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Stagnant construction productivity is a worldwide problem

Forget the usual blame game about local zoning boards or specific political administrations; the real story is that the entire developed world is stuck in a construction productivity trap. Brian Potter's latest analysis for Construction Physics delivers a sobering reality check: the stagnation we see in American building costs isn't a unique national failure, but a global phenomenon that defies our expectations of technological progress. This matters now because it forces us to abandon the hope that simply copying a foreign model will fix our infrastructure crisis.

The Global Pattern of Stagnation

Potter begins by dismantling the comforting narrative that the US is uniquely broken. While much of the discourse focuses on American regulatory hurdles, Potter digs into the KLEMS databases—aggregates of capital, labor, energy, materials, and services—to reveal a startling uniformity. "We've spent a lot of time examining the problem of construction productivity in the US... But it's also worth looking at construction productivity trends in other countries," he writes, setting the stage for a comparative analysis that quickly turns the tables. The data shows that from 1970 through the early 1990s, the US was actually the outlier, with declining productivity while peers improved. "From 1970 through 1995, US construction productivity declined by about 1.9% per year on average," Potter notes, contrasting this with the 1-2% annual gains seen in Western Europe and Japan.

Stagnant construction productivity is a worldwide problem

However, the plot thickens in the mid-1990s. The US managed to stop the bleeding, but so did almost everyone else. "Since roughly the mid-1990s, however, the trends look somewhat different," Potter observes. The global acceleration halted. Nations like Germany, France, and Japan, once models of efficiency, saw their growth flatten or turn negative. This shift suggests that the problem isn't just about American red tape, but something more systemic affecting the industry globally. Potter's framing is crucial here: he forces us to consider that the stagnation might be inherent to the nature of modern construction itself, rather than a policy failure we can easily legislate away.

"Most other countries show improving construction productivity of around 1-2% per year... but it's nevertheless a positive trend. Since roughly the mid-1990s, however, the trends look somewhat different."

The Myth of the Foreign Savior

One of the most valuable contributions Potter makes is debunking the romanticized view of international construction prowess. Policymakers often point to specific countries as blueprints for reform, yet the data tells a different story. "Sweden, for instance, is often praised for its high adoption of prefabricated construction, but since the 1990s Sweden has had roughly flat construction labor productivity," Potter points out. Similarly, Japan, despite its reputation for innovation and willingness to experiment with automated skyscraper construction, has seen "virtually no construction productivity improvement since the 1970s."

Even China, frequently cited as a model of rapid infrastructure development, fails to show the miraculous efficiency gains one might expect. "China does not appear to have particularly impressive growth in construction productivity," Potter writes, noting that its growth rate of roughly 1.4% since 1995 is comparable to Western Europe's slower decades. This is a critical intervention for busy readers looking for quick fixes. It suggests that the "Baumol effect"—where labor-intensive sectors like construction naturally lag behind manufacturing in productivity gains—is a powerful, perhaps inescapable force. The data implies that simply importing prefabrication techniques or mimicking foreign investment strategies may not yield the dramatic cost reductions we crave.

Critics might argue that Potter relies too heavily on labor productivity metrics, which can obscure gains in quality or safety. However, his broader point holds: if the output value isn't rising relative to the hours worked, the fundamental economics of building haven't changed. The lack of improvement in countries with vastly different regulatory environments suggests a deeper, perhaps technological, ceiling.

The Data Problem: Are We Measuring the Right Thing?

Perhaps the most fascinating section of Potter's piece is his admission of the difficulty in measuring this very phenomenon. He doesn't just present the numbers; he interrogates the reliability of the tools used to generate them. "I've noted previously that in general I prefer cost as a measure of construction process improvement rather than productivity, and that I'm somewhat suspicious of these sorts of abstract measures," Potter admits. He highlights how minor changes in data revisions can flip a narrative from "declining" to "flat" or even "growing."

The discrepancy between Potter's findings and a major 2017 McKinsey report illustrates this fragility. While Potter calculates negative growth for the UK since 1995, McKinsey saw positive growth. "The chief culprit appears to be revisions in the KLEMS data over time," he explains. The same dataset, analyzed a few years apart, tells two different stories. This is a vital reminder for any reader consuming high-level economic data. "Slightly different analysis choices... can result in pretty different conclusions, so they should be used and interpreted with care," Potter warns.

He even identifies Belgium as a statistical anomaly, a country showing sustained high growth that doesn't seem to match its construction costs. "It's not clear to me if this is some sort of statistical or accounting artifact, or if Belgium has figured something out," he muses, before leaning toward the former. This intellectual honesty strengthens his argument. By acknowledging the messiness of the data, he makes the underlying trend of stagnation even more credible—if the numbers are this hard to pin down, yet still point to a global plateau, the problem is likely real.

"The accounting required for sector-wide productivity estimates is just hard to do reliably... slightly different analysis choices... can result in pretty different conclusions."

Bottom Line

Potter's analysis delivers a necessary, if uncomfortable, verdict: the stagnation of construction productivity is a global structural issue, not a uniquely American policy failure that can be solved by deregulation alone. The strongest part of his argument is the rigorous debunking of international "best practices," showing that even the most innovative nations have hit the same wall. The biggest vulnerability remains the inherent difficulty of the data itself, which leaves room for debate on whether we are truly stagnant or just bad at measuring our progress. Readers should watch for future research that moves beyond labor metrics to examine how technology and materials are actually changing the cost and quality of the built environment.

Deep Dives

Explore these related deep dives:

  • Baumol effect

    This economic theory directly explains why labor-intensive industries like construction struggle to improve productivity compared to manufacturing - wages rise across sectors but productivity gains are uneven, making construction relatively more expensive over time

  • Total factor productivity

    The article discusses labor productivity measurement using KLEMS databases but doesn't explain the broader concept of how economists measure productivity - understanding TFP provides crucial context for why construction productivity is so hard to measure and improve

  • Japanese asset price bubble

    The article notes Japan's flat construction productivity since the 1970s without explaining why - the 1980s bubble and subsequent 'Lost Decades' fundamentally reshaped Japanese construction practices and investment patterns

Sources

Stagnant construction productivity is a worldwide problem

We’ve spent a lot of time examining the problem of construction productivity in the US — the fact that, across a variety of different metrics, construction never seems to get any more efficient (in terms of how much output you get for a given amount of input), or any cheaper. A paper I wrote about by Goolsbee and Syverson, for instance, titled “The Strange and Awful Path of Productivity in the US Construction Sector,” looked at a variety of different productivity metrics and found that they all show either flat or declining productivity. By contrast, other sectors (such as manufacturing), as well as the economy overall, tend to show increasing productivity.

Much of our investigations have been focused specifically on the issues of construction productivity in the US. But it’s also worth looking at construction productivity trends in other countries — if other countries are showing steadily improving construction productivity, that may give us ideas for ways to improve US construction productivity. If they’re not improving, by contrast, that suggests that US-specific things (such as various regulations) aren’t what’s holding American construction productivity back.

International construction productivity.

To look at international construction productivity, we can use KLEMS databases, which aggregate productivity statistics for different industries in countries around the world. (KLEMS stands for capital (K), labor (L), energy (E), materials (M), and services (S).) These KLEMS datasets are a bit scattered and not amazingly well-maintained (I had to retrieve a lot of the data from archive.org), but by pulling them together we can assemble construction productivity datasets for dozens of different countries going back quite far:

The EU KLEMS dataset has productivity data for European nations, as well as a smattering of other countries. The current EU KLEMS release goes from 1995 to 2021, and in addition to European countries also includes the US, the UK, and Japan. Older EU KLEMS releases (I used the 2008 release) go all the way back to 1970, and in addition to the US, UK, and Japan, also include Korea, Canada, and Australia.

Asia KLEMS has productivity data for Korea, Japan, Taiwan, and India, going from 1980 to 2012.

LA KLEMS has productivity data for several latin american countries, going from 1990 to around 2019.

World KLEMS, in addition to links to the above datasets, also has links to Canada, Russia, and China KLEMS data.

To calculate productivity using this data — specifically, labor ...