How fees are expressed on chain
On Bitcoin-style chains transaction fees are determined by fee rate multiplied by transaction size. Bitcoin Core developer Pieter Wuille at Blockstream explains that wallets set a fee rate in satoshis per byte and that miners include transactions offering the highest fee rates first. Because each transaction consumes a variable number of bytes depending on inputs and outputs, a larger, more complex transaction pays more in absolute fees for the same fee rate. This model ties fees directly to scarce block space and the market for inclusion.
On Ethereum and other account-model chains fees are calculated using gas multiplied by gas price, with modern Ethereum using a dual mechanism where a network base fee is algorithmically set per block and a priority fee (tip) is paid to validators. Ethereum Foundation researcher Vitalik Buterin has described how the base fee adjusts with block demand so that when blocks are consistently over target utilization the base fee rises, and when underutilized it falls. The base fee is burned while the priority fee compensates validators, shifting incentives and affecting user cost in different ways than simple fee-per-byte systems.
Demand, supply and algorithmic adjustments
Fee dynamics result from three interacting factors: limited per-block capacity, arrival rate of transactions, and miners’ or validators’ selection criteria. When demand exceeds capacity, users offer higher fee rates or priority fees to gain faster inclusion. Miners and validators maximize revenue by selecting the highest-fee transactions within a block’s constraints. The mempool, the temporary queue of waiting transactions, becomes the market where fee competition happens. Under congestion, predictable fee algorithms like Ethereum’s base-fee reduce some volatility but do not eliminate spikes during surges of activity such as token launches or decentralized finance events.
Empirical work from the Cambridge Centre for Alternative Finance at the University of Cambridge highlights how network congestion, regional adoption patterns and application-level activity drive fee pressure. Higher fees make small-value payments impractical, shifting cultural use toward custodial or layer-2 solutions in many territories where on-chain costs are a significant share of income.
Consequences and adaptations
High on-chain fees change behavior across the ecosystem. Users and wallets adopt fee-estimation algorithms and features like replace-by-fee to bump transactions; service providers batch payments to reduce per-transfer cost; developers pursue layer-2 scaling and alternative chains to restore low-cost transfers. Miner or validator revenue from fees also affects long-term security economics: in proof-of-work networks fees supplement block subsidy while in proof-of-stake networks fee distribution affects staking incentives. These effects intersect with social and economic dimensions: in lower-income regions, persistent high fees can exclude users and concentrate activity in custodial services, altering decentralization and access.
Understanding on-chain fee calculation therefore requires both the simple arithmetic—fee rate times size or gas times price—and recognition of the institutional mechanisms, algorithmic rules, and human behaviors that translate scarce block or gas capacity into real cost for users.