Blockchain enables peer-to-peer transactions in cyberspace without a trusted third party. The rapid growth of Ethereum and smart contract blockchains generally calls for well-designed Transaction Fee Mechanisms (TFMs) to allocate limited storage and computation resources. However, existing research on TFMs must consider the waiting time for transactions, which is essential for computer security and economic efficiency. Integrating data from the Ethereum blockchain and memory pool (mempool), we explore how two types of events affect transaction latency. First, we apply regression discontinuity design (RDD) to study the causal inference of the Merge, the most recent significant upgrade of Ethereum. Our results show that the Merge significantly reduces the long waiting time, network loads, and market congestion. In addition, we verify our results' robustness by inspecting other compounding factors, such as censorship and unobserved delays of transactions via private changes. Second, examining three major protocol changes during the merge, we identify block interval shortening as the most plausible cause for our empirical results. Furthermore, in a mathematical model, we show block interval as a unique mechanism design choice for EIP1559 TFM to achieve better security and efficiency, generally applicable to the market congestion caused by demand surges. Finally, we apply time series analysis to research the interaction of Non-Fungible token (NFT) drops and market congestion using Facebook Prophet, an open-source algorithm for generating time-series models. Our study identified NFT drops as a unique source of market congestion -- holiday effects -- beyond trend and season effects. Finally, we envision three future research directions of TFM.

翻译：区块链技术使得网络空间中的点对点交易无需可信第三方即可实现。以太坊及智能合约区块链的快速发展要求设计良好的交易费用机制（Transaction Fee Mechanisms, TFMs）来分配有限的存储和计算资源。然而，现有关于TFM的研究必须考虑交易的等待时间，这对计算机安全和经济效率至关重要。结合以太坊区块链和内存池（mempool）的数据，我们探讨了两种类型事件如何影响交易延迟。首先，我们应用断点回归设计（Regression Discontinuity Design, RDD）研究以太坊最近重大升级——合并——的因果推断。结果表明，合并显著减少了长等待时间、网络负载和市场拥堵。此外，我们通过检查其他复合因素（如审查制度和通过私有变更导致的未观察到的交易延迟）验证了结果的稳健性。其次，在研究合并期间的三大主要协议变更时，我们确定缩短区块间隔是造成实证结果的最可能原因。进一步地，通过数学模型，我们证明区块间隔是EIP1559 TFM实现更好安全性和效率的独特机制设计选择，这普遍适用于需求激增引起的市场拥堵。最后，我们应用时间序列分析，使用开源算法Facebook Prophet生成时间序列模型，研究非同质化代币（Non-Fungible Token, NFT）发行和市场拥堵之间的相互作用。我们的研究识别出NFT发行是除趋势效应和季节效应之外的独特市场拥堵来源——假日效应。最后，我们展望了TFM的未来三个研究方向。