Now, the disagreements:

4. The case for BTC as leading SoV contender is not that strong, and weakening

From where we are today, an objective observer would give Bitcoin significantly higher odds than ETH of becoming [the dominant non-sovereign] store of value. (p 11)

Relative to John’s more general arguments about utility protocols vs stores of value, this claim for Bitcoin takes up only a small portion of the paper (a paragraph on p 11, pp 19–21), and I find it unconvincing.

People give too much weight to how coins are branded. So (in 2018…), Bitcoin = store of value, Bitcoin Cash = payments, Ethereum = “virtual machine”/“utility token”/platform for smart contracts. But let’s forget these labels for a minute. In particular, forget about smart contracts — how does ETH compare to BTC, purely as a store of value?

This is probably the question that’s preoccupied me the most since late 2015: it would fill an essay of its own (which is probably why John focused on the more general analysis). Bitcoin retains the lead in important areas, like track record, public/investor awareness, code robustness and (arguably) developer depth, which is why I’m not as big an ETH bull as, say, Eli Dourado. Still, even in these strength areas BTC’s lead has shrunk significantly since the scaling wars broke out in 2015, and on important criteria like pace of development, developer adoption and decision-making process, I’d give ETH the edge.

BTC brands itself as immutable, whereas the ETH community projects a murkier “immutable, except when a change is totally reasonable”. But the distinction is only a matter of degree and is often exaggerated. ETH hasn’t suffered a split or interfered with its ledger since the DAO fork of July 2016, just before its first birthday. Meanwhile, most Bitcoin devs acknowledge that 1. A hard fork will be needed at some point and 2. A minority will probably reject it. So it’s not as simple as “more immutable = better SoV”. In fact there are many situations, like a mining cartel attack or a SHA-256 vulnerability, where refusing to modify the protocol would make the ledger less immutable.

Plus, again, price trajectory is a pretty fundamental measure for a store of value, and year on year ETH/BTC has trended steeply up. It’s easy to forget that ETH started 2017 below 5% of BTC’s market cap (currently 35%), and started 2015 not yet in production.

5. Forking blockchains viably is not so easy, open-source or not

A central theme of the paper is that utility protocols will have trouble capturing economic rents, because they’re vulnerable to being forked:

A protocol fork is analogous to a team of Facebook developers who decide one Tuesday morning that Zuck is not paying them enough; they could simply flip a switch and use the servers and software that run Facebook to run a new Facebook that is functionally identical, with all the same users and data up to that point. That can, does, and will happen all the time in protocol-land, but would be theft in the context of private companies that own their code, data, intellectual property, etc. Those property rights are why Zuck is rich, and their absence in the protocol economy has profound implications. The ability to fork protocols maximises utility for users but suppresses economic rent for token holders. (p 4)

I believe this greatly overestimates 1. the ease of getting users to adopt a fork, and 2. the role of the law in protecting incumbents against forks. Network effects, switching costs, coordination problems — call it what you will, but users resist switching, especially if they need to be compatible with each other and thus can only switch en masse.

Switching costs are relatively low now because very few people or institutions rely critically on any blockchain, and those who do are tech-savvy early adopters. As user base grows, switching will get harder. To a software developer this is a familiar problem: most people want to ditch obsolete technologies like PHP, Python 2, early versions of HTML, etc, and yet they stick around. It’s true that these migrations involve more effort than a typical blockchain fork, but even a trivial fix — say, renaming a confusingly-named function — is hard to coordinate.

Furthermore, a healthy blockchain/token protocol isn’t just a static chunk of software, but a dynamic, evolving project. If you fork off your own, cheaper protocol, but the devs stay with the old code, good luck getting users to follow you. This is why the vast majority of blockchain forks without majority dev backing have underperformed the chains they forked from.

The “Forking is easy” argument has echoes of “Settlement over blockchain can save banks $10b per year.” Yes, banking infrastructure is antiquated, but that was never because better tech was unavailable. It’s because inducing a community to switch is hard, especially when the cost to each user is moderate. Similarly, blockchains may have to get quite expensive before a fork has a real chance of adoption.

6. A token’s price determines the amount of computing resources allocated to it, not the other way around

Many sections suggest that the amount of computing resources allocated to a token’s network drive its price, eg:

If Ethereum successfully moves to a proof-of-stake mining system and thereby substantially reduces the computational inefficiency inherent in proof-of-work where 99% of the computing power goes to proof-of-work and only a very small portion to actually maintaining the ledger, the PQ of the blockchain would fall massively and along with it the Ethereum network value. (p 10)

This seems to me completely backwards. The market dictates a token’s price, as the gold market dictates gold’s. That price guides how much miners are willing to pay to mine it, and therefore how secure it is from attack. That is, as Elliot Olds noted, price drives computing resources (and thus security) — not the other way around.

One might respond that the cost of gold extraction does drive the price of gold: cheaper extraction releases more gold into circulation, driving down the price. But tokens like Bitcoin are fundamentally different in that their supply is inelastic: not only the total supply but also the rate of issuance are algorithmically set in stone (apart from minor week-to-week fluctuations).

Quite likely John meant this claim only in the context of utility tokens, in equilibrium. But then the error is assuming ETH’s value derives from utility, rather than from gold-like store-of-value adoption as BTC’s does: see “Don’t read too much into branding” above.

7. Proof-of-stake (PoS) is not prima facie bearish for investors

A consequence of computing resources not driving price is that there’s no obvious reason reducing the computing resources would reduce price: see again Elliot’s post above.

One way to dissect the value of a cryptoasset like Bitcoin is as a hybrid of a payment tech startup and an e-gold. The startup has value because it provides a useful service, or is hoped to in the future; the e-gold’s value is harder to analyze, but comes down to a “collective delusion” — “Because others believe it has value, you do too.”

So, if you believe a token’s price is mostly driven by the startup component, then yes, cutting the cost of providing the service will plausibly reduce the token’s price: find a way to operate flights more cheaply, and passengers will end up paying less. But if a token’s price is mostly from its e-gold component, no such market efficiency applies. When I buy a Jackson Pollock, I don’t care about cost of production: the scarcity is the product.

Another way of putting it: When I buy a flight, I’m looking for the cheapest fare that will get me to my destination. But when I invest $100 in gold, I don’t care how many grams of gold I get. Dollar-demand for a store of value isn’t correlated to its cost of production the way dollar-demand for a service is.

We may get to see the “computing drives price” hypothesis tested if ETH manages its planned switch to PoS: will its price plummet?

8. Proof-of-work (PoW) to PoS will reduce computation and energy use by much more than 100x

The impetus for moving from proof-of-work to proof-of-stake is to reduce the amount of computational resource and energy required to maintain the network by a couple orders of magnitude. (p 5)

“Minor” point, but this understates the saving: a better way to think of it is, how much gas does one save by moving from a gas-powered car to an electric one? As one experimental staking pool says, “In the future …, we can’t tell if they’re staking using a laptop with poor resources or a giant Amazon EC2 instance.”

PoS is not so much an efficiency improvement as a qualitative shift from an external (“exogenous”, “out-of-network”) voting unit — hashes, or basically electricity — to an internal (“endogenous”, “in-network”) one: the token itself.

9. Payments/transactions are an important driver of token value

John analyzes the payments/medium-of-exchange (MoE) use case vs store-of-value (SoV) at some length, esp pp 12–17. He concludes that the two are likely to be handled by different tokens, and that SoV offers greater rewards for investors.

My main critique here is that the traditional separation of these functions was largely because no form of money satisfied both roles. Handy means of payment like credit cards don’t come bundled with a reliably scarce asset, and scarce assets like gold aren’t convenient for spending. But there’s no fundamental reason one cryptoasset can’t do both. Scarcity is effectively a solved problem since Satoshi — most of the 1,000+ cryptoassets achieve it — so ease of spending, with its well-known scaling challenges, is a much greater differentiator.

Why should we expect an easy-to-spend token to prevail as SoV? This is an old topic: in brief, my answer is that one lesson of the trendy equation of exchange, MV=PQ, is that increasing usage for payments creates upward pressure on token price, assuming roughly stable token velocity.

How important will this spending pressure be in determining which tokens dominate SoV? An open question, but my view has always been that if token X reaches billions of users, and token Y only millions, X is likely to dominate market cap as well.

10. Token velocity is likely to stay roughly stable, compared to price

Friction moving among cryptoassets is already low and will quickly disappear entirely with technologies like atomic swaps. Consequently, one would expect velocity to be very high at equilibrium. (p 6)

We agree that high payment volume could fail to lift token price, if velocity grows too. But, as discussed elsewhere, I don’t see why velocity would climb this way. What is the individual user’s incentive to spend a token immediately, apart from price volatility, which we can expect to lessen over time?

It is possible that the velocity of utility tokens will grow: I’ve heard claims that ETH’s velocity is already ~10x BTC’s. But four notes on this case: