Radical Markets

Radical Markets

Roughly 3-4 times per year, I’ll find a book that is really surprising and novel. Radical Markets is that book.

The core thesis of the book is that the debate around economic structures is incredibly limited. When we hear politicians and journalists talk, the proposals regularly fall into socialism vs capitalism.

When it comes to both socialism and capitalism, both doctrines ignore a big part of today’s problems: global inequality. Radical markets seeks to break outside those lines, and bring markets to new areas where they didn’t previously exist.

The book is structured as a series of 6 radical ideas. Each one starts with a vignette about how the future might look, before diving into specifics.

I’ll add one big caveat that I think these ideas are fascinating… but I struggle to see how we’d take steps towards getting them implemented. All of them are a big departure from the status quo, which is perhaps the point.

A (truly free) market for land

In some ways, land is the ultimate monopoly. Every parcel of land is completely unique, and the seller has complete ability to decide whether to sell their land or not.

The only entity who can force a sale of land is the federal government, using laws of eminent domain.

The result? Well, land doesn’t really rise to its most valuable usage. You see vacant lots and abandoned warehouses sitting in the heart of SF. Public works projects are blocked for years as developers try and negotiate the path for rail, airports, and the like. The results mean that society isn’t getting as much value from the land as we could.

The scheme outlined in the book takes a new approach, and here’s the idea…

  • anyone who owns land sets a public price on that land, which they’d update via an app
  • the owner pays taxes on that land at a certain percentage (say 7%) annually. there are no government appraisers, or other tax considerations
  • anyone can buy that land for the stated price at any time, and use it for whatever they’d like after a 3-month settling/move-out period. the owner can’t refuse
  • all of the taxes are redistributed as a ‘social dividend’, essentially a form of universal basic income.

The incentives are structured so that a land or homeowner won’t set too low of a price to avoid taxation, but also will set a price they are happy to receive and then move out. Any taxes paid via this scheme would be re-distributed per capita as a form of universal basic income, which helps reduce inequality.

A new model of voting

Historically, our democracy has worked via one-person, one-vote. It means that most choices are made via the majority.

But what about cases where a minority of people might care a lot about some issue, that is relatively insignificant to the majority?

In this case, the minority will typically always lose in an election, until a case is raised to the supreme court (see gay marriage), who notably is not elected by the majority, but appointed.

This new model of voting the authors introduce is known as “quadratic voting”. The rules behind it are interesting, though they can be hard to wrap one’s head around.

  • every election, each person gets the same number of “voice credits”
  • each voter can decide to turn the voice credits they have accrued into vote, or save those credits for a future election and issue
  • when an individual spends credits, the number of votes is equal to the square root of the number of credits used. (e.g. 4 credits means 2 votes, 9 credits means 3 votes, etc.)

The idea here is that as you try and add more votes to a given issue, the cost to do so gets more expensive. The goal is to allow a minority group to express views for an issue they care strongly about, while still balancing that against really fringe movements.

Even more radical, you could potentially imagine countries voting this way in international coalitions like the U.N. The authors propose a scheme where countries which exert more power get more credits. The idea is that it helps bring some sort of clear exchange to policies which right now happen through obfuscated negotiations.

I think this maybe the most achievable scheme to implement, not on a country level, but on a business level. You might imagine that if a corporate leadership team is trying to decide between different areas of a company strategy, they could each vote with some number of credits. They might even ask many different parts of the org to weigh in with their votes. Each subsequent vote from an individual gets more expensive to cast, which keeps people from pushing wholeheartedly for an idea unless they think it should really come at the cost of everything else.

Making visa sponsorship available to all

Since the push for free trade, we’ve seen markets expand drastically across the globe. More and more countries are able to freely trade goods and services.

And yet there’s a big piece that’s missing from that equation: labor! Most countries will happily accept new goods into their borders, but will put up large restrictions for accepting the workers who produce those goods.

In today’s economy, companies hold most of the power to sponsor new workers. Tech companies in particular are fond of using H1-B visas to continue to hire the best talent from all over the world.

And yet, that option isn’t available to most normal people. The authors present a new idea which would effectively open up individuals to sponsor immigrants.

  • there would be a significant fee that the immigrant would have to pay. even if this were thousands of dollars, the authors claim the earning differential of the US would outpace the cost.
  • the sponsor would be responsible for vetting and ensuring the immigrant could find work
  • the sponsor would receive a portion of the immigrant’s pay

I’m a bit more skeptical of this scheme, though generally speaking I’m a believer in opening up more immigration and more open borders.

Breaking up institutional investors

There’s this infamous “rule of institutional investors” that Matt Levine talks a lot about. The general idea is that most of the world’s public companies are owned by a small number of very large asset managers: Blackrock, Vanguard, Fidelity, and friends.

These institutional investors tend to be more in the business of owning these assets on behalf of pension funds, retirement accounts, and endowments. Yet there’s some evidence that there’s a more pernicious aspect to them owning ~20-30% of most large cap public companies.

The authors make the claim that this shared ownership causes companies to be less competitive. The general idea is that in a monopoly, prices are exorbitant, because there is no substitute. In duopoly, prices are less than a monopoly, but higher than if there are three competitors, etc, etc.

Therefore, it is in the interest of the institutional investors for their companies not to be too competitive. If you own 30% of United, 30% of Delta, and 30% of Southwest… you might think about nudging each of their CFOs to avoid undercutting the competition on price.

The result is a system which isn’t exactly governed by the rules of U.S. anti-trust law, but also isn’t as competitive as it could be. The authors propose a scheme where…

  • an institutional investor could own as much of they like of one company in a given industry (e.g. you could own United or Delta, but not both)
  • an institutional investor could not hold more than 1% of two companies which compete

There’s a lot of details to sort out with this one, but the gist is that having a more concentrated interest within a single industry, while maintaining a diversified position across industries still gives you diversified returns, while increasing competition.

Paid for your data

Today, the biggest companies in the world are more or less powered by data. Facebook, Google, Amazon, Netflix-all of them profit wildly off their ability to understand and market to their users.

The author’s argue that there’s something a bit unequal about this outcome… that even though Facebook is providing a great service to you for free, they tend to make far more money than each user would be willing to pay. The result is a scheme where…

  • each user would get paid a certain amount for submitting information that the company can use
  • because information becomes a paid service, tech companies could stop taking shady actions to try and capture data and just be up-front about what data they need, and pay for it
  • individual creators can make a livable wage by supplying valuable data

In effect, the scheme mirrors exactly what Nielsen used to do in the age of TV by paying people to respond to surveys about what they watch, or what Mechanical Turk aims to do now.

I’ll say that I’m pretty dubious of this proposal, both in terms of the incentives and the implementation. I don’t think large tech companies have much incentive to adopt this pattern, as it puts more of a focus on an area that both they and most users seem somewhat content to ignore this idea vs pay for a service. Perhaps we’ll see more paid services arise in the future.

Capitalism as a computer

One last final thought that I thought was interesting-modeling capitalism and free markets as a way of detecting information.

Effectively most markets move based upon a single set of inputs: the price of goods. The U.S. government doesn’t need to figure out how much corn should be produced by each individual farmer, each farmer can make their own choice depending on the price they can buy, cultivate, and sell corn crops at.

In this way, we’ve thought of free markets as having the best exchange of information for the last hundred years. No centrally planned system could even come close to understanding all of our innate preferences, or even the supply chains for fulfilling millions of different types of goods each day. Instead, each individual closest to a domain sets the prices, and then acts on those decisions.

But it does make you wonder… could there ever be such a system? Could there eventually be a computer system powerful enough to ensure that food always made it to those who need it?

This idea sounds farfetched to me, in part because of how bad computers are at understanding and modeling human preferences outside of the market context. Outside of a service knowing who our friends are, or what shows I want to watch next… how much more advanced would a system have to be to understand my hopes and dreams? It certainly seems like an area of HCI which is underexplored.