Putting innovation in the foreground

Four loosely related pieces that I’ve read lately:

A great Quartz profile of economist Mariana Mazzucato:

The central premise of Mazzucato’s work is about the role of the state in innovation. She is an ardent believer that governments should do more than play a passive role in fixing market failures, and be allowed to embrace their entrepreneurial spirit to steer the direction of innovation and economic growth.

The Richmond Fed interviews Enrico Moretti:

In the first three decades after World War II, manufacturing was the most important source of high-paying jobs in the United States. Manufacturing was geographically clustered, but the amount of clustering was limited. Over the past 30 years, manufacturing employment has declined, and the innovation sector has become a key source of good jobs. The innovation sector tends to be much more geographically clustered. Thus, in the past, having access to good jobs was not tied to a specific location as much as it is today. I expect the difference in wages, earnings, and household incomes across cities to continue growing at least for the foreseeable future.

In The Atlantic Tyler Cowen and Patrick Collison call for the creation of an interdisciplinary field called “Progress Studies”:

Progress itself is understudied. By “progress,” we mean the combination of economic, technological, scientific, cultural, and organizational advancement that has transformed our lives and raised standards of living over the past couple of centuries. For a number of reasons, there is no broad-based intellectual movement focused on understanding the dynamics of progress, or targeting the deeper goal of speeding it up. We believe that it deserves a dedicated field of study. We suggest inaugurating the discipline of “Progress Studies.”

Before digging into what Progress Studies would entail, it’s worth noting that we still need a lot of progress. We haven’t yet cured all diseases; we don’t yet know how to solve climate change; we’re still a very long way from enabling most of the world’s population to live as comfortably as the wealthiest people do today; we don’t yet understand how best to predict or mitigate all kinds of natural disasters; we aren’t yet able to travel as cheaply and quickly as we’d like; we could be far better than we are at educating young people. The list of opportunities for improvement is still extremely long.

And Nick Bloom, John Van Reenen, and Heidi Williams have an article in the Journal of Economic Perspectives on innovation policy:

Innovation is the only way for the most developed countries to secure sustainable long-run productivity growth. For nations farther from the technological frontier, catch-up growth is a viable option, but this cannot be the case for leading-edge economies such as the United States, Japan, and the nations of Western Europe. For countries such as these, what are the most effective policies for stimulating technological innovation? In this article, we take a practical approach to addressing this question. If a policymaker came to us with a fixed budget of financial and political capital to invest in innovation policy, what would we advise?

What all these pieces share, despite quite different topics and philosophies, is their foregrounding of innovation. This is, in my view, an underrated vector along which to categorize thinkers. We tend to obsess over peoples’ ideological perspectives with respect to markets or business or the size of government but we don’t do the same for innovation. We ought to. One of the most underrated divisions in politics, I’d suggest, is the degree to which people prioritize innovation and technological advancement.

Update: Cowen links to a reading list on technological progress.

Update 2: so does Collison.

And another.

A very good paragraph on superstar firms

Neil Irwin, writing at The Atlantic, excerpted from his book How to Win in a Winner-Take-All World:

And among economists, the evidence keeps building that the concentration of major industries among a handful of superstar firms might be connected to deep economic dysfunctions. When there are fewer employers in an industry, for example, they have more power to depress workers’ wages. Big dominant companies might focus more on defending what they have than on generating the kinds of innovations that drive economy-wide productivity growth. And the rise of superstar firms is likely related to the rise of superstar cities and the hollowing out of many local economies.

This is important and persuasive work—much of which I’ve written about in my day job as an economics writer at The New York Times. But in all the piling on, I fear something really important is missing from the conversation. The rise of superstar firms is rooted in fundamental technological and economic shifts that are mostly desirable. And policy changes aimed at limiting the downsides of corporate concentration—an important goal—wouldn’t restore an economy built on local, artisanal companies. They would instead leave us with a slightly larger variety of very big, technologically advanced companies dominating the corporate landscape.

Emphasis mine.

I’m broadly supportive of using public policy to address market power and industry concentration, but within the political sphere calls for those policies seem, in my view, to ignore the point that Irwin makes above.

Future of capitalism links

Just a space to link to reading that’s focused on the future of capitalism:


Zingales: “Dear Graduates”

The Guardian’s “Broken Capitalism” series

Paul Polman

Bill Gates

BusinessWeek: 7 Fixes for American Capitalism


Jump-Starting America

The Value of Everything

Can American Capitalism Survive?

The Future of Capitalism

Rebecca Henderson (forthcoming)

Journalists as analysts

This is a great thread from Ben Casselman, economics reporter at The New York Times and formerly FiveThirtyEight, on working with data.

Casselman is careful to note that he’s not an economist and that losing sight of that would lead him to err. But the approach he outlines — humble, integrative, quantitative — is why I suspect analytical journalists can outperform experts in some circumstances in terms of reaching better empirical assessments. See here, here, and here.

After social media

A couple pieces that made me a bit hopeful for the internet:

Can “Indie” Social Media Save Us? – New Yorker

Could the IndieWeb movement—or a streamlined, user-friendly version of it to come—succeed in redeeming the promise of social media? If we itemize the woes currently afflicting the major platforms, there’s a strong case to be made that the IndieWeb avoids them. When social-media servers aren’t controlled by a small number of massive public companies, the incentive to exploit users diminishes. The homegrown, community-oriented feel of the IndieWeb is superior to the vibe of anxious narcissism that’s degrading existing services. And, in a sense, decentralization also helps solve the problem of content moderation. One reason Mark Zuckerberg has called for the establishment of a third-party moderation organization is, presumably, that he’s realized how difficult it is to come up with a single set of guidelines capable of satisfying over a billion users; the IndieWeb would allow many different standards to emerge, trusting users to gravitate toward the ones that work for them. Decentralization still provides corners in which dark ideas can fester, but knowing that there’s a neo-Nazi Mastodon instance out there somewhere may be preferable to encountering neo-Nazis in your Twitter mentions. The Internet may work better when it’s spread out, as originally designed.

Will social media die as private networks become more popular? – Metro

Data collected by the Pew Research Centre has showed that social media user growth is plateauing among most age groups. Twitter’s active users actually declined in the US in 2017 whilst teenagers are either leaving Facebook in droves or are becoming ‘Facebook-nevers’ having never signed up to the platform. ‘While the idea that social media could go out of fashion or that popular sites could suddenly disappear may seem unthinkable, it’s possible to discern the beginnings of another radical change bubbling under the surface,’ Alex Warren, author of Technoutopia: How Optimism Ruined The Internet, says.

One final bellwether: I started using Feedly this week (Teams) and for the first time I’m seeing an RSS reader that’s not just a sad clone of Google Reader but actively better. Who knows, maybe blogging will even come back into fashion…

Econ 101 and model thinking

There was a bunch of Twitter discussion this week inspired by a Vox article by Dylan Matthews about Raj Chetty’s introductory economics course at Harvard. TLDR: The course is basically a review of recent, large-scale empirical work on important social problems like inequality. And it has little to no theory. I’ve watched some of the lectures and I’d recommend them. But the discussion on Twitter was about whether this was a good way to introduce students to economics. Some stuck up for traditional Econ 101; some argued it complemented Chetty’s big data course; some plugged the excellent new(ish) CORE introductory text.

My reaction was this:

Whereas academic economists are concerned with the science of economics, including making their models as accurate as possible, most people who take econ 101 need to learn how to use those models in some way in their work and lives. They need to learn to be analysts, not scientists.

And the way to use economic models is to recognize that they are deeply incomplete approximations of the world, that they’ll be more useful in some cases than in others, and that the best results come from combining them with other useful models from other disciplines. I’m all for more people learning economic models other than just perfectly competitive markets, of course. But even more important is for people who do learn about competitive markets to realize that it’s an approximation that is never true but can sometimes be useful.

As good as the Chetty course is, my preferred update would also borrow heavily from, say, Scott Page or Philip Tetlock.

More on economic models here and here.

Prediction markets or crowdsourcing?

Are markets more accurate than polls? The surprising informational value of “just asking”

Psychologists typically measure beliefs and preferences using self-reports, whereas economists are much more likely to infer them from behavior. Prediction markets appear to be a victory for the economic approach, having yielded more accurate probability estimates than opinion polls or experts for a wide variety of events, all without ever asking for self-reported beliefs. We conduct the most direct comparison to date of prediction markets to simple self-reports using a within-subject design. Our participants traded on the likelihood of geopolitical events. Each time they placed a trade, they first had to report their belief that the event would occur on a 0–100 scale. When previously validated aggregation algorithms were applied to self-reported beliefs, they were at least as accurate as prediction-market prices in predicting a wide range of geopolitical events. Furthermore, the combination of approaches was significantly more accurate than prediction-market prices alone, indicating that self-reports contained information that the market did not efficiently aggregate. Combining measurement techniques across behavioral and social sciences may have greater benefits than previously thought.

Skills gap, again

An excellent piece arguing against the “skills gap” hypothesis. The conclusion:

There is no denying the importance of education and training to long-term outcomes for workers. But that does not mean the solution to stagnant or inadequate wage increases lies in addressing a skills gap. To address the wage problem, Congress and regulators need to ensure that workers retain the ability to organize into unions, and unions need to have the power to bargain collectively—and effectively—to negotiate fair wage levels. In addition, policymakers need to establish wage floors that spill over into higher pay for workers along the distribution. Policies like these will compensate for power imbalances that have maintained wage stagnation.

It is possible to overstate the importance of skills, and it’s also possible to understate it. But that piece is well done and links to great evidence throughout. My writing on this subject is here, here, here.

Technological change and fatalism

“Don’t blame robots for low wages,” writes Paul Krugman. “Automation just isn’t a big part of the story of what happened to American workers over the past 40 years,” he continues. “We do have a big problem — but it has very little to do with technology, and a lot to do with politics and power.”

This is misleading, which is a real shame because Krugman’s ultimate point is incredibly important.

His argument is roughly:

  1. Technological disruption is not new.
  2. This particular wave of technological change is not particularly rapid or unprecedented.
  3. Therefore, technology cannot explain stagnant wages and rising inequality; something else must be causing it.
  4. That something else is politics and power.
  5. We shouldn’t fall for the fatalistic narrative that technology necessitates stagnant wages and rising inequality.

I want to sign on to where he ends up (#5) but not the way he gets there.

Do stagnant wages really have “very little to do with technology”? As I’ve already said, I don’t think technological change necessarily leads to stagnant wages — though it has happened before.

However, I think a more straightforward reading of Krugman’s claim would start with a counterfactual. Holding power and politics constant, what effect has information technology had on wages?

There is abundant evidence that information technology has contributed to stagnant wages and rising inequality, by changing the skills that are demanded and polarizing the labor market. This is occurring across advanced economies. Within the policy variation we observe in OECD countries, at least, it seems that some increase in inequality is the norm.

It therefore seems much more reasonable to conclude that stagnant wages and rising inequality have quite a bit to do with technology. Of course, they also have quite a bit to do with politics and power. The latter likely helps explain why these phenomena have been particularly pronounced in the U.S., and why the U.S. has seen such a staggering increase in the incomes of its top 1%.

I’ve written about this all before, and that was also in response to weirdly overstated claims by Krugman. My assumption is that this is well-intentioned, that he hopes to shift the U.S. policy debate away from fatalism toward action, and that he thinks implicating politics over more impersonal forces like technology will help.

Maybe he’s right.

I certainly don’t think we should be at all fatalistic about inequality, and I certainly agree that politics and power are a major contributor. I’ve emphasized this in my writing and my editing. But technology clearly is a big part of the inequality story, as are education and skills. I suspect that brushing them aside will make solving our problems harder, not easier.