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

Articles

Zingales: “Dear Graduates”

The Guardian’s “Broken Capitalism” series

Paul Polman

Bill Gates

BusinessWeek: 7 Fixes for American Capitalism

Books

Jump-Starting America

The Value of Everything

Can American Capitalism Survive?

The Future of Capitalism

Rebecca Henderson (forthcoming)

Principles of industrial policy – VoxEU

Where are we on the economics of industrial policy? – Dani Rodrik

Industrial Policy 4.0 – Padmashree Gehl Sampath

Overview of national AI strategies

An empirical paper

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.

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.

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:

About fixing Econ 101… whatever one decides to change content-wise, the biggest thing IMO would be to open w/ a full lecture on models & many-model thinking. Then say: What follows are not ironclad truths but partial explanations that will sometimes prove to be useful.

— Walt Frick (@wfrick) May 23, 2019

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.

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.

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.