This paper connects the literature on demand estimation to the literature on causal inference by interpreting nonparametric structural assumptions as restrictions on counterfactual outcomes. It offers nontrivial and equivalent restatements of key demand estimation assumptions in the Neyman-Rubin potential outcomes model, for both settings with market-level data (Berry and Haile, 2014) and settings with demographic-specific market shares (Berry and Haile, 2024). This exercise helps bridge the literatures on structural estimation and on causal inference by separating notational and linguistic differences from substantive ones.

翻译：本文通过将非参数结构假设解释为对反事实结果的限制，将需求估计文献与因果推断文献联系起来。针对市场层面数据（Berry and Haile, 2014）和人口特征细分市场份额（Berry and Haile, 2024）两种设定，本文在Neyman-Rubin潜在结果模型中提出了对关键需求估计假设的非平凡等价重述。这项工作通过区分符号与语言差异与实质差异，有助于弥合结构估计文献与因果推断文献之间的鸿沟。