monetary – Earlybirds Invest

The primary expense that must be paid by a blockchain is that of security. The blockchain must pay miners or validators to economically participate in its consensus protocol, whether proof of work or proof of stake, and this inevitably incurs some cost. There are two ways to pay for this cost: inflation and transaction fees. Currently, Bitcoin and Ethereum, the two leading proof-of-work blockchains, both use high levels of inflation to pay for security; the Bitcoin community presently intends to decrease the inflation over time and eventually switch to a transaction-fee-only model. NXT, one of the larger proof-of-stake blockchains, pays for security entirely with transaction fees, and in fact has negative net inflation because some on-chain features require destroying NXT; the current supply is 0.1% lower than the original 1 billion. The question is, how much “defense spending” is required for a blockchain to be secure, and given a particular amount of spending required, which is the best way to get it?

Absolute size of PoW / PoS Rewards

To provide some empirical data for the next section, let us consider bitcoin as an example. Over the past few years, bitcoin transaction revenues have been in the range of 15-75 BTC per day, or about 0.35 BTC per block (or 1.4% of current mining rewards), and this has remained true throughout large changes in the level of adoption.

It is not difficult to see why this may be the case: increases in BTC adoption will increase the total sum of USD-denominated fees (whether through transaction volume increases or average fee increases or a combination of both) but also decrease the amount of BTC in a given quantity of USD, so it is entirely reasonable that, absent exogenous block size crises, changes in adoption that do not come with changes to underlying market structure will simply leave the BTC-denominanted total transaction fee levels largely unchanged.

In 25 years, bitcoin mining rewards are going to almost disappear; hence, the 0.35 BTC per block will be the only source of revenue. At today’s prices, this works out to ~$35000 per day or $10 million per year. We can estimate the cost of buying up enough mining power to take over the network given these conditions in several ways.

First, we can look at the network hashpower and the cost of consumer miners. The network currently has 1471723 TH/s of hashpower, the best available miners cost $100 per 1 TH/s, so buying enough of these miners to overwhelm the existing network will cost ~$147 million USD. If we take away mining rewards, revenues will decrease by a factor of 36, so the mining ecosystem will in the long term decrease by a factor of 36, so the cost becomes $4.08m USD. Note that this is if you are buying new miners; if you are willing to buy existing miners, then you need to only buy half the network, knocking the cost of what Tim Swanson calls a “Maginot line” attack all the way down to ~$2.04m USD.

However, professional mining farms are likely able to obtain miners at substantially cheaper than consumer costs. We can look at the available information on Bitfury’s $100 million data center, which is expected to consume 100 MW of electricity. The farm will contain a combination of 28nm and 16nm chips; the 16nm chips “achieve energy efficiency of 0.06 joules per gigahash”. Since we care about determining the cost for a new attacker, we will assume that an attacker replicating Bitfury’s feat will use 16nm chips exclusively. 100 MW at 0.06 joules per gigahash (physics reminder: 1 joule per GH = 1 watt per GH/sec) is 1.67 billion GH/s, or 1.67M TH/s. Hence, Bitfury was able to do $60 per TH/s, a statistic that would give a $2.45m cost of attacking “from outside” and a $1.22m cost from buying existing miners.

Hence, we have $1.2-4m as an approximate estimate for a “Maginot line attack” against a fee-only network. Cheaper attacks (eg. “renting” hardware) may cost 10-100 times less. If the bitcoin ecosystem increases in size, then this value will of course increase, but then the size of transactions conducted over the network will also increase and so the incentive to attack will also increase. Is this level of security enough in order to secure the blockchain against attacks? It is hard to tell; it is my own opinion that the risk is very high that this is insufficient and so it is dangerous for a blockchain protocol to commit itself to this level of security with no way of increasing it (note that Ethereum’s current proof of work carries no fundamental improvements to Bitcoin’s in this regard; this is why I personally have not been willing to commit to an ether supply cap at this point).

In a proof of stake context, security is likely to be substantially higher. To see why, note that the ratio between the computed cost of taking over the bitcoin network, and the annual mining revenue ($932 million at current BTC price levels), is extremely low: the capital costs are only worth about two months of revenue. In a proof of stake context, the cost of deposits should be equal to the infinite future discounted sum of the returns; that is, assuming a risk-adjusted discount rate of, say, 5%, the capital costs are worth 20 years of revenue. Note that if ASIC miners consumed no electricity and lasted forever, the equilibrium in proof of work would be the same (with the exception that proof of work would still be more “wasteful” than proof of stake in an economic sense, and recovery from successful attacks would be harder); however, because electricity and especially hardware depreciation do make up the great bulk of the costs of ASIC mining, the large discrepancy exists. Hence, with proof of stake, we may see an attack cost of $20-100 million for a network the size of Bitcoin; hence it is more likely that the level of security will be enough, but still not certain.

The Ramsey Problem

Let us suppose that relying purely on current transaction fees is insufficient to secure the network. There are two ways to raise more revenue. One is to increase transaction fees by constraining supply to below efficient levels, and the other is to add inflation. How do we choose which one, or what proportions of both, to use?

Fortunately, there is an established rule in economics for solving the problem in a way that minimizes economic deadweight loss, known as Ramsey pricing. Ramsey’s original scenario was as follows. Suppose that there is a regulated monopoly that has the requirement to achieve a particular profit target (possibly to break even after paying fixed costs), and competitive pricing (ie. where the price of a good was set to equal the marginal cost of producing one more unit of the good) would not be sufficient to achieve that requirement. The Ramsey rule says that markup should be inversely proportional to demand elasticity, ie. if a 1% increase in price in good A causes a 2% reduction in demand, whereas a 1% increase in price in good B causes a 4% reduction in demand, then the socially optimal thing to do is to have the markup on good A be twice as high as the markup on good B (you may notice that this essentially decreases demand uniformly).

The reason why this kind of balanced approach is taken, rather than just putting the entire markup on the most inelastic part of the demand, is that the harm from charging prices above marginal cost goes up with the square of the markup. Suppose that a given item takes $20 to produce, and you charge $21. There are likely a few people who value the item at somewhere between $20 and $21 (we’ll say average of $20.5), and it is a tragic loss to society that these people will not be able to buy the item even though they would gain more from having it than the seller would lose from giving it up. However, the number of people is small and the net loss (average $0.5) is small. Now, suppose that you charge $30. There are now likely ten times more people with “reserve prices” between $20 and $30, and their average valuation is likely around $25; hence, there are ten times more people who suffer, and the average social loss from each one of them is now $5 instead of $0.5, and so the net social loss is 100x greater. Because of this superlinear growth, taking a little from everyone is less bad than taking a lot from one small group.

In Bitcoin’s case, right now we see that transaction fees are and consistently have been in the neighborhood of ~50 BTC per day, or ~18000 BTC per year, which is ~0.1% of the coin supply. We can estimate as a first approximation that, say, a 2x fee increase would reduce transaction load by 20%. In practice, it seems like bitcoin fees are up ~2x since a year ago and it seems plausible that transaction load is now ~20% stunted compared to what it would be without the fee increase (see this rough projection); these estimates are highly unscientific but they are a decent first approximation.

Now, suppose that 0.5% annual inflation would reduce interest in holding BTC by perhaps 10%, but we’ll conservatively say 25%. If at some point the Bitcoin community decides that it wants to increase security expenditures by ~200,000 BTC per year, then under those estimates, and assuming that current txfees are optimal before taking into account security expenditure considerations, the optimum would be to push up fees by 2.96x and introduce 0.784% annual inflation. Other estimates of these measures would give other results, but in any case the optimal level of both the fee increase and the inflation would be nonzero. I use Bitcoin as an example because it is the one case where we can actually try to observe the effects of growing usage restrained by a fixed cap, but identical arguments apply to Ethereum as well.

Game-Theoretic Attacks

There is also another argument to bolster the case for inflation. This is that relying on transaction fees too much opens up the playing field for a very large and difficult-to-analyze category of game-theoretic attacks. The fundamental cause is simple: if you act in a way that prevents another block from getting into the chain, then you can steal that block’s transactions. Hence there is an incentive for a validator to not just help themselves, but also to hurt others. This is even more direct than selfish-mining attacks, as in the case of selfish mining you hurt a specific validator to the benefit of all other validators, whereas here there are often opportunities for the attacker to benefit exclusively.

In proof of work, one simple attack would be that if you see a block with a high fee, you attempt to mine a sister block containing the same transactions, and then offer a bounty of 1 BTC to the next miner to mine on top of your block, so that subsequent validators have the incentive to include your block and not the original. Of course, the original miner can then follow up by increasing the bounty further, starting a bidding war, and the miner could also pre-empt such attacks by voluntarily giving up most of the fee to the creator of the next block; the end result is hard to predict and it’s not at all clear that it is anywhere close to efficient for the network. In proof of stake, similar attacks are possible.

How to distribute fees?

Even given a particular distribution of revenues from inflation and revenues from transaction fees, there is an additional choice of how the transaction fees are collected. Though most protocols so far have taken one single route, there is actually quite a bit of latitude here. The three primary choices are:

Arguably, the more salient difference is between the first and the second; the difference between the second and the third can be described as a targeting policy choice, and so we will deal with this issue separately in a later section. The difference between the first two options is this: if the validator that creates a block gets the fees, that validator has an incentive equal to the size of the fees to include as many transactions as possible. If it’s the validators equally, each one has a negligible incentive.

Note that literally redistributing 100% of fees (or, for that matter, any fixed percentage of fees) is infeasible due to “tax evasion” attacks via side-channel payment: instead of adding a transaction fee using the standard mechanism, transaction senders will put a zero or near-zero “official fee” and pay validators directly via other cryptocurrencies (or even PayPal), allowing validators to collect 100% of the revenue. However, we can get what we want by using another trick: determine in protocol a minimum fee that transactions must pay, and have the protocol “confiscate” that portion but let the miners keep the entire excess (alternatively, miners keep all transaction fees but must in turn pay a fee per byte or unit gas to the protocol; this a mathematically equivalent formulation). This removes tax evasion incentives, while still placing a large portion of transaction fee revenue under the control of the protocol, allowing us to keep fee-based issuance without introducing the game-theoretic malicentives of a traditional pure-fee model.

One possible algorithm for determining this minimum fee would be a difficulty-like adjustment process that targets a medium-term average gas usage equal to 1/3 of the protocol gas limit, decreasing the minimum fee if average usage is below this value and increasing the minimum fee if average usage is higher.

We can extend this model further to provide other interesting properties. One possibility is that of a flexible gas limit: instead of a hard gas limit that blocks cannot exceed, we have a soft limit G1 and a hard limit G2 (say, G2 = 2 * G1). Suppose that the protocol fee is 20 shannon per gas (in non-Ethereum contexts, substitute other cryptocurrency units and “bytes” or other block resource limits as needed). All transactions up to G1 would have to pay 20 shannon per gas. Above that point, however, fees would increase: at (G2 + G1) / 2, the marginal unit of gas would cost 40 shannon, at (3 * G2 + G1) / 4 it would go up to 80 shannon, and so forth until hitting a limit of infinity at G2. This would give the chain a limited ability to expand capacity to meet sudden spikes in demand, reducing the price shock (a feature that some critics of the concept of a “fee market” may find attractive).

What to Target

Let us suppose that we agree with the points above. Then, a question still remains: how do we target our policy variables, and particularly inflation? Do we target a fixed level of participation in proof of stake (eg. 30% of all ether), and adjust interest rates to compensate? Do we target a fixed level of total inflation? Or do we just set a fixed interest rate, and allow participation and inflation to adjust? Or do we take some middle road where greater interest in participating leads to a combination of increased inflation, increased participation and a lower interest rate?

In general, tradeoffs between targeting rules are fundamentally tradeoffs about what kinds of uncertainty we are more willing to accept, and what variables we want to reduce volatility on. The main reason to target a fixed level of participation is to have certainty about the level of security. The main reason to target a fixed level of inflation is to satisfy the demands of some token holders for supply predictability, and at the same time have a weaker but still present guarantee about security (it is theoretically possible that in equilibrium only 5% of ether would be participating, but in that case it would be getting a high interest rate, creating a partial counter-pressure). The main reason to target a fixed interest rate is to minimize selfish-validating risks, as there would be no way for a validator to benefit themselves simply by hurting the interests of other validators. A hybrid route in proof of stake could combine these guarantees, for example providing selfish mining protection if possible but sticking to a hard minimum target of 5% stake participation.

Now, we can also get to discussing the difference between redistributing and burning transaction fees. It is clear that, in expectation, the two are equivalent: redistributing 50 ETH per day and inflating 50 ETH per day is the same as burning 50 ETH per day and inflating 100 ETH per day. The tradeoff, once again, comes in the variance. If fees are redistributed, then we have more certainty about the supply, but less certainty about the level of security, as we have certainty about the size of the validation incentive. If fees are burned, we lose certainty about the supply, but gain certainty about the size of the validation incentive and hence the level of security. Burning fees also has the benefit that it minimizes cartel risks, as validators cannot gain as much by artificially pushing transaction fees up (eg. through censorship, or via capacity-restriction soft forks). Once again, a hybrid route is possible and may well be optimal, though at present it seems like an approach targeted more toward burning fees, and thereby accepting an uncertain cryptocurrency supply that may well see low decreases on net during high-usage times and low increases on net during low-usage times, is best. If usage is high enough, this may even lead to low deflation on average.

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Stablecoins Are a Monetary Revolution in the Making https://earlybirdsinvest.com/stablecoins-are-a-monetary-revolution-in-the-making/ https://earlybirdsinvest.com/stablecoins-are-a-monetary-revolution-in-the-making/#respond Mon, 23 Jun 2025 23:08:12 +0000 https://earlybirdsinvest.com/stablecoins-are-a-monetary-revolution-in-the-making/

We may be on the verge of a revolution in monetary finance that is the century-long dream of many prominent economists. Financial innovation is laying the foundation for their dream just as the U.S. political economy is shifting to support it. This revolution, if it proceeds, has major implications for global finance, economic development, and geopolitics, and will create many winners and losers. The shift I’m referring to is “narrow banking” built on stablecoins. If those are unfamiliar concepts to you, let me review 800 years of financial innovation in 500 words.

The origins of fractional reserve banking

Our current financial system is built on the concept of fractional-reserve banking. In the 13th and 14th century, Italian money changers cum bankers began to figure out that because depositors (rarely) demand their money back at the same time, they could hold only a fraction of the coin needed to back their deposits. Not only was this more profitable but it also facilitated payments across great distances: rather than send gold coins over dangerous roads, a Medici in Florence need only sent a letter to his agent in Venice instructing him to debit one account and credit another.

Though highly profitable and effective for payments in normal circumstances, fractional reserve banking has a downside. Its inherent leverage makes the system unstable. A downturn in the economy might cause more depositors to withdraw savings at once, or worse, generate rumors that the loans backing banks’ deposits are going to default, causing a “run” on the bank. A bank unable to meet its depositors’ demands collapses into bankruptcy. But more than just depositors’ wealth is lost when banks fail in a fractional reserve system. Because banks both generate credit and facilitate payment, economic activity is severely constricted when banks fail since payment for goods and services is impaired and lending isn’t available for new investment.

Governments attempt to fix its problems

Over the centuries, as banks became simultaneously more leveraged and more critical to economic functioning, governments stepped in to try to reduce the risks of banking crises. In 1668, Sweden chartered the first central bank, the Riksbank, to lend to other banks experiencing runs. The Bank of England followed 26 years later. While that helped solve liquidity problems (banks with good assets but insufficient cash), it didn’t stop solvency crises (banks with bad loans). The U.S. created deposit insurance in 1933 to help stop solvency-based bank runs, but as illustrated by the many banking crises since, including the U.S. subprime mortgage crisis in 2008, neither deposit insurance nor bank capital regulations solved fractional reserve banking’s endemic fragility. Government intervention reduced only the frequency of crises and shifted their costs from depositors to taxpayers.

Economists build a better mousetrap

Around the time that the Roosevelt Administration was introducing deposit insurance, some of the era’s top names in economics at the University of Chicago were hatching a different solution: the so-called Chicago Plan, or “narrow banking.” During the U.S. savings and loan crisis of the 1980s and ‘90s the idea had a resurgence among economists.

Narrow banking solves the central problem of fractional reserve banking by separating the critical functions of payments and money creation from credit creation. Many people think that central banks create money. But that’s not true in a fractional reserve system: banks do. Central banks manage the rate at which banks manufacture money (by controlling their access to reserves), but money is created by banks whenever they lend money, magically generating corresponding deposits in the process. This system – and its chaotic unwind – ties money growth to credit growth, and through banks’ network effects, to payments.

Splitting banks in two

The Chicago Plan separates the critical functions of money creation and payments from credit by splitting banking functions in two. “Narrow” banks that accept deposits and facilitate payments are required to back their deposits one for one with safe instruments like T-bills or central bank reserves. Think of them like a money market fund with a debit card. Lending is done by “broad” or “merchant” banks that fund themselves with equity capital or long-term bonds, hence aren’t subject to runs.

This segmentation of banking makes each function safe from the others. Deposit runs are eliminated because they are fully backed by high-quality assets (as well as access to the central bank). Since narrow banks facilitate payments, their safety removes the risk to the payments system. Because money is no longer created by credit creation, bad lending decisions at merchant banks don’t affect the money supply, deposits or payments. Conversely, neither natural fluctuations in the economy’s demand for money – booms or recessions – nor concerns over loan quality affect merchant banks’ lending because it is funded with long-term debt and equity.

But why didn’t we adopt this wonderful solution?

You may be asking yourself now, “If narrow banking is so wonderful, why don’t we have it today?” The answer is twofold: the transition is painful and there has never been a political economy to support legislation to make the change.

Because narrow banking requires 100% backing of deposits by either T-bills or central bank reserves, the transition to narrow banking would require existing banks to either call in their loans, shrinking the money supply dramatically, or if they could find non-bank buyers, sell off their loan portfolios to buy short-term government paper. Both would precipitate a massive credit crunch, and the former would create liquidity shortages and payments problems.

As to the political economy, fractional reserve banking is extremely profitable – “a license to steal” as my father calls it (admiringly) – and generates a lot of jobs. Economists, in contrast, are a small group that are questionably employed themselves. As anyone in Washington, DC will tell you, the American Bankers Association (ABA) is among the most powerful lobbies in town. The same play with different actors runs in London, Brussels, Zürich, Tokyo, et cetera. Hence the continuance of fractional reserve banking is not a banking conspiracy; it’s just been good politics and cautious economics.

Financial innovation meets shifting politics

That may no longer be so. Both the costs of transition and the political economy have changed, particularly in the U.S. Developments in decentralized finance – a.k.a. “DeFi” or “crypto” – and the coincident evolution of the U.S. political economy, national interests, and financial structure have generated conditions that make a shift to narrow banking in the U.S. not only feasible, but increasingly likely in my view.

Let’s start with the critical DeFi development: the rapid growth of stablecoins. Stablecoins are decentralized “digital dollars” (or euros, yen, et cetera). Unlike central bank digital currencies (CBDCs) that are issued, cleared and settled centrally by central banks, stablecoins are privately created “digital tokens” (electronic records). Like cryptocurrencies, ownership and transactions are stored and cleared through blockchain technology on distributed ledgers (decentralized registries). The combination of blockchain immutability and universally replicated registries facilitates trust between unknown parties without a government guarantee.

Stablecoins differ from cryptocurrencies in being pegged to fiat currencies, gold or other stores of value that are more “stable” than bitcoin or other cryptocurrencies. They were designed to be on- and off-ramps between the traditional world of fiat money and the blockchain-based world of DeFi and cryptocurrencies, and to provide a steady “on-blockchain” unit of account to facilitate DeFi trading. But stablecoins’ use case has evolved significantly amid spectacular growth in acceptance and usage. Stablecoin annual transaction volumes through March totalled $35 trillion, more than doubling the prior 12-month period, while users have increased more than 50% to over 30 million, and the outstanding value of stablecoins has hit $250 billion.

More than 90% of stablecoin transactions still involve either on/off-ramping or DeFi trading, but an increasing share of transaction growth involves “real world” uses. Person-to-person and business transactions in countries with unstable local currencies, like Argentina, Nigeria and Venezuela, have been a key source of growth, but one of the largest has been increasing use in global remittances by migrant labor, over a quarter of the total according to one estimate.

With the help of Congress

Stablecoins’ increasingly rapid acceptance and growth as an alternative payments system is coming just as the Trump Administration and Congress are moving to institutionalize them.

How do stablecoins maintain their value versus a particular currency like the dollar? In theory each stable coin unit is backed one for one with the currency it is pegged to. In practice, this hasn’t always been the case. But the U.S. legislation defines what are acceptable high-quality, liquid assets (HQLA), mandates one-for-one backing and requires regular audits to establish compliance. Thus, Congress is creating the legal basis for entities that (1) take deposits; (2) are required to fully back deposits by HQLA; and (3) facilitate payments in the economy.

Deja vu

Does that sound familiar to you? Isn’t that a narrow bank?

There are a few missing pieces. Most notably that neither the GENIUS nor STABLE Acts grant stablecoin issuers access to the Federal Reserve and neither defines stablecoins as money for tax purposes. The omission of access to the Fed likely reflects both necessary prudence to avoid undermining the fractional reserve banking system (too quickly) with a direct competitor and the ABA’s lobbying efforts to protect banks’ monopoly. But even here there are intriguing breadcrumbs that hint banks’ protection may be temporary and only long enough to transition to a narrow banking model: among the approved HQLA for stablecoin issuers in both bills are reserves at the Federal Reserve, currently accessible only by banks.

Shifting political sands

Both the Trump campaign’s pivot to crypto last year and both houses of Congress moving to normalize stablecoins reflects a profound shift in America’s domestic political economy and its sense of national interests. Bipartisan populist anger at banks and their relationship with Washington hasn’t dissipated since the Global Financial Crisis. The Fed’s QE and recent inflationary policy errors have only increased populist fury. This is just as much a part of the crypto phenomenon as FOMO.

But crypto also has generated immense new wealth and opportunities for business, creating a well financed rival to the ABA. Even institutional asset managers now are diverging with their traditional allies in banking, salivating at the opportunities they see in DeFi. The combination of popular base and economic muscle is creating, for the first time, a political economy supportive of narrow banking.

Further, the U.S. now has compelling national interests in developing stablecoins. First, in a world where China (and other U.S. rivals) increasingly seek to displace U.S. payment systems like SWIFT with their own, an independent, third-party payment system that prevents countries from being “trapped” in a Chinese payments system is appealing. The other national interest is the one that Treasury Secretary Scott Bessent keeps mentioning: a systemic shift towards stablecoin-based narrow banking creates “one of the largest buyers of U.S. T-bills.”

And the new financial architecture

U.S. financial structure has become far more conducive to a non-disruptive transition relative to any time in its history, or relative to other countries today, giving it an advantage over rivals. While the U.S. has long been less bank dependent for credit than other major economies due to its greater use of corporate bond markets and securitized mortgages, the growth of so-called “shadow” banking in the last two decades has made it even more so. Bank credit in the U.S. is little more than a third of total credit to the private non-financial sector. The rest is provided by bond markets and the shadow sector that are in fact the broad or merchant banks envisioned under the Chicago Plan.

The economic, geopolitical and financial implications of a shift to stablecoin-based narrow banking in the United States are huge. It would create significant winners and losers both within the U.S. and around the world.