At Barron’s: Thank Full Employment, Not AI, for Rising Productivity

(I write a monthly opinion piece for Barron’s. This one was published there in September. My previous pieces are here.)

New data about productivity are some of the best on record in recent years. That’s good news for economic growth. But just as important, it offers support for the unorthodox idea that demand shapes the economy’s productive potential. Taking this idea seriously would require us to rethink much conventional wisdom on macroeconomic policy. 

Real output per hour grew 2.6% in 2023, according to the Bureau of Labor Statistics, exceeding the highest rates seen between 2010 and the eve of the pandemic. That said, productivity is one of the most challenging macroeconomic outcomes to measure. It is constructed from three distinct series—nominal output, prices, and employment. Short-term movements often turn out to be noise. It’s an open question whether that high rate will be sustained. But if it is, that will tell us something important about economic growth. 

Discussions of productivity growth tend to treat it as the result of unpredictable scientific breakthroughs and new technologies, whose appearance has nothing to do with current economic conditions. This view of technological change as “exogenous,” in the jargon, is entrenched in economics textbooks. And it’s reinforced by the self-mythologizing barons of Silicon Valley, who are only too happy to take credit for economic good news. 

The economic conditions that lead companies to actually adopt new technologies get much less attention, as does the fact that much productivity growth comes from people shifting from lower-value to higher-value activities without the need for any new technology at all.

A recent New York Times article is typical. It discusses faster productivity growth almost entirely in terms of the new technologies — AI, Zoom, internet shopping — that might, or might not, be contributing. Not until 40 paragraphs in is there a brief mention of the strong labor market, and the incentives that rising wages create to squeeze more out of each hour of labor.

What if we didn’t treat this as an afterthought? There’s a case to be made that demand is, in fact, a central factor in productivity growth. 

The economic historian Gavin Wright has made this case for both the 1990s — our modern benchmarks for productivity success stories — and the 1920s, an earlier period of rapid productivity growth and technological change. Wright considers the adoption of general-purpose technologies: electricity in the ‘20s and computers in the ‘90s. Both had existed for some time but weren’t widely adopted until rising labor costs provided the right incentives. He observes that in both periods strong wage growth started before productivity accelerated. 

In the retail sector, for instance, it was in the 1990s that IT applications like electronic monitoring of shelf levels, barcode scanning and electronic payments came into general use. None of these technologies were new at the time; what had changed was the tight market for retail employment that made automation worthwhile.

The idea that demand can have lasting effects on the economy’s productive potential – what economists call hysteresis — has gotten attention in recent years. Discussions of hysteresis tend to focus on labor supply — people dropping out of the labor market when jobs are scarce, and re-entering when conditions improve. The effect of demand on productivity is less often discussed. But it may be even more important.

After the 2007-2009 recession, gross domestic product in the U.S. (and most other rich countries) failed to return to its pre-recession trend. By 2017, a decade after the recession began, real GDP was a full 10% below what prerecession forecasters had expected. There is wide agreement that much, if not all, of this shortfall was the result of the collapse of demand in the recession. Former Treasury Secretary Larry Summers at the time called the decisive role of demand in the slow growth of the 2010s a matter of “elementary signal identification.” 

Why did growth fall short? If you look at the CBO’s last economic forecasts before the recession, the agency was predicting 6% growth in employment between 2007 and 2017. And as it turned out, over those ten years, employment grew by exactly 6%. The entire gap between actual GDP and the CBO’s pre-recession forecasts was from slower growth in output per worker. In other words, this shortfall was entirely due to lower productivity. 

If you believe that slow growth in the 2010s was largely due to the lingering effects of the recession — and I agree with Summers that the evidence is overwhelming on this point — then what we saw in that decade was weak demand holding back productivity. And if depressed demand can slow down productivity growth, then, logically, we would expect strong demand to speed it up.

A few economists have consistently made the case for this link. Followers of John Maynard Keynes often emphasize this link under the name “Verdoorn’s law.” The law, as Keynesian economist Matias Vernengo puts it in a new article, holds that “technical change is the result, and not the fundamental cause of economic growth.” Steve Fazzari, another Keynesian economist, has explored this idea in several recent papers. But for the most part, mainstream economists have yet to embrace it. 

This perspective does occasionally make it into the world of policy debates. In a 2017 report, Josh Bivens of the Economic Policy Institute argued that “low rates of unemployment and rapid wage growth would likely induce faster productivity growth.” Skanda Amarnath and his colleagues at Employ America have made similar arguments. In a 2017 report for the Roosevelt Institute, I discussed a long list of mechanisms linking demand to productivity growth, as well as evidence that this was what explained slower growth since the recession.

If you take these sorts of arguments seriously, the recent acceleration in productivity should not be a surprise. And we don’t need to go looking for some tech startup to thank for it. It’s the natural result of a sustained period of tight labor markets and rising wages.

There are many good reasons for productivity growth to be faster in a tight labor market, as I discussed in the Roosevelt report. Businesses have a stronger incentive to adopt less labor-intensive techniques, and they are more likely to invest when they are running at full capacity. Higher-productivity firms can outbid lower-productivity ones for scarce workers. New firms are easier to start in a boom than in a slump.

When you think about it, it’s strange that concepts like Verdoorn’s law are not part of the economics mainstream. Shouldn’t they be common sense?

Nonetheless, the opposite view underlies much of policymaking, particularly at the Federal Reserve. At his most recent press conference, Fed Chair Jay Powell was asked whether he still thought that wage growth was too high for price stability. Powell confirmed that, indeed, he thought that wage gains were still excessively strong. But, he said, they were gradually moving back to levels “associated — given assumptions about productivity growth — with 2% inflation.”

The Fed’s view that price stability requires limiting workers’ bargaining power is a long-standing problem. But focus now on those assumptions. Taking productivity growth as given, unaffected by policy, risks making the Fed’s pessimism self-confirming. (This is something that Fed economists have worried about in the past.) If the Fed succeeds in getting wages down to the level consistent with the relatively slow productivity growth it expects, that itself may be what stops us from getting the faster productivity growth that the economy is capable of.

The good news is that, as I’ve written here before, the Fed is not all-powerful. The current round of rate hikes has not, so far, done much to cool off the labor market. If that continues to be the case, then we may be in for a period of sustained productivity growth and rising income.