Coasean Compression

Markets have become astonishingly good at giving people what they want — for certain kinds of wants. You can order a computer with more processing power than a supercomputer from the 1990s and have it delivered tomorrow, or book a flight across the world in seconds.

But when it comes to some of the things people want most — love, friendship, belonging, meaning — the trend seems to run in the opposite direction.

Social media promised connection, yet the share of Americans with no close friends has quintupled since 1990.¹ Dating apps promised partnership, yet nearly half of Americans under 30 are single, roughly double the share three decades ago.² Many forces drive these trends, but the markets pitched as solutions aren’t delivering on their promises.

Why do markets coordinate so effectively for things like laptops and logistics, yet struggle with many of our deeper wants?

This is the first of three essays exploring that question. Here, I introduce what I call Coasean Compression: a reason markets lose sight of certain kinds of value as they scale. The second essay examines why these losses don’t self-correct. The third, what kinds of market upgrades might help address this, and better tie the economy to what actually matters.

Buying and Compression

When you buy something in the market you’re agreeing to a set of terms. Economists call this a contract: a specification of what’s to be delivered, at what price, under what conditions. When you buy a MacBook, for example, Apple promises a machine with a certain processor, memory, display, and battery life, and you pay the given price. If you’re buying the MacBook to do software engineering, those specifications largely track what you care about: a faster chip means your code compiles faster, more memory means more tabs and processes, longer battery life means more hours at a café. You can observe the specs and get a good sense of whether the machine will deliver on your underlying wants. If it does not, you can return it.

When the contract tracks what you actually care about, markets work remarkably well. Every year, competition makes the MacBook better, faster and cheaper. Since what was promised is legible and clear to both buyer and seller, you can return it if it’s not performing as intended. This is the case for electronics, appliances, raw materials, flights, package delivery, cloud storage.³ But most goods aren’t like this.⁴ Especially for many of our deeper needs, the contracts are incomplete at best.

Consider dating. From a dating service, you may want the conditions for finding a long-term partner, someone that clicks with you in a certain way. What you buy on a dating app is access or swipes. You’re left hoping these will convert to your underlying wants. If they don’t (which is often the case), you can’t go back and complain that you want a refund. The swipes were delivered and the contract was fulfilled.

You could imagine a contract that tried to track what you’re really after more closely: pay if a small number of genuine connections form within some time window, pay more if one of them turns into a lasting relationship, pay nothing if you got nothing out of it. But this contract becomes untenable. The thing being promised (genuine connection, a lasting relationship) is hard to specify in advance (what is meant by genuine connection?), hard to independently verify (did genuine connection occur?) and risky for the supplier (whether “genuine connection” occurs hinges on factors outside of their control). And so the contract most dating providers go with is pay-for-access.⁵

Fuller contracts do exist at the high end — elite matchmakers charge success fees tied to marriage. But that works because marriage is a legal event you can verify. The kind of qualitative match most people actually want from dating doesn’t have that property.

When there is a big skew between what’s being contracted around and what’s actually valuable to the customer, the business model no longer has to be tightly coupled to delivering user value. In the case of most dating apps, providers are incentivized to avoid delivering on what the customer actually wants as that would mean a churned user.

When Value Depends on Other People

A dating platform is arranging encounters between two people. For many goods, your experience depends on a whole group, which makes things even trickier.

Consider a neighborhood pub. Technically, customers are buying beer, but they come for the sense of familiarity, the chance encounter that turns into a conversation — in short: the “vibe.” But this vibe is an emergent property from who shows up and how they show up. You can’t swap out the crowd for random strangers and put a new hire behind the bar without killing the vibe. The contract captures only the private good (the beer). What people actually value is what economists would call a “positive externality”.

You could imagine a contract that prices in this externality: pay more if the pub maintains a stable community such that familiar faces appear on most visits and you feel like a participant rather than a consumer, pay less if it turns into an anonymous throughput machine. But similar to the dating contract, the outcome is difficult to specify (what counts as a good vibe?), hard to verify (did it actually happen?), risky to promise (the pub doesn’t directly control the vibe), and additionally, dependent on the participation of others (who else walks through the door and how they show up).

The problem is not that positive externalities exist, of course. The problem is that when they go unpriced, they’re foregone by optimization pressures from the market. At small scales, normative infrastructure (norms, reputation, social sanctions) make up for the incompleteness of the contract. Customers who talk too loudly get sneered at by others until they get the hint. A bar owner who let the vibe decay has his personal reputation on the line.⁶ But a franchise chain with rotating staff serving anonymous customers across a thousand locations cannot be constrained by this kind of normative infrastructure. No-one knows anyone else well enough to enforce norms and no one’s personal reputation is at stake when everyone’s an interchangeable customer or an interchangeable employee.⁷ And since the franchise bar has better unit economics, the franchise chain that delivers on the explicit contract is poised to outcompete the neighborhood bar that delivers on what people actually want.⁸

The Coasean Compression

In 1937, the economist Ronald Coase asked a simple question: if markets are so efficient, why do firms exist? His answer, which later won him a Nobel Prize, was that using markets come at a cost. Finding trading partners, negotiating terms, and enforcing agreements all impose costs, and when those costs rise, coordination moves inside firms or other institutions.

But there is another possibility, which is what this essay is about: rather than moving activity out of markets, you can replace what’s being contracted around with a proxy; you can think of the contract as having been “compressed”. Maintaining a contract for genuine connection becomes extremely expensive, but maintaining a contract for swipes works perfectly well in the market, in terms of transaction costs. Platforms can then market “connection,” “community,” or “love” without being meaningfully accountable for whether those things materialize. I’ve hinted at the frictions that drive this compression in the examples above. They fall into roughly four categories:⁹

Specification. With a MacBook, the translation from intention to specification is straightforward. With a sense of belonging or a life partner, it is not. The work of translating deep wants into deliverable terms might require introspection to identify what it is that you’re really seeking, and finding a way to write it out concretely in language that could hold up in case of dispute.

ResponseRyan Lowe argues that the work of specification isn’t only a translation cost: for many of these goods, the want is partly constituted by the act of articulating it. Compression runs from the buyer in.

Verification. Even if a deeper want could be specified, verifying that it has been satisfied is hard. You can benchmark a MacBook. You cannot easily benchmark whether a relationship worked or whether a festival delivered the sense of serendipity you wanted out of it. These outcomes are often subjective, emergent, and only legible over long time horizons. Besides, evaluating for example a friendship can make it feel transactional, and thereby depriving it of value.¹⁰

Risk. Whether a MacBook delivers as promised is largely in Apple’s hands. Whether a date leads to genuine connection is to a large extent outside the immediate control of Tinder. Richer specifications expose suppliers to more risk from factors they do not control: timing, mood, other people’s choices, contingency. Promising access is much safer than promising outcomes.

Configuration. A MacBook is a product sold to you as an individual. Events, parties, festivals, concerts, intellectual salons — their value to you as a participant depends on who else participates and how they show up. Trying to capture this complexity in a contract is very difficult, as contracts are generally bilateral between you and a provider.¹¹

This is what I mean by Coasean Compression. When what people want is easy to specify, easy to verify, safe to promise, and independent of who else shows up, markets see clearly and coordinate well. When it isn’t, markets at scale go partially blind, coordinating through proxies that carry less and less of the original value. Hence we see a proliferation of dating apps and AI companions, while becoming more lonely and isolated than ever.

Two questions come up naturally here. If markets are only delivering thin proxies, wouldn’t you expect competition to close the gap? And if markets can’t handle dating or friendship or adventure, why not just find those things elsewhere — in communities, churches, neighborhoods?

I address these in the next essay. The short answer is that the compressed version gets cheaper every year while the fuller version gets more expensive, and the compressed version can erode the non-market spaces you’d presumably exit into.

In the third post, I’ll outline some ideas for how to upgrade markets to make sure what we actually care about becomes legible to them at scale. I don’t think this is an intractable problem, especially not with AI. Markets have been reimagined many times in the past, and it’s time to do it again.

Thanks to Joe Edelman, Merlin Stein, Maximilian Kroner-Dale, and Tobias Werner for comments on earlier drafts.