Bitcoin transaction fees will become more important as the block subsidy declines, but fee formation is hard to study with blockchain data alone because the relevant queueing environment is unobserved. We develop and estimate a structural model of Bitcoin fee choice that treats the mempool as a market for scarce blockspace. We assemble a novel, high-frequency mempool panel, from a self-run Bitcoin node that records transaction arrivals, exits, block inclusion, fee-bumping events, and congestion snapshots. We characterize the fee market as a Vickery-Clarke-Groves mechanism and derive an equation to estimate fees. In the first-stage we estimate a monotone delay technology linking fee-rate priority and network state to expected confirmation delay. We then estimate how fees respond to that delay technology and to transaction characteristics. We find that congestion is the main determinant of delay; that the marginal value of priority is priced in fees, which is increasing in the gradient of confirmation time reduction per movement up in the fee queue; and that transactor choice of RBF, CPFP, and block conditions have economically important effects on fees.

翻译：随着区块补贴减少，比特币交易费用将变得更加重要，但仅凭区块链数据难以研究费用形成机制，因为相关的排队环境无法观测。我们构建并估计了一个比特币费用选择的结构模型，将内存池视为稀缺区块空间的交易市场。通过自行运行的比特币节点，我们收集了一个新颖的高频内存池面板数据，记录了交易到达、退出、区块包含、费用提升事件以及拥堵快照。我们将费用市场描述为维克里-克拉克-格罗夫斯机制，并推导出费用估计方程。在第一阶段，我们估计了一个单调延迟技术，将费用率优先顺序和网络状态与预期确认延迟联系起来。随后，我们估计费用如何对该延迟技术及交易特征做出反应。研究发现：拥堵是延迟的主要决定因素；优先级的边际价值在费用中有所体现，且随着费用队列中每上升一个梯度所减少的确认时间梯度而增加；交易者对RBF、CPFP及区块条件的选择对费用具有经济上显著的影响。