Identification in Differentiated Products Markets Using Market Level Data

Steven T. Berry, Philip A. Haile
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引用次数: 313

Abstract

We present new identification results for nonparametric models of differentiated products markets, using only market level observables. We specify a nonparametric random utility discrete choice model of demand allowing rich preference heterogeneity, product/market unobservables, and endogenous prices. Our supply model posits nonparametric cost functions, allows latent cost shocks, and nests a range of standard oligopoly models. We consider identification of demand, identification of changes in aggregate consumer welfare, identification of marginal costs, identification of firms' marginal cost functions, and discrimination between alternative models of firm conduct. We explore two complementary approaches. The first demonstrates identification under the same nonparametric instrumental variables conditions required for identification of regression models. The second treats demand and supply in a system of nonparametric simultaneous equations, leading to constructive proofs exploiting exogenous variation in demand shifters and cost shifters. We also derive testable restrictions that provide the first general formalization of Bresnahan's (1982) intuition for empirically distinguishing between alternative models of oligopoly competition. From a practical perspective, our results clarify the types of instrumental variables needed with market level data, including tradeoffs between functional form and exclusion restrictions.
利用市场水平数据识别差异化产品市场
我们提出了差异化产品市场的非参数模型的新识别结果,仅使用市场水平的可观测值。我们指定了一个非参数随机效用的需求离散选择模型,允许丰富的偏好异质性、产品/市场不可观察性和内生价格。我们的供给模型假定了非参数成本函数,允许潜在成本冲击,并嵌套了一系列标准寡头垄断模型。我们考虑了需求的识别、消费者总福利变化的识别、边际成本的识别、企业边际成本函数的识别以及企业行为的不同模型之间的区别。我们探索两种互补的方法。第一个演示了在识别回归模型所需的相同非参数工具变量条件下的识别。第二部分在非参数联立方程系统中处理需求和供给,导致利用需求转移和成本转移的外生变化的建设性证明。我们还推导了可测试的限制,这些限制为Bresnahan(1982)的直觉提供了第一个一般形式,以经验区分寡头垄断竞争的替代模型。从实际的角度来看,我们的结果澄清了市场水平数据所需的工具变量类型,包括功能形式和排除限制之间的权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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