Transaction

j"19HxigV4QyBv3tHpQVcUEQyq1pzZVdoAutMá-# The Economic Effect of the Bitcoin Mempool on the Transaction Fee Market This article was originally posted on Yours.org, with a pay wall in place that kept most of the truly valuable content of the article hidden to non-paying readers. I now present it to you with minimal editing, and in its entirety, for free. In this article, I discuss the economics of the Bitcoin mempool, especially while constrained by an effective artifical block size limit. The models presented within can easily be extended to discuss alternative scenarios, such as under a market driven block size limit where miners choose the size of the blocks they are both willing to create, and willing to mine on top of. ## You Get What You Pay For It has been suggested that an increase in the size of the mempool causes an increase in transaction fees. While there is a strong correlation between the rate of change in the size of the mempool and the rate of change in the price of transaciton fees, this analysis is simplistic and ultimately fails to accurately model the effects of the mempool on transaction fees because it places a direct causal relationship between the size of the mempool and the price of transactions. While a relationship does exist between the mempool and transaction fees, it is not a direct cause and effect. To identify the solution to this misunderstanding of the causal relationships involved, it must be stated that users are not paying for space in the mempool, rather, they are paying for their transaction to be accepted into a block. Most people understand and agree with this point when stated so plainly, but fail to account for this when analyzing the effect of the mempool on transaction fees. The true source of the relationship between the size of the mempool and pricing of the transaction fee comes from the following: A change in the size of the mempool must come through either a change in the number of transactions broadcast for acceptance in a block, or through a change in the supply of transaction acceptance into blocks. Readers may have already recognized that these two possible causes of changes in the size of the mempool are the same fundamental market forces involved in setting the market equilibrium for transaction fee pricing. These two potential causes can be narrowed down to one because an increase in the size of the mempool necessitates that miners are either unwilling or unable to increase the size of blocks to clear all transactions at a given block find rate. As such, the only remaining causal link between the size of the mempool and the price of transaction fees is the demand for transactions to be placed on the network. In short, increases in the size of the mempool do not cause increases in transaction fees, rather, changes in both share a common root cause: changes in demand for transactions to be placed on the network. ## The Mempool as an Order Book Does this mean the mempool has no effect on transaction fees? Not at all. In fact, it has a very important role to play. The mempool acts as a buy-side order book, just like those found on exchanges, and serves to resist downward pressure on price movement. Broadcasting a transaction to the network can be considered placement of an order for acceptance of your transaction at the fee that you set. It is up to miners to either accept or ignore your transaction for inclusion in the next block they mine. Economic incentives drive miners to only accept the highest available fees, just like sellers on an exchange do not intentionally sell at a lower price than buyers have already listed for their orders. Using this understanding of the transaction fee market, we can now accurately model the mempool’s effects on transaction fees. ## Modeling the Mempool Order Book There are two relevant characteristics of a transaction that effect its inclusion into a block: first, the total fee attached to the transaction, and second, the size in bytes of that transaction. The ratio between these characteristics is the price that miners use to determine acceptance of a transaction in a block. That ratio is the size of the fee, divided by the size of the block, usually measured as satoshis per byte (sat/B). This can be modeled on a graph where the price is placed on the x-axis, and order book volume is placed on the y-axis. Because the limiting factor for block size on the Bitcoin network is currently set at 1 megabyte regardless of number of transactions, volume is best measured in megabytes (MB). An unlimited, miner configurable block size may lead to costs of inclusion in a block being more limited by transaction verification computation rather than bandwidth or storage costs. In this case, other measures may be more appropriate for volume, such as number of transactions, or number of transaction inputs, depending on where bottlenecks arise. <a href="https://ibb.co/ft19Hw"><img src="https://preview.ibb.co/dLRbxw/Blank-Mempool.png" alt="Blank-Mempool" border="0" /></a> Now let’s fill our mempool with some unconfirmed transactions. <a href="https://ibb.co/hozJAG"><img src="https://preview.ibb.co/iDsujb/Avg-Mempool.png" alt="Avg-Mempool" border="0" /></a> Notice how the next block will only clear a portion of the mempool - in this case, pushing down the highest transaction fees to 46 sat/B, regardless of what the highest transaction fee is. In a market with perfect information, all transactions included in this next block would be at a fee of no greater than 46 sat/B. It is also worthwhile to see how much of the mempool would have to be cleared in order to reach a given fee. In this graph, this lower fee is 35 sat/B, and will require 18 MB of the mempool to be cleared before it is reached, not counting transactions added to the mempool over the time required to clear 18 MB of transactions. We will continue with this example of 35 sat/B to demonstrate the effect that different mempool constructions have resistance against downward price pressures. ## Size Really Does Matter First let’s analyze the mempool from a perspective of size. <a href="https://ibb.co/bWrWVG"><img src="https://preview.ibb.co/jaEUHw/Small-Mempool.png" alt="Small-Mempool" border="0" /></a> <a href="https://ibb.co/bUEJAG"><img src="https://preview.ibb.co/ifbWVG/Large-Mempool.png" alt="Large-Mempool" border="0" /></a> The bigger the mempool, the longer it will take for miners to push transaction fees down given the artificial limitations placed on them by the block size limit. As you can see, a smaller mempool will tend to result in less resistance against downward movements in price. In the small mempool example above, only 10 MB of transactions must be cleared until the lowest transaction fee included in the next block equals 35 sat/B, whereas in the large mempool example, that goes as high as 65 MB. In and of itself, this does nothing to put upward pressure on transaction fees, as new transaction orders placed below the 1 megabyte line do not increase the price within that 1 megabyte acceptance range. Said differently, price making transactions exist only within the 1 megabyte which is ultimately accepted into the next mined block, whereas transactions remaining unconfirmed after the next block have no direct price making effects. To push transaction fees up, new transactions must be placed within the next block’s clearance range, thus crowding out lower fee transactions. But what of the makeup of the mempool as a proportion of small fee transactions to large fee transactions? <a href="https://ibb.co/jSsicw"><img src="https://preview.ibb.co/mzSGxw/Low-End-Bulky-Mempool.png" alt="Low-End-Bulky-Mempool" border="0" /></a> If the mempool consists of a lot of low fee transactions, it becomes relatively easy for miners to push the transaction fee down. In the example above, the mempool is 75 MB in size, but it only takes 3 MB of clearance to move transaction fees in the market with no high fee support. In this particular case, the next block will even take a few as low as 41 sat/B. <a href="https://ibb.co/cwKJAG"><img src="https://preview.ibb.co/jWZ74b/High-End-Bulky-Mempool.png" alt="High-End-Bulky-Mempool" border="0" /></a> However, if the mempool consists of overwhelmingly high transaction fees, there is a lot more resistance against downward price movement. In the above example, the mempool is still 75 MB in size, but it will take a full 72 MB of block clearance to move the transaction fee down to 35 sat/B. Additionally, in this particular case, the next block will only bring the transaction fee down to 57 sat/B. Clearly, the formation of the mempool has a large effect on the movement of transaction fee pricing over time. The question then becomes, how do users respond to a given mempool state? ## A Perspective on User Response to Mempool Bloat As users add new transactions to the network, they must decide how long they expect it will take for the miners to work through the order book, and how long they are willing to wait for their transaction to be accepted on the network. Essentially, this means that user time preference is a significant factor in price and mempool formation. Regardless of the significance of each user’s time preference for a given transaction, if the mempool is large, with a lot of high end resistance to mempool clearance, users will tend to place new transactions at higher fee levels than would occur if the mempool were smaller or its resistance to clearance were lower, even given similar transaction fees accepted into blocks at that moment. This effect tends to move mempool clearance resistance in response to transaction fee price patterns, with more transaction fee variance leading to a greater variance in new transaction fees placed in the mempool. Alternatively, stability of transaction fee pricing tends to draw resistance towards the equilibrium transaction fee price, thus creating higher resistance at higher fee levels leading up to that equilibrium. Without the ability for miners to adjust block size or to meaningfully change the block find rate over the long run, this results in an interesting effect. Resistance to downward price pressure increases with upward adjustments in transaction fees, but there is no method by which miners can increase resistance to upward price pressure on transaction fees. As a result, it can be expected that upward shifts in transaction fee pricing will be sudden given rightward shifts in demand, whereas downward shifts in transaction fee pricing will lag behind leftward shifts in demand, resulting in transaction fee stickiness. I leave it as an exercise for the reader to consider further implications of the economic structures described here, including the role that transaction fee stickiness may play in potential shocks to the Bitcoin economy. ## Final Thoughts Ultimately, this model of the mempool as a transaction order book enables far more valuable and accurate analysis of the transaction fee market, and provides users and businesses alike a better method of anticipating market moving events that effect the user experience. Additionally, better understandings of the economics involved in transaction markets such as the Bitcoin network allows for more accurate analysis of the economic impacts of technical configurations and implementations of network software. Dedicated readers will note that I have mostly ignored the temporal elements of clearing the mempool, which include block find rates, transaction broadcasting rates, and the variance in mining power over time. These effects are also incredibly important, but are left at this time as an exercise for the reader to explore and model for themselves or others. text/markdownUTF-8HThe Economic Effect of the Bitcoin Mempool on the Transaction Fee Market
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