Bitcoin and Ethereum Fees Explained

Why Fees are Important

Transaction fees play a crucial role in maintaining blockchain networks’ security and functionality. Network fees, as opposed to application-level fees, generally serve as an incentive for miners (in proof-of-work systems) and validators (in proof-of-stake systems) to confirm transactions and add them to the existing blockchain. This paper provides an introductory comparison and analysis of the network-level transaction fees for Bitcoin and Ethereum. While both networks use transaction fees for the reasons above, their mechanisms are different, reflecting their unique functionalities and use cases.

Comparison of Bitcoin and Ethereum Fees

Bitcoin

In the Bitcoin network, transaction fees are voluntary amounts users pay to incentivize miners to include users’ transactions in miners’ blocks. The fee is typically proportional to the transaction size in bytes, not the amount of bitcoin transacted. Therefore, transactions with multiple inputs and outputs will generally have a higher fee than those with a single input and output.

This relationship between transaction fee and transaction size is due, in part, to the block size limit. For example, Bitcoin has a 1-megabyte (MB) block size limit. Therefore, miners use the measurement of satoshis per byte to determine the most economically efficient block construction. At its core, miners prioritize transactions that will provide them with the highest fees per MB (block) to maximize revenue.

From the user’s perspective, one would choose to pay higher or lower fees depending on how quickly the transactions need to be processed, which is a function of network congestion called “timeliness.” In this case, a transaction with high timeliness would be inclined to pay a higher amount of satoshis per byte of transaction data than others are paying at that time.

When combined, these factors result in an auction-style fee market that is directly based on the satoshis per byte that all users are willing to pay to be included in each Bitcoin block.

Ethereum

Ethereum’s fee structure is slightly more complex due to the network’s expanded capabilities, more specifically, executing smart contracts. Ethereum fees can be categorized into two buckets: 1) the priority tip, and 2) the base fee.

The priority tip works similarly to Bitcoin fees in that users typically pay a tip based on their transaction’s timeliness. This incentivizes validators to include their transaction in blocks. Instead of a block size limit, Ethereum blocks have a gas limit. Gas is the unit of measurement for computational work, meaning each operation, whether it is a simple transfer or a complex interaction with a smart contract, requires a certain amount of gas to complete. Therefore, validators choose transactions based on the amount of ether per unit of gas because there is a limited amount of computational work that can be executed in each block.

For example, transferring ether from one address to another costs a minimum of 21,000 gas, while using a multiplication function (within an app) costs 5 gas. The gas price, specified by the user, is the amount of ether the user is willing to pay for each unit of gas, which is a function of network congestion.

Therefore, the total transaction fee is the product of the gas used (computational power needed) and the gas price (based on network congestion) plus the priority tip. Network congestion has a dual effect on Ethereum fees because of the gas price and the priority tip being influenced by it. The fact that network congestion directly influences the cost of operations and timeliness is what makes Ethereum’s current fee structure unique.

While both networks use transaction fees as incentives for validation, the structures and inputs are different. Bitcoin’s fees are based on transaction size, while Ethereum’s fees depend on computational complexity, measured in gas. These differences reflect the unique functionalities of the two networks: Bitcoin as a digital currency and Ethereum as a platform for applications.

Implications to Network Security

One of the largest concerns for the Bitcoin network’s future is the programmatically declining issuance rate and the impact that this will have on miner profitability. As the block reward for miners halves roughly every four years, fees make up an increasing proportion of miner revenue. Therefore, as issuance continues to decrease, income from fees becomes more important to miners until it is their only source of revenue.

Since inception, the bitcoin price, along with advancements in mining efficiency, has been able to support mining operations, and thus, has allowed hash rate to consistently increase, improving overall network security. However, the price increase and technological advancement trends are not guaranteed to continue, in which case fees would need to make up for the network’s decreasing block rewards.

While revenue from issuance is the main source of income for Ethereum validators, it does not pose a similar threat to the validators’ survivability. There has been a steady increase in validators since The Merge, which has resulted in lower yields per validator over time.¹ However, since validators have such low input costs compared to proof-of-work miners, their operational resiliency and ability to continue securing the network over the longer term is much greater compared to bitcoin miners.

However, the value of staked ether is one of the main security paradigms preventing attacks on Ethereum, so higher yields to validators directly impact the opportunity cost of staking. In other words, if the fees paid to validators increases, overall yield increases, incentivizing more validators and a higher value of total staked ether.

Now that the reliance these networks will continue to have on fees over the longer term has been presented, let us look at some basic analysis of the historical relationship between fees and other network metrics.

Correlation of Transaction Fees to Network Metrics

Using a simple correlation analysis between fees and other network metrics, one can start to paint a picture to help determine what has historically been moving alongside fees and whether these relationships may continue.

Two important points must be mentioned before delving further into this correlation analysis:

1. Correlation does not equal causation.
2. The Bitcoin data used begins at the start of 2015. This date range was chosen because of Bitcoin’s slow initial uptake because it primarily only consisted of smaller communities focused on the technology. However, digital assets became more mainstream around the time of Ethereum’s launch in 2016. Still, keep in mind that the date ranges used can significantly alter the resulting correlation data.

Green indicates a moderate-strong positive correlation.

Orange indicates a weak-moderate positive correlation.

Red indicates a negative correlation.

The above table shows the correlation between Ethereum and Bitcoin fees and various network metrics. This dataset, combined with existing knowledge, may allow us to infer why fees for each network may be showing their respective correlations.

Bitcoin fees show weak or near zero correlation to transaction count, price, and active addresses. This may be the case due to some people’s perception of Bitcoin as a store of value asset. As demand to use the network increases, it does not equate to timeliness because users and investors are more likely to buy and hold the asset and, therefore, are willing to wait longer for transaction execution. This could imply that, in the short term, mining profitability may rely more heavily on price increases and lowering input costs than increased adoption, leading to higher fees.​​​​​

Total Ethereum fees show moderate or strong positive correlation to transaction count, price, and active addresses. This may be the case due to Ethereum’s use case as a platform for applications, especially considering the most popular applications, such as Uniswap, revolve around trading and finance. Thus, users and investors are more likely to buy and use the asset for trading, speculation, etc., driving up timeliness and, therefore, the fees that users are willing to pay for transaction execution.

Interestingly, the strongest correlation observed is between fees and ether’s price. This data point suggests that the highest urgency transactions occur alongside the movement in ether’s price, which likely involves trading and speculation based on asset prices.

This could imply that validator profitability relies more heavily on network usage and an increase in price of the underlying staked ether. Additionally, since input costs for running validators are already quite low, there may be less room for node operators to cut costs and increase margins.

What’s Next?

The most interesting question left to be answered is whether these relationships will continue to hold into the future. While there are no certainties, here are some data-driven conclusions on the matter that are subject to change as the networks evolve:

Bullish case for fees

BRC-20 technology and standards are brand new for the Bitcoin network and allow users to label specific satoshis with arbitrary data, also known as ordinals and inscriptions. If this trend continues to evolve, Bitcoin could become a more popular platform for new tokens that could spark higher urgency for user transactions.

Even as the world’s largest digital asset networks, Bitcoin and Ethereum are still incredibly early in their adoption curves with large institutional players only recently beginning to take a favorable approach to the asset class. A dramatic increase in demand from new institutions and retail investors could push the average transaction fee higher.

Bearish case for fees

Layer 2 networks, or off-chain networks built on top of a blockchain’s base layer, for both Bitcoin and Ethereum have the potential to bring fees much closer to zero in the long term than their respective base layers, which could have meaningful implications to the sustainability of the network’s security providers. However, if lower fees on layer 2s allow more users to transact more frequently, it will be interesting to see if the potentially increased usage is able to offset the possible decrease in fee revenue to the base layer.

The Bottom Line for Investors

We’ve learned that increased Ethereum usage directly equals more revenue for validators due to the timely nature of finance- and speculation-related use cases, whereas network congestion on Bitcoin does not necessarily equate to higher fees for miners. However, users have been demanding lower, more reliable fees from both networks, which layer 2 platforms can provide. While layer 2 platforms may bring more users on board, some value will accrue to other ecosystems/tokens, which would have otherwise gone to miners and validators.

Therefore, investors may want to continue to monitor this potential tension over the next few years. Will the growth and uptake of layer 2 platforms bring in more users and foster more activity on the base layer, increasing fees? Or could it redirect fees up and away from the base layer, and if so, would there be a negative effect on security or the value accrual to their respective native tokens? This is something that we will continue to observe closely and seek to model in the coming months.

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