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Transaction Fees on a Honeymoon: Ethereum's EIP-1559 One Month Later

Abstract

Ethereum Improvement Proposal (EIP) 1559 was recently implemented to transform Ethereum's transaction fee market. EIP-1559 utilizes an algorithmic update rule with a constant learning rate to estimate a base fee. The base fee reflects prevailing network conditions and hence provides a more reliable oracle for current gas prices. Using on-chain data from the period after its launch, we evaluate the impact of EIP-1559 on user experience and market performance. Our empirical findings suggest that while EIP-1559 achieves its goals on average, short-term behavior is marked by intense oscillations in block sizes and slow adjustments during periods of demand bursts (e.g., NFT drops). Both phenomena lead to unwanted inter-block variability in mining rewards. We then study the effect of different learning rates and propose an alternative mechanism that uses a variable learning rate. Our simulations show that the latter outperforms the standard EIP-1559 mechanism under various demand scenarios. These results provide evidence that such mechanisms may constitute a promising direction for future research and contribute to the ongoing discussion on EIP-1559 (and EIP-1559 based) mechanisms and to design of more efficient transaction fee markets.

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