全球智库信息集成服务系统(G2TT): Identification and Estimation of Hedonic Models

G2TT

来源类型	Working Paper
规范类型	报告
DOI	10.3386/w9910
来源ID	Working Paper 9910
	Identification and Estimation of Hedonic Models
	Ivar Ekeland; James J. Heckman; Lars P. Nesheim
发表日期	2003-08-18
出版年	2003
语种	英语
摘要	This paper considers the identification and estimation of hedonic models. We establish that in an additive version of the hedonic model, technology and preferences are generically identified up to affine transformations from data on demand and supply in a single hedonic market. For a very general parametric structure, preferences and technology are fully identified. This is true under a strong assumption of statistical independence of the error term. It is also true under the weaker assumption of mean independence of the error term. Much of the confusion in the empirical literature that claims that hedonic models estimated on data from a single market are fundamentally underidentified is based on linearizations that do not use all of the information in the model. The exact economic model that justifies widely used linear approximations has strange properties so the approximation is doubly poor. A semiparametric estimation method is proposed that is valid when a statistical independence assumption is valid. Alternatively, under the weaker condition of mean independence instrumental variables estimators can be applied to identify technology and preference parameters from a single market. They are justified by nonlinearities that are generic features of equilibrium in hedonic models.
主题	Econometrics ; Estimation Methods
URL	https://www.nber.org/papers/w9910
来源智库	National Bureau of Economic Research (United States)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/567535
推荐引用方式 GB/T 7714	Ivar Ekeland,James J. Heckman,Lars P. Nesheim. Identification and Estimation of Hedonic Models. 2003.

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w9910.pdf（593KB）	智库出版物		限制开放	CC BY-NC-SA	浏览