Digital economics in one paragraph

Search costs are lower in digital environments, enlarging the potential scope and quality of search. Digital goods can be replicated at zero cost, meaning they are often non-rival. The role of geographic distance changes as the cost of transportation for digital goods and information is approximately zero. Digital technologies make it easy to track any one individual’s behavior. Last, digital verification can make it easier to verify the reputation and trustworthiness of any one individual, firm, or organization in the digital economy. Each of these cost changes draws on a different set of well-established economic models: Primarily search models, non-rival goods models, transportation cost models, price discrimination models, and reputation models.

From a review paper by Avi Goldfarb and Catherine Tucker, which discusses the empirical findings for each of the points above.

3 very different views of economic models

The first is a famous one, from Milton Friedman, via Justin Fox’s The Myth of the Rational Market:

[T]he relevant question to ask about the “assumptions of a theory is not whether they are descriptively “realistic,” for they never are, but whether they are sufficiently good approximations for the purpose at hand. And this question can be answered only be seeing whether the theory works, which means whether it yields sufficiently accurate predictions.

As Fox writes:

To head off the obvious objection that it was ridiculous to think regular folks reason according to complex statistical rules, Friedman and Savage argued that billiards players couldn’t write down the physics formulas that underlay their shot selections but nonetheless acted as if they did.

Here’s quite a different take that I just came up on recently, from J.W. Mason of the Roosevelt Institute:

It seems to me that Deirdre McCloskey was right: Economics is not the study of the economy. Economics is just what economists do. Economic theory is essentially a closed formal system; it’s a historical accident that there is some overlap between its technical vocabulary and the language used to describe concrete economic phenomena. Economics the discipline is to the economy, the sphere of social reality, as chess theory is to medieval history: The statement, say, that “queens are most effective when supported by strong bishops” might be reasonable in both domains, but studying its application in the one case will not help at all in applying it in in the other.

Finally, a third view, from Dani Rodrik’s excellent book Economics Rules:

I wrote this book to try to explain why economics sometimes gets it right and sometimes doesn’t. “Models” — the abstract, typically mathematical frameworks that economists use to make sense of the world — form the heart of the book. Models are both economics’ strength and its Achilles’ heel; they are also what makes economics a science — not a science like quantum physics or molecular biology, but a science nonetheless.

Rather than a single, specific model, economics encompasses a collection of models. The discipline advances by expanding its library of models and by improving the mapping between these models and the real world. The diversity of models in economics is the necessary counterpart to the flexibility of the social world. Different social settings require different models. Economists are unlikely ever to uncover universal, general-purpose models.

But, in part because economists take the natural sciences as their example, they have a tendency to misuse their models. They are prone to mistake a model for the model, relevant and applicable under all conditions. Economists must overcome this temptation. They have to select their models carefully as circumstances change, or as they turn their gaze from one setting to another. They need to learn how to shift among different models more fluidly.

Would better antitrust rein in the 1%?

The American economy has grown more concentrated in recent years — in most industries, the top few firms account for more revenue than they did 10 or 15 years ago. This phenomenon appears linked to the decline in the share of national income going to labor, as opposed to capital.

Would better antitrust help reverse that trend, resulting in higher wages and less inequality? That seems plausible, and my inclination is toward stronger antitrust. But the answer may depend on the sort of inequality we’re talking about.

It’s helpful, I think, to consider two types of inequality: the gap between the 1% and the rest, and the gap between educated professionals/the top 20% and the rest. Both gaps have grown, albeit for different reasons. The terrific rise of the 1% is largely an American phenomenon, whereas the other is more global.

Generally speaking, the international nature of the latter inequality has led economists to look beyond policy for explanations, to things like technology or globalization. The localized nature of the 1% inequality has led to an emphasis on U.S. policy decisions.

But the theme of a small number of top firms pulling away from the rest in terms of productivity and wages — not exactly the same as industry concentration necessarily, but related — appears to be international.

That suggests to me that the sort of inequality that would be addressed by tackling industry concentration is the widespread gap between educated professionals and the average worker, not the gap between the 1% and the rest.

This is all speculative, of course. It could be that concentration is a necessary but not a sufficient condition for the rise of the 1%, such that we don’t observe the same inequality around the world but that antitrust would address it. But it’s worth remembering what Alvaredo, Atkinson, Piketty and Saez concluded in their paper on the 1%:

The most obvious policy difference—between countries and over time—regards taxation.

That’s not the only cause they highlight. But the spectacular rise of the 1% is a mostly American phenomenon and so likely the result of something specifically American. The rise of incredibly powerful, productive superstar firms doesn’t fit the bill.

A reading list on market power, superstar firms, and inequality

My best attempt at an overview of the corporate concentration issue, from a recent piece:

The basic facts are these: Most industries in the U.S. have grown more concentrated, meaning the largest firms account for a larger share of revenue. At the same time, corporate profits have reached all-time highs, despite lackluster rates of business investment. And the number of new businesses being founded has declined; the number of new growth startups being founded has risen, yet these firms struggle to scale. The cause of these trends is not clear. Theories include the rise of IT and the network effects it creates, less-rigorous antitrust enforcement, and lobbying and excess regulation.

And a reading list (I’ll try and update it, and let me know what I’ve missed):

The Pro Market blog at the Stigler Center has been excellent on this. Here are a few examples:

Economists: “Totality of Evidence” Underscores Concentration Problem in the U.S.

The Rise of Market Power and the Decline of Labor’s Share

Is the Digital Economy Much Less Competitive Than We Think It Is?

So has the Washington Center for Equitable Growth. 

Market power in the U.S. economy today

Is declining competition causing slow U.S. business investment growth?

U.S. antitrust and competition policy amid the new merger wave

A communications oligopoly on steroids: Why antitrust enforcement and regulatory oversight in digital communications matter

The New America Foundation’s Open Markets program is focused on this:

(update: New America and the Open Markets program have parted ways)

Amazon’s Antitrust Paradox

The Economist has done several great pieces:

The problem with profits

Too much of a good thing

A giant problem

The rise of the superstars

So has The Atlantic:

America’s Monopoly Problem

America’s Monopolies Are Holding Back the Economy

So has ProPublica:

The American Way

These Professors Make More Than a Thousand Bucks an Hour Peddling Mega-Mergers

This is a great piece from Fivethirtyeight on the state of startups:

The Next Amazon (Or Apple, Or GE) Is Probably Failing Right Now

Neil Irwin on winner-take-all at The Upshot:

The Amazon-Walmart Showdown That Explains the Modern Economy

Noah Smith at Bloomberg and on his blog:

Monopolies Are Worse Than We Thought

The Market Power Story

America’s Superstar Companies Are a Drag on Growth

Tyler Cowen on rising markups: “the whole story just doesn’t add up”:

The Rise of Market Power

Productivity and market power in general equilibrium

Intangible investment and monopoly profits

More on the rising markups paper (linked below):

Karl Smith

Robin Hanson

Arnold Kling

Litan and Hathaway on decline of new business formation:

Declining Business Dynamism in the United States: A Look at States and Metros

Jason Furman was involved in two papers on this topic:

A Firm-Level Perspective on the Role of Rents in the Rise in Inequality


Vox’s Matt Yglesias and Ezra Klein did a podcast on this:

The Weeds

Justin Fox on winner-take-all industries:

America’s Most Winner-Take-All Industry, Visualized

Greg Ip

A Provocative Look at the Harm From Corporate Heft

A few of the academic papers that are good starting points in my opinion:

Are U.S. Industries Becoming More Concentrated?

The Fall of the Labor Share and the Rise of Superstar Firms

Declining Competition and Investment in the U.S.

The Rise of Market Power and the Macroeconomic Implications

An interesting anonymous contribution, via Tyler Cowen

Large U.S. firms have always commanded monopolistic rents–think Dupont, Bethlehem Steel, IBM, GM/Ford/Chrysler in their respective heydays. However, several developments have worked to dramatically change how those rents are shared. Before the 1980s shareholder revolution, monopolistic rents of dominant firms were more broadly shared–not just with rank and file employees but with the local community. (link)

We’ve done tons at HBR on this…

…firms are failing faster:

The Biology of Corporate Survival

The Scary Truth About Corporate Survival

…on startups being started but not scaling:

The U.S. Startup Economy Is in Both Better and Worse Shape than We Thought

…on superstar firms, and the pay inequality that comes with them:

Productivity Is Soaring at Top Firms and Sluggish Everywhere Else

A Study of 16 Countries Shows That the Most Productive Firms (and Their Employees) Are Pulling Away from Everyone Else

Research: The Rise of Superstar Firms Has Been Better for Investors than for Employees

Corporate Inequality is the Defining Fact of Business Today

Corporations in the Age of Inequality

Investing in the IT That Makes a Competitive Difference

…on digital firms pulling ahead:

The Most Digital Companies Are Leaving All the Rest Behind

What the Companies on the Right Side of the Digital Business Divide Have in Common

Managing Our Hub Economy

(see also several of the items in the superstar section above)

…an interview with Jason Furman:

Competition Is on the Decline, and That’s Fueling Inequality

…on mergers:

Mergers May Be Profitable, but Are They Good for the Economy?

…on data, AI, and antitrust:

How Pricing Bots Could Form Cartels and Make Things More Expensive

Should Antitrust Regulators Stop Companies from Collecting So Much Data?

…on lobbying and rent-seeking:

Lobbyists Are Behind the Rise in Corporate Profits

…on common ownership:

One Big Reason There’s So Little Competition Among U.S. Banks

Warren Buffett Is Betting the Airline Oligopoly Is Here to Stay

…on big companies paying more than small ones, but less so than they used to:

Big Companies Don’t Pay As Well As They Used To

…and trying to sum it all up:

Making Sense of Our Very Competitive, Super Monopolistic Economy