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Robert Solow, winner of the 1987 Nobel Memorial Prize in Economic Sciences, is famous for, in the recent words of a high-ranking State Department official, “showing that technological innovation was responsible for over 80 percent of economic growth in the United States between 1909 and 1949.” Or as Frank Lichtenberg of Columbia University’s business school has written, “In his seminal 1956 paper, Robert Solow showed that technical progress is necessary for there to be sustained growth in output per hour worked.”
Typically, technical or technological progress isn’t explicitly defined by those invoking Solow, but people take it to mean new gadgets.
However, Solow meant something much broader. On the first page of “Technical Change and the Aggregate Production Function,” the second of his two major papers, he wrote: “I am using the phrase ‘technical change’ as a shorthand expression for any kind of shift in the production function. Thus slowdowns, speedups, improvements in the education of the labor force, and all sorts of things will appear as ‘technical change.’ ” But his willfully inclusive definition tends to be forgotten.
Solow was constructing a simple mathematical model of how economic growth takes place. On one side was output. On the other side was capital and labor. Classical economists going back to Adam Smith and David Ricardo had defined the “production function”—how much stuff you got out of the economy—in terms of capital and labor (as well as land). Solow’s point was that other factors besides capital, labor, and land were important. But he knew his limitations: He wasn’t clear on what those factors were. This is why he defined “technical change” as any kind of shift (the italics are his) in the production function. He wasn’t proving that technology was important, as economists in recent years have taken to saying he did. All Solow was saying is that the sources of economic growth are poorly understood.
The cautionary tale of Solow is emblematic of how economists get science and technology wrong. One economist creates a highly idealized mathematical model. The model’s creator is, as Solow was, honest about its limitations. But it quickly gets passed through the mill and acquires authority by means of citation. A few years after Solow’s paper came out, Kenneth Arrow, another Nobel Prize winner, would write that Solow proved the “overwhelming importance [of technological change in economic growth] relative to capital formation.” It’s a sort of idea laundering: Solow said that we don’t know where growth in economic output comes from and, for want of a better alternative, termed that missing information “technical change.” But his admission of ignorance morphed into a supposed proof that new technologies drive economic growth.
It would take a thick head indeed to believe that new technologies aren’t valuable to the economy. But determining how they are important, and how important they are, gets thorny. That’s because we don’t have access to a counterfactual world in which a given technology was never developed. Even if you buy the methodology behind, say, a McKinsey study of 13 large economies that says the Internet contributed “7 percent of growth from 1995 to 2009 and 11 percent from 2004 to 2009,” that doesn’t mean that in the absence of the Internet, the world’s economy would have grown by 7 percent or 11 percent less. We don’t, and can’t, know what the world’s economy would have looked like had packet-switched data networks not evolved as they did in the last 20 years. (And if the Internet hadn’t emerged as it did in the final few years of the last century, we probably wouldn’t have experienced the dotcom boom-and-bust cycle, which then changes the entire trajectory of the global economy over the last decade and a half.)
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