Nonparametric Identification of Differentiated Products Demand Using Micro Data
研究了当拥有连接个体消费者特征与选择的微观数据时，如何识别差异化产品需求，并讨论了非价格特征内生性下的需求弹性识别，对应用研究有指导意义。
We examine identification of differentiated products demand when one has “micro data” linking the characteristics and choices of individual consumers. Our model nests standard specifications featuring rich observed and unobserved consumer heterogeneity as well as product/market‐level unobservables that introduce the problem of econometric endogeneity. Previous work establishes identification of such models using market‐level data and instruments for all prices and quantities. Micro data provides a panel structure that facilitates richer demand specifications and reduces requirements on both the number and types of instrumental variables. We address identification of demand in the standard case in which nonprice product characteristics are assumed exogenous, but also cover identification of demand elasticities and other key features when these product characteristics are endogenous and not instrumented. We discuss implications of these results for applied work.