency or health-related withdrawal and where associations with fertility are weak. In Korea, it is driven in large part by competitive preparation: young men spending months or years studying for civil service entrance exams, company hiring tests, or professional certifications. This is not withdrawal in the psychological sense. It is a rational, if individually costly, response to a labor market in which the gap between regular and non-regular employment is vast in wages, benefits, job security, and social status, and in which the entry points to regular employment are intensely competitive and narrowly gated.

But the composition of the inactive population has shifted. Among economically inactive Korean men aged 25 to 29, the share who are not students rose from 49% in 2000 to 67% by 2022. When inactivity reflects enrollment in a graduate program, it has a clear endpoint and a plausible payoff. When two-thirds of inactive young men are not enrolled in any educational program, when they are instead preparing for exams they may never pass, cycling through informal training, or simply stuck, the story changes.

And when they do eventually enter the labor market, they pay a lasting penalty. Those who experience prolonged inactivity or NEET status tend to be channeled into non-regular, temporary, or part-time positions with lower long-term wages and fewer protections. The preparation, in other words, often doesn’t work.

Numbers

The paper's country-level regression analysis puts numbers to the intuition. After controlling for seven other variables (male unemployment, female LFP, real house price index, paid leave, public spending on family benefits, GNI per capita, and Gender Inequality Index), the male economic inactivity rate for ages 25 to 29 is negatively and significantly associated with the age-specific fertility rate for women in the same age group. The coefficient is −2.488: each percentage-point increase in male inactivity is associated with a decline of roughly 2.5 births per 1,000 women aged 25 to 29.

Separating first births from second-and-higher births matters. Male inactivity suppresses both, but the mechanisms are different. For first births, male inactivity and male unemployment are the significant predictors; female labor force participation is not. For second and higher births, female labor force participation becomes strongly significant alongside male inactivity. The implication is that male economic exclusion blocks entry into parenthood altogether. Female employment, by contrast, constrains expansion of family size once a couple has already started. The first problem is about clearing the path to marriage; the second is about making it possible for working mothers to have more than one child.

Korea’s male inactivity rate increased by approximately 17 percentage points between the late 1990s and the early 2020s. Multiply 17 by 2.488 and you get a predicted decline of about 43 births per 1,000 women. The actual observed decline in the 25 to 29 birth rate over this period was roughly 130 births per 1,000 women. The rise in male inactivity thus accounts for approximately 33% of the total decline. For Japan, the same coefficient applied to a 1.3-percentage-point increase in inactivity predicts a decline of only 3.3 births per 1,000 women, about 10% of Japan’s (much smaller) observed decline.

The other variables in the model moved similarly in both countries. Male inactivity didn’t, and it explains a third of the divergence.

The panel regression draws on 48 country-year observations across two countries. That’s thin. But the results survive two important robustness checks, re-estimation using only pre-pandemic data (2000 to 2019) and an alternative lag structure, and they are corroborated by two entirely independent analyses using individual-level data. Triangulation across macro regressions, vital statistics, and survey data is the real evidential strength here, not any single regression table.

Marriage Markets

Among marriages involving men aged 25 to 29, the share in which the groom was unemployed or inactive at the time of registration was 7.7% in 2000 and fell below 5% by 2022.

This seems to cut against the paper’s argument. But the reading is exactly backward. The declining share tells us not that inactive men are marrying at reasonable rates, but that they are being excluded from the marriage market almost entirely. The total number of marriages among men aged 25 to 29 fell by approximately 89% between 2000 and 2022, from roughly 121,000 to about 14,000. The marriages that still occur are overwhelmingly between employed men and their partners. The inactive men aren’t marrying at a discount. They’re not marrying at all.

The standard 4B framing places women’s refusal at the center of the fertility decline, but the marriage market is shrinking in large part because a growing share of men lack the economic standing that social norms treat as a prerequisite for marriage, not just in Korea but also in most of the developed world. If you don’t marry, you almost certainly don’t have children.

What inactive men believe about their own futures

The paper’s final analysis draws on survey data from the Korean Labor and Income Panel Study. Compared to employed peers, economically inactive non-students report significantly lower confidence across every dimension of the life-course sequence Korean society expects young men to complete: securing a desired job, obtaining housing, dating and marriage, having and raising children. These are not men who have rejected the aspiration. They want what their parents had. They just don’t believe they can get it.

The popular discourse frames Korea’s fertility crisis in terms of choice: young people choosing careers over families, freedom over obligation, protest over conformity. The attitudinal data suggests something different for a large share of the population. Not choice but exclusion. Not what people want but what they believe is possible.

Why Korea and not Japan?

If the mechanism is correct, then the Korea-Japan divergence resolves into a prior question: why did male inactivity rise so dramatically in Korea and not in Japan?

The paper points to several structural factors. The retirement of Japan’s large baby boomer cohort (born 1947 to 1949) created labor market vacancies that younger workers could fill. Korea’s demographic structure offered no comparable opening. Japan’s post-2010 stimulus policies also improved youth employment.

Beyond the study’s analysis, the structural environment facing a young Korean man compounds the labor market gap.

Housing is one example. Monthly rents in Seoul are actually somewhat cheaper than in Tokyo, but that comparison is misleading. Korea’s housing market operates on jeonse, a system in which tenants pay a lump-sum deposit of 60 to 80% of a property’s market value in exchange for living rent-free for two years. For a modest apartment in Seoul, that deposit can easily reach $75,000 or more. The deposit is theoretically refundable, but jeonse fraud, where landlords cannot or will not return deposits, has become a serious and growing problem. For a young man who is economically inactive or precariously employed, accumulating a jeonse deposit is functionally impossible, and the alternative (monthly rent, known as wolse) is rising as the jeonse system frays. Seoul apartment prices have roughly doubled in five years, with a price-to-income ratio of approximately 10 to 1, three to four times that of comparable economies. Tokyo’s upfront deposit requirements are far lower.

Then labor market conditions. Japan’s acute labor shortage, driven by boomer retirements and a shrinking working-age population, has created something approaching a seller’s market for young job seekers. The ratio of job openings to applicants has hovered well above 1.0 for most of the past decade. Korea offers no such tailwind. Korean wages have actually surpassed Japan’s in recent years (about 4 million won monthly at firms with 10+ employees in 2022, versus 3.8 million won at Japanese equivalents), but these wages accrue to those who have made it through the gate. Those who haven’t face temporary, part-time, and precarious positions that pay far less.

It is almost like aggregate wage statistics hide a mind-boggling amount of variation between workers, and the best way forward is to eliminate slack in the labor market. Fancy that.

One factor the paper does not discuss: mandatory military service. Korean men serve approximately 18 months, typically between ages 18 and 21. Japanese men face no such obligation. Military service does not explain the trend (it is a constant, not a variable) but it does explain why Korea’s system is structurally more fragile. An 18-month delay compresses the window between completing education and the late twenties into an extremely tight band. When the post-service pathway was straightforward, this was manageable. As the pathway has gotten longer and more uncertain, the fixed delay leaves less and less margin.

The right problem

The implications cut against both sides of the culture war around Korea’s fertility decline.

To conservatives who blame feminism: the data shows that Korea’s fertility collapse is driven by men who cannot enter the labor market, cannot enter marriage, and cannot have children. Blaming 4B for a demographic transformation driven by the economic exclusion of hundreds of thousands of young men is a distraction from the structural reforms that might actually help.

To progressives who celebrate 4B as effective resistance: Korean women face genuine grievances about gender inequality, violence, and the unequal division of domestic labor. But framing the fertility decline as a successful “birth strike” misidentifies the mechanism and risks obscuring the labor market crisis trapping a generation of young men in economic limbo. It doesn’t take much thought to realize just how bad of an idea that is.

Not to mention, if the goal is to maximize fertility rates, based on this paper (and others) the goal is an extremely tight job market for all genders. Gender conflict and labor market exclusion are not competing explanations. They are compounding ones. But we cannot fix what we refuse to see.

So, the point being?

Korea may not be an outlier. It may be a leading indicator. China’s youth unemployment rate hit record levels in 2023, high enough that the government temporarily stopped publishing the data. The structural conditions that produce male economic inactivity in Korea (intense credentialism, dual labor markets, limited entry points to stable employment, strong male-breadwinner norms) are present across the region in varying degrees.

If male labor market detachment is a significant driver of fertility decline and that detachment is intensifying across East Asia’s high-pressure economies, then the policy conversation needs to shift. The question is not only how to make it easier for employed, married couples to have children. It is how to ensure that young men can enter the labor force at all, early enough, and with enough stability, to contemplate family formation.

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Elon Musk has called declining birth rates a threat of “mass extinction.” JD Vance wants “more babies in America.” Nigel Farage, at a Birmingham rally, warned of demographic decline. All three are also among the most aggressive opponents of working from home. Musk banned remote work at Tesla, SpaceX, and X, called it “morally wrong,” and spearheaded the push to force federal employees back to the office five days a week. Farage dismissed remote work as “a load of nonsense” and demanded “an attitudinal change to hard work rather than work-life balance.”

This isn't a partisan issue. Both Biden and Trump administrations, Canada's Liberal government, Labour governments in the UK and New South Wales, centre-right and centre-left alike across Europe: all are dismantling flexible work. The one thing the entire political spectrum agrees on is that someone working from home is getting away with something, results be damned!

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A new paper (on a mountain of papers which own paper is the bedrock of) suggests they are actively undermining their own stated goals.

“Work from Home and Fertility,” by Aksoy, Barrero, Bloom, Cranney, Davis, Dolls, and Zarate, draws on original survey data from 38 countries and U.S. Census data to investigate the relationship between remote work and having children. The team spans Stanford, Princeton, the European Bank for Reconstruction and Development, Mexico’s ITAM, and Germany’s Ifo Institute. The central finding is striking: working from home is associated with substantially higher fertility, the relationship is robust across multiple datasets and identification strategies, and the implied contribution to national birth rates is large enough to matter. Interpreted causally, their estimates imply that WFH accounts for roughly 291,000 U.S. births per year, about 8.1% of all American births as of 2024. By comparison, government spending on early childhood care and education appears to deliver less, at far greater cost. We’ll return to that comparison with full numbers later.

This paper can’t definitively rule out every alternative explanation for the patterns it documents. But it is a pretty comprehensive examination of the WFH-fertility relationship to date, the broadest in geographic scope and the most careful in its use of multiple empirical strategies.

What the paper finds

The study draws on two surveys of the authors’ own design: the Global Survey of Working Arrangements (G-SWA), covering 38 countries with data from late 2024 and early 2025, and the U.S. Survey of Working Arrangements and Attitudes (SWAA), a monthly survey with observations from December 2022 to December 2025. Both contain questions on working arrangements, demographics, and a detailed module on realized and planned fertility. The analysis focuses on respondents aged 20 to 45.

The pattern is consistent in both datasets. People who work from home at least one day per week have higher realized fertility (children actually born since 2023), higher planned future fertility, and higher total lifetime fertility (children to date plus plans for more). For couples, the relationship strengthens when both partners work from home. In the 38-country G-SWA data, estimated lifetime fertility is 0.32 children per woman higher when both partners WFH at least one day a week than when neither does, a 14% difference relative to mean total fertility. In the U.S. SWAA data, the gap is even larger: 0.45 children per woman, or 18% of the mean.

These patterns hold after controlling for age, education, marital status, number of children before 2023, own and partner’s employment status, and country or state fixed effects. They hold separately for men and women. They hold in the raw data and in conditional regressions. They hold across 38 countries on four continents.

The extensive margin matters most

One of the paper’s most policy-relevant findings concerns the shape of the WFH-fertility relationship. When the authors replace their binary WFH indicator with a continuous measure (how many days per week?), the continuous measure does show a positive relationship with fertility, statistically significant in the U.S. data, marginally significant in the 38-country sample. More WFH days, more fertility. So far, so intuitive.

But the picture changes when you let the two measures compete. In specifications that pit the binary indicator against the continuous variable, the binary indicator wins decisively: it remains positive and statistically significant while the continuous variable goes small, insignificant, or sometimes wrong-signed. The authors' conclusion is direct: "the data suggest that some ability to WFH over the week is the key feature of working arrangements that relates to fertility. Given the ability to WFH at least one day a week, we find no evidence that fertility rises with each extra WFH day." And when both partners have that flexibility, the effect compounds: estimated lifetime fertility is 0.32 children per woman higher when both partners WFH at least one day a week than when neither does.

The standalone positive result for WFH days is largely picking up the extensive margin, the jump from zero days to one. That jump is where the action is. Once you let the binary indicator absorb it, the additional contribution of a second, third, or fourth day fades. This doesn’t mean extra WFH days are harmful to fertility, or that they confer no other benefits. It means the bulk of fertility benefit concentrates heavily at the threshold: the difference between some flexibility and none.

For anyone designing workplace policy, or anyone currently dismantling existing flexibility, this is critical. You don’t need to go fully remote to get the fertility benefit. You just need to break the five-day-in-office mandate. One day of flexibility changes the calculus. Conversely, the move from a hybrid schedule to a rigid five-day mandate, which is precisely what many governments and corporations are now trying to impose, eliminates the one feature of working arrangements most clearly linked to higher fertility.

How the evidence is built

What makes this paper more than another “interesting correlation” story is the care with which the authors triangulate their result. The argument is best understood as three concentric rings of evidence, each addressing the causal question with increasing force.

The first ring is the individual-level association between WFH status and fertility outcomes, documented in the G-SWA and SWAA data. The positive relationship is strong and consistent. The obvious objection is selection: perhaps people who want children (or already have them) sort into jobs that offer remote work. The authors don’t deny this possibility at this stage. They establish the pattern and move on.

The second ring is more ambitious. Turning to the U.S. Current Population Survey from 2023 to 2025, the authors examine how individual fertility responds not to a person’s own WFH status, but to the occupation-level prevalence of WFH jobs. To measure this, they use the Hansen et al. (2026) index, derived from a large language model applied to roughly half a billion online job postings to flag those that advertise hybrid or fully remote work. The model achieves 99% accuracy by human audit, greatly outperforming dictionary methods.

The results are clear. One-year fertility rates rise with the share of WFH jobs in one’s own occupation. For partnered respondents, fertility also rises with WFH opportunities in the partner’s occupation. For a sense of magnitudes: raising both own and partner’s occupational WFH shares by one standard deviation (about seven percentage points) is associated with a 13.8% increase in one-year fertility for women and a 10% increase for men, relative to the mean. These are large effects, more than half the cross-sectional standard deviation of one-year fertility for partnered women.

Why does this matter for causal interpretation? Because a person’s occupation-level WFH prevalence is far less under individual control than their personal WFH status. You can choose to work from home (if your employer allows it); you have much less say over the WFH norms of your entire occupation. Selection becomes a weaker explanation.

The third ring pushes the identification strategy further still. Since WFH opportunities rise steeply with educational attainment in the post-pandemic era, and since people aged 30 to 45 chose their education levels many years before the pandemic made WFH widely available, educational attainment provides a proxy for WFH opportunities that is effectively immune to reverse causality concerns. Nobody earned a college degree in 2010 in anticipation of hybrid work policies that would arrive a decade later.

The results confirm the pattern. In the CPS data, college-educated respondents aged 30 to 45 have substantially higher one-year fertility in 2023–2025. Relative to respondents who did not attend college, women with a Bachelor’s degree have a one-year fertility rate 29% higher (in the sample of partnered women). If her partner also holds a college degree, fertility rises by a further 24%. The magnitudes are similar for men.

The authors are forthright about what this ring of evidence can and cannot establish. They cannot rule out the possibility that other characteristics of college-educated couples (income, relationship stability, cultural attitudes) independently raise fertility in this period. But the consistency across all three approaches is telling. Individual WFH status, occupation-level WFH opportunities, and education as a WFH proxy all point in the same direction. Either WFH raises fertility, or there exists some powerful confound that simultaneously correlates with all three measures and operates independently of the extensive controls the authors include. Not impossible, but increasingly implausible.

The time-series logic

A methodological choice worth noting: the authors deliberately exclude fertility data from 2020 to 2022. Two reasons, both sensible. First, the pandemic itself (health shocks, contagion fears, social distancing, economic uncertainty) had potentially large and confounding effects on fertility that cannot be easily separated from WFH effects. Second, fertility decisions are forward-looking. People who contemplated having children in 2020 or 2021 could not have been confident that the surge in remote work was permanent. By 2023, it had become apparent that WFH rates would not revert to pre-pandemic levels. U.S. monthly data show WFH rates stabilizing by early 2023 and fluctuating in a narrow band since then. Data from 2023 onward are therefore more informative about the longer-term relationship between WFH and fertility, and that is the period the authors focus on.

The cross-country picture

The paper’s 38-country scope yields some of its most vivid material. WFH rates among workers aged 20 to 45 vary enormously: from 21% in Japan to 60% in Vietnam. (The high rates in some lower-income countries, including Vietnam, Egypt, the Philippines, and Thailand, partly reflect farming, craft work, and small-scale production that takes place at or near home, rather than laptop-based knowledge work.) Among high-income countries, the spread is wide. The United States (39%), the United Kingdom (54%), and Canada (53%) stand well above Japan (21%), South Korea (24%), and Italy (24%).

This variation matters because the paper translates it into fertility consequences. Using a straightforward accounting framework, the authors calculate the contribution of WFH to each country’s total fertility rate (TFR) in the post-pandemic era. The results range from a WFH contribution of 0.038 children per woman in Japan and 0.037 in Italy to 0.101 in Canada and 0.131 in the United States. As a share of TFR, that’s 3.1% in Japan and Italy, 7.6% in Canada, and 8.1% in the United States.

The more provocative exercise asks: what if countries with low WFH rates raised them to the average of the U.S., U.K., and Canada, about 45% of working women? The implied fertility gains are modest but nontrivial. Japan would gain an estimated 0.057 children per woman, translating to roughly 31,800 extra births per year. South Korea would gain 0.033 children per woman, or about 10,500 extra births per year. France and Italy would each gain about 0.042 children per woman, some 17,000 extra births per year in France and 12,800 in Italy.

These numbers won’t reverse decades of fertility decline, but it would reverse a few years. Not to mention, these fertility gains come at essentially zero cost to the public purse.

The missing intercept

There is a subtlety in the paper’s accounting that sophisticated readers should note. All of the estimates rest on cross-sectional variation: they capture whether your WFH status or opportunities predict your fertility relative to others. They do not capture what the authors call a “missing intercept,” the possibility that living in a society where WFH is broadly available raises fertility for everyone, including people who don’t currently work from home. The logic is intuitive. If a woman knows that WFH jobs are widely available in her economy, and will likely remain so, the prospect of combining employment with motherhood looks less daunting even if her current job is fully on-site, because she could switch to a more flexible role later. Economic reasoning suggests this aggregate effect has a positive sign. If so, the paper’s estimates are lower bounds on the true contribution of WFH to fertility. The authors flag this honestly; we flag it because it bears on the policy implications.

Mechanisms: what’s driving this?

The authors identify three stories that could underpin the positive relationship, and they resist the temptation to declare a winner.

The first is straightforward causation: WFH jobs make it easier to combine child-rearing with paid employment (managing school pickups, being present when a child is sick, avoiding long commutes) and this directly leads women and their partners to choose higher fertility.

The second is pure selection: families with children (or plans for children) sort into WFH jobs for the flexibility they offer, but the availability of WFH doesn’t actually change fertility decisions. Under this story, WFH and fertility are correlated but causally unrelated.

The third, and most interesting, is selection operating as a causal force: the availability of WFH jobs raises fertility by expanding current and future opportunities to select into parent-friendly work. Under this story, selection is itself the mechanism through which WFH affects fertility. People have more children because they know flexible jobs exist, even before they take one.

All three stories are consistent with the underlying idea that WFH makes it easier for parents to combine work and family. The occupation-level analysis (ring two) and the education-as-proxy analysis (ring three) are designed to put pressure on the pure selection story, and they do. In the CPS sample, respondents aged 30 to 45 are restricted precisely because occupational mobility at these ages is low: nearly nine in ten don’t switch occupations from one year to the next. It’s hard to argue that a 35-year-old woman chose her occupation in response to a fertility event when she’s been in that occupation for years. The pure selection story isn’t impossible, but it looks increasingly strained.

The comparison that reframes the debate

Olivetti and Petrongolo (2017), using annual data for 22 high-income countries from 1970 to 2010, find that additional government spending on early childhood care and education equal to one percent of GDP is associated with 0.2 extra children per woman. The United States spends about 0.4% of GDP on such programs. Interpreted causally, that implies a fertility contribution of roughly 0.08 children per woman. The paper’s estimate of WFH’s contribution to U.S. fertility is 0.131 children per woman, more than 60% larger.

The comparison is not entirely clean. The Olivetti and Petrongolo estimates come from panel data with country and year fixed effects; the Aksoy et al. estimates come from cross-sectional variation. Different methods, different data, different periods. We should be cautious about drawing too precise a conclusion. But the broad implication is hard to ignore: the fertility benefit of a workplace practice that costs the government nothing appears to be in the same ballpark as, and may exceed, the fertility benefit of programs that absorb meaningful shares of GDP.

What we don’t know

First, the three-ring evidence structure is persuasive in aggregate, but each ring has vulnerabilities. The individual-level analysis is subject to selection bias. The occupation-level analysis could reflect unobserved occupation-level characteristics that correlate with both WFH prevalence and fertility norms. The education analysis can’t rule out other features of college-educated couples. The authors know all of this and say so explicitly. What they have is a strong circumstantial case, not a randomized experiment.

Second, the planned fertility measures rely on stated intentions. People say they plan to have two more children; whether they actually will is another matter. The authors partially address this by examining realized fertility (children actually born since 2023) alongside planned fertility, and the patterns hold for both. But the total fertility measure, which drives many of the paper’s headline numbers, is a composite that depends on intentions.

Third, the cross-country estimates rest on a common treatment effect (β) for all countries except the United States, because the G-SWA isn’t large enough to support reliable country-specific estimates. The actual fertility response to WFH could differ substantially across cultures. In East Asian societies, where status-driven competition in children’s education is a major driver of low fertility, WFH may help less than in contexts where the binding constraint is primarily logistical.

Fourth, the paper says nothing about WFH’s effects on productivity, collaboration, innovation, or any of the other outcomes that (not so) legitimately concern employers and policymakers. Other academic research on productivity points that remote work has no effect or boosts productivity, and most employers on investor calls will admit that RTOs is often used to push people to quit as a soft layoff, rather than productivity.

The policy contradiction

We come back to where we started. Governments of every political complexion are simultaneously lamenting falling birth rates and tightening return-to-office mandates. But the paper's extensive-margin finding makes these incremental rollbacks more damaging than they appear. A mandate that goes from two required office days to three, then three to four, doesn't just reduce flexibility. It tells every worker that the last remaining WFH day is next. And people making fertility decisions don't plan around what they have today. Each step looks like it only removes one day, but what it actually removes is the confidence that any flexibility will survive, which is where the fertility effect lives.

In the United States, RTO started under the Biden Administration, with significant support from city mayors and center governors, but it was reinforced by the Trump administration’s executive order requiring full return-to-office for federal employees was among its earliest acts. Musk and Ramaswamy, in a Wall Street Journal op-ed, explicitly welcomed the “wave of voluntary terminations” they expected it to produce, framing it not as a side effect but as a feature: a tool for shrinking the federal workforce by making conditions unpleasant enough that people quit.

In the United Kingdom, the Labour government maintained the previous Conservative administration’s 60% office attendance mandate for civil servants, set out in the Civil Service People Plan 2024–2027. Staff at the Land Registry and the Office for National Statistics voted for strike action over compulsory attendance. Metropolitan Police civilian staff walked out over similar mandates. This is not a right-wing government; it is a centre-left one, enforcing the same policy its predecessor introduced.

Farage went further than any mainstream British politician at his Birmingham rally on February 9th, dismissing the entire concept of work-life balance and calling for remote work to end entirely. He offered no evidence. The Spectator noted that his audience was overwhelmingly pensioners and that his own party had previously advertised remote-working roles. Even Reform’s own council leader in Nottinghamshire contradicted him, saying their hybrid policy “works very well.”

Canada tells a similar story. The Liberal government mandated three days a week in the office for federal public servants starting September 2024, up from two. By February 2026, Prime Minister Mark Carney’s government announced a further tightening to four days per week, with executives required on-site five days. This despite the fact that Carney himself has written extensively about the economic benefits of flexible work. The union representing federal scientists called it “a slap in the face”; multiple unions are exploring legal action. Meanwhile, Ontario and Alberta, conservative provinces, went further still, requiring full five-day return-to-office for their public servants in early 2026.

In Australia, the Labour premier of New South Wales ordered all 430,000 public servants back to office-based work in August 2024, giving staff one day’s notice. The union warned of 20% vacancy rates in critical agencies like child protection. The neighbouring state of Victoria, also Labour-run, took the opposite approach, offering to poach disgruntled NSW workers with its maintained flexible work policies.

In France, public administration workers are mandated to be in the office an average of 3.7 days per week, nearly double the mandate in London. The corporate sector is moving in the same direction. Amazon, JP Morgan, Goldman Sachs, and Meta have all imposed five-day return-to-office policies. Some of these mandates are openly designed to trigger attrition. Amazon’s CEO denied it was a “backdoor layoff”; few were persuaded.

This is not a left-versus-right issue. It is a cross-partisan consensus that remote work is a perk workers don't deserve. Evidence that it also raises fertility doesn't soften the position; it enrages it. The idea that letting people work from home one day a week might be good policy is intolerable to leaders who have already decided that flexibility is something to be clawed back.

Research from King’s College London finds that 55% of women say they would seek a new job if required to return full-time, compared to 43% of men. If RTO mandates disproportionately push women out of the workforce, or into less flexible, lower-WFH occupations, the fertility implications run in both directions. More WFH means more babies. Less WFH may mean fewer.

The Aksoy paper suggests that work-life balance, operationalized as even one day of remote work per week, is associated with 0.32 extra children per woman across 38 countries. One of the paper’s co-authors, Cevat Giray Aksoy, a lecturer at King’s College London, told LBC directly that “the research does not support his blanket claim that working from home is nonsense.” The Spectator observed that Farage’s position makes him “not a conservative, but a malcontent of boomer liberalism.” Even the TaxPayers’ Alliance cautioned that a party claiming to support free markets “cannot, in the same breath, start micromanaging how private firms organise their workforce.”

If you think that there are tensions in the WFH debate that the paper does not resolve. That some organizations may suffer from reduced in-person collaboration. Some roles genuinely require physical presence. One-size-fits-all mandates in either direction are probably a bad idea. But if you believe, as Musk says he does, that low fertility rates threaten civilization itself, and he has donated $10 million to population research at the University of Texas to back up that belief (which isn’t enough in the grand scheme of things), the evidence increasingly suggests you should be expanding remote work opportunities, not eliminating them.

The cheapest pro-natalist policy available is guaranteeing that people work from home one day a week, if the role allows for it. It costs the taxpayer nothing. It requires no new legislation. And a growing mountain of evidence, including this study encompassing 38 countries and multiple identification strategies, suggests it raises fertility by a nontrivial amount. The question is whether anyone who claims to care about birth rates is willing to take the evidence seriously, or whether the culture war over remote work will continue to trump the demographic concerns that supposedly animate it.

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In 2023, South Korea recorded a total fertility rate of 0.72 children per woman, the lowest figure any country has produced in the modern era of demographic measurement. Not Japan. Not Italy. Not any of the famously low-fertility societies of Southern or Eastern Europe. Korea.

The speed of the collapse is what makes it extraordinary. In the early 1960s, Korean women averaged nearly six children each. By 1983, the rate had dropped below the replacement level of 2.1. That was fast but not historically unusual; many developing countries compressed their fertility transitions into a few decades. What happened next was unusual. The rate kept falling. It never rebounded. After 2010 the decline accelerated, and in 2018 the TFR slipped below one child per woman for the first time in recorded history. Five years later: 0.72. Maternity wards are closing. Elementary schools are consolidating. The government projects the population, currently around 52 million, could fall below 40 million by 2060 without a dramatic reversal.

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Now consider the economic trajectory alongside the demographic one. In 1960, Korea’s GDP stood at roughly $4 billion. By 2023, it had surpassed $1.7 trillion. The country’s Human Development Index ranks among the highest in the world. Korea produces the planet’s most advanced semiconductors, builds globally competitive automobiles, and exports film, music and television that dominate international markets. A Korean company probably manufactured the phone in your pocket or the screen you are reading this on.

By every conventional measure of national prosperity, Korea is a triumph. By the single most consequential measure of demographic sustainability, it is in crisis. GDP growth of roughly 42,000 per cent over six decades. A fertility rate of 0.72.

How do these two facts coexist? A recent study by Kyungjae Lee and Seongwoo Lee (2026), published in Population, Space and Place, offers an interesting answer. Not in the choices of individual women, and not in national economic aggregates, but in the widening economic distance between Korean regions. The relationship between regional inequality and fertility turns out to be subtler than the standard accounts suggest, and the subtlety matters a great deal.

The usual suspects

The standard story about Korea’s fertility collapse is not wrong. It is incomplete.

Korea’s labour market has become increasingly split between protected regular employment and precarious contract work, with younger cohorts disproportionately stuck in the latter. Stable jobs facilitate family formation; unstable ones suppress it. In the Seoul metropolitan area, apartment prices have reached levels that make purchasing a home, long considered a cultural prerequisite for marriage, feel like an impossible aspiration for young couples. And women who want careers face enormous pressure to sacrifice childbearing, because the institutions and norms that might allow them to do both (genuinely shared parenting, flexible work arrangements, affordable childcare) remain underdeveloped.

Hwang (2023) demonstrates that fertility decline in Korea has occurred broadly across educational and employment groups. Not just among the highly educated. Not just among the precariously employed. Across the board. Decomposition analyses show the decline is driven primarily by within-group changes: women at every level of education and in every employment category are having fewer children. If the collapse were really about more women attending university or entering the labour force, the decline should concentrate among those groups. It doesn’t.

Something structural is operating above the level of personal characteristics, reshaping the conditions under which families form regardless of who the individuals are. The usual suspects have been correctly identified. But they are not the ringleaders.

So what is?

What the maps reveal

Lee and Lee’s answer begins with geography. Literally, with maps.

Compare the spatial distribution of crude birth rates across Korea’s 229 districts in 2015 and 2021. The first pattern is straightforward: the CBR declined substantially in nearly every district over the six-year period. This is not a story of births migrating from one region to another. The entire distribution shifted downward. Fertility fell almost everywhere.

The second pattern is the one that matters. The relative economic positioning of districts shifted simultaneously. Lee and Lee measure regional economic disparity using Yitzhaki’s relative deprivation index, which calculates each district’s position by averaging the gap between its gross regional domestic product and the GRDP of every district above it. The result is a unique deprivation score for each of the 229 districts. Between 2015 and 2021, relative deprivation increased across the distribution. Districts that were already disadvantaged fell further behind. The economic hierarchy steepened.

Fertility decline and widening regional disparity unfolded in tandem, across the same space, over the same years. That visual correspondence is descriptive only; it does not establish causation. But it is suggestive enough to warrant digging deeper.

The backstory of Korea’s regional inequality makes the pattern easier to understand. In the 1960s and 1970s, industrial cities along the Seoul-Busan corridor and the southeastern coast developed concurrently. Regional disparities were not particularly pronounced. But since the 2000s, population and industry have concentrated relentlessly in the Seoul Metropolitan Area: Seoul, Incheon and Gyeonggi-do. Today, more than half of Korea’s population and GDP are packed into the SMA. High-skill employment clusters in the capital region. Non-metropolitan areas experience what the academic literature calls “weakening industrial bases” and what residents experience as the slow disappearance of jobs, young people and civic life. Entire towns in the rural south now have more residents over 65 than under 40.

The SMA is not, however, a fertility-friendly environment. It faces crushing housing costs, intense competition for scarce school and childcare places, and a private education arms race that makes raising children in Seoul extraordinarily expensive. Non-SMA regions have lower living costs, but the outflow of young adults has hollowed out their demographic foundations.

Both sides of the divide face fertility-suppressing pressures, for different reasons. Lee and Lee’s argument is that the growing distance between these two worlds is itself a mechanism. It is not simply that Seoul is expensive or that provincial cities are declining. It is that the gap between them has widened into a spatial hierarchy that constrains family formation regardless of where you stand within it. The standard expectation (get rich, have kids again, the so-called J-curve hypothesis of Myrskylä) fails in Korea because national prosperity has been distributed so unevenly across space that aggregate growth coexists with intensifying regional deprivation. When national wealth concentrates in one place, neither the rich region nor the poor one produces enough children.

People do not just respond to what they have. They respond to what they have relative to what they see others having. Regions positioned differently within a national economic hierarchy face different constraints on fertility, even when the people living in those regions share similar personal characteristics.

That is the theory. Here is how Lee and Lee tested it, and what they found.

The evidence, and its surprise

The study employed two complementary approaches: a spatial panel analysis of all 229 Korean districts from 2015 to 2021, and a multilevel model of 86,980 married women aged 19 to 49 drawn from the 2020 Population and Housing Census.

The methods matter here. Birth rates in neighbouring districts are not independent. Moran’s I tests confirm statistically significant spatial clustering of fertility rates in every year of the study period, all at the 1 per cent level. Ignoring this spatial dependence biases standard regression estimates. The spatial panel models account for it. Two-way fixed effects remove time-invariant regional characteristics and year-specific shocks common to all regions, isolating the effect of changes in relative deprivation on changes in birth rates. The multilevel model, meanwhile, nests individual women within their districts, separating compositional effects (who the woman is) from contextual effects (where the woman lives). Together, the two approaches let the authors check whether a pattern visible in regional aggregates also shows up in individual women’s childbearing behaviour.

The regional results are clear and consistent. Across all three spatial model specifications, the coefficient on relative deprivation is negative and statistically significant at the 1 per cent level. In substantive terms, a 1 per cent increase in a district’s relative deprivation is associated with a decrease of approximately 0.013 in the crude birth rate per thousand population. Relative deprivation increased substantially and broadly across districts over the study period; aggregated across 229 districts and six years, the cumulative drag on fertility is considerable.

Among the control variables, two are worth pausing on. Regional economic output (GRDP) carries a significant negative coefficient. That is: economic growth, as it has actually occurred in Korea, concentrated in the metropolitan core and accompanied by rising costs, is associated with lower fertility, not higher. The marriage rate, meanwhile, is strongly positive, reflecting the near-universal norm in Korea that childbirth occurs within formal unions. Housing costs and population density are both negative, as expected.

Now for the surprise. When Lee and Lee turn to the individual-level multilevel models, the first result seems to contradict everything the spatial panel analysis just established.

In Model 1, which includes the level of relative deprivation as a regional variable, the coefficient is positive. Economically disadvantaged regions had somewhat higher fertility in the 2020 cross-section. If regional deprivation suppresses fertility, why do more deprived regions have more births per woman?

Tempting, but wrong. That positive association reflects level differences, a snapshot. Some lower-income regions in Korea have historically maintained somewhat higher fertility, often linked to more conservative family norms and lower costs of living. But a snapshot is not a trajectory. When the authors move to Model 2 and examine the growth rate of relative deprivation, the change from 2019 to 2020, the coefficient flips sharply negative (−0.56, significant at the 1 per cent level). Districts where the gap widened saw married women bear fewer children, even after controlling for age, education, homeownership, housing type, and employment status of both the woman and her spouse.

It is not the level of disadvantage that suppresses childbearing. It is the widening of the gap.

That distinction matters enormously. A region can have relatively low economic output and still sustain reasonable fertility, so long as its position in the hierarchy is not deteriorating. But when the distance to the prosperous core grows, fertility falls.

The convergence of these results across both levels of analysis is what makes the finding hard to dismiss. The negative association between widening regional inequality and fertility is not an artefact of aggregation. It appears in district-level panel data, and it appears in the childbearing behaviour of individual married women. Both point the same direction.

What this means for Korea and beyond

Lee and Lee’s findings suggest pronatalist interventions may be considerably more effective when paired with strategies that keep young people in places outside the capital. The significant positive coefficients on the share of young adults and women in the spatial models reinforce this: regions that retain these demographic groups maintain stronger fertility potential. The question, and it is genuinely difficult, is how.

Korea is an extreme case, but the underlying dynamics are not unique. Japan’s economy and population have been concentrating in the Tokyo metropolitan area for decades while rural prefectures empty out, and Japanese fertility has followed a strikingly similar downward path. Italy’s Mezzogiorno-North divide tells a version of the same story. The mechanism Lee and Lee identify, spatial relative deprivation operating as a contextual constraint on family formation, follows from the logic of uneven development itself.

I should be candid about what the study does not yet settle. It demonstrates a robust negative association between widening regional disparities and fertility, but it does not fully trace the causal pathways. Cultural norms, local policy interventions and migration decisions all likely mediate the relationship in ways the data cannot yet model. The two-way fixed effects and extensive controls mitigate omitted variable bias, but they cannot eliminate it.

The core finding, though, reframes the conversation about demographic decline. Lee and Lee argue that regional economic disparity is the structural force operating above individual characteristics, and their evidence, drawn from both district-level panels and the childbearing behavior of nearly 87,000 women, is consistent at every level of analysis.

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recently wrote a piece arguing that the pronatalist movement doesn’t care about mothers. She describes women experiencing panic attacks when they return to hospitals where they had traumatic births. She cites research showing unplanned cesareans reduce subsequent fertility by 28-34%. She points out that Richard Hanania’s “ideal fertility rate of 6.5” translates, for a third of American women, into multiple major abdominal surgeries with escalating risks.

I agree with almost all of her substance. It’s exactly the kind of quality of life/systems-level analysis I’ve been trying to bring to this discourse.

And then I (or more specifically pronatalists) get lumped in with Hanania and Musk.

More than likely, she isn’t really aware of what pronatalism is in real life or aware of anything I written. I have a strong feeling she would like the stories of Minamiminowa in Japan, South Tyrol in Italy, or Yeonggwang in Korea. I also like to think she would be surprised on how much pronatalist academic research focus on the quality of life issue. None of it required Musk to tweet about population collapse or Hanania to calculate optimal fertility rates.

Still, lumping me in with Musk, Hanania, etc? I’m a bit miffed of being associated with people whose actual practices contradict both real world research and I personally advocate for. I’m even more miffed about relitigating terminology when there’s more interesting things to discuss.

So here’s my attempt to redirect to conversation toward towards said interesting things, and answer some questions in the meantime.

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The Conversation So Far

kicked this off by explaining why she’s not a pronatalist. Heavy-handed rhetoric alienates women. National spending in Hungary and Korea hasn’t moved the needle. American fertility isn’t broken yet. The label carries baggage she doesn’t want.

pushed back: if you want more babies, say so. “Pro-family” is evasive. Refusing to name what you’re for cedes ground to people who are happened to be against.

shares some of Greco’s concerns (Musk’s surrogacy arrangements, eugenicist rhetoric at conferences, proposals that pressure women without asking men to change) but thinks Stone is asking the right question.

Now Ledbetter has sharpened Greco’s critique from the perspective of someone who actually delivers babies. Her point isn’t about rhetoric or coalition management. It’s about what happens in exam rooms and operating theaters. A movement that talks about “ideal fertility rates of 6.5” without acknowledging what that means for women’s health isn’t serious.

Meanwhile, a genre of lazy commentary positions itself above the fray: everyone’s shoehorning their priors, nothing works, prosperity itself is the problem, wait for artificial wombs.

The questions below are my attempt to move past the terminology fight toward what the evidence actually shows.

Part I: The Terminology Fight

Q1: Should we just say “pronatalist”?

Yes. Stone is right about this.

“Pro-family” is a flag of convenience. Conservatives use it to mean traditional marriage; progressives use it to mean paid leave. The term means nothing.

On that note, what makes you think bad actors won’t just co-opt the new term? Let’s save time.

I’m a pronatalist. More babies. Specifically: helping people have the children they already want. Removing barriers, reducing risk.

And before people go conservative policy on me, pointed out, liberal countries have more children than conservative ones. So things are not as clear cut as people pretend.

Q2: Greco, Brown, and Ledbetter all hesitate to embrace the label. Are their concerns trivial?

No. They’re identifying real problems.

Greco worries that heavy-handed rhetoric will politicize fertility and drive liberal women away. The messenger matters, and the movement’s worst voices are often its loudest.

Brown worries about capture by bad actors: Musk’s surrogacy-and-NDA arrangements, men seeking multiple partners for “civilizational” reasons, proposals that pressure women without asking men to step up.

Ledbetter goes further: when Hanania proposes 4-8 children per woman, is he proposing multiple major abdominal surgeries for a third of American women? Would he care about their health? We know he doesn’t care about economic losers. Hanania treats this as a detail, but as much as he would hand wave it away, it doesn’t change the fact that traumatic births reduce subsequent fertility.

Part II: The Measurement Problem

Q3: Greco points to Hungary and Korea as evidence that national spending doesn’t move fertility. Is she right?

Wrong on the spending, right on the variation.

Hungary’s fertility rose from 1.25 in 2012 to 1.52 in 2022 after implementing marriage bonuses, housing programs, and cash benefits. Evaluating it by post-invasion fertility (during Europe’s energy crisis and austerity) is like weighing someone after hospitalization.

Lyman Stone’s research directly addresses the “cash doesn’t work” claim. His analysis of 43 studies covering 58 policies (yes,hat is a lot) shows clear correlation between benefit generosity and fertility increases. The 17 countries implementing major policies since 2000 saw increases of 0.09-0.18 births per woman, persisting 10+ years.

Mongolia increased fertility from 2.0 to nearly 3.0 after implementing cash benefits. Japan’s 2010 reforms prevented collapse from 1.4 to 0.8. Czechia vs. Slovakia provides a natural experiment: after their split, Czechia maintained steadier support while Slovakia cut aggressively. Result: 0.31 swing toward Czechia.

But here’s what Greco’s skepticism correctly identifies: national averages hide enormous local variation. Japan has cities like Akashi and Nagareyama with much higher rates. Korea’s Yeonggwang County achieves 1.71 (double the national 0.75) while Busan’s Jung District hits 0.38.

Treating national averages as “proof nothing works” ignores what actually varies: local policy choices and sustained commitment.

Q4: Everyone uses Total Fertility Rate. Is that the right metric?

No. And the problems run deeper than most people recognize.

TFR conflates two independent dynamics: how many women become mothers at all (Total Motherhood Rate) and how many children mothers have (Children Per Mother). research across 314 million mothers found these show near zero correlation. They respond to different forces and need different interventions. Using TFR alone discards half the diagnostic information.

Consider: In 1980, 76.1% of American women became mothers and averaged 2.39 children each (TFR 1.82). By 2016, only 69.4% became mothers but averaged 2.63 children (same TFR).

Greco says American fertility “isn’t broken” because cohort TFR remains near 1.95. The decomposition tells a different story. France achieves higher fertility by helping more women become mothers. The US achieves similar numbers through concentration.

Edward Deming was scathing about management by single numerical targets. You cannot improve what you cannot measure, but measuring the wrong things produces perverse outcomes. TFR invites this error.

Policymakers optimize for the headline number while ignoring underlying dynamics. A TFR increase driven by economic winners having more children while everyone else is excluded isn’t success. It’s just going to give us wrong ideas on what is the problem and how to deal with the problem.

Track TMR and CPM separately should be the first, but not only, step that people should take next.

Q5: What’s driving the decline in motherhood specifically?

The biggest reason is economic scarring of young people, especially young men. Every recession collapses TMR and marriage rates. If they fail to recover, damage compounds when the next shock hits.

TMR tracks marriage, which tracks male economic stability, which tracks the shocks we keep inflicting on entry-level labor markets. Researchers tracked 400 regions in Germany across 13 years and found job destruction reduced fertility 38% more than job creation increased it. When factories closed, birth rates plummeted. When new positions opened, fertility barely budged.

The 2008 financial crisis didn’t cause a temporary dip. TMR dropped 6.7 percentage points and never recovered. Men who experience employment instability in their twenties need fifteen years of stable employment to match their peers’ marriage prospects.

Japan shows the same pattern. Women in non-regular employment express half the fertility intentions of regular employees. Precarity makes both ambition and motherhood impossible.

The mechanism is repeating now. The 20-24 unemployment rate jumped from 5.5% to 8.2% in eighteen months after Fed tightening. We’re creating the next generation of 45-year-olds who never recovered.

Q6: Ledbetter argues that birth experiences shape subsequent fertility. Is that measurable?

Yes, and the effect is large. This is one of the most important feedback loops the standard discourse ignores.

Haley Wilbert’s study used Army health claims and medical records to isolate the effect of cesarean delivery on future childbearing. Among women with unplanned cesareans, the probability of subsequent childbirth within four years dropped by 28% to 34%. The mechanism runs through both physical and psychological pathways: increased hospital readmission and mental health visits following unplanned procedures.

Deming insisted that 94% of problems are attributable to the system, not to individuals. The maternity care crisis isn’t about bad doctors or weak mothers. It’s about a system optimized for defensive medicine, liability avoidance, and throughput. When 32% of births are cesareans and only 16% of counties offer VBAC, that’s system output.

Blaming women for being “too scared” after traumatic births misses the point: what about this system produces traumatic births?

Part III: The Systems Framework

Q7: What framework should guide fertility policy?

I don’t share the theological commitments that animate some of Stone’s work, or the Catholic social teaching behind Brown’s. My framework comes from a different tradition: Deming’s quality management, Beer’s organizational cybernetics, Juran’s quality trilogy. Measure the right things. Break down silos. Constancy of purpose. Build systems with enough redundancy to absorb shocks.

One of my favorite useful tool from this world to think about things is Stafford Beer’s The Purpose of a System Is What It Does (POSIWID). Not what the mission statement says, not what designers intended, but what the system actually produces. If a maternity care system consistently produces traumatic birth experiences, that’s what the system does. If online discourse produces viral threads and personal brands but no policy changes, that’s what the discourse is for.

Jospeh Juran distinguished three phases: quality planning (designing processes capable of meeting goals), quality control (monitoring and correcting deviations), and quality improvement (systematically raising baseline performance). Most government fertility policy skips planning and improvement entirely, leaving only reactive control: throwing money at symptoms without understanding the system that produces them.

Korea has spent billions “addressing low fertility” without thinking about how to design a system capable of producing higher fertility under real-world conditions. No one planned the current system; it accreted. And because there’s no systematic improvement process, the same failure modes persist indefinitely.

What distinguishes successful places is what Deming called constancy of purpose: sustained commitment to improvement over decades rather than flavor-of-the-month initiatives. Systems change slowly. Leaders must persist.

Q8: What makes family formation feel so fragile now?

The compensatory pathways have been stripped out. The system has lost redundancy.

A “simple complex system” is simple enough to be prone to cascades but complex enough that you can’t predict what will fail. Family formation has become this. The pathways that used to compensate for each other are gone:

• Extended family nearby? Increasingly rare.

• Single income sufficient for housing? Gone in most metros.

• Flexible work permitting engaged parenting? Until 2020, almost nonexistent.

• Stable employment in your twenties? Destroyed every time the Fed tightens, let alone economic shocks since the 70s oil crisis.

• Supportive birth experience? For many women, no longer available.

• Each failure stresses the remaining paths. Each cohort has fewer options.

Taking a page from cybernetics is Ashby’s Law, that a system’s regulatory capacity must match the variety of disturbances it faces. When the environment grows more complex but organizational capacity doesn’t keep pace, failure is inevitable. Family formation now faces more variety than ever (dual careers, geographic mobility, housing cost volatility, gig employment, delayed partnership formation) but with social and economic systems that would have supported family formation collapsed.

One-size-fits-all national policies lack the requisite variety to address diverse local conditions. The way forward isn’t one policy that solves everything. It’s restoring this “socioeconomic” redundancy: multiple pathways to stable employment, housing, childcare, and birth experiences that don’t traumatize women out of subsequent pregnancies.

Q9: If “family policy” is too narrow, what actually counts?

Everything that shapes the barriers. The silos between policy domains obscure that the system is interconnected.

The silos aren’t just administrative inconvenience. They break feedback loops. The people making monetary policy decisions don’t receive information about fertility effects fifteen years later. The people setting childcare ratios don’t see the families priced out. Decision-makers never learn the consequences of their decisions because the information arrives too late or flows to different people.

Housing is family policy. Rising values mean rising rents, fewer first-time buyers, lower fertility.

Work flexibility is family policy. Norway’s 2020 lockdown gave rigid-job workers schedule control for the first time. Births increased 10%, with the effect 152% stronger among workers who’d never had flexibility. The 40-hour fixed-schedule workweek actively prevents engaged parenting.

Maternity care is family policy. The cesarean-to-subsequent-fertility feedback loop is a 28-34% effect.

Energy prices and monetary policy are family policy. Energy shocks collapse fertility worldwide. Fed tightening scars young workers with fifteen-year echoes.

The system is already shaping outcomes. The question is whether we’re honest about what we’re doing.

Part IV: What That Work

Q10: Where has pronatalism actually worked?

In places where systems produce the outcomes they claim to want, through sustained implementation at multiple levels.

National policy sets the floor. Stone’s research shows Japan’s 2010 interventions prevented fertility from collapsing to 0.8; Mongolia’s cash benefits produced a 50% increase; Hungary rose from 1.25 to 1.52. The “financial incentives don’t work” consensus is wrong.

But national policy alone doesn’t explain the variation. The places achieving outlier results share common features: sustained local commitment, operational focus, barrier removal across multiple domains.

Japan: National Floor Plus Municipal Excellence

Akashi (1.65 fertility): Former Mayor Fusaho Izumi cut public works spending, doubled childcare allocations, and sustained it through a decade of opposition. Free medical care to age 18, free school lunches, free nursery for families with two or more children. Cleverest intervention: free diapers delivered by midwives, combining material support with professional outreach. Population grew ten consecutive years.

Nagareyama: Station-based childcare handles pickup and dropoff, letting parents commute to Tokyo. 29% of elementary families in the city have three or more children. Whether Nagareyama’s policies caused this directly, or just attracted families who already wanted more kids, or whether concentrating young families together creates its own momentum, I’d genuinely love to have the funding to research it.

Minamiminowa Village (1.76 fertility): Former mayor Karaki Kazunao persisted despite criticism, creating systematic childcare reductions, free healthcare through high school, participatory governance. With 73.3% transplants, the village developed “appropriately weak ties,” connections that provide support without overbearing pressure.

Korea: Yeonggwang County

Yeonggwang County (영광군) hit a total fertility rate of 1.71 in 2024 (more than double Korea’s national average of 0.75) and has held the nation’s top spot for six consecutive years. There’s no single magic subsidy here. Former Mayor Kang Jong-man credited the “connectivity” (연계성) of policies: youth employment support linked to marriage support linked to birth support linked to childcare.

The county runs about 80 programs covering the whole lifecycle. Birth payments get more generous with each child: 5 million won for the first, 12 million for the second, 30 million for the third through fifth, and 35 million for the sixth onward. There’s also a 500-million-won marriage incentive, a 3-million-won allowance for fathers taking paternity leave, and infertility treatment subsidies up to 1.5 million won.

But the money alone doesn’t explain it. Yeonggwang ties fertility support to jobs and housing. The county set up the nation’s first 10-billion-won Youth Development Fund in 2021, built youth housing at “Neulpum Village,” and partnered with LH to supply 300 public rental units for newlyweds. Stable jobs at the Hanbit Nuclear Power Plant and a growing e-mobility cluster mean young families can actually stay.

The numbers back it up: marriages rose 40% year-over-year in 2024, and the county’s population grew by 1,693 residents, with notable gains among young people and infants.

South Tyrol, Italy

did a neat article on South Tyrol, a provincial area in Italy. Parents receive 200 euros monthly per child until age three, plus an annual 1,900 euros from the Italian government. All newborns registered in the province come with a 'Ben Arrivato Bebé' package including baby items, books, a voucher for more books, and an 'Euregio Family Pass' for discounted public transport. The Family+ card offers shop discounts for parents with three or more children. The 'Casa Bimbo' system provides flexible childcare through local teachers operating home-based nurseries. That is not what made it successful, but the fact that South Tyrol been working at improving quality for families over forty years of sustained commitment, not one-off bonuses cut during as soon politics demanded it. Result: 1.64 fertility with 73% female employment, 37% above Italy’s national rate.

As one demographer put it: “Nobody plans to have children on the basis of one-off policies.”

The Pattern

What these places share isn’t a specific policy mix. It’s constancy of purpose sustained through political opposition. The pattern is scale-invariant: sustained commitment, barrier removal across domains, feedback from families to decision-makers, requisite variety in policy tools.

Q11: Does effective pronatalism require massive spending?

No. Some of the highest-impact interventions cost nothing. They remove barriers the government created.

at the Centre for Family and Education compiled zero-cost family support measures for the UK:

Childcare ratios. The UK has Europe’s strictest staff-to-child requirements. Denmark, Spain, and Sweden have no mandates. Research shows ratios don’t significantly affect quality but dramatically affect cost. British childminder numbers fell 50% between 2013 and 2023 from regulatory burden alone. Relaxing ratios to European norms would expand supply immediately. Cost: zero.

OFSTED registration. Requiring childminders to document curriculum progress for infants creates compliance burden without improving care. Replace it with basic safeguarding checks. Cost: negative.

Planning reform. Liberalize permission for family-friendly housing (extensions, granny annexes, standardized designs). The constraint is political will, not money.

This doesn’t mean spending never helps. Stone’s meta-analysis shows cash transfers have consistent effects (and yes I would spend 10% of GDP on family policy if given the chance). But “we can’t afford pronatalism” is a really bad way of thinking about things, and often cause people to miss low hanging fruit.

Q12: Conservatives have more children than liberals. Doesn’t that mean conservative values produce higher fertility?

At the individual level, yes. At the system level, the opposite is true.

Individual conservatives have more children than individual liberals. But countries with conservative policy regimes have lower fertility than liberal ones. The Nordics and France outperform Southern Europe. Catholic Italy and Spain have Europe’s lowest fertility despite cultural emphasis on family. So we have a situation where social conservatives thrive and live their best lives under generous welfare states.

POSIWID resolves the paradox. What matters isn’t what a system values. It’s what it produces.

Conservative values say family is important. Liberal systems remove barriers to family formation. Traditional societies say “have children” while their systems say “good luck.” People respond to the system.

France and northern Western European countries have high fertility because their systems.

That said, Western European governments are now dismantling these decades-old systems since the Great Recession, with lots of academic research confirming the results. Meanwhile in Eastern Europe, right-wing parties sometimes advocate for family spending, as Stone would gladly attest. In Poland, notes it was the right-wing PiS who implemented universal healthcare, not the left.

The question isn’t whether you value family. It’s whether your system removes barriers and risk that prevents family formation.

Q13: Does keeping women out of the workplace increase birth rates?

No. The evidence points in the opposite direction.

International data shows higher-earning women have more children:

Netherlands: Administrative records found men and women with higher personal incomes had higher birth rates, with the highest-earning women having 60% higher birth rates than the poorest.

Japan: Working women with career ambitions show higher fertility intentions. Women planning for children were nearly twice as likely to hold stable, regular employment. Career advancement motivation scored significantly higher among women with fertility intentions.

Germany: Job creation in female-dominated industries (healthcare, education) boosts birth rates. A 1% increase in female-dominated jobs correlates with a 0.01 increase in fertility rates. Women in non-regular employment express half the fertility intentions of regular employees.

Sweden: Women’s income association with birth rates shifted from slightly negative to positive over time. In recent cohorts, earnings of mothers with 1-3 children exceed those of childless women.

It’s not employment that suppresses fertility. It’s economic precarity and it reinforces the fall in maternity rates that Shaw demonstrates. Stable employment in family-friendly industries with higher incomes enables both career and family formation. Women in irregular, low-paying jobs have lower fertility intentions and outcomes.

The brief historical period when richer people had fewer children is ending. We’re returning to the ancient norm: higher-status people having more babies.

Part V: The Coalition Problem

Q14: Who’s giving pronatalism a bad name?

The evidence base for barrier-removal pronatalism existed decades before Elon Musk discovered that tweeting about population collapse generates engagement.

South Tyrol started in the 1980s. Akashi began in 2011. Minamiminowa’s transformation started in 2005. Yeonggwang has led Korea for six consecutive years. None of it required the likes Musk or Hanania.

Musk is a late arrival polluting a conversation that should be about implementation.

He warns about civilizational collapse while implementing RTO mandates as an explicit “attrition tool” (his word with Vivek Ramaswamy: forced office return “would result in a wave of voluntary terminations that we welcome”). Research by Nicholas Bloom estimates this costs roughly 100,000 births annually compared to hybrid work.

Apply POSIWID: What does Musk’s system produce? Brand value about demographic concerns, plus labor cost savings through attrition. What doesn’t it produce? Babies.

Hanania calculates “ideal fertility rates” of 4-8 per woman while dismissing the framing that people want more children than they have. He says he “thinks less of” childless people and wants childlessness “negatively marked in the broader culture.” That’s not barrier removal. It’s demographic engineering through social coercion.

Deming had a word for reacting to every fluctuation as if it were a special event: tampering. The online discourse is chronic tampering. Every Musk tweet becomes representative of “pronatalism.” Every quarterly fertility number triggers hot takes. Tampering makes systems worse, not better.

Here’s what baffles me: we have Hayao Miyazaki.

Miyazaki is a known pronatalist who advocates supporting young families. His films celebrate childhood, family bonds, intergenerational care, rural community, the natural world children should inherit. He’s as famous as Musk globally, more beloved, less controversial. His entire body of work is an argument for why children matter and what kind of world we should build for them.

And yet the discourse is hellbent on making Musk and his hangers-on like the Collins couple the face of pronatalism.

Q15: Why does the discourse seem disconnected from what works?

Because online incentives produce engagement, not outcomes, and you can’t avoid that with a name change. If there’s any hope of changing the tide, it requires better organization and coordination from the less deranged parts of the discourse, regardless of whether they’re progressive, conservative, or eccentrics like myself.

Effective systems require feedback from outputs to decision-makers. Online advocacy gets instant engagement metrics but zero feedback about policy outcomes unfolding over years.

The always-online pronatalist discourse systematically focuses on worthless grandstanding: terminology fights, coalition policing, responding to provocateurs, symbolic positioning. The vital few (cesarean rates, VBAC access, housing costs, employment stability, childcare logistics) get ignored because they’re boring, technical, and don’t generate engagement.

The real-world interventions most likely to succeed are precisely those least likely to go viral: remote work policies , budget reallocations are unglamorous municipal finance, forty years of sustained payments is the opposite of viral, Yeonggwang’s 80+ lifecycle-connected support policies require reading Korean local government documents.

What generates engagement? Calculating “ideal fertility rates.” Tweeting about civilizational collapse. Fighting about terminology.

Ledbetter writes that pronatalist “advocacy for mothers seems quiet to nonexistent.” Quiet, yes. Because the boring operational work that takes decades happens where engagement metrics don’t reach.

Q16: There’s a genre arguing “nothing works.” Is that sophisticated or defeatist?

Defeatist, and wrong.

If nothing works, explain the variation from local governments and national benefits. Why is Japan have higher fertility rates than poorer countries in East Asia? Why does France have higher rates in America? Why does this city that “does something” have higher rates than the city that does “nothing”.

“Nothing works” requires treating national averages as the only data and dismissing subnational variation as noise. But the variation is the evidence.

The tell is when critics invoke Romania’s Decree 770 as if that’s what most pronatalists propose, despite decades of counterevidence. Forced gynecological monitoring isn’t barrier removal. Conflating the two lets critics attack a strawman while ignoring actual proposals.

Juran taught that poor quality isn’t free. It costs more through rework, waste, inspection, and failure. The “nothing works” crowd treats the “poor quality” status quo as costless default. It isn’t.

Every traumatic birth that deters subsequent pregnancy is a cost. Every young man whose employment instability prevents family formation is a cost. Every woman who wanted children but couldn’t because of macro factors is a cost.

The question isn’t whether intervention is expensive. The question is whether the cost of intervention exceeds the cost of continued system failure. “Nothing works” is an accounting error that ignores the losses already accumulating.

Back To My Point (and the Regular Scheduled Programing)

Edward Deming’s most humane principle: drive out fear. When women fear traumatic births, they don’t have more children. When young men fear economic instability, they don’t form families.

But here’s what I’ve avoided: what “building” actually requires.

I’ve spent 4,000ish words criticizing discourse while participating in it. What have I produced? Another Substack essay. Not changed hospital policies, passed legislation, or supported mothers.

We just really don’t need more terminology debates.

Even in the pronatalist online sphere, people still haven’t never heard of Akashi, South Tyrol, or Yeonggwang. They only hear false cliches about how xyz policy failed, when it didn’t. They’ve only heard Musk tweeting about collapse. When someone says “pronatalist,” they picture Hanania calculating fertility rates, not free diapers delivered by healthcare workers.

That’s the problem. We need to make the boring work less boring. How do we show more people what forty years of commitment looks like.

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By 2023, only 56% of Korean men were on track to ever marry, compared to 67% of women. Three decades earlier, both figures exceeded 95%. Marriage in Korea hasn’t just declined; it’s become gendered in ways that reveal how economic shocks operates.

Women’s retreat from marriage has been gradual, predictable, almost stately. You could draw the trend line with a ruler. Men’s trajectory is jagged, think sharp drops, partial recoveries, then steeper drops. Between 2019 and 2021 alone, men’s marriage rates collapsed nearly ten percentage points.

Sam Hyun Yoo’s new study in Demographic Research allows us to distinguish between “later” and “never.” For Korea, the answer is increasingly “never.”

It isn’t that men aren’t doing enough chores, Korean men been increasing their share of household chores. It is just that mechanism isn’t just about marriage. Economic shocks and instability, in spite of economic growth, makes young people, especially men, undateable before it makes them unmarriageable. This isn’t just about Korea.

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The Numbers

Marriage rates have collapsed over three decades. Among women, the total first marriage rate fell from 0.83 in 1993 to 0.49 in 2023. Among men, it fell from 0.80 to 0.46. The period proportion ever married dropped from 97% to 67% for women and from 95% to 56% for men. Mean age at first marriage rose six years for women (from 25.2 to 31.2) and five and a half years for men (from 28.3 to 33.8).

The critical distinction lies in comparing adjusted and unadjusted measures. For women, timing-adjusted and unadjusted measures track almost identically, indicating structural retreat. For men, timing effects are larger and the measures diverge, indicating both postponement and structural retreat, plus greater volatility.

The pandemic revealed underlying dynamics that had been partially obscured. Marriage rates hit their lowest point in 2021. International marriages involving Korean grooms collapsed when borders closed. Male mean age at marriage temporarily stopped rising. The reason wasn’t that young men started marrying; older grooms, typically those in international marriages, had simply disappeared from the data.

Structural Retreat, Not Just Delay

The conventional story about declining marriage goes like this: people are marrying later, but they’ll get there eventually. Fertility rates look alarming, but they’re distorted by timing. Once postponed marriages and births occur, the picture will normalize.

We think this story is importantly wrong, at least for Korea.

The evidence comes from comparing two measures: the period proportion ever married (PPEM) and its tempo-adjusted counterpart (PPEM*). The technical details matter less than what the comparison reveals. PPEM tells us what share of a synthetic cohort would ever marry under current marriage rates. PPEM* adjusts for the distortion created when everyone delays marriage simultaneously, a distortion that makes period rates look artificially low during postponement phases.

If Korea’s marriage decline were primarily about timing, we’d expect a substantial gap between these measures. PPEM would fall, but PPEM* would hold relatively steady, revealing that underlying marriage propensity remained intact beneath the timing shifts.

That’s not what the data show.

For women, PPEM and PPEM* have declined in near-parallel since 1993. The gap between them, typically 2 to 6 percentage points, is modest and stable. Korean women aren’t just marrying later. They’re opting out. The decline in period rates reflects genuine behavioral change, not statistical artifact.

Men’s patterns differ. The PPEM-PPEM* gap is larger and more variable, indicating stronger timing effects. But both measures have still declined substantially. Men are postponing and retreating. Their rates also jump around more from year to year.

What looked like delay has revealed itself as decline. The transition from near-universal marriage to a society where a third or more may never marry represents genuine structural transformation, not a timing artifact waiting to correct.

The Male Volatility Problem

Here’s something the aggregate numbers obscure: Korean women’s retreat from marriage has been gradual, predictable, almost stately in its decline. The trend line slopes steadily downward with minimal year-to-year variation. You could practically draw it with a ruler.

Men’s trajectory looks nothing like this. It’s jagged. Sharp drops, partial recoveries, then steeper drops. Between 2019 and 2021, men’s PPEM plummeted from 65% to 56%, a collapse of nearly ten percentage points in two years. Women’s decline over the same period was significant but far smoother.

Why are men more volatile?

Start with international marriages. Korean men, particularly those in rural areas or with limited economic prospects, became increasingly reliant on foreign brides starting in the mid-2000s. Women from Vietnam, China, and the Philippines provided an alternative for men who struggled in the domestic marriage market. When COVID-19 closed borders in 2020, that channel shut overnight. Male marriage rates didn’t just decline. They collapsed.

Economic precarity hits men’s marriageability harder too. Korea’s marriage market, like marriage markets everywhere, prices male economic stability at a premium. When economic conditions deteriorate, men don’t just delay marriage. They fall out of the eligible pool. The 1997-98 Asian Financial Crisis shows up in the data as a sharp marriage rate drop for both sexes, but men’s recovery was slower and weaker.

The technical structure of male marriage timing also amplifies shocks. Men marry later than women on average and across a wider age range. When the composition of who marries shifts (fewer international grooms one year, fewer younger domestic grooms the next) male period indicators swing more sharply. Women’s more concentrated marriage timing creates stability; men’s dispersal creates exposure.

The 2020 pandemic offers a natural experiment. That year, something unusual appeared in the data: men’s adjusted and unadjusted marriage rates suddenly converged. The reason wasn’t that men stopped postponing marriage. The type of man getting married had changed overnight. With international marriages gone, the remaining grooms were younger and domestic. And there were far fewer of them. The male mean age at first marriage, which had been rising steadily for decades, temporarily plateaued.

If you want to understand where marriage is heading, watch the men. Their rates are more exposed to economic and institutional shocks, more sensitive to cross-border dynamics. By 2023, men’s PPEM stood at 56%, compared with 67% for women.

The Partnership Threshold

The marriageability problem is real, but framing it as a marriage problem understates the damage. Economic precarity doesn’t just prevent wedding ceremonies. Just to be cliche, let me point out that it prevents relationships from forming in the first place.

Consider the evidence from the United States, where we have richer data on partnership and dating. Partnership rates among young adults have fallen steadily, and cohabitation hasn’t backfilled the decline. General Social Survey data show the share of men under 30 reporting no sexual partners in the past year rose from around 10% in 2008 to nearly 30% by 2018. Dating apps show stark asymmetries: Hinge’s internal data suggest the top 10% of men receive the majority of female “likes,” while a large share of men receive almost none. These patterns predate the pandemic by years.

The mechanism operates at the dating stage, not just when couples consider commitment.

Let me ask you a question. Why does no one want to date a gig worker? Relationships require planning. Even casual dating involves coordination: schedules, shared activities, splitting costs. A partner whose work hours shift based on algorithmic demand, whose income fluctuates from $1,000 to $6,000 monthly (theoretical high), is difficult to date. The logistical friction compounds before anyone’s thinking about marriage.

Economic instability also signals other instabilities. Fair or not, gig work reads as unsettledness. Someone driving for a rideshare app at 34 prompts questions: Why doesn’t he have a regular job? What’s the plan? Is something wrong? These judgments may be uncharitable. Plenty of gig workers are capable people navigating a labor market that offers them little else. But the judgments operate in dating markets regardless. Gig work is an extreme (and increasingly common) example, but you get the gist.

Valerie Oppenheimer identified the key dynamic in her 1988 work on marriage timing: marriage markets don’t just require male income, they require signal clarity about future economic trajectories. Stable employment at modest wages sends a clearer signal than the theoretical gig work averaging higher earnings with massive variance. (Side note: In real life, gig workers earn low earnings while keeping the massive variance.) A teacher earning a predictable salary is more legible as a partner than a freelancer whose monthly income swings between feast and famine. The variance matters as much as the mean.

This legibility problem doesn’t require long-term planning to matter. Even early-stage dating involves implicit assessment: Is this person’s life together? Can I picture a future here? Income variance and schedule chaos make those assessments harder. Uncertainty is unattractive at every relationship stage.

The effects compound. Men priced out of the dating market don’t gain experience or build confidence. Meanwhile, stably employed men become relatively more attractive, concentrating attention on a narrowing pool. The dynamics feed on themselves.

Institutional Variation, Universal Mechanism

We want to be careful here. The marriageability threshold operates across every developed economy. What varies is how different institutional configurations mediate its effects, and what becomes visible as a result.

In societies where cohabitation has become normalized (Scandinavia, France, increasingly the United States), couples priced out of marriage frequently cohabit instead. Partnership still forms; it takes a different legal shape. The marriageability threshold affects marriage rates, but its impact on partnership formation and fertility is partially buffered. Partially: partnership rates are falling in these countries too, not just marriage rates.

In societies where cohabitation remains uncommon (Korea, Japan, Taiwan, parts of Southern Europe), the same threshold operates differently. When marriage becomes inaccessible, there’s no alternative partnership form to absorb the pressure. Men who can’t clear the bar don’t cohabit; they remain unpartnered. Nonmarital births don’t rise to compensate; they remain rare. In Korea, under 5% of births occur outside marriage. On that note, nonmarital births are falling in the west, so that buffer is evaporating.

This institutional difference doesn’t make one configuration more or less functional. But it does affect what the data reveal. Korean marriage statistics capture partnership decline more directly than Western marriage statistics do. The TFMR and PPEM indicators aren’t just measuring willingness to formalize a relationship legally. They’re measuring union formation itself.

The underlying mechanism is the same everywhere: economic instability makes people less attractive as partners. The institutional channeling determines where the effects become most visible. Korean data offer unusual clarity on dynamics that are harder to isolate in high-cohabitation societies, because there’s less statistical noise from alternative partnership forms.

What This Means

Fertility policy that ignores the marriage market is incomplete. Korea has invested heavily in childcare subsidies, parental leave, and other policies aimed at reducing the costs of childrearing. These matter. But if the binding constraint is increasingly partnership formation, if people aren’t reaching the stage where fertility decisions become relevant, then downstream policies will have limited effect. The bottleneck is earlier in the pipeline.

Labor market policy is family policy. The connection between employment precarity and relationship formation isn’t just a Korean phenomenon. It operates in Chicago, Berlin, and Tokyo alike. Societies that tolerate high levels of unemployment, gig work, contract employment, and income volatility among young adults are implicitly accepting the relationship-market consequences. Those consequences are now visible in the data.

Male outcomes deserve specific attention. We’re accustomed to analyzing gender gaps in ways that focus on women’s disadvantages, and those disadvantages are real. But on partnership formation, men are increasingly the ones falling behind. Men’s marriage rates are lower and more volatile. Men’s dating market outcomes show starker inequality. A policy conversation that treats “family formation” as gender-neutral will miss where the constraints are tightening fastest.

The international marriage dynamic warrants scrutiny. For roughly a decade, international marriages provided a release valve for Korean men priced out of the domestic marriage market. When that valve closed in 2020, the underlying dysfunction became visible. This suggests the domestic marriage market had already failed for a significant share of men. International marriages just made the failure less statistically apparent. As those flows resume unevenly, the data will become harder to interpret, but the underlying domestic dynamics haven’t changed.

We don’t know whether Korean marriage rates will stabilize at current levels, decline further, or partially recover. What we can say is that three decades of data show no sign of a floor. Each cohort has married at lower rates than the last. The modest rebound in 2022-2023 appears to reflect postponed pandemic marriages being realized, not a genuine reversal. The structural transformation continues.

The point

The optimistic interpretation of falling marriage rates, that people are just delaying, has become difficult to sustain. In Korea, where unusually clean data allow us to distinguish timing from structure, the answer is now clear: this is structural retreat. People aren’t marrying later. They’re not marrying.

The dynamics are gendered. Women’s decline has been steady and predictable. Men’s decline has been steeper and more volatile, buffeted by economic shocks and migration policy. Men’s partnership rates are lower and falling faster.

The mechanism isn’t unique to Korea. Economic precarity makes people unmarriageable; more than that, it makes them undateable. The marriageability threshold operates in every developed economy. What varies is the institutional context that channels its effects and determines what becomes visible in aggregate statistics.

Korea’s marriage data offer a window onto dynamics that are harder to see elsewhere, because its institutional structure produces unusually clear signals. The gig economy, housing costs, and employment instability don’t just delay family formation. They prevent it. That’s the lesson from three decades of Korean marriage data, and there’s no reason to think it applies only there.

A growing share of people in developed economies, disproportionately men, are not forming the partnerships that previous generations took for granted. Whether that’s a problem depends on your values. That it’s happening is no longer in doubt.

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We are about to face a caregiving crisis, and the labor market is woefully unprepared. By 2050, the informal care burden per person in Europe will climb nearly 50% above early-century levels. Populations are aging. Fertility rates are falling. Professional care systems are buckling. More workers will step away from their jobs to care for sick children, aging parents, or ailing partners.

When those caregivers try to return to work, employers are skeptical. Still, recruiters prefer caregivers over the unemployed

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That’s the central finding of “Couldn’t Care Less? Understanding and Reducing the Hiring Penalty of Care-Related Career Breaks,” a new study by Liam D’hert, Morien El Haj, and Stijn Baert at Ghent University. Using a factorial survey experiment with 260 professional recruiters in Flanders, Belgium, the team found that job applicants returning from caregiving breaks score roughly 7 to 8 percentage points lower on both interview invitation and hiring probability scales compared to continuously employed candidates.

Yet policy agendas across Europe treat inactive workers, caregivers among them, as a latent labor reserve waiting to be “activated.” The assumption is that supply is the problem. The data suggest demand matters just as much.

Why Employers Discriminate

D’hert and colleagues tested six theoretical channels. Three explained the penalty.

Employers expect workers to be fully devoted to their jobs and available at all hours. Caregiving violates these norms. It signals that a candidate prioritized family over work, and might do so again.

Hours spent caregiving are hours not spent working. Absent explicit information that duties have ceased, recruiters assume they continue.

Time away from work, regardless of cause, is assumed to erode job-relevant competencies. Caregivers suffer this penalty just as the unemployed do, though less severely.

Two other theoretical channels didn’t pan out. Enrichment theory suggests caregiving builds transferable skills (organizational capacity, emotional intelligence) that should enhance employability. The data show no evidence that employers recognize these competencies. Social role theory predicts caregivers might be penalized for lacking “agency,” meaning traits like leadership and self-confidence associated with masculine professional ideals. They weren’t. Caregivers scored no differently than continuously employed candidates on perceived agency or competence.

One exception: caregivers are rated higher on warmth. Recruiters see them as more likeable and attuned to others’ feelings. But warmth alone doesn’t open doors.

By The Numbers

• Caregivers score 7.9 percentage points lower on interview invitations than continuously employed candidates

• Caregivers score 6.9 percentage points lower on hiring probability

• The unemployed fare worse: 17.5 percentage points lower on interviews, 16.7 points lower on hiring

• Caregivers receive a warmth bonus of +0.7 points on a 10-point scale

• Gaps of 1 to 3 years add an extra penalty of 5.2 points (interview) and 3.4 points (hiring) compared to gaps under one year

• Gaps over 3 years add 9.0 points (interview) and 7.5 points (hiring)

• The informal care burden in Europe is projected to rise 50% per person by 2050

• The study drew on 260 recruiters evaluating 1,300 fictitious candidates across 9 occupations

The Unemployment Comparison

Caregivers fare considerably better than the unemployed. The unemployment penalty runs roughly twice as severe, with drops of about 17 percentage points on interview and hiring scales.

A caregiving break offers a clear, socially acceptable explanation for time away from work. Unemployment carries the stigma of market rejection. Employers wonder what’s wrong with someone nobody else wanted.

The perception data add texture. On commitment and skill deterioration, unemployed candidates fare far worse than caregivers. On availability, the two groups look identical. Recruiters assume both will struggle to show up reliably, stay late when needed, or remain free of competing obligations.

The Childcare Paradox

The study included five types of caregiving breaks: caring for a sick child, caring for an aging parent, caring for an ill partner, foster care, and stay-at-home parenting. On interview invitations and hiring decisions, recruiters didn’t distinguish between them.

Beneath those aggregate numbers, a pattern emerges in the perception data. Parents who stepped away for their own children face the harshest judgments on commitment and availability. Stay-at-home parents and those caring for sick children were rated as poorly as the unemployed on commitment, and worse than the unemployed on availability.

We might expect the opposite. Childcare needs stabilize over time; children grow up. Eldercare typically escalates until death. Recruiters should view childcare breaks as more bounded. They don’t.

The explanation likely lies in perceived voluntariness. Caring for a dying parent reads as unavoidable. Staying home with healthy children reads as a choice. Recruiters punish the choice more than the circumstance.

What Works (And What Doesn’t)

The experiment embedded randomized “availability statements” in candidate profiles to test whether targeted signals could counteract employer bias.

Two statements improved caregivers’ ratings: “The candidate is flexible” (emphasizing willingness to adjust hours) and “The candidate is able to adapt well to rapidly changing situations.” The adaptability signal lifted not just availability perceptions but also judgments of commitment, agency, and competence.

One statement just flat out flopped: “The candidate has few responsibilities outside of work” produced no improvement. Employers aren’t reassured by candidates who claim to have shed their outside obligations. The denial may seem implausible, or it may be the wrong frame. Active signals (”I am flexible”) outperform passive ones (”I don’t have constraints”).

Even the successful signals didn’t close the gap. The care penalty shrank but didn’t disappear. For unemployed applicants, nothing worked.

Context Matters

The care penalty shrinks when recruiters evaluate jobs they know well. In familiar occupational contexts, the penalty dropped by roughly one-third.

When recruiters understand a job’s actual demands, they rely less on crude heuristics about what caregivers can or cannot do. Caregivers may face better odds applying to employers and roles where they have existing relationships or industry knowledge. Cold applications to unfamiliar sectors are likely harder.

What Isn’t There

The study has limitations worth noting.

The experiment was conducted in Flanders, Belgium. Labor market norms and employer attitudes vary across countries. The care penalty may be larger or smaller elsewhere.

Factorial surveys present stylized candidate descriptions, not full resumes. Real hiring decisions involve cover letters, LinkedIn profiles, and interviews that could amplify or attenuate the effects observed here.

Recruiters learned the reason for the career break and its length, but not its intensity (24/7 care or part-time?) or current status (have duties ended?). Both factors could shape employer perceptions.

The study found no significant difference in how male and female caregivers were penalized. Some prior studies have found men punished for deviating from breadwinner norms; others have found women punished through motherhood penalties. Weisshaar (2018) found larger penalties for men. Raiber (2025) found a male premium. The null result here may reflect offsetting effects.

What Should Change

Activation policies that push caregivers into a labor market where employers systematically screen them out accomplish little. The paper suggested that anti-discrimination frameworks may need to explicitly address caregiving-related employment gaps.

Employers are excluding candidates based on assumptions about availability and commitment that may bear no relationship to actual circumstances. Structured interview processes and bias training should address caregiving history as a dimension where unconscious discrimination is likely. Employers facing labor shortages should recognize that former caregivers represent an underutilized talent pool.

Caregivers should emphasize flexibility and adaptability, particularly the adaptability framing, which signals competence alongside availability. Applications to familiar industries, where information asymmetry is lower, may yield better results than cold outreach.

The paper’s point being?

Caregivers returning to work face discrimination rooted in assumptions about their skills, commitment, and availability. These assumptions persist after caregiving ends. They apply equally regardless of whom the caregiver supported.

Our labor markets punish people for doing something society needs them to do. As care demands intensify, that contradiction will become harder to ignore. Employers who screen out former caregivers are shrinking their talent pools at precisely the moment labor supply is tightening.

On that note, It’s pretty clear that the labor supply isn’t tight enough else employers would be singing a different tune.

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Swedish men who can’t assess whether they’d recover from job loss aren’t planning for children. This inability to form expectations, distinct from fearing unemployment itself, offers new insight into why fertility keeps dropping even as economies grow.

The research: Oskar Lindström of Stockholm University (now at University of Florence) analyzed survey data from 681 childless Swedish couples collected during the COVID-19 pandemic in 2021 (Uncertainty, resilience, and fertility: Perceived capacity to overcome loss of employment and fertility intentions in Sweden, 2021).

Why it matters: Sweden’s fertility rate dropped to 1.45 children per woman in 2023, the lowest ever recorded. Unemployment rates, GDP, and standard economic indicators don’t explain the decline. People’s perceptions of their economic futures have changed in ways demographers are still mapping.

The Pattern in the Data

Among childless Swedish couples, 61% wanted a child within three years. Three-quarters said they could recover from job loss. But 15.6% couldn’t assess their recovery chances at all. Job security felt solid to 82%, yet this confidence mattered less than believing in the possibility of rebuilding a career.

Men unsure about recovery wanted children at 44%, dropping 17 percentage points below confident men. Men who simply rated their prospects as poor showed no such decline. Women wanted children at 63% to 64% across all recovery assessments. Uncertainty depressed fertility. Pessimism did not.

Certain groups bore heavier effects. Foreign-born individuals unsure about recovery: 35% wanted children versus 62% among confident foreign-born. Native-born individuals hovered near 60% regardless of recovery confidence. Low income paired with poor recovery prospects: 36% versus 69% for low-income individuals confident in recovery. Middle income with uncertainty: 50% versus 67% with confidence. Risk-averse individuals facing uncertainty: 51% versus 66% when confident about recovery.

Sweden’s rate hit 1.45 in 2023. Finland dropped to 1.26, Norway to 1.40. The entire Nordic region, long known for stable fertility, now faces decline concentrated in first births among childless couples. The sharpest drops appear among people with tenuous labor market positions.

The survey included 681 people aged 20 to 40, half male, most native-born. Small subgroups create uncertainty in some findings: 59 reported poor recovery prospects, 104 couldn’t assess them, only 7 combined poor prospects with job insecurity. The response rate reached 27%.

The data point to a specific mechanism. Not knowing whether you could rebuild your career matters more than expecting you couldn’t.

Risk You Can Calculate Versus Futures You Can’t Picture

Risk involves probabilities. You estimate 30% odds of losing your job, save six months of expenses, develop a plan. You tell yourself: “If X happens, I’ll do Y.”

Genuine uncertainty eliminates calculation, after all you can’t estimate the probability of finding any work, let alone the same work, because you lack the framework to make the estimate. Your decision-making is going to stall, especially without hypothetical futures, you can’t orient action toward any of them.

The Narrative Framework in fertility research argues people base fertility decisions on imagined futures rather than current conditions. Economic volatility doesn’t just alter those imaginaries. It blocks their formation. Childbearing always carries uncertainty, an irreversible choice with consequences playing out over decades. People act by building narratives. When you can’t visualize surviving an employment shock, you can’t visualize a future stable enough for raising children.

Men rating their recovery prospects as “low” reached a pessimistic calculation but still formed intentions at normal rates. Men selecting “unsure” signaled inability to assess the question and showed far lower intentions. Pessimistic expectations differed fundamentally from absent expectations.

Why Globalization Changed the Question

High-income countries saw fertility decline after the Great Recession in patterns too uniform across contexts to reflect local factors alone. The declines persisted through economic recovery. Recession, unemployment, wage stagnation don’t match the timeline. Studies examining job insecurity produced mixed results, especially in countries with robust safety nets.

In 2003, sociologists Melinda Mills and Hans-Peter Blossfeld described how globalization creates structural uncertainty. International markets expose local employment to distant shocks. Intensified competition demands constant skill updates. Technology expands networks but also accelerates change. Volatile markets become inescapable. These forces make the future harder to predict regardless of current employment statistics.

Losing a job in this environment might mean your skills became obsolete, your industry relocated overseas, your profession contracted or disappeared. The question isn’t whether you’ll find work. It’s whether you can rebuild your career, maintain your professional identity, preserve your earning trajectory. Sweden cushions unemployment through generous benefits (which itself has been cut and chipped slowly away since the Great Recession) but can’t guarantee career continuity. The safety net catches falls (for now) but doesn’t restore positions.

This represents structural uncertainty built into contemporary economic systems rather than cyclical uncertainty tied to downturns. How we conceptualize economic security (preventing job loss) mismatches how people experience it (adapting to continuous change).

Which Groups Face the Strongest Effects

Foreign-born individuals showed the starkest patterns. When unable to assess recovery prospects, only 35% wanted children, down 25 percentage points from confident foreign-born individuals. Migration already requires navigating unfamiliar credential systems, professional networks, and workplace norms. Layering genuine economic uncertainty on top makes stable futures nearly impossible to construct. Sweden offers integration support through language instruction and job placement services. If immigrants can’t assess whether they could recover from employment disruption due to credential recognition barriers, discrimination, or unfamiliarity with labor market dynamics, that support doesn’t translate into family formation.

Middle-income households including teachers, nurses, and mid-level managers showed 50% fertility intentions when uncertain about recovery versus 67% when confident. They’ve accumulated enough to lose but lack sufficient cushion to feel secure in losing it.

Low-income individuals responded differently. The degree of resilience, not uncertainty about it, drove their fertility intentions. Poor recovery prospects combined with low income: 36% wanted children versus 69% among low-income individuals confident about recovery. Economic vulnerability makes even clear perception of inability to recover enough to deter childbearing. Seven individuals combined poor recovery prospects with job insecurity. They showed 24% fertility intentions, 40 percentage points below those secure on both measures. The number is tiny but marks the boundary where family formation becomes nearly unthinkable.

Risk-averse individuals showed a 15 percentage point gap (51% versus 66%) between uncertain and confident groups. Risk-takers showed no pattern. Risk-averse people struggle most when risk calculation becomes impossible. They aim to minimize bad outcomes, but genuine uncertainty prevents identifying what those outcomes might be or estimating their likelihood. Risk attitudes don’t simply correlate with both employment prospects and fertility preferences. They moderate whether economic uncertainty paralyzes fertility decisions.

Job Security Versus Recovery Capacity

The study separated perceived job security (will I lose my job within twelve months?) from perceived recovery capacity (could I rebuild my career?). Job security showed weaker, less consistent links to fertility intentions. People expecting job loss had lower intentions, but the associations often fell short of statistical significance. Being “unsure” about job security showed no consistent negative pattern. Being “unsure” about recovery capacity did.

Job security measures immediate threat. Recovery capacity measures adaptive capability. Immediate threats might trigger short-term postponement. Inability to imagine rebuilding blocks long-term planning entirely.

Some 82% of respondents felt secure in their jobs versus 75% confident in recovery ability. The survey ran during COVID-19, when employment uncertainty typically spikes. Swedes felt less confident they could bounce back than they felt about keeping their jobs in the first place. That gap between current security and future adaptability may locate where fertility decline actually happens.

The Gender Split

Women showed no link between recovery confidence and fertility intentions. Their likelihood of wanting children held steady at 63% to 64% across all recovery assessments. Men’s intentions varied sharply by recovery confidence. This split aligns with persistent gender norms around economic provision. Men apparently internalize expectations of ensuring economic stability before fatherhood, even in Sweden where gender equality ranks high by international measures.

Several explanations remain untested. Women might assess economic security at the couple level, making their individual employment resilience less relevant to fertility decisions. Women might face different employment uncertainties centered on career penalties from motherhood rather than recovery from job loss. This measure wouldn’t capture that dimension. The study lacked complete data on partner characteristics, but fertility decisions emerge from couple dynamics. One partner’s uncertainty might be offset by the other’s confidence or amplified when both face uncertainty.

What Policy Currently Misses

If genuine uncertainty inhibits fertility more than calculable risk, current interventions may address the wrong problem. Most policies target what happens if you lose a job or working a job unable to cover cost of living: unemployment insurance, housing benefits, healthcare subsidies, etc. These buffer against known risks but don’t address unpredictability.

Sweden invests heavily in active labor market policies including job search assistance, retraining, and subsidized employment. Fertility keeps declining. The issue may not be support availability but assurance and underwriting that available support would preserve professional standing and earning potential. Finding a job differs from maintaining a career trajectory.

A communication gap might exist. If Sweden’s labor market is more forgiving than people believe, the problem involves information and expectations rather than material conditions. Workers may also be reading their environment accurately. In globalized labor markets, specific skills do become obsolete quickly. Professional identities do prove fragile. The perception might match reality.

Unanswered Questions

How does recovery uncertainty connect to fertility intentions mechanically? Does uncertainty prevent forming any fertility desires, or does it prevent acting on existing desires? Does it make childbearing seem impossible or merely inadvisable temporarily? The 2012 GGS wave found only 45% of Swedish women with positive intentions actually had a child within three years (3% of those with negative intentions did). Does recovery uncertainty produce delayed births or forgone births?

We don’t know how perceptions align with actual labor market outcomes. Do people reporting uncertainty about finding equivalent work face worse reemployment prospects in practice? If perceptions diverge from reality, interventions might target expectations. If perceptions match reality, interventions must address material conditions.

Longitudinal data could track how perceptions evolve alongside fertility intentions and behaviors. Couple-level analysis could examine how partners navigate uncertainty together. Cross-national comparisons could determine whether these patterns reflect Swedish institutions or appear more broadly. Cross-temporal comparisons could show whether recovery uncertainty always affected fertility or emerged recently with globalized labor markets.

Study Constraints and Broader Context

Small subgroups create uncertainty: 59 individuals reported poor recovery prospects, 104 couldn’t assess them, 7 combined poor prospects with job insecurity, 18 foreign-born individuals were unsure. The cross-sectional design prevents tracking how changing recovery perceptions affect fertility decisions over time. The measure captures one dimension of adaptive capacity (employment prospects) but not financial reserves, family support networks, or psychological adaptability.

This research is another challenge the second demographic transition thesis. That theory holds fertility decline reflects cultural shifts toward individualism and post-materialist values rather than economic constraints. Economic factors haven’t vanished. They’ve transformed. Affording children remains relevant but now runs through narrative construction. Can you build a coherent life story that includes children? Economic volatility disrupts that narrative construction not by making children too expensive but by making long-term commitments too unpredictable. Economic forces operate through culture, cognition, and meaning-making.

If fertility decline reflects values alone, policy has limited leverage. You can’t mandate that people want more children. If fertility decline reflects structural economic uncertainty preventing people from having children they desire, policy can intervene by restoring capacity to imagine stable futures. Contemporary fertility decline might represent not just delayed childbearing but an expanding group of people who want children but can’t reconcile that desire with the economic futures they envision. The demographic consequences would be profound. The required policy responses would reach far beyond increasing parental leave or subsidizing childcare.

The pointing being

This decline in fertility intentions requires better theories and better measures of uncertainty. This study distinguishes risk (calculable probabilities) from unpredictability (inability to form expectations), specific threats from general volatility, material conditions from subjective perceptions. It demonstrates that “I don’t know” carries substantive information rather than representing missing data.

Will people facing genuine uncertainty today eventually have children they desire under better conditions? Or are we watching a permanent contraction in who becomes a parent and under what circumstances?

Japan’s fertility rate sits at 1.38, well below the 2.07 replacement level. Fewer than 800,000 babies were born in 2022, the lowest figure since records began in 1899. By 2070, the elderly dependency ratio will hit 38.7%, making pension systems unworkable and regional economies unviable.

Where you live matters more than national policy. New research on all 1,741 Japanese municipalities calculated local “desired birth rates” (希望出生率, kibō shusseritsu) and found something striking: only 15% can realistically hit the national target of 1.8 under optimistic assumptions. Under conservative assumptions, none can. The variation is enormous, from 0.81 to 1.97, a 143% spread between lowest and highest. Anyone who been noticing a pattern with me, is that I care *a lot* about varation and the causes behind variation (it’s in the name “Governance Cybernetics*). Local governance choices can affect birthrates along side national policy, in some cases may have a bigger impact.

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Akashi city (明石市) west of Kobe hit 1.65 fertility against a national 1.3 through aggressive municipal spending. Bloomberg found that Nagareyama (流山市), a Tokyo suburb with innovative childcare logistics, reached 1.50 versus the national 1.26. These aren’t are not one offs (or limited to Japan). They result from specific, replicable policy choices that most Japanese localities simply don’t make.

The research, published in the Journal of the City Planning Institute of Japan by Kaoru Kawasaki of NTT East and Eiji Morimoto of Shinshu University, exposes an uncomfortable reality. The national target of 1.8, adopted uniformly by prefectures and municipalities, bears no relationship to structural conditions in 85% of Japanese territory. When local governments chase unachievable goals, they design interventions for demographic situations that don’t exist. The analysis identifies what distinguishes successful municipalities from failing ones. The answers suggest Japanese demographic policy has been looking in largely the wrong places for a decade.

Understanding the Measurement Problem

Japan introduced “desired birth rate” in 2014 to capture something the standard fertility rate misses: the gap between what people say they want and what they achieve. The calculation combines the proportion of young women (15-34) already married with regional survey data on marriage intentions, ideal family size, and remarriage effects. If unmarried women say they intend to marry, and married women want 2.1 children on average, then Japan’s “real” preference sits around 1.8, far above the actual 1.36 total fertility rate (TFR, 合計特殊出生率).

This improves on TFR alone but doesn’t fully decompose the problem. Stephen J. Shaw’s 2025 analysis in Scientific Reports examined 314 million mothers across 33 countries and found that TFR conflates two statistically independent phenomena. The proportion of women becoming mothers (Total Maternal Rate, or TMR) moves separately from average family size among those who do become mothers (Children Per Mother, or CPM). These respond to different forces and need entirely different policy interventions.

Shaw’s information theory is that the TMR alone contains more diagnostic information (3.64 bits) than combined TFR (3.43 bits). Policymakers using TFR as their primary metric are missing nearly half the information needed to design effective interventions. What’s needed is a basket of complementary metrics, not reliance on one or two headline numbers.

The calculation depends on regional survey data (11 broad regions from Hokkaido to Kyushu), not municipality-specific responses. This means hundreds of cities within each region get assigned identical marriage intention figures. The regression therefore captures variation in who’s actually getting married more than variation in aspirations themselves.

The optimal approach combines multiple diagnostic tools. TFR tracks the outcome. Desired birth rate shows intention-behavior gaps. TMR/CPM decomposition identifies which mechanism is failing.

Kawasaki and Morimoto’s municipality-level calculations extend this diagnostic framework geographically. Their desired birth rates vary from 0.81 to 1.97 across Japanese municipalities, patterns that neither national TFR figures nor uniform policy targets capture. Combined with Shaw’s TMR/CPM lens, this creates a comprehensive diagnostic toolkit showing not just that fertility is low, but where it’s low, why it’s low (entry problem vs family size problem), and what residents say they want but aren’t achieving.

Success Stories

The spatial analysis produces stark patterns. Kyushu and rural regions show elevated desired rates, often reaching 1.7-1.9. Tokyo and Osaka metropolitan areas consistently underperform, clustering around 1.0-1.2. Hokkaido and Tohoku show the lowest rates, while Chugoku and Kyushu show the highest, a west-high, east-low pattern that matches existing social capital research showing similar geographic distributions of community trust and civic engagement.

The variation within regions proves more instructive than the regional patterns themselves. Tokunoshima Town, Kagoshima (徳之島町、鹿児島県) registers Japan’s highest actual fertility rate at 2.25, extraordinary in a developed economy. Municipal surveys in the paper indicate most residents report parents, siblings, friends, and neighbors actively providing childcare support. The social infrastructure for child-rearing exists organically, embedded in daily life rather than delivered through formal programs.

Minamidaito Village, Okinawa (南大東村、沖縄県), another remote island barely accessible and with minimal urban amenities, shows similarly elevated desired rates. The remote island pattern proves statistically significant. Municipalities designated for official remote island promotion programs (離島振興対策実施地域) show desired birth rates 0.12 standard deviations higher than otherwise similar locations, even controlling for income, services, and employment. Designated mountainous areas (特定農山村) show no comparable effect. Both categories face depopulation and receive targeted subsidies, but something about island isolation drives higher desire for children in ways mountainous isolation does not.

Horonobu Town, Hokkaido (幌延町) presents a counterintuitive case. Despite Hokkaido’s generally depressed fertility, this municipality of roughly 2,500 shows relatively elevated desired rates. The distinguishing factor: active recruitment of energy and geological research facilities, creating stable professional employment in a remote location. Young scientists with secure positions adjust family formation plans upward compared to peers in uncertain urban labor markets.

Kasuga Town, Fukuoka (粕屋町) pursued the most aggressive fiscal strategy. Allocating approximately 41% of municipal budget to child welfare spending (児童福祉費), an extreme figure nationally, this bedroom community operates six train stations connecting to Hakata, explicitly positioning itself as family-friendly for metropolitan commuters. This level of spending is roughly triple what most comparable municipalities allocate. Desired birth rates substantially exceed the Fukuoka average.

NPR reporting provides additional detail. Akashi city’s former mayor Fusaho Izumi doubled child welfare spending during his 2011-2022 tenure, funding the increase by cutting public works rather than raising taxes. The fiscal reallocation offended bureaucrats and construction interests but attracted young families at rates that increased tax revenue enough to sustain the programs, a self-reinforcing cycle. Akashi offers free medical care to age 18, free school lunches to 15, free nursery school and kindergarten for families with two or more children, and free diapers for babies under age 1, delivered by midwives who provide professional advice.

Bloomberg found that Nagareyama’s Mayor Yoshiharu Izaki, who took office in 2003, recognized that the town’s baby boomer cohort created an aging crisis the municipality couldn’t financially survive. He implemented station-based childcare pickup and dropoff systems allowing parents to commute to Tokyo while children are transported to daycares, rapid construction eliminating nursery waitlists entirely, and careful cultivation of the town’s identity as “the forest city nearest to Tokyo.” The 30-minute Tsukuba Express (つくばエクスプレス) connection to central Tokyo proved critical. Nagareyama’s data shows 29% of elementary school families have three or more children and only 13% have one child, suggesting the environment enables families to approach their ideal family sizes.

Tokyo’s 23 Wards

Tokyo’s 23 special wards show among the lowest desired rates nationally, averaging around 1.1 despite having the highest incomes in Japan. The wards face binding constraints the research cannot fully measure: housing costs that make family-sized apartments unaffordable, commute patterns that impose severe time poverty, and cultural norms around children in public spaces.

But the comparison with Nagoya is instructive. Nagoya metropolitan area (名古屋都市圏) municipalities show no significant fertility penalty despite similar density and income levels. The difference traces to fiscal priorities. Residual analysis shows Nagoya-area municipalities spend significantly more on social welfare (社会福祉費), elderly welfare (老人福祉費), and child welfare compared to Tokyo or Osaka counterparts, even controlling for tax base. Municipal governments can offset big-city fertility penalties through aggressive family support spending. Tokyo’s wards choose not to, probably because elderly voters who outnumber young families prefer different spending priorities.

What Actually Matters

Child welfare spending dominates everything else. Municipalities that allocate more budget share to child services show dramatically higher desired rates, a 0.47 coefficient that dwarfs all other factors. Kasuga Town pushes this to the extreme at 41% of budget, roughly triple what comparable cities spend. Without municipal income data, though, distinguishing wealth effects from priorities blurs. Richer localities can afford generous programs. Or resource-constrained cities can prioritize differently. The data can’t separate these.

Working close to home shows up strongly too. Places where residents work locally (自市区町村で従業) show desired rates 0.19 standard deviations higher than places where residents commute elsewhere. The statistical effect is larger than anything related to transit access or high-speed rail connections. Tokyo built the Tsukuba Express to connect Nagareyama in 30 minutes, but Nagareyama’s success probably has more to do with Mayor Izaki’s station childcare system than the train itself.

Commute method matters more than commute length. Car commuters show higher desired rates than train commuters (0.30 vs -0.13), not because cars are faster but because they offer flexibility. You can handle an unexpected daycare pickup. You’re not locked into the 5:47 departure. Walking to work also shows loosely positive effects (0.05), though this overlaps with the proximity-to-work finding. If you can walk to work, you’re definitionally working close to home. Walking combines both advantages, proximity and total flexibility, making dual-income family structures operationally feasible.

Kindergarten access (幼稚園) predicts higher desired rates (0.19). So does municipal administrative office accessibility (市区町村機関, 0.18), probably because busy families need to handle tasks without travel. Hospital density (病院) shows modest effects (0.07), though grocery retail (飲食料品小売業) shows none.

Community festivals and events (各種イベントの開催) drive higher desired rates (0.13). General community function (集落機能) shows borderline significance (0.05), but other forms of civic organization show no effects. The mechanism probably runs through social connection and informal childcare support networks. Parents, siblings, friends, neighbors who watch children briefly, provide backup during illness, collectively supervise outdoor play. These networks emerge from repeated neighborhood interaction. Festival culture both reflects and reinforces this.

Agriculture, forestry, fishery employment (第1次産業就業者) correlates with higher desired rates (0.07), though the modest coefficient suggests this represents one factor among many. Remote island designation (離島振興対策) shows positive effects (0.12) even controlling for other factors, suggesting that targeted regional policy can work if designed appropriately.

Living in Tokyo or Osaka metros (東京都市圏・大阪都市圏) lowers desired rates beyond what employment, income, or services explain. Both show identical -0.26 coefficients. Big-city residence itself suppresses desire for children. Nagoya shows no such penalty, suggesting fiscal priorities can offset urban constraints. University presence (高等教育機関) shows negative effects (-0.12), possibly reflecting career timeline delays or age composition effects. Railway commuting drives lower rates, the inflexibility problem noted above.

Budget Priorities

Beyond child welfare spending, the analysis shows how different budget allocations link to desired birth rates. The patterns suggest municipalities face tradeoffs:

Strong positive link:

• Child welfare spending: +0.47

Moderate positive link:

• Agriculture, forestry, fishery spending (農林水産業費): +0.14

Loose positive link:

• Social education spending (社会教育費): +0.04

Moderate negative link:

• General social welfare spending, non-child: -0.10

Loose negative links:

• Livelihood protection spending (生活保護費): -0.08

• Commerce and industry spending (商工費): -0.08

• Fire service spending (消防費): -0.08

• Labor spending (労働費): -0.07

• Urban planning spending (都市計画費): -0.06

• Health and physical education spending (保健体育費): -0.06

The negative links for general social welfare and livelihood protection suggest municipalities facing greater poverty struggle to maintain high desired birth rates. The negative links for commerce, urban planning, fire services, and labor spending suggest municipalities forced to allocate substantial resources to economic development, infrastructure, and emergency services face tradeoffs that constrain family support spending.

The evacuation zone designation (帰宅困難区域) for Fukushima-related displacement shows negative effects (-0.04). Nuclear family household share (核家族世帯割合) shows no significant relationship. The widespread assumption that multi-generational households enable higher fertility finds no confirmation in preference data.

For Families Deciding Where to Live

The research translates to concrete considerations for dual-income families weighing location choices.

Proximity to work matters more than transit access. Municipalities where most residents work locally show 0.19 standard deviations higher desired rates than commuter towns. If you must commute, car flexibility matters more than shorter train rides. The ability to handle unexpected pickup or route changes makes dual-income parenting operationally feasible.

Municipal budget priorities predict family-friendliness better than city size. These priorities are measurable through public documents. Localities allocating substantial shares to child welfare, not just elderly care or infrastructure, show dramatically higher desired rates. Kasuga Town’s 41% allocation represents an extreme, but municipalities above 25-30% consistently outperform peers.

Community matters, but in specific ways. Festival culture and local events correlate with higher desired rates. General civic organizations don’t. This reflects informal childcare networks that emerge from repeated neighborhood interaction.

The urban penalty isn’t universal. Tokyo and Osaka show large fertility penalties, but Nagoya doesn’t, because Nagoya-area municipalities spend more aggressively on family support. If considering urban locations, municipal fiscal priorities matter more than density itself.

What the Research Cannot Show

The authors construct two scenarios around marriage intentions. “Good” (89.3% of unmarried women “intend to marry eventually” いずれ結婚するつもり) and “Bad” (only near-term marriage intentions: “within one year” 一年以内に結婚したい or “with ideal partner within one year” 理想の相手なら一年以内に結婚してもよい). The 89.3% figure appears high compared to a 2021 Cabinet Office survey finding only 60% marriage intentions, probably reflecting social desirability bias. The “Bad” scenario captures more genuine intentions but is analytically unhelpful. No municipalities reach 1.8.

The research lacks municipal-level income data, a glaring omission the authors acknowledge. The analysis cannot directly measure economic security. Housing costs receive no measurement despite probably being the binding constraint in metropolitan areas. The cross-sectional design prevents causal claims. The 2015 data predates COVID-19 and remote work normalization. If commuting friction suppresses desire for children, flexible work arrangements should theoretically elevate desired birth rates, but we still have limited studies on this.

National Policy Misses What Matters

The Japanese government’s 2023 “Children’s Future Strategy” emphasizes income support: child allowances, parental leave, subsidized childcare. Former Prime Minister Kishida pledged to double child care spending by the early 2030s, calling it “the last chance to reverse the declining birth rate trend.” An Asahi Shimbun poll found 73% of respondents don’t believe it will work. Three decades of similar initiatives producing nothing justifies their skepticism.

The regression shows why. Time poverty from commuting, spatial constraints from housing, social infrastructure from community networks, and municipal spending priorities matter as much as income support. These require local control: zoning, transit, public space, budgets. National policy barely touches them.

Akashi’s mayor cut public works to fund child welfare. Nagareyama built station childcare systems that make dual-income parenting physically possible. Most municipalities don’t do this. Elderly voters outnumber young families. Construction interests want their budgets. No national policy can force municipal spending shifts when local incentives point elsewhere.

The data has holes. No municipal income data exists. Housing costs get no measurement. The 2015 timing predates remote work. The cross-sectional design can’t prove causation.

What This Shows

The 143% variation between municipalities (0.81 to 1.97) isn’t measurement error. Shaw’s research shows TFR conflates two (and maybe even more) independent processes. Using it as your primary metric means you are flying blind. Policy designed with single or couple metrics reduce the chance for success.

The local pattern repeats. Akashi hit 1.65 versus national 1.3. Nagareyama reached 1.50 versus 1.26. Tokunoshima sustains 2.25 through organic networks. Child welfare spending dominates every other predictor (0.47 coefficient). Nagoya shows no urban fertility penalty despite similar density to Tokyo and Osaka because Nagoya municipalities spend aggressively on family support.

Local governments control every lever here: budgets, commute patterns, housing policy. They alone can’t get us above replacement level, but they are part of the solution to get us there, provincial, state, prefecture, and national level governments need to do their part. The evidence accumulates that they can move the needle. Akashi and Nagareyama aren’t miracles. They’re proof.

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In the first three articles, we’ve seen how Shaw’s decomposition reveals two independent crises (Are We Measuring Fertility Wrong?), how economic shocks permanently collapse motherhood rates (Why economic (especially energy) shocks permanently lower fertility rates & total maternal rates (TMR)?), and how America’s inequality temporarily masked the problem through rising CPM (Why Rising Family Size Temporarily Hid America’s Motherhood Decline (1980-2016)). Now we examine the fourth piece: why CPM erodes relentlessly in most developed nations.

Shaw’s data reveals a striking pattern across 33 countries: while Total Maternal Rate (% of women who become mothers)(TMR) shows sharp (even crisp), crisis-driven breaks (all 47 Japanese prefectures simultaneously in 1974, US collapse in 2008), Children per Mother (CPM) declines gradually and continuously regardless of economic conditions. Italy dropped from 2.10 to 2.02 since the 1980s. France fell from 2.40 to 2.28, stable until 2010 then declining. The United Kingdom went from 2.35 to 2.23 since the 1990s. Japan declined from 2.20 to 2.13 over the same period. The United States increased from 2.39 to 2.63, covered in third article.

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Shaw describes CPM as showing “remarkably stable” patterns with “tight clustering and limited variability.” Not unchanging, but exhibiting gradual trends rather than crisis-driven shocks. What drives slow, continuous CPM erosion independent of the economic shocks that devastate TMR?

Mario Draghi’s April 2024 admission provides part of the answer: “Especially after the crises, we made a deliberate effort to suppress wage growth to increase external competitiveness.” European governments ensured families couldn’t survive on one income, forcing both parents into full-time work, then watched fertility collapse.

Why Statistical Independence Matters for Policy

Shaw’s finding that TMR and CPM are statistically independent (knowing one tells you nothing about the other) has been missed for decades by policymakers.

Traditional thinking assumed fertility decline is one crisis requiring one solution. But independence shows these are two crises needing different interventions. Economic recovery restores TMR without reversing CPM erosion.

The 2008 Financial Crisis demonstrates this. TMR collapsed sharply, the US going from 76.1% to 69.4%. CPM continued its gradual trend, rising from 2.39 to 2.63. Crisis affects family formation (employment, partnership, confidence) without touching constraints on expansion (time poverty, biology, cumulative burdens).

TMR responds to crisis-sensitive variables: employment stability collapses during recessions, partnership formation freezes during uncertainty, economic confidence crashes during shocks, and marriage market conditions get scarred by instability. CPM responds to crisis-insensitive forces: biological windows narrow continuously with maternal age, time and economic constraints build gradually, work-family compatibility erodes through policy drift, and geographic proximity to support disperses slowly.

Economic crises devastate variables affecting whether people become parents. Mothers with one child contemplating a second are already partnered, employed enough to have afforded the first child, committed to parenthood. Their decision depends on capacity for additional children: biological time remaining, accumulated resources, available time. These erode gradually rather than collapsing suddenly.

The Gap Between Desired and Achieved Fertility

Eva Beaujouan’s 2023 comprehensive analysis documents a critical finding: people aren’t choosing to have fewer children. They’re failing to have the children they want.

Women starting childbearing at age 25 achieve 96% of their desired fertility. By age 30, this drops to 90%. By age 35, women achieve only 75% of what they intended. The gap isn’t about changing preferences. It’s about accumulating constraints that prevent people from reaching goals they hold.

At age 30, women have a 75% chance of conception within one year and 85% achieve a second birth. By age 35, conception chance drops to 66% and only 62% achieve a second birth. The biological window narrows independent of intention.

Beaujouan documents the mechanism: “Fertility delay implies that people are spending a shorter period trying to have children” combined with biological efficiency declining exponentially. Each year of delay doesn’t just postpone fertility. It mathematically reduces maximum achievable family size.

This pattern repeats! The Dutch study captured women’s fertility hesitation centered not on whether they wanted children but on logistics: “impossibility of managing pregnancy while maintaining careers.” Dutch women live in one of Europe’s most generous welfare states yet cited this impossibility even as that welfare state faced cuts. The Netherlands provides an example of gradual policy degradation: childcare subsidies reduced 3% in 2012 (leading to 72,000 fewer children in formal childcare by 2014), healthcare co-payments increased in 2010, public sector wages frozen 2004-2005. These represent selected examples among broader retrenchment trends. The desire exists. The structural capability was being reduced.

The question isn’t “How do we convince people to want more children?” The question is “Why can’t people have the children they already want?”

France: What 40 Years of Success Reveals About Removing Barriers

France maintained CPM of 2.30-2.40 from the 1970s through 2010. Nearly 40 years while Italy and UK declined. This wasn’t accident.

Real wage growth enabled single-income viability. Universal cash transfers scaled with family size. Universal childcare operated 6am-7pm, matching work schedules rather than creating gaps parents had to cover. The 35-hour workweek provided genuine time restoration. Housing policy enabled family proximity to work. Children were integrated into public spaces. Cross-party political commitment was sustained for 58 years.

Lyman Stone’s review documented that cash transfers successfully increase second+ births. France generated 5-10 million additional people over 80 years through sustained investment.

France’s success proves people will have additional children when barriers are removed. This wasn’t about convincing French couples to want larger families. The policies enabled people to reach fertility goals they held.

Then the erosion began. The Socialist government introduced means-testing in 2014. The study showed when benefits were eliminated, women increased work by 4.2 additional hours weekly and men 2.1 hours weekly. This shifted time toward wage labor when benefits no longer covered childcare costs. France’s CPM decline became detectable around 2019, roughly five years after the policy change.

Macron’s presidency (2017-2024) accelerated the shift. France remained OECD’s highest spender (over 57% GDP) without addressing time poverty. Labor “flexibility” meant easier firing, not schedule autonomy. The zero net land development law by 2050 made it illegal to develop land unless existing development was demolished. Nation-wide rent controls proceeded without supply expansion. The result: housing costs eats a higher % of income, geographic dispersion accelerated, and 75-90 minute commutes became normal. Not to mention the burning of YIMBY credibility in France as Macron represents the “centrists”.

CPM fell from 2.30 to 2.28 between 2010 and 2024, and French TFR went from 2.0 to 1.66.

Sustained comprehensive support prevented CPM erosion for four decades by enabling people to achieve their fertility intentions. Policy changes to a previously functional system prevented people from reaching their goals, and what’s worse it seems that nothing was gained because of it..

Taiwan HSR: Remove the Barrier, Fertility Increases Immediately

Taiwan’s 2007 high-speed rail (Yeow Hwee Chua, Pei-Syuan Lin, and Tien Foo Sing) provides the cleanest natural experiment. No cultural campaign. No financial incentives. Just infrastructure removing a logistical barrier.

The HSR connected Taipei’s expensive job market with affordable southern cities, cutting travel time from 4.5 hours to 90 minutes. Couples previously separated by economic necessity could now live together while accessing both Taipei employment and Kaohsiung housing affordability.

The fertility response was immediate and substantial. Couples previously separated showed +6.5% fertility. First births increased 16.2%. Later births rose 6-8%.

This wasn’t about changing preferences. Geographic separation made parenthood difficult. One partner in Taipei for work, the other in Kaohsiung for affordable housing, seeing each other occasionally. Managing one child under these conditions was difficult. Contemplating a second was unrealistic.

The HSR removed the geographic barrier preventing families from having the children they contemplated. Within months, fertility increased.

The Taiwan finding is critical because it proves the constraint is structural, not cultural or preferential. No government campaign told these couples to value family more. No financial incentive changed the economics. Pure infrastructure enabling proximity was sufficient.

For mothers contemplating a second child, grandparent availability often determines feasibility. The HSR reduced Taipei-Kaohsiung from impossible for routine support (4.5 hours) to feasible for weekly help (90 minutes). Grandparents who wanted to help their children raise families could suddenly do so. Infrastructure made it possible.

With one child, couples managed 4.5-hour separation with difficulty, seeing each other weekends. With a second child, that arrangement becomes impossible. Two children of different ages with different needs require coordination that weekend visits can’t provide. The HSR enabled existing fertility intentions.

South Korea’s 2019 study quantified the same pattern. Same municipality residence shows 21.6% higher birth odds. 60-minute commute shows 28% lower odds. 90-minute commute shows 41% lower odds.

Norway: Work Rigidity as Binding Constraint

Norway’s March 2020 lockdown created another unintended natural experiment, triggering a 10% birth rate increase nine months later. Employed women showed +10% fertility while unemployed women showed +0% fertility. Women in rigid occupations showed +15.2% fertility, a 152% stronger effect.

The mechanism reveals the constraint. Unemployed women were home with no fertility increase. They already had time. Employed women gained schedule control and fertility jumped. These weren’t women who suddenly decided they wanted children. These were women constrained by rigid work schedules preventing them from managing additional children.

Women in the most inflexible jobs (teachers, nurses, office workers) showed the strongest responses. These professionals, theoretically best positioned to afford children, were most constrained by work rigidity. The lockdown removed the structural barrier.

Mothers with one child were already employed and managing. The barrier to second child was the incompatibility between rigid work schedules and managing two children. When work rigidity disappeared, these employed mothers (who already had resources, partnerships, and one child) could contemplate additional children.

Norwegian women maintained reduced working hours through 2024, four years after lockdowns. Firms discovered pre-pandemic rigid scheduling was unnecessary. The fertility increase persisted because the barrier removal persisted.

The pattern repeated in Singapore (Senhu Wang and Hao Dong), where hypothetical reduced working hours increased fertility intentions 79% among employed, partnered women. Professionals, theoretically best positioned to afford children, showed the strongest responses. Work rigidity prevented achievement of intentions.

Norway’s experiment isolates work rigidity as a specific constraint on family size people contemplate. The 10% fertility increase when rigid work disappeared reveals how much current work arrangements suppress births people would otherwise have.

The Biological Constraint on Wanted Fertility

Compare a mother in 1980 versus 2020 contemplating a second child. In 1980, single-income families were viable. Father’s wage was sufficient for a family of 3-4, mother’s time was available for childcare. The decision was “Do we want another child?” By 2020, the dual-income trap had closed. Combined wages are barely sufficient for family of 3, both parents’ time is consumed by mandatory 40-hour weeks. The decision became “Can we economically and logistically survive another child?”

The change isn’t about desire. It’s about feasibility.

Denmark and Germany’s unemployment study (Kreyenfeld & Andersson, 2014) reveals how economic constraints affect fertility timing. Less-educated young unemployed women showed 50% higher fertility than employed peers. They had time but needed money. Highly educated unemployed women showed 20% lower fertility. They had money but valued career progression and delayed to establish themselves professionally.

The highly educated delay childbearing for career establishment, then face biological constraints when attempting the larger families they contemplated. They’re forced into smaller families by the interaction between career timing pressures and biological windows.

The study documented childcare matching work schedules. Denmark provided availability from 6am-6pm matching actual work hours, with no benefit cliffs forcing additional work hours. This enabled mothers to have additional children by removing the logistical gap where work requires presence but childcare is unavailable.

But Denmark’s celebrated flexicurity model was eroding through gradual cuts. In 2010, responding to rising unemployment costs, Denmark cut unemployment benefits from four years to two years, one of the most controversial reforms in recent Danish history to the point that they temporarily rolled parts of it back in 2013 because it turned out it wasn’t a good idea to limit benefits in wake of the Great Recession.

The reform required workers to have 52 weeks of employment to regain benefits, doubled from the previous 26 weeks. By 2013, over 30,000 Danes annually ran out of unemployment benefits, compared to only a few thousand previously.

There is a nice and rich research pile on how unemployment benefits protect both income and fertility rates. Considering how others are trying to sell Danish “flexicurity” to their own counties, this doesn’t bold well.

Not to mention, modern partnership patterns compound biological constraints. Increasing numbers experience short childless unions that dissolve before childbearing begins, consuming prime fertility years. In Spain, median age at first stable union rose from 23 to 29. But 40% of these unions dissolve within 5 years if childless. Women re-partner around 32-33, beginning childbearing at ages where second birth probabilities already decline.

These women don’t want smaller families. They wanted stable partnerships earlier, faced instability, and by the time they find stability, biological windows have narrowed. The fertility gap between desired and achieved widens with each delay.

As TMR falls and average age at first birth rises simultaneously, that’s going to lower TFRs. Now adding to the independent downward pressure on CPM, you have women who become mothers later have narrower biological windows for subsequent births regardless of their preferences. Delaying first birth from 25 to 30 reduces maximum achievable family size from 2.5 children to 2.2 children on average. Not because women at 30 want fewer children than women at 25. Because biology constrains achievement of existing fertility intentions.

Draghi’s Wage Suppression and the Dual-Income Trap

Draghi’s admission exposes policy choices: “Our real wages failed to keep pace even with our slow productivity, while US real wages rose 9 percentage points more than wages in the euro area. We pursued a deliberate strategy of trying to lower wage costs relative to each other, and, combined with procyclical fiscal policy, the net effect was only to weaken our own domestic demand and undermine our social model.”

The policy implementation was systematic. In the United Kingdom, real wages fell 8-10% since 2008 and remain 2% lower in 2024 than 2010. LSE research shows UK had worst wage stagnation since records began in the 1860s. Greece cut minimum wage 22% and public sector pay 15% total, while private sector wages fell 12% from 2010 peak. Ireland cut public sector pay 15% average between 2009-2010. Spain cut public employees’ wages 5% and froze retirement benefits while youth unemployment exceeded 50%. Italy’s real wages stagnated for 20 years after abolishing automatic wage indexation in 1992, leaving average salaries 45% below Germany’s.

Wage suppression didn’t change what families wanted. It changed what they could afford. Many couples prefer one parent available for childcare, especially when children are young. Wage suppression made that choice unaffordable. Both parents must work full-time, creating time poverty that prevents additional children couples would otherwise have.

The income-fertility relationship shifted. In the Netherlands (van Wijk, 2024), high-income men are 3.11x more likely to become fathers than low-income men, up from 2.38x in 2008. Among women the ratio is 2.44x, up from 1.63x. Sweden (Kolk, 2021) shows fertility now rises monotonically with lifetime income for men, with childless men earning 40% less lifetime income than fathers of 3+ children.

This isn’t because poor people don’t want children. It’s because wage suppression prevents them from affording the children they contemplate. Wealthy people can still have larger families because they escape the dual-income trap. Everyone else is forced into smaller families than they intend.

Sweden’s pattern is particularly telling. The country embarked on sustained welfare retrenchment from the 1990s through 2010s. A 2020 study documented how Sweden cut social expenses, privatized its pension system, and made significant cuts to unemployment benefits. After two decades of continuous decline in income replacement and rising stringency in qualifying conditions, the country showed decreasing healthcare provision with higher eligibility conditions. Public sector wages were frozen in 2004-2005. Sweden became a dual-earner society as single-income viability eroded through accumulated cuts. Despite maintaining high government spending, Sweden saw the OECD’s fastest-growing inequality measured by percentage change from its previously exceptional equality baseline, with poverty rates rising most among single-adults. Starting from OECD’s lowest inequality, Sweden experienced the steepest relative increase while remaining more equal than most countries.

Even in Sweden, once held up as proof that comprehensive welfare enables fertility, the policy direction moved toward requiring dual employment while making additional children harder to afford through gradual benefit reductions. The 1990s crisis affected Sweden’s universalistic welfare state, weakening it substantially through successive reforms. The impact on families contemplating additional children was clear: the safety net that had enabled risk-taking (having another child) eroded cut by cut, precisely as dual employment became mandatory.

German Job Destruction and Employment Security

German researchers (Chen Luo and Ewa Jarosz) tracked 400 regions across 13 years, finding job destruction reduced fertility 40% more than job creation increased it. Male manufacturing workers faced the strongest effects. When factories closed, birth rates plummeted. When new positions opened, fertility barely budged.

The asymmetry reveals something about security versus opportunity. Couples want economic stability before having additional children. Job creation provides potential income but doesn’t eliminate the uncertainty scarring from previous instability. Job destruction creates immediate constraints mothers feel when contemplating additional children.

These mothers don’t want smaller families. They want economic security sufficient for larger families. Job destruction prevents them from achieving what they contemplated.

Time Theft Through Benefit Cuts

Vanhuysse, Medgyesi, and Gál’s 2023 European study quantifies the burden shift. Parents contribute 2.66 times more total transfers than non-parents: 27% visible in public accounts, 49% invisible family labor, 24% private spending.

Governments combined wage suppression with benefit cuts. A few (more) early examples as governments responded to the Great Recession, we have the United Kingdom, child benefit was withdrawn from families with higher-rate taxpayers from January 2013, and IFS shows families with children lost £2,200/year average from tax and benefit changes since 2010.

Parents didn’t suddenly want to spend less time with children. Benefit cuts required them to work more hours to compensate. Time that would go to caring for additional children gets extracted for wage labor. The intention to parent remains. The time to do so doesn’t.

Nordic Countries: Gradual Erosion Through Accumulated Cuts

Nordic countries maintained higher CPM longer than Southern Europe. Denmark went from 2.40 to 2.20 (slower than Italy’s drop from 2.10 to 2.02). Sweden declined from 2.35 to 2.25 (slower than UK’s fall from 2.35 to 2.23). Norway dropped from 2.50 to 2.30 while maintaining a higher baseline.

Nordic countries show CPM decline roughly half the Southern European rate, around 0.005 annually versus 0.010-0.012. But this slower erosion doesn’t reflect policy stability. Nordic countries have progressively converged toward EU average in social security spending through accumulated cuts. Unemployment benefit schemes experienced significant retrenchment, gradually converging toward the European mean through sustained reduction.

The examples documented above (Denmark’s unemployment benefits from four to two years exhausting 30,000 people annually, Sweden’s welfare cuts producing OECD’s fastest-growing inequality from an exceptionally equal baseline, Netherlands’ childcare subsidy reductions and healthcare co-payment increases) represent selected instances among hundreds of smaller policy changes. Each cut is defended individually as necessary fiscal prudence. Collectively, they’ve transformed systems that once enabled achievement of fertility intentions. The process continues today.

The irony is that these cuts may not save money. When Denmark cut unemployment benefits duration, over 30,000 people annually exhausted benefits and required other support. When Netherlands cut childcare subsidies, 72,000 fewer children attended formal childcare, but this didn’t eliminate the care need or the cost. When healthcare provision was cut while tightening eligibility across Europe, research documented 1.5 million extra people with unmet healthcare needs since the crisis began. The cuts shift costs rather than eliminating them: from public budgets to families, from visible spending to invisible family labor, from preventing problems to managing crises.

Despite retrenchment, Nordic countries maintained some advantages that Southern Europe lost entirely. Wage growth remained more robust than Southern Europe’s collapse. While Draghi admitted deliberate wage suppression across the Eurozone, Nordic currencies (Norway, Sweden) or special arrangements (Denmark) allowed somewhat more independent monetary policy. Single-earner families, while increasingly difficult, remained possible longer as erosion was gradual rather than sudden. Geographic density enabled proximity. Nordic cities, though facing housing cost pressures, avoided the extreme dispersion seen in France or Spain. Work culture retained more flexibility than Southern European or Anglo systems despite formal retrenchment.

But even these remaining advantages couldn’t prevent CPM erosion. The biological constraints from delayed childbearing affect all countries. The work-family tensions remain even in better systems. The policy direction (toward retrenchment through accumulated cuts rather than expansion or maintenance) matched the rest of Europe.

The Nordic pattern reveals that comprehensive support from a high baseline slows CPM erosion significantly. The 0.005 annual decline versus 0.010-0.012 in Southern Europe shows policy choices matter. Starting with more support and cutting it gradually produces slower erosion than starting with less and cutting aggressively. But both produce erosion. Nordic countries are converging toward the same 2.0-2.2 CPM equilibrium as the rest of Europe. The process is gradual (cut by cut), ongoing (still happening), and questionable economically (shifting rather than eliminating costs). Without policy reversal, they’ll reach the same destination as Southern Europe, just more slowly.

Physical Exclusion and Coordination Problems

The dual-income trap creates multiplicative constraint. Parents must be in child-free spaces 40+ hours weekly, requiring childcare. Childcare closes at 5pm while work demands presence until 6-7pm.

With one child, parents cobble together solutions through grandparent coverage, leaving work early, or after-school programs. With two children, these solutions often don’t scale. Grandparents struggle managing two different-aged children. After-school programs have different pickup times. Career impact of leaving early every day becomes severe.

Modern economies systematically exclude children from adult spaces. Restaurants discourage families, offices prohibit children, shops lack accommodation, and public transport resists strollers. Parents who would prefer occasionally integrating children into adult activities can’t. They’re forced into constant childcare arrangements that become increasingly difficult for multiple children.

Iceland’s Third Birth Surge Among Educated Mothers

Iceland (Arnalds et al., 2025) showed third births jumped 38% among tertiary-educated women during lockdowns. One woman explained: “I thought it rather nice to be pregnant and not be able to do anything when you cannot do anything anyway.”

This specifically boosted progression from second to third child among wealthy mothers. The pandemic temporarily removed barriers by eliminating commutes and reducing obligations. Mothers who had contemplated third children but couldn’t manage them suddenly could.

The Iceland finding confirms the Norway pattern: work rigidity and time poverty prevent births women contemplate. When those barriers temporarily lifted, fertility increased specifically among women who had been constrained. The selectivity reinforces that wealthy mothers already had the resources and contemplated additional children. They needed the barriers removed.

Why CPM Erosion Differs From TMR Collapse

TMR policies could theoretically help at any age through improving marriage markets or reducing economic instability. CPM interventions face biological deadlines and escalating constraints that limit when barriers can be removed.

The first to second child transition (ages 27-35) occurs while biological windows remain relatively wide but requires immediate barrier removal. The second to third child transition (ages 32-40) happens as biological windows narrow significantly and requires removing multiple barriers simultaneously.

Shaw’s data reveals countries converging toward CPM of 2.0-2.2 regardless of starting point. This isn’t an equilibrium of desired fertility. It’s an equilibrium of achievable fertility under current barriers. Italy has reached 2.02. France sits at 2.28, declining toward 2.2 as barriers accumulate. Nordic countries range from 2.20-2.30, showing slow decline toward the same equilibrium.

The convergence suggests current barriers constrain achievement to around 2.0-2.2 even when desired fertility is higher. Beaujouan’s data confirms this: women starting childbearing at 25 achieve 96% of desired fertility. By age 35, only 75%. The gap widens as barriers accumulate.

What Policy Changes Would Remove Barriers

France between 2010-2024 proved that re-imposing barriers reduces fertility among people whose intentions haven’t changed. Taiwan HSR proved removing logistical barriers immediately increases fertility—16.2% for first births. Norway proved removing work rigidity immediately increases fertility—10% overall, 15.2% in rigid occupations.

The lesson: people want more children than they’re having. Remove the barriers, and fertility responds immediately.

Slowing erosion requires ending wage suppression that forces both parents into full-time work. Default flexibility rather than rigidity. Remote work rights eliminating commute time. Earlier childbearing support when fertility windows are widest. Housing policy that allows building where families can afford proximity to work and extended family.

The Nordic evidence shows comprehensive support slowed erosion to 0.005 annually, roughly half the Southern European rate, despite decades of gradual cuts.

Bottomline

Shaw’s CPM documentation reveals what policymakers have missed: barriers prevent people from having the children they contemplate.

France removed barriers 1970-2010 and CPM stayed stable at 2.30-2.40 for forty years. Then France re-imposed barriers 2010-2024 through means-testing and zero-net-development. CPM eroded to 2.02. Fertility intentions hadn’t changed. Achievement couldn’t keep pace.

The mystery’s solution reveals two parallel crises. During economic shocks, TMR collapses as people cannot enter parenthood. Between shocks, CPM erodes as barriers prevent people from having additional children they contemplate.

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Organizations worldwide grapple with post-pandemic work arrangements. New research demonstrates that the mental health benefits of working from home hinge on whether employees can choose it freely rather than having it imposed upon them. The findings explain why previous studies on remote work and wellbeing have yielded such conflicting results.

Mental health issues impose economic burdens through reduced productivity, increased healthcare costs, and diminished workforce participation. Businesses navigating tight labor markets need to understand how work arrangements affect employee mental health.

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Big picture

The paper (Working from Home and Mental Health: Giving Employees a Choice Does Make a Difference) by Uwe Jirjahn and Cinzia Rienzo analyzed data from Understanding Society, a comprehensive UK household panel survey.

The study examined over 106,000 observations from nearly 40,000 employees aged 16-64, tracking both job-related mental health (anxiety and depression at work) and overall mental health problems using the validated General Health Questionnaire. The analysis covers 2010 to 2024, controlling for occupation, firm size, education, performance pay, commuting time, family structure, and regional variation.

What they found

The research distinguishes between three employee groups: those who use work-from-home arrangements, those who have the option available but don’t use it, and those for whom remote work isn’t available.

Before and after the pandemic, both using remote work and having it available as an option were associated with improved mental health outcomes. Employees who worked from home reported lower overall mental health problems, reduced job-related depression, and decreased job-related anxiety compared to those without any remote work option.

Even employees who had remote work available but chose not to use it showed better mental health than those lacking the option entirely. Simply knowing flexibility exists provides psychological benefits.

During the COVID-19 crisis (March 2020 to July 2021), the picture reversed. When government lockdowns eliminated choice and mandated remote work, using work-from-home arrangements became associated with worse overall mental health. Employees who worked from home during lockdowns reported increased mental health problems rather than the improvements seen in normal periods.

The pandemic period itself showed no direct effect on mental health once the interaction with remote work was accounted for. The lockdowns and enforced remote work, rather than the pandemic itself, drove the mental health deterioration.

Previous research underestimated the benefits

Most studies compared employees who work from home against those who don’t, creating a reference group that lumps together people who have the option but choose not to use it with people who have no option at all.

When the researchers replicated this conventional approach, the positive effects of using remote work appeared much smaller or disappeared entirely. For overall mental health problems, the estimated benefit dropped by approximately 49 percent and lost statistical significance. For job-related depression, it fell by about 20 percent.

Existing research may underestimate remote work’s benefits by failing to account for the psychological value of simply having flexibility available.

The gender stuff

Women working full-time who both used remote work and had it available showed better job-related and overall mental health. All measures improved: anxiety, depression, and overall mental health problems.

Women continue to bear disproportionate responsibility for family and household management even when employed full-time. Remote work helps them reconcile these competing demands. During the pandemic, women experienced the negative reversal: the use of work-from-home became associated with increased mental health problems as the elimination of choice and intensification of caregiving demands (including school closures) overwhelmed remote work’s typical benefits.

Men working full-time who used remote work reported lower job-related anxiety and depression, but using remote work showed no association with their overall mental health during normal periods.

Having remote work available (without using it) was associated with better overall mental health for men, a benefit that vanished when they actually worked from home regularly.

Men appear to overestimate remote work’s benefits for their overall wellbeing, perhaps not anticipating that working from home would require taking on additional family responsibilities. They underestimate remote work’s benefits for job-related wellbeing, discovering through actual use that it reduces workplace anxiety and depression.

Men cannot fully assess remote work’s qualities before trying it. Women appear to more accurately anticipate both the work-related and personal benefits.

Why choice matters

Employees have different preferences. Remote work involves both demands (blurred work-life boundaries, potential isolation, reduced social support) and resources (reduced commuting time, fewer workplace interruptions, greater ability to integrate work and family). When employees can choose, those who benefit self-select into remote work while those who would experience net disadvantages opt out. Forced remote work eliminates this beneficial matching.

The need for self-determination and autonomy is a fundamental human motivation. Giving employees control over their work arrangements enhances their sense of self-determination, which independently contributes to wellbeing regardless of which option they choose.

Organizations that offer remote work as an option signal that they care about employee wellbeing. This contributes to a work climate characterized by procedural fairness, influencing employees’ beliefs about whether workplace demands are threatening or manageable.

Implications

Policy design: Frame remote work as an option rather than a mandate. The pure availability of flexibility provides mental health benefits even for employees who choose not to use it regularly. The cost of offering the option may be lower than the cost of widespread use (in terms of coordination challenges), while still providing psychological benefits.

Talent management: The mental health benefits of having remote work available help attract and retain talent, particularly female employees and those who value work-life balance.

Gender differences: The gender differences suggest value in tailored approaches. Women may benefit from explicit messaging about work-life balance support. Men might benefit from trial periods to help them accurately assess fit.

Hybrid arrangements: The positive effects when choice existed versus the negative effects during mandated lockdowns suggest that hybrid arrangements (where employees have control over when they work remotely) may optimize outcomes better than either full-time remote or full-time office mandates.

Crisis management: When remote work becomes enforced rather than optional, its mental health effects can reverse. Organizations facing future disruptions should consider how to preserve employee autonomy even in constrained circumstances.

By the numbers

Key findings:

• Using remote work reduced overall mental health problems by 0.25 points before/after pandemic

• Using remote work reduced job-related depression by 0.20 points before/after pandemic

• Remote work availability alone (without use) reduced overall mental health problems by 0.27 points

• During pandemic, using remote work increased overall mental health problems by 0.21 points (net effect)

• Previous studies underestimated benefits by 10-50% by not accounting for availability

Full-time women:

• Using remote work reduced overall mental health problems by 0.59 points

• Using remote work reduced job-related depression by 0.30 points

• Availability alone reduced overall mental health problems by 0.33 points

Full-time men:

• Using remote work reduced job-related anxiety and depression

• Using remote work showed no effect on overall mental health

• Availability alone reduced overall mental health problems by 0.35 points

Sample:

• 106,932 employee observations from 38,706 individuals

• 2010-2024 study period

• 9.1% regularly used remote work; 9.3% had it available but unused

• 81.6% had no remote work option

Bottomline

The mental health effects of remote work depend on whether it’s offered as genuine choice rather than mandated. The pure availability of flexibility, even when unused, provides mental benefits by signaling organizational support and enhancing employee autonomy.

The reversal of effects during COVID-19 lockdowns provides real-world validation of this idea. Organizations designing post-pandemic work policies should maximize employee choice over work arrangements. Offering options provides value even for those who don’t use them. Remote work affects men and women differently due to persistent household responsibility “differences”.

The path forward isn’t about mandating remote work or demanding office presence, but about providing genuine choice and giving employees more “free will” to make decisions that optimize their own wellbeing and performance.

Note : Expect tomorrow’s post be a bit of a read (6000+ words and counting)

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Pronatalism faces a peculiar contradiction with its image (doesn’t really help is that who or what is a pronatalist is very loosely defined). Its own researchers produce a LOT of evidence that structural economic barriers determine whether people have children. Yet some of the more visible debates (like those in all mostly online movements) seem esoteric or even crunchy. It reflects the movement’s fragmented nature. Mostly online except for pockets of certain cities and a handful of countries, pronatalism effectively is civil or semicivil flame wars to outsiders. There are groups like who is trying to bring pronatalism IRL, but that’s more of an exception than the rule to most outsiders.

Pronatalistic research, especially in the 2024-2025 pipeline, is a completely different story. Just to give you a sample (God knows I can make this post so much MUCH longer) is Norwegian lockdown data revealed how workplace flexibility affects fertility decisions. German employment studies tracked how job security (not income) drives family formation. Japanese labor market analysis showed the fertility gap between precarious and stable employment. Taiwan’s train investments demonstrated how reducing geographic separation between couples increases births.

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These studies (out of many I might add) consistently point to the same conclusion: workplace rigidity, housing costs, and economic concerns/troubles are what actually prevent people from having children. The evidence is there. It just needs to be the focus.

Norway’s Accidental Experiment

Norway’s March 2020 lockdown triggered a 10% birth rate increase nine months later. The cause wasn’t pandemic proximity or boredom. Unemployed women showed zero fertility increase. The paper (The impact of flexibility at work on fertility by Bernt Bratsberga and Selma Walther) entire effect came from employed women, particularly those in rigid occupations who gained schedule control for the first time.

Women in the most inflexible jobs showed fertility responses 152% stronger than those already working flexibly. The pattern repeated in Singapore (Flexible Working Arrangements and Fertility Intentions: A Survey Experiment in Singapore by Senhu Wang and Hao Dong), where hypothetical reduced working hours increased fertility intentions 79% among employed, partnered women. Professionals, theoretically best positioned to afford children, showed the strongest responses.

These weren’t marginal adjustments. Norwegian women maintained reduced working hours and avoided overtime through 2024, four years after initial lockdowns. The persistence suggests firms discovered that pre-pandemic rigid scheduling was unnecessary, not that workers accepted productivity losses for flexibility.

The implication is straightforward. The 40-hour workweek with fixed scheduling and mandatory physical presence prevents parenting. Not optimal parenting or natural parenting, but any engaged parenting whatsoever.

Job Loss as Birth Control

German researchers (Job creation, job destruction, and fertility in Germany by Chen Luo and Ewa Jarosz) tracked 400 regions across 13 years, finding job destruction reduced fertility 40% more than job creation increased it. Male manufacturing workers faced the strongest effects. When factories closed, birth rates plummeted. When new positions opened, fertility barely budged (releativly).

Japan (Career advancement and fertility intention among working women in Japan: a cross-sectional survey study by Honami Yoshida) demonstrates the same dynamic through employment type rather than job loss. Women in non-regular employment express half the fertility intentions of regular employees. The gap persists controlling for age, education, and income. Notably, women seeking career advancement show higher fertility intentions when they have employment security. Ambition and motherhood aren’t opposed; precarity makes both impossible.

Taiwan’s high-speed rail inadvertently created a natural experiment in 2007 (Mobility and Fertility: Evidence from High-Speed Rail in Taiwan by Yeow Hwee Chua, Pei-Syuan Lin, and Tien Foo Sing). High-Speed Rail connected Taipei’s expensive job market with affordable southern cities, cutting travel time from 4.5 hours to 90 minutes. Fertility increased 6.5% among couples who previously lived apart for economic reasons. First births increased 16.2%. The infrastructure investment didn’t change parenting philosophies. It made family life economically feasible.

Work Accommodating Children Matters

Modern societies physically exclude children from adult spaces, we all seen the viral stories and headlines. Restaurants discourage families. Offices prohibit children. Shops lack changing facilities. Public transport resists prams. This separation of productive and reproductive labor is historically anomalous. Pre-industrial societies integrated children into daily life because excluding them was economically impossible.

The Dutch fertility study (Understanding Narratives of Uncertainty in Fertility Intentions of Dutch Women: A Neural Topic Modeling Approach by Xiao Xu, Anne Gauthier, Gert Stulp, and Antal van den Bosch) revealed this clearly. Using neural topic modeling on open-ended responses from 423 women, researchers found structural concerns dominated fertility hesitation. Dutch women live in one of Europe’s most generous welfare states. They still cited the impossibility of managing pregnancy while maintaining careers. Women with identical demographics (age, income, education, partnership status) expressed completely different fertility intentions based on whether their specific work situation could accommodate children.

Traditional policy levers didn’t address their concerns. Childcare subsidies don’t help if pickup is at 5pm and meetings run until 6pm. Parental leave doesn’t help if using it destroys career advancement. Women needed to believe they could remain economically secure and professionally engaged while parenting. Most didn’t.

Reduced working hours meant different things to different workers

The Singapore flexible work paper revealed some uncomfortable class dynamics. Reduced working hours meant different things to different workers. For professionals, it meant eliminating slack time and focusing on core tasks. For service workers, it might mean lost wages. Flexible scheduling helps knowledge workers who can shift tasks. It doesn’t help retail workers whose presence defines their job.

This creates coalition problems for reform. Universal reduced hours might help professional families while harming working-class incomes. Flexible scheduling might advantage laptop workers while leaving service workers behind. Child-friendly public spaces might cluster in wealthy neighborhoods while poor areas remain hostile.

On that note, there is evidence suggests broad benefits from structural reform. Germany’s job creation in female-dominated sectors (healthcare, education, social services) increased fertility across income levels. These sectors offered security and predictability rather than high wages. Stability mattered more than income.

Some Common Points

Just by looking at, well, the tip of a (very large) research iceberg we can see a few interesting notes.

First, no parenting optimization overcomes the growing time poverty, especially with dual-career households. This requires wage growth, housing cost reduction, or any number of fixes. The Taiwan research showed couples literally living apart because neither could afford housing near their workplace. That’s not a problem natural parenting can solve.

Second, genuine workplace flexibility must replace fake flexibility. Real flexibility means controlling when and where work happens, not answering emails at midnight. The Norwegian evidence showed that forced flexibility during lockdowns persisted because it worked. Firms discovered that rigid scheduling was organizational habit, not operational necessity.

Third, children need reintegration into public life. This means designing spaces that accommodate families, not segregating them into child-specific zones working parents can’t access. It means normalizing children’s presence in restaurants, shops, and when possible, workplaces. The systematic exclusion of children from adult spaces makes parenting a logistical nightmare regardless of philosophy.

Beyond The Boring Discourse

The Dutch women’s narratives revealed something interesting. When asked about fertility hesitation, they didn’t discuss parenting philosophies. They discussed whether their lives permitted children at all. Health anxieties weren’t about pregnancy complications but managing pregnancy while working. Life stage concerns weren’t biological but economic, waiting for security that never arrived.

The pronatalist movement’s has a lot of interesting research that just doesn’t get talked enough about (unless it is part of some broader narrative, usually not about helping people who want kids, get kids). Fertility decline reflects the rational response to structural conditions.

The evidence points clearly. Flexibility increased Norwegian births 10%. Job security doubled Japanese fertility intentions. Connecting separate households increased Taiwanese fertility 16%. All interesting stuff (I think).

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Giving fathers two weeks of paid leave cuts divorce rates by ~19% over 15 years, but shorter leaves increase marital dissolution. “The Impact of Paid Paternity Leave Reforms on Divorce Rates in Europe” by Marina Morales of Universidad de Zaragoza tracked crude divorce rates from 1971 to 2023 against World Bank Women, Business and Law data on paternity leave legislation. The study controls for maternity provisions, parental leave allocations, unilateral divorce laws, joint custody reforms, and seven gender equality indicators.

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The evidence

Static effects: Each additional week of paid paternity leave correlates with 0.03 fewer divorces per 1,000 inhabitants. The relationship turns negative only when examining leave duration rather than mere existence of any policy.

Dynamic patterns by leave duration:

• Any length: Divorce rates increase 0.35 percentage points after 15 years

• At least 1 week: Mixed effects, mostly insignificant

• At least 2 weeks: Rates drop 0.14 points within 3-4 years, reaching 0.36 points after 15 years

• At least 3 weeks: Effects strengthen to 0.29 point reduction after 15 years

• At least 4 weeks: Maximum impact of 0.64 point reduction, though sample size limited

Current European landscape

Historical progression:

• 1971: France, Belgium, Spain introduce minimal leave (days only)

• Early 1980s: Finland and Sweden establish 2-week provisions

• 2000: Eight countries offer some form of paternity leave

• 2010: Seventeen countries provide entitlements, eight offering 2+ weeks

• 2023: Twenty-five of 27 EU members recognize paid paternity leave

Present allocations:

• Most generous: Spain (16 weeks), Finland (14 weeks)

• Substantial: Estonia, Ireland, Lithuania, Netherlands, Portugal, Romania, Slovenia (4+ weeks)

• Moderate: Denmark (2 weeks plus 9 earmarked parental weeks)

• Minimal: Czech Republic, Cyprus, Italy (under 1 week)

• None explicitly: Germany, Slovakia (though Germany provides extensive parental leave)

The mechanism

Research identifies two distinct phases explaining the divergent effects:

Phase 1: Labor market transformation Short paternity leaves enable mothers’ workforce reentry without shifting domestic responsibilities. The Parenthood indicator from Women, Business and Law shows countries with stronger post-childbirth employment protections exhibit higher divorce rates. This dual burden of unchanged household duties plus increased financial independence correlates with marital instability.

Phase 2: Domestic rebalancing Extended leaves (2+ weeks) allow sustained paternal engagement. Evidence shows fathers maintain elevated childcare involvement beyond the leave period. Public expenditure data on parental leave, which increased elevenfold for fathers versus doubling for mothers since 1971, confirms actual uptake when durations are meaningful. Higher spending correlates with lower divorce rates even controlling for fertility trends.

Policy design considerations

Non-transferable provisions matter: “Daddy quotas” that cannot be transferred to mothers show stronger effects than shared parental leave, where mothers traditionally take most days despite formal equality.

Timing of effects: Benefits emerge 3-4 years post-implementation and strengthen over time. Countries cannot expect immediate results.

Total leave calculations: When including parental leave reserved for fathers (not just paternity leave), effects remain consistent though slightly smaller in magnitude.

Implementation windows: Most effective when taken immediately after childbirth rather than spread across years. Denmark’s model requires fathers to use their allocation before the child turns one.

Data specifications

Sources:

• Women, Business and Law (World Bank): Leave legislation from 1971

• Eurostat: Crude divorce rates per 1,000 inhabitants

• OECD Social Expenditure Database: Public spending percentages

• UN Demographic Yearbooks: Gap-filling for missing Eurostat data

Sample limitations:

• Divorce legally unavailable in some countries during portions studied

• Public expenditure data incomplete for Malta and Cyprus

• 2020 data potentially affected by COVID-19 administrative delays

Bottomline

The EU’s 2019 directive requires all member states to provide 10 working days of paid paternity leave, with two months of parental leave non-transferable between parents. Germany obtained exemption through existing parental provisions. Slovakia implemented compliance in November 2022.

Countries providing minimal leave may inadvertently destabilize marriages rather than supporting them. The two-week threshold identified by this research suggests the directive’s requirements align with the minimum needed for positive family outcomes.

Length does matter: Europe’s five-decade natural experiment demonstrates that paternity leave policies require sufficient duration to shift from disrupting traditional arrangements to establishing new equilibrium. Half measures correlate with higher divorce rates, while meaningful allocations deliver promised benefits of stronger partnerships and family stability.

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You've probably heard time and time again that Japan's birth rate hit a record low of 1.26 in 2022 (well below replacement) threatening workforce sustainability and social security systems. (Though for some reason, people think Japan is unique in this regard when it's not, I mean Italy, China, Chile, etc.) Speaking of clichés, a common one is the work-versus-family dilemma. However, research from Kanagawa University of Human Services suggests that career advancement and childbearing aren't mutually exclusive goals, reminding us that clichés are just that, clichés .

The study: "Career advancement and fertility intention among working women in Japan: a cross-sectional survey study" by Honami Yoshida, Mariko Nishikitani, Masumi Okamoto, Akio Kurokawa, Mika Hoshina, Mizuki Yazawa and Nao Ichihara, published in BMC Women's Health (2025).

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By the numbers:

• 3,425 women surveyed across 14 companies in Tokyo's Marunouchi district (September-October 2022)

• 1,621 women under 40 included in final analysis

• 68.4% expressed intention to have children or additional children

• 94% with fertility intentions held regular full-time positions vs. 87% without

• 32% in sales roles wanted children vs. 22% without fertility plans

• 10% with childbearing plans had undergone fertility treatment vs. 1% without

The Career-Fertility Connection

The Working Women's Health Score survey, an industry-academia collaboration between Mitsubishi Estate, Femmes Médicaux, and Kanagawa University, reveals that women planning for children were nearly twice as likely to hold stable, regular employment (odds ratio 1.99). Sales workers showed 51% higher odds of fertility intention compared to clerical staff, while those in clerical positions were 25% less likely to want children.

Career advancement motivation scored significantly higher among women with fertility intentions (OR 1.13), contradicting Japan's traditional "motherhood track" versus "career track" dichotomy. These women also demonstrated distinct health management patterns: 66% reported confidence in their physical strength versus 58% without fertility plans, while 57% reported good sleep quality compared to 49% in the no-intention group.

What Didn't Matter

Surprisingly, several workplace factors showed no significant association with fertility intentions. Work engagement levels, psychological job demands, and job control measures were similar across both groups. Male colleagues' understanding of female health issues registered identically at 45-46%, while satisfaction with work (74% vs. 72%) and home life (88% vs. 84%) showed minimal differences.

Physical symptoms also failed to differentiate the groups. Dysmenorrhea severity scores (median 8 vs. 7), premenstrual syndrome scores (42 vs. 41), and overall health literacy for female-specific conditions showed no meaningful variations. Both groups worked similar hours (median 9 per day) and reported comparable workplace atmosphere friendliness (86% vs. 84%).

Structural Context

Japan's demographic challenge unfolds against profound workplace inequities. Women hold only 13% of managerial positions compared to 44% in the United States, while male participation in childcare leave remains at 17.13% versus 80.2% for women as of 2023. The social security system, originally designed for single-income households, faces strain as double-income households doubled between 2004 and 2021.

Traditional workplace practices persist despite policy initiatives. Long working hours, limited childcare support, and gendered career tracking create structural barriers for women attempting to balance professional advancement with family formation. (Dave’s note: Those in non-standard employment, regardless of gender, face their own particular challenges in what amounts to an equalish?-opportunity lack of traditional "careers.") However, the research suggests these challenges may be less decisive than previously assumed, with career-confident women potentially seeing themselves as better positioned to manage multiple life roles.

Study Limitations

The cross-sectional design prevents causal inference, capturing associations rather than determining whether career motivation drives fertility intention or vice versa. The urban sample from major Tokyo companies may not represent broader Japanese working women, particularly those in rural areas or smaller firms. Selection bias inherently excludes women who left the workforce for family reasons, potentially overestimating the association between career motivation and fertility intention.

Researchers lacked access to direct income data, as participating companies' human resources departments declined to include salary questions. The study relied on self-reported measures without objective validation, and cannot track whether expressed intentions translate into actual births. Working hours data showed quality issues, with 8.3% of participants providing inconsistent responses about standard versus overtime hours.

These limitations aside, emerging international research reveals similar patterns challenging what increasingly appears to be an outdated cliché (while I dislike clichés, my god I love using that word). Martin Kolk's longitudinal study in Sweden demonstrates how women's income association with birth rates shifted from slightly negative to positive over time. In recent Swedish cohorts, accumulated disposable income correlates strongly with fertility. While high-parity mothers still have relatively low incomes, earnings of mothers with 1-3 children now exceed those of childless women, suggesting the career-fertility relationship may be fundamentally changing across developed economies.

Policy Implications

The findings suggest workplace policies supporting continuous career development need not conflict with demographic goals. However, implementation requires careful consideration to avoid reinforcing traditional gender expectations or creating additional pressure on women to excel in both domains simultaneously.

Future research should employ longitudinal designs tracking whether intentions become births, include women who have exited the workforce, and expand beyond Tokyo to diverse geographic contexts (would love to see it on a prefecture based level or comparing to different wards in a large city like Tokyo personally). Specific interventions worth testing include career advancement paths that accommodate family formation timing, expanded childcare facilities, mandatory paternity leave, and performance evaluation systems that don't penalize parental leave usage.

Bottomline: Rather than forcing women into, again, clichés choices between career and motherhood, workplace policies (or more likely considering the RTO shitstorm, government policy) and support both goals. I would like to stress, this isn’t a Japan only route to deal with falling birthrates, we seen other studies saying similar things.

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Chinese adults with higher interpersonal trust want significantly more children, according to a major study of 64,161 people that challenges conventional wisdom about the country's demographic crisis. Each unit increase in social trust raises ideal family size by 0.018 children (think moving from "neutral" to "somewhat agree" that people can be trusted). The effect 4x in urban areas where traditional support networks have eroded.

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Why it matters: This paper from North China University of Technology economists Xin Deng, Yang Wang, and Xiaobo Tao suggests Beijing is treating one part of the puzzle, but ignoring other parts: collapsing social cohesion that makes young Chinese wary of bringing children into an uncertain world. For investors and policymakers tracking China's economic trajectory, the findings imply that demographic recovery requires rebuilding social trust.

Understanding the trust measurements: The study uses a 5-point scale asking "Do you agree most people in society can be trusted?"

• Average Chinese response: 3.48 (between neutral and somewhat trusting)

• Provincial averages range from 3.2 to 3.8

The evidence at a glance:

• 64,161 respondents surveyed across seven waves from 2010 to 2021

• 2.118 ideal children versus 1.09 actual fertility rate reveals massive intention-action gap

• 0.018 child increase per unit of individual trust, i.e. moving from complete distrust to complete trust correlates with wanting 0.09 more children

• 0.005 additional increase when individual trust combines with high provincial trust environment

• 4x stronger effect in cities: urban residents who move up one trust point in a high-trust city want 0.008 more children, while rural residents making the same shift want only 0.002

• 15.6 percent of China now over 65, up from 8.9 percent in 2010

• Negative 0.99 per thousand population growth rate in 2024

A natural experiment : The researchers faced a challenge: does trust cause higher fertility desires, or do family-oriented people become more trusting? To untangle causation, they used China's mountains as a natural experiment. Historically, people in mountainous provinces like Tibet (averaging 22-degree slopes) had to rely on neighbors for survival, building stronger trust traditions than those in flat provinces like Jiangsu (3-degree slopes).

Using NASA elevation data at 30-meter resolution, they found each degree of average slope correlates with 0.236 higher trust scores. This geographic variation, unrelated to contemporary economic factors, provided clean identification of trust's causal effect on fertility.

How trust shapes fertility decisions: The study develops an overlapping generations model revealing two mechanisms. First, trust reduces perceived childbearing costs by lowering uncertainty about finding reliable childcare, medical care, and education. Second, trust enhances expected returns from children by increasing confidence in long-term reciprocal support. Simulations show these effects create self-reinforcing spirals: high-trust societies maintain higher fertility, while low-trust environments see both metrics decline together.

The concept of "contextualized trust": You can’t just expect one person being super trusting in the city would have the same expectations as being trusting in a small town. After all, a trusting person in distrustful Shanghai faces different fertility calculations than an equally trusting person in high-trust Tibet. The researchers attempt to measure both individual trust and provincial average trust, then multiplied them together to capture how much your personal trust matters in your social environment. This interaction effect adds 0.005 children per unit on top of individual trust's direct effect.

The provincial divide tells the story: Western provinces with traditional kinship networks show highest fertility intentions: Xinjiang (2.8 children), Tibet (2.6), Ningxia (2.5), and Qinghai (2.5). Coastal cities show lowest: Shanghai (1.7), Beijing (1.8), Jiangsu (1.9), and Zhejiang (1.9). The pattern holds even controlling for income, education, and urbanization.

Income paradox in concrete terms: Trust matters most for those who can't buy their way out of uncertainty. A middle-income family (earning 10,000-50,000 RMB annually) that moves up one trust point sees desired family size increase by 0.006 children. For a couple moving from distrust to trust in a supportive community, that translates to wanting roughly 0.12 more children.

• Low-income (under 10,000 RMB): 0.004 increase per trust unit

• Middle-income (10,000-50,000 RMB): 0.006 increase per trust unit

• High-income (above 50,000 RMB): 0.007 increase but with lower statistical confidence

The rich has a buffer against uncertainty; everyone else needs social bonds to feel secure about parenthood.

Demographics reveal targeted effects:

• Women respond 25% more strongly than men: each trust unit increases women's fertility intentions by 0.005 children versus men's 0.004

• Childbearing-age adults (18-49) show amplified response at 0.006 children per trust unit

• Urban vs rural divide: Urban hukou holders show 0.008 increase per trust unit—four times rural residents' 0.002, suggesting traditional village networks already provide what trust offers in cities

• Daughter preference increases by 0.014 children per trust unit, nearly double the 0.008 increase for son preference

Belief in a Happy & Fair world: Trust doesn't just reduce economic anxiety, but how you see the world:

• Happiness channel: Each unit increase in happiness (1-5 scale) correlates with wanting 0.083 more children. Trust significantly boosts happiness.

• Fairness channel: Each unit increase in perceived societal fairness correlates with desiring 0.042 more children. Trust enhances fairness perceptions.

To put these in perspective: the trust effect (0.018) is roughly equivalent to a 10% income increase or one additional year of education. It's smaller than getting married (increases desired children by 0.3) but larger than homeownership (0.01).

What moves the needle on Chinese fertility intentions:

• Moving from complete distrust to complete trust: +0.36 children (massive effect for those making full shift)

• Living in high-trust vs low-trust province: +0.12 children (moderate community effect)

• Urban resident gaining trust in trusting city: +0.032 children (4x rural effect)

• Each point of happiness gained: +0.083 children (large psychological effect)

• Each point of fairness perception: +0.042 children (moderate psychological effect)

Methodological rigor: The findings survive multiple robustness tests. Using an alternative trust measure based on reverse-coded suspicion ("others will take advantage of you") yields a coefficient of 0.025. Post-Double Selection Lasso with 249 control variables maintains the effect at 0.004. Alternative terrain instruments using slope standard deviation produce consistent results. The instrumental variable F-statistics exceed 5,282—far above the conventional threshold of 10 for instrument strength.

The data foundation: The China General Social Survey covers all 31 provinces using stratified multi-stage probability sampling. Researchers merged seven survey waves (2010, 2012, 2013, 2015, 2017, 2018, 2021), excluding outliers reporting over 10 desired children. The study controls for 84 variables including education, political affiliation, hukou status, marital status, health, housing, income, employment, plus province and year fixed effects.

What Beijing's policies miss: The 20th Party Congress elevated fertility to strategic priority. The 2024 Government Work Report expanded childbirth support. Yet macro-level incentives have failed to reverse decline. This research suggests why: you cannot subsidize your way to social cohesion. Trust evolves through transparent governance, reliable institutions, and repeated positive interactions—none of which appear in current policy packages.

The global pattern emerges: China isn't alone in discovering that fertility depends on faith in society. When Russia faced crisis in 2022-2023, researchers surveying 7,967 citizens found an even starker pattern: psychological factors including political trust explained 76 percent of fertility decision variance, while economic factors explained only 24 percent. Russians who trusted their government despite the crisis were 17.2 percentage points less likely to postpone childbearing (an effect equivalent to doubling household income). Those feeling fear were 10.2 percentage points more likely to delay. Even when 45 percent valued their maternity capital payments highly, financial support couldn't overcome emotional uncertainty.

Study limitations acknowledged: The research captures intentions, not actual births, though intentions strongly predict behavior. Post-2021 pandemic effects remain unmeasured. Digital networks' role in trust formation needs investigation. The mechanisms linking trust to happiness and fairness require deeper exploration. Cross-national comparisons would strengthen external validity.

The authors' conclusion: Deng, Wang, and Tao argue that "recognizing trust as a modifiable social asset may offer new levers for addressing demographic challenges beyond conventional economic incentives." Their simulations demonstrate how small changes in trust persistence and transmission, parameters governments can influence through policy, can shift entire societies between demographic growth and decline.

Bottomline: China faces a trust deficit as much as a baby deficit. People don't bring children into societies they don't trust. The quadrupled urban effect, stronger impact on lower incomes, and psychological mediation through happiness and fairness all point toward the same conclusion.

These findings align with emerging global evidence about institutional quality and fertility. A European study of 216 regions by Giannantoni and Rodríguez-Pose finds that a 1 percent improvement in regional government quality correlates with an 8 percent increase in fertility rates. Higher-quality governance reduces by 11.1 percent the chance of regions experiencing both low fertility and low female employment. Nordic regions with strong institutions maintain both high female workforce participation (over 78 percent) and healthier birth rates, while Southern European regions with weaker governance see both metrics collapse (i.e. Italy's Campania has just 27.7 percent female employment and fertility below replacement)

The Russian crisis data reinforces this pattern: subjective factors including political trust explained 76 percent of fertility decision variance during 2022-2023, while objective economic factors explained only 24 percent. Russians who supported their government were 17.2 percentage points less likely to postpone childbearing, while those feeling fear were 10.2 points more likely to delay. Even valued maternity payments couldn't overcome institutional uncertainty.

These converging findings from China, Europe, and Russia reveal that economics and social psychology are deeply interconnected in fertility decisions. Trust and institutional quality don't replace the need for financial support, god only knows how much stuff I written about incomes and birthrates. But money alone cannot purchase the confidence required for parenthood. When trust erodes or institutions fail, that’s a multiplier effect (like x1.1 or -x1.2) that weakens other parts like support. When trust strengthens and governance improves, the same economic resources generate greater impact.

I mean, how can you trust someone (or government) who refuses to put their money where their mouth is?

Reversing demographic decline requires rebuilding the social trust (among other things) that make people confident about the future, not just their finances at that point in time. The challenge isn't choosing between economic and social policies but understanding how trust and institutional quality amplify or undermine every economic intervention Beijing attempts.

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"Insuring Labor Income Shocks: The Role of the Dynasty" by Andreas Fagereng, Luigi Guiso, Luigi Pistaferri, and Marius Ring looks at parents strategically manage wealth to insure children against labor market shocks, dissaving 19 cents per dollar of temporary losses while paradoxically saving 12 cents per dollar of persistent losses to fund future transfers. This “dynastic” insurance (Note: I just love how these guys keep using the word “dynastic”) covers 43% of transitory and 27% of permanent income drops, altering how economists should model household consumption smoothing and macroeconomic fluctuations (because you aren’t just dealing with one isolated household but two or three intergenerational households).

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The Paper

Norwegian population data tracking 13.8 million parent-child observations (1997-2014) exposes an insurance mechanism economists have overlooked. Parents respond asymmetrically to children's income changes: negative shocks trigger wealth adjustments, positive shocks generate zero response.

The paradox: temporary income losses cause parents to spend down savings, while permanent losses cause them to build reserves. Parents face a calculated trade-off between immediate transfers and future support capacity. When children's losses appear lasting, parents compress current consumption to accumulate resources for sustained assistance.

The identification strategy: Separating temporary from persistent shocks required exploiting firm productivity changes that pass through to wages. When companies permanently shrink, workers face lasting pay cuts. The researchers confirmed 98% of firm-driven wage variation stems from persistent shocks, making these ideal instruments.

The theoretical model predicts transfers activate only below a negative income threshold, determined by relative wealth positions and degree of altruism. Optimal transfers equalize consumption smoothing across periods when parents expect to help in multiple years.

The Evidence

Coverage rates:

• 43% of temporary income losses offset by parental transfers

• 27% of persistent income losses covered through wealth adjustments

• Zero response to positive income changes

Response magnitudes:

• $3,500 median parental wealth reduction for 10% temporary child income drop ($8,200 loss)

• $2,200 extra parental savings for 10% persistent shock

• 0.39 elasticity of parental dissaving to transitory negative shocks (parents dissave 39 cents per dollar)

• -0.25 elasticity of parental saving to persistent negative shocks (parents save 25 cents per dollar)

• 0.19 marginal effect for temporary losses at median wealth/income

• -0.12 marginal effect for persistent losses at median

Statistical validation:

• Transitory shocks explain 42% of earnings growth variance

• Persistent firm shocks pass through at 0.025-0.030, transitory at 0.002 (insignificant)

Sample characteristics:

• 3 million child-parent pairs, children aged 25-55, private sector

• 27-year average age gap between generations

• Parents hold 2x children's liquid wealth at median ($35,280 vs $16,915)

• 72% of children married, 95% of spouses work

The Variations

Does marriage matter? Single children receive 0.33 elasticity for transitory shocks (not significant) versus married children's 0.39 (highly significant). Single children may access in-kind insurance (returning home), while married couples need monetary transfers.

Does spouse employment matter? The starkest heterogeneity emerges here:

• Non-working spouse: 1.08 elasticity for transitory, -0.75 for persistent

• Working spouse: 0.35 elasticity for transitory, -0.22 for persistent

• Threefold reduction when spouses provide alternative insurance

Does blood matter?

• Own child persistent shock: -0.29 elasticity (significant)

• Child-in-law persistent shock: -0.22 elasticity (not significant)

• Excluding couples divorcing within 5 years: in-law response rises to -0.33

• Parents condition in-law support on marriage stability expectations

Does competition matter?

• One set of parents: 0.36 elasticity for transitory shocks

• Two sets of parents: 0.42 elasticity

• Evidence against free-riding; suggests "competition for attention"

Does distance matter? Parents in different counties provide larger monetary transfers, while same-county parents likely substitute in-kind support (housing, childcare).

Key Mechanisms

Instrumental variable approach: Firm value-added shocks (revenues minus operating costs) serve as instruments after removing predictable components through fixed effects for industry-county-year interactions.

Income process: Permanent components follow random walk patterns while transitory components are one-time events. GMM estimation separates variance components. Indirect inference validates structural parameters.

Wealth measurement: Financial assets include deposits, bonds, mutual funds, stocks. All third-party reported to tax authorities. Housing excluded from liquid wealth measure. Changes residualized to remove predictable portfolio shifts.

Control variables: Lagged parental financial wealth, lagged parental income, lagged child's cash-on-hand, age controls, year-specific fixed effects by family size, education, and municipality.

One-Way Street

Children don't reciprocate:

• Child savings elasticity to parent persistent shocks: -0.057

• Child savings elasticity to parent transitory shocks: 0.073

• No labor supply adjustments: -0.004 employment response

Parents average age 66 with $88,320 financial wealth versus children age 39 with $47,229. The wealth gradient makes reverse insurance impossible. Even restricting to employed parents generates null results.

Validation

Robustness confirms core findings:

• Ages 25-45: Smaller but significant effects

• Parents under 75: Qualitatively similar

• Excluding stockholders: elasticities of 0.44 and -0.28

• January employment only: Rules out selection

• Different counties: Larger monetary transfers

What parents don't do:

• No labor supply response: 0.04 elasticity (s.e. 0.04)

• No employment changes for reverse insurance

• No response to positive shocks across all specifications

Context and Implications

Previous estimates severely understated parental insurance. Andersen et al. (2020) found 7% replacement using Danish bank transfers, missing indirect payments and cash. Kaplan (2012) focused on in-kind support through boomerang effects. Boar (2021) examined precautionary saving, not ex-post transfers.

Data advantages:

• Norwegian wealth tax creates comprehensive asset reporting

• Third-party reporting by banks and employers eliminates self-reporting bias

• Population coverage includes both wealth distribution tails

• Long panel captures multiple shock realizations

• Links both spouses to all living parents

Theoretical contribution: Three-period altruistic model with credit-constrained children and liquid parents generates testable predictions about asymmetric responses and the dissaving/saving split for transitory/persistent shocks. Transfer thresholds depend on relative wealth and altruism strength.

Bottomline

Parents act as a powerful, informal insurance system for their adult children. When a child suffers a major financial shock, parents, who typically have twice as much savings, step in to help. This family safety net is so effective that it reduces the wider economic impact of personal income shocks by 27% to 43%. This is makes things incredibly messy. It implies that formal government programs aren’t fully compensating for economic losses from shocks. In the real word, programs, like pensions, become a very messy family based social program, rather than just benefiting pensioners. Standard economic models that ignore this family support overstate the effects of financial uncertainty.

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