短期定价面板中的跨设计不确定性：来自模拟价格轨迹的证据
Across-Design Uncertainty in Short Pricing Panels: Inference and Identification
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中文总结 AI 辅助
本文针对短期定价面板的跨设计不确定性，通过合成数据模拟，明确其占估计误差方差97.6%，给出经验关系，发现Paule-Mandel方差成分可提升覆盖率，为数据生成过程设计提供方向。
中文摘要 AI 辅助
短期观测定价面板可包含大量观测值，却仅提供少量不同的价格变动。本文在针对稀疏定价机制校准的合成数据生成过程中，研究了这一差异带来的推断后果。我们将基于已实现价格轨迹的条件不确定性，与同一定价过程生成的不同轨迹间的估计误差变异相分离。在基准模拟中，对于梯度提升设定，后一成分占估计误差方差的97.6%。面板内重采样程序利用单一已实现轨迹的信息，无法识别这种跨设计成分。分析由三个结果组织：第一，跨设计离散度可由经验关系σ̂≈0.182V^(-0.271)良好描述，其中V等于变动次数乘以变动幅度的平方；第二，添加拥有共同价格路径的区域可降低结果噪声，但不会产生独立的价格轨迹；相反，对具有独立设计特异性误差的单元取平均，可按标准平方根比率降低离散度；第三，对独立定价单元估计的Paule-Mandel方差成分，在同质模拟中可将经验覆盖率从0.469大幅提升至0.931。更广泛的启示是，应转向设计能产生独立识别变异的数据生成过程，而非仅依赖固定被动面板。
英文摘要
Short observational pricing panels often contain many data points but very few actual price changes. This paper shows that this sparsity creates a hidden source of error that standard statistical methods miss. When estimating price effects, most of the uncertainty does not come from sample size within a panel, but from the specific history of price movements observed. Standard confidence intervals fail because they only measure variation within the panel, ignoring this broader design-level error. Using simulations, we find that this cross-design variation accounts for most of the estimation error, causing standard methods to significantly understate uncertainty. First, we show that cross-design error decreases predictably as the total volume of price variation increases. Second, adding more data from regions that share the same price trends does not fix the issue; true precision improves only when combining data across units with independent price trajectories. Third, applying a simple variance-component adjustment across independently priced units restores accurate statistical coverage. We confirm these findings in real-world store scanner data, showing that products and pricing zones behave as if they have far fewer independent price movements than their raw counts suggest. Ultimately, reliable inference in passive pricing data requires genuine, independent variation, which can be achieved through controlled regional price testing.
发表机构
- Universidad de Huelva（韦尔瓦大学）
机构由 AI 辅助整理，请以论文原文为准。
