Empirical Analysis of EIP-1559: Transaction Fees, Waiting Time, and Consensus Security
arXiv:2201.05574 · doi:10.1145/3548606.3559341
Abstract
A transaction fee mechanism (TFM) is an essential component of a blockchain protocol. However, a systematic evaluation of the real-world impact of TFMs is still absent. Using rich data from the Ethereum blockchain, the mempool, and exchanges, we study the effect of EIP-1559, one of the earliest-deployed TFMs that depart from the traditional first-price auction paradigm. We conduct a rigorous and comprehensive empirical study to examine its causal effect on blockchain transaction fee dynamics, transaction waiting times, and consensus security. Our results show that EIP-1559 improves the user experience by mitigating intrablock differences in the gas price paid and reducing users' waiting times. However, EIP-1559 has only a small effect on gas fee levels and consensus security. In addition, we find that when Ether's price is more volatile, the waiting time is significantly higher. We also verify that a larger block size increases the presence of siblings. These findings suggest new directions for improving TFMs.
References in corpus (2)
Cited by in corpus (16)
- Empirical Analysis of EIP-1559: Transaction Fees, Waiting Time, and Consensus Security
- Did the Roll-Out of Community Notes Reduce Engagement With Misinformation on X/Twitter?
- Demystifying DeFi MEV Activities in Flashbots Bundle
- AI Ethics on Blockchain: Topic Analysis on Twitter Data for Blockchain Security
- Blockchain Network Analysis: A Comparative Study of Decentralized Banks
- "Centralized or Decentralized?": Concerns and Value Judgments of Stakeholders in the Non-Fungible Tokens (NFTs) Market
- Quantifying the Blockchain Trilemma: A Comparative Analysis of Algorand, Ethereum 2.0, and Beyond
- Cryptocurrency Valuation: An Explainable AI Approach
- Time-Varying Bidirectional Causal Relationships Between Transaction Fees and Economic Activity of Subsystems Utilizing the Ethereum Blockchain Network
- Blockchain Transaction Fee Forecasting: A Comparison of Machine Learning Methods
- A Dataset of Uniswap daily transaction indices by network
- Bitcoin Gold, Litecoin Silver:An Introduction to Cryptocurrency's Valuation and Trading Strategy
- The Economics of Blockchain Governance: Evaluate Liquid Democracy on the Internet Computer
- Analyzing Reward Dynamics and Decentralization in Ethereum 2.0: An Advanced Data Engineering Workflow and Comprehensive Datasets for Proof-of-Stake Incentives
- A Game Theoretic Analysis of Validator Strategies in Ethereum 2.0
- DAM: A Universal Dual Attention Mechanism for Multimodal Timeseries Cryptocurrency Trend Forecasting