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As scholars like Robert Gordon and Tyler Cowan have begun to call out a slowing of progress and growth in the U.S., others are beginning to wonder if “innovation clusters” like Silicon Valley are still advantageous. For example, Brian J. Asquith…

In 2011, the economist Tyler Cowen published The Great Stagnation, a short treatise with a provocative hypothesis. Cowen challenged his audience to look beyond the gleam of the internet and personal compu­ting, arguing that these innovations masked a more troubling reality. Cowen contended that, since the 1970s, there has been a marked stagna­tion in critical economic indicators: median family income, total factor productivity growth, and average annual GDP growth have all plateaued…

In the years since the publication of the Great Stagnation hypothesis, others have stepped forward to offer support for this theory. Robert Gordon’s 2017 The Rise and Fall of American Growth chronicles in engrossing detail the beginnings of the Second Industrial Revolution in the United States, starting around 1870, the acceleration of growth spanning the 1920–70 period, and then a general slowdown and stagnation since about 1970. Gordon’s key finding is that, while the growth rate of average total factor productivity from 1920 to 1970 was 1.9 percent, it was just 0.6 percent from 1970 to 2014, where 1970 represents a secular trend break for reasons still not entirely understood. Cowen’s and Gordon’s insights have since been further corroborated by numerous research papers. Research productivity across a variety of measures (researchers per paper, R&D spending needed to maintain existing growth rates, etc.) has been on the decline across the developed world. Languishing productivity growth extends beyond research-intensive industries. In sectors such as construction, the value added per worker was 40 percent lower in 2020 than it was in 1970. The trend is mirrored in firm productivity growth, where a small number of superstar firms see exceptionally strong growth and the rest of the distribution increasingly lags behind.

A 2020 article by Nicholas Bloom and three coauthors in the American Economic Review cut right to the chase by asking, “Are Ideas Getting Harder to Find?,” and answered its own question in the affirm­ative.⁶ Depending on the data source, the authors find that while the number of researchers has grown sharply, output per researcher has declined sharply, leading aggregate research productivity to decline by 5 percent per year.

This stagnation should elicit greater surprise and concern because it persists despite advanced economies adhering to the established eco­nomics prescription intended to boost growth and inno­vation rates: (1) promote mass higher education, (2) identify particularly bright young people via standardized testing and direct them to re­search‑intensive universities, and (3) pipe basic research grants through the university system to foster locally-driven research and development networks that supercharge productivity…

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… the tech cluster phenomenon stands out because there is a fundamental discrepancy between how the clusters function in practice versus their theoretical contributions to greater growth rates. The emergence of tech clusters has been celebrated by many leading economists because of a range of findings that innovative people become more productive (by various metrics) when they work in the same location as other talented people in the same field. In this telling, the essence of innovation can be boiled down to three things: co-location, co-location, co-location. No other urban form seems to facili­tate innovation like a cluster of interconnected researchers and firms.

This line of reasoning yields a straightforward syllogism: technology clusters enhance individual innovation and productivity. The local na­ture of innovation notwithstanding, technologies developed within these clusters can be adopted and enjoyed globally. Thus, while not everyone can live in a tech cluster, individuals worldwide benefit from new advances and innovations generated there, and some of the outsized economic gains the clusters produce can then be redistributed to people outside of the clusters to smooth over any lingering inequalities. There­fore, any policy that weakens these tech clusters leads to a diminished rate of innovation and leaves humanity as a whole poorer.

Yet the fact that the emergence of the tech clusters has also coincided with Cowen’s Great Stagnation raises certain questions. Are there shortcomings in the empirical evidence on the effects of the tech clusters? Does technology really diffuse across the rest of the economy as many economists assume? Do the tech clusters inherently prioritize welfare-enhancing technologies? Is there some role for federal or state action to improve the situation? Clusters are not unique to the postwar period: Detroit famously achieved a large agglomeration economy based on automobiles in the early twentieth century, and several authors have drawn parallels between the ascents of Detroit and Silicon Valley. What makes today’s tech clusters distinct from past ones? The fact that the tech clusters have not yielded the same society-enhancing benefits that they once promised should invite further scrutiny…

How could this be? What can we do about it? Eminently worth reading in full: “Superstars or Black Holes: Are Tech Clusters Causing Stagnation?” (possible soft paywall), from @basquith827.

See also: Brad DeLong, on comments from Eric Schmidt: “That an externality market failure is partly counterbalanced and offset by a behavioral-irrationality-herd-mania cognitive failure is a fact about the world. But it does not mean that we should not be thinking and working very hard to build a better system—or that those who profit mightily from herd mania on the part of others should feel good about themselves.”

* Robert Gilpin

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As we contemplate co-location, we might recall that it was on this date in 1956 that a denizen of one of America’s leading tech/innovation hubs, Jay Forrester at MIT [see here and here], was awarded a patent for his coincident current magnetic core memory (Patent No. 2,736,880). Forrester’s invention, a “multicoordinate digital information storage device,” became the standard memory device for digital computers until supplanted by solid state (semiconductor) RAM in the mid-1970s.

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