Noah Smith turns the spotlight on a paradox that could reshape how we view the future of work: the idea that fewer babies might actually make us richer. While most economists warn of economic collapse from aging populations, Smith dissects a provocative new claim from Nobel laureate Daron Acemoglu suggesting that labor scarcity forces the very innovation needed to sustain growth. For busy readers tracking the intersection of demographics and technology, this is not just a theoretical debate—it is a direct challenge to the prevailing anxiety about the coming demographic winter.
The Hierarchy Problem
Smith opens by addressing a recent Economist article that critiques Acemoglu, a titan of the field whose work on institutions and technology has dominated economic discourse for decades. Smith notes the irony that while Acemoglu is the subject of the critique, the magazine highlights Smith's own long-standing skepticism. He writes, "I go after Acemoglu's work because I know he can take it; he's a titan of the economics field, and I am but a lowly blogger." This framing is crucial: Smith positions himself not as a rival, but as a necessary corrective to a profession that has become too insulated.
The core of Smith's argument here is that the economics profession suffers from a "crisis of unreliability" driven by its own hierarchy. He argues that "young and less accomplished researchers routinely defer to the authority of famous and senior figures," creating a literature skewed toward the intuitions of the elite rather than hard data. This is a bold meta-commentary on how science functions, or fails to function, within academia. It suggests that the real story isn't just about birth rates, but about who gets to decide what counts as economic truth.
"Science is the belief in the ignorance of experts."
Critics might argue that deferring to established figures provides necessary stability in a complex field, preventing every new paper from overturning decades of consensus. However, Smith's point holds weight when considering how long it takes for flawed methodologies to be corrected. He notes that even top economists admit Acemoglu's empirical foundations can be "fairly shaky," yet his influence remains unchallenged until external pressure mounts.
The Demographic Paradox
Shifting to the specific policy debate, Smith tackles the fear of low fertility rates. The conventional wisdom, he explains, is that aging populations create a burden on the young and shrink the total market size. However, Acemoglu and his co-authors propose a counter-intuitive mechanism: when workers become scarce, businesses are forced to invest in labor-saving technology, which boosts productivity enough to offset the loss of population.
Smith breaks down the abstract of this new paper, which claims that "lower birth rates are associated with higher growth in GDP per working-age adult... with no negative impact on aggregate GDP or earnings." He acknowledges the logic is sound in theory, drawing a parallel to historical growth theories where labor scarcity drove the Industrial Revolution. He notes that "some economic historians, like Robert Allen, even think this is what caused the Industrial Revolution!" This historical context, reminiscent of the Solow residual discussions on how much growth comes from technology versus capital, adds necessary depth to the argument.
However, Smith immediately introduces a critical friction point. He points out that this new optimism about automation contradicts Acemoglu's own previous warnings about AI and robots. In his 2021 paper "Harms of AI," Acemoglu argued that automation could be "excessively automating work, fueling inequality, inefficiently pushing down wages, and failing to improve worker productivity." Smith writes, "If modern automation technologies push down wages without raising productivity much, it cannot compensate for population aging in the way that Acemoglu... claim that it must."
This contradiction is the piece's most damaging insight. If the administration or policymakers rely on the "scarcity drives innovation" argument to justify inaction on demographic decline, they may be ignoring the very real risk that the technology won't deliver the promised productivity gains. As Smith puts it, "if Acemoglu goes around simultaneously telling us: not to worry about population aging... and to worry a lot about automation... then we have a problem."
"Human beings aren't just labor supply; they also create labor demand."
Smith challenges the "supply-side" view of the new paper by emphasizing the demand side. He argues that fewer people mean fewer consumers, which reduces the incentive for businesses to buy new machines in the first place. "Babies are not that different from immigrants," he writes, noting that a larger market size often drives innovation. This is a vital distinction for readers to grasp: you cannot simply replace people with robots if the robots have no one to sell to.
The Flawed Data
The commentary then dives into the empirical weaknesses of the new study. Smith scrutinizes the statistical methods, noting that the positive correlation between low birth rates and growth "loses statistical significance" once the authors control for other factors like education and urbanization. He highlights a key table from the paper, observing that "the more controls the authors add, the weaker the estimated effect becomes."
This is a classic red flag in econometrics. Smith explains that if the result is so fragile that adding a few control variables makes it disappear, the finding is likely spurious. He questions why the authors ignore the role of institutions, which Acemoglu has famously championed as the primary driver of development. "If the legacy of colonialism can be canceled out by passing out free condoms, why did Acemoglu win a Nobel prize?" Smith asks, using sharp irony to highlight the omission.
Furthermore, Smith points out that the paper focuses on GDP per working-age adult rather than GDP per capita, which is the metric that actually matters for living standards. "They do look at total GDP, and here they find no correlation, but a big standard error," he notes. He criticizes the authors for blurring the line between "no negative impact" and "we can't find a negative impact," a subtle but important distinction in policy analysis.
"Cross-country regressions have small samples and tons of heterogeneity, so their standard errors tend to be huge."
The analysis of U.S. commuting zones faces similar scrutiny. Smith argues that the results likely reflect "sorting and clustering" rather than a causal link between birth rates and automation. He suggests that talented people and high-tech industries simply moved to coastal cities like Boston and San Francisco, driving up wages there, while other regions stagnated. This migration pattern, he notes, has nothing to do with local birth rates in 1940. He cites Enrico Moretti's research to show that "the sorting of talent and knowledge industries was strongly correlated with income divergences between American regions after 1970."
Critics might argue that even if sorting is a factor, the correlation still offers a useful heuristic for regional planning. But Smith's insistence on the lack of independence between regions is compelling. If ideas and capital flow freely across the country, a local shortage of workers in Gary, Indiana doesn't necessarily force that specific city to automate; it might just force the company to move to Boston.
Bottom Line
Smith's commentary succeeds in exposing the fragility of a comforting narrative: that technology will automatically save us from demographic decline. His strongest move is highlighting the internal contradiction in Acemoglu's work, forcing a re-evaluation of whether automation is a savior or a destabilizer. The biggest vulnerability in the argument he critiques is its reliance on statistical noise and its dismissal of the demand-side constraints of a shrinking population. For policymakers and observers, the takeaway is clear: do not bet the future on the assumption that fewer people will magically spark a productivity boom.