  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.
