Blog Post

AEIdeas

In recent days, a bunch of smart people — including at AEI — have addressed the apparent productivity paradox that makes our economy so hard to gauge right now. Silicon Valley is booming, and yet productivity growth is tepid. But if productivity growth is so awful, then how can super-high-skill workers and robots also be eating so many jobs?

Speaking at the Peterson Institute, Larry Summers offered some thoughtful observations. Summers takes seriously the idea of technological disemployment, pointing toward the discouraging trends for working age men especially. “And yet,” he wonders

…if technical change is a major source of dis-employment, it is hard to see how it could be a major source of dis-employment without also being a major source of productivity improvement. In part, if the technology is replacing people that means that productivity should be expected to go up at least if you measure simple labor productivity. And if more of that is happening than used to be happening, then you would expect productivity to be rising more rapidly than it used to be rising. There is the further wonkier, but not that wonky observation that if the lower tail of the workforce is increasingly not working, than if you remove the least productive people, the average productivity of those who remain should be increasing. So, I think, the largest thing that I do not understand in this area, is how to square the “new economy is producing substantial dis-employment” view, with the “productivity growth is slowing” view.

Summers offered a second explanation for the paradox.

I think it is at least possible that there are substantial mismeasurement aspects and that there is a reasonable prospect at accelerating mismeasurement as an explanation for some part of this puzzle. I do not base this judgment on calculations about the consumer surplus from Google or Facebook; I think those are important conceptual issues for measuring the welfare of the average citizen. I am not sure that they are important conceptual issues when quantified for measuring market GDP, as economists traditionally understand market GDP. Rather, I am struck that there is likely what may well be an increase in unmeasured quality improvement.

But if productivity is actually higher than we think, then inflation is actually lower than we think, and real interest rates are not as low as we think. Thus, Summers admitted, he is now questioning his own idea of demand-side secular stagnation. Several days before Summers’ comments, AEI’s own Jim Pethokoukis and Steve Oliner hosted a related discussion of innovation, productivity, jobs, and wages, asking if we are in a great stagnation — or perhaps just the opposite, an acceleration.

It’s a fascinating topic that happens to animate a significant portion of my new paper on the 50th anniversary of Moore’s law, which surveys the past and prospects of exponential computer trends. While I don’t address the macroeconomic factors or implications, I do look at the mismeasurement question, pointing toward Steve Oliner’s good work on microprocessor prices as a prime example of what is likely a much more pervasive and multifaceted measurement challenge. It turns out, for example, that the price of computer power, as measured by the producer price index, might be overstated by a factor of 27.

Moore’s Law at 50 also addresses the future. Some have argued that the information revolution was not nearly as powerful as the Industrial Revolution and that the information age is in fact winding down. Innovation is thus likely to limp for decades to come. I argue just the opposite — that information technologies are poised to deliver some of their most potent economic benefits, specifically in the perennial productivity laggards we call health care and education.

Health care, I argue in another new report, The App-ification of Medicine , will be transformed into an information industry. Computers and the Internet are on the cusp of making healthcare more personal, consumer oriented, cost effective, innovative, agile, and entrepreneurial. The powerful combination of smartphones and personal technology, Big Data and Social Data, and accelerating breakthroughs in our understanding of the Code of Life (or biological information networks) will empower consumers and physicians, dramatically cut costs, and open up vast frontiers for medical research and entrepreneurial business models. Bad policy can of course retard this vision, but the potential is clear.