Nonparametric Identification and Estimation of Nonadditive Hedonic Models

• 成果类型: Article
• 署名作者: Heckman, James J.; Matzkin, Rosa L.; Nesheim, Lars
• 署名单位: University of Chicago; Yale University; University of California System; University of California Los Angeles; University of London; University College London
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA6388
• 发表日期: 2010
• 页码: 1569-1591
• 关键词: demand; prices; differentials; benefits

摘要

This paper studies the identification and estimation of preferences and technologies in equilibrium hedonic models. In it, we identify nonparametric structural relationships with nonadditive heterogeneity. We determine what features of hedonic models can be identified from equilibrium observations in a single market under weak assumptions about the available information. We then consider use of additional information about structural functions and heterogeneity distributions. Separability conditions facilitate identification of consumer marginal utility and firm marginal product functions. We also consider how identification is facilitated using multimarket data.