无外部商品份额的需求估计
Demand estimation without outside good shares
AI总结：
针对BLP模型中外部商品份额不可观测的问题，本文推导了结构参数的部分识别集，并开发了基于矩不等式的推断方法，以金枪鱼数据验证。
摘要：
BLP模型是使用聚合产品份额估计差异化产品需求的主流框架。然而，在实践中，外部商品的份额通常不可得。本文研究了当外部商品份额不可观测时BLP模型中的识别和推断问题。我们证明该模型是部分识别的，并推导了结构参数和其他经济感兴趣量的识别集。我们还开发了基于矩不等式的推断程序，为这些结构参数和经济感兴趣量提供有效的置信集。我们通过Gandhi等人（2023）分析的金枪鱼数据实证应用来说明我们的结果。
英文摘要：
The BLP model is the workhorse framework for estimating demand for differentiated products using aggregate product shares. In practice, however, the share of the outside good is often unavailable. This paper studies identification and inference in the BLP model when the share of the outside good is unobserved. We show that the model is partially identified, and we derive the identified sets for the structural parameters and other quantities of economic interest. We also develop inference procedures based on moment inequalities that deliver valid confidence sets for these structural parameters and quantities of economic interest. We illustrate our results with an empirical application based on the tuna data analyzed by Gandhi et al. (2023).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
