Does value capture even matter?

A story of prices and social scalability

Few topics in the cryptocurrency world are as passionately debated as the question of value capture and price. Which tokens will appreciate in value, and which will be worthless? Who will be the winners? How and why will this happen? These questions drive investment theses, public attention, crypto-valuation theories, and even determine which projects people will want to get involved with. Fat protocols, hyperbitcoinization, staking, work tokens, on-chain cash flows — you name it.

Yet, one aspect has been overlooked so far: why does value capture matter at all? The answer may seem blindingly obvious at first, but I believe it’s actually worth formulating clearly, so that the consequences can be explored.

Note that I will not be diving into the various valuation theories here. Instead, I want to focus on the “why” of value capture, and explore what the answer implies for the people thinking about and designing those systems.

Why do we care?

When moon?

Sure, value capture is primordial for investors. Special cases aside, it’s safe to assume that anyone buying a token for any reason that involves holding it for a certain amount of time expects its price to rise. Thus, it is generally expected by those buyers that as a token sees more adoption, its value increases accordingly.

But still, this doesn’t answer the question: why is it important that token holders receive profits? Why should the token price be directly correlated to the value created by the use of the network? For example, if a certain token becomes widely adopted but its value remains the same, it might not make for a great investment, but that doesn’t prevent the network of participants from doing their stuff (theoretically).

Going a bit further, as a token increases in price, this value goes to the ones that are holding that token during this period of price increase: holders can be investors, miners, stakers, speculators, contributors (in case of a work token). But it also rewards those that receive payments that are denominated in that token —such as Bitcoin miners.

This brings us to our first point: incentives scale with price.

A price increase rewards holders and contributors, increases the value of payouts to miners or some subset of contributors, and provides strong virality by bringing in new investors and participants.

Now, this may seem obvious — and it is. So, onto the second point: reliable value capture is necessary to sustain a price correlated with the activity of the network.

Which also means that a network with high activity that is creating tremendous amounts of value for its users might not capture any of it. The simplest way to see it is to look at the “thin” protocols of the Internet, but in the case of cryptocurrency networks, this can happen if there are no reasons for anybody to hold the network token for a certain amount of time. Aka there’s no demand for the token — either because it is a “utility” token that is bought and sold as fast as possible, or because the applications built on top simply bypass it (which could happen to Ethereum, as many have pointed out¹).

In the case of Bitcoin, the value capture is very straightforward: acting as a monetary good, the value it provides is equal to the value stored in bitcoins. Combine that with a fixed (or predictible) supply and you get a price that is by definition correlated to the value created by the network. In other cases, this value capture can come in the form of returns to staking, fees paid out to workers, and more. The important part is that it should be reliable relative to the actual value of the network.

Combining the previous two arguments, we finally get to our main point. Why does value capture matter? The answer is deceptively simple: value capture is necessary for social scalability.

Let’s unpack that for a second.

Understanding social scalability

Social scalability is the ability of an institution […] to overcome shortcomings in human minds […] that limit who or how many can successfully participate.

Nick Szabo coined the concept of social scalability in his seminal essay on “Money, blockchains and social scalability”, as he was thinking about the specific property that Bitcoin gained through its unique design, by sacrificing efficiency and vast amounts of energy to enable a network of untrusted participants to successfully coordinate.

Fundamentally, achieving better social scalability is about new technologies or institutions that enable us to overcome previous human limitations and coordinate for a certain purpose on a larger scale than we could before.

One of the prime examples of a technology and an institution enabling much greater social scalability is the combination of money and markets. Essentially, these two lower the mental costs of trade by solving the problem of the double coincidence of wants², drastically reduce the trust needed in other participants by relying on their self-interested and not altruistic motivations, and improve the transmission of information between participants through the price mechanism³.

In the case of Bitcoin, the main breakthrough is very high trust minimization, by reducing vulnerability to other actors trying to counterfeit money or double-spend their holdings. Without the need for external third parties, the network can scale to any number of participants anywhere, not limited by any existing jurisdiction or institution.

Every cryptocurrency potentially has the whole world as its playground.

The honeypot and the castle

So, how are value capture and social scalability correlated exactly?

We know that in the case of Bitcoin, the social scalability that comes from trust minimization is secured by incentives: as more value is held in bitcoins, the price increases and so do the rewards for the miners, leading to an increase in hash rate and in security of the network directly proportional to the value stored.

In the case of Ethereum, there has been a lot of debate about the actual value of the ETH token¹, but one thing is sure: if the ETH token doesn’t reliably capture value with adoption, we’re running straight into a tragedy of the commons where incredible value may be created by the applications on top, but the base layer is highly unsecure, because the price of ETH remained low.

Without reliable value capture, the honeypot keeps on growing, but the castle around it stays a wooden hut. Once the bears become hungry enough, they’ll just tear it down.

Basically, the same reasons that make companies much better at scaling than non-profit organizations also apply to decentralized networks: as size increases, more work needs to be done, thus the economic incentives need to grow as well, to keep fueling the machine.

But if those incentives are able to scale, then there are rational motivations for new or existing actors within the company or the network to contribute even more, creating further value and reinforcing incentives, and the network or company grows until friction takes over.

Value capture creates the self-reinforcing feedback loops that powers a network.

But now it also becomes clear that optimizing for value is a mean, and not a goal. What we should be aiming for is social scalability.

Towards greater social scalability

The only problem is that social scalability cannot be measured directly, making it hard to optimize. However, there are some proxies that can be very useful to think about it more precisely.

Ideally, a network should optimize towards providing the maximum amount of value to its participants before it gets too big and friction costs take over. It would be a good way to measure social scalability. Still, “value” is a nebulous concept here. It depends on the purpose of the network and is often not quantifiable — we don’t know the utility function of each participant regarding the benefits they get from being in the network.

Another, more straightforward way to approach social scalability is simply the number of participants that can successfully participate in the network. Once again, scale here is bounded by friction costs that prevent new entrants from receiving a benefit after a certain point. For example, if 7 billion people tried to directly use the Bitcoin blockchain for all their transactions, we’d be in serious trouble. Transaction fees would rise so high, that most people would drop out quickly, thus lowering transaction fees to a more reasonable level. This is what friction looks like.

Let’s keep the concept of friction in mind, it’s going to come in handy.

Generally, increasing the number of participants that can benefit from a network works as a good proxy for maximizing the value created — but like all good metrics, the trick lies in how you use it. Obviously adding massive inconvenience to all existing participants just for the sake of bringing in a few more is not a good idea.

Now, since value capture is so important and creates this super-strong self-reinforcing incentive feedback loop, I should definitely focus on this really hard for my token, right? Well, no. Because the exact same thing applies: value capture is a tool, and the trick lies in how you use it.

Adding staking mechanisms everywhere just so that your users have to hold their tokens for some time is simply not a good design. Sure, your token might theoretically be better at accruing value, but the friction just gets so high that you’re killing your social scalability. Without users, you can be pretty sure that your token won’t be worth much in the long run, despite its great velocity mechanics. Friction is ruthless.

Trying to improve one aspect of your network, like better price appreciation, is bound to have collateral effects, and thinking about the consequences of each design choice is absolutely necessary.

Sometimes it can lead to counterintuitive decisions: transaction fees add friction but can lead to a much better experience, as some value is captured and redistributed to service providers that contribute to the network. Add too many fees, and the network will be limited to the people that value very highly the service it provides. As an example, the problem around fees in Augur to pay reporters and market creators is an interesting one, as they are both weighing down on the users and necessary for the incentive structure. Adding a token to your application, or even a secondary token to the economics of your network, creates friction — but the coordination benefits can vastly outweigh this friction in terms of social scalability.

Another fascinating possibility is that we could start seeing networks self-organizing around incentives to start providing services on-chain, as open financial networks, markets for storage and computing power, new forms of corporations operating as DAOs and more. Redistributing the value created in the form of on-chain cash flows to the contributors of those networks, combined with the lack of friction of operating through smart contracts, would create exactly the self-reinforcing feedback loops needed for these systems to grow to scales previously unattainable.⁴

Finally, I believe it has become clear now that we should be thinking more about how these networks we are building will be able to grow on human terms, and not just about how they should theoretically operate and accrue value.

Scalability is not just a technical term. It also encompasses early adoption, capacity for growth and the technical and social limits of the network as an institution in which people participate.

The proper question is not just “Can this token capture value?” but “How does this token capture value?” — and where does it accrue, who benefits from it, the incentives it creates, and how it all helps the network grow and provide even more value in the end. If it doesn’t, forget about the token.

— — — — — — — — —

  1. The latest debate has been around this Techcrunch article from Jeremy Rubin on how Ethereum could be widely successful but ETH could still go to zero. See Vitalik’s anwer here. Also see this thread from Martin Köppelmann.
  2. Shelling Out: The Origins of Money — Nick Szabo (2002)
  3. The Use of Knowledge in Society — Hayek (1945)
  4. See this excellent (and somewhat crazy) post by Lawson Baker

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