Identification and Estimation of Hedonic Models
证明在可加享乐模型中，技术和偏好可以从单一市场的供需数据中非参数识别，驳斥了以往文献认为模型无法识别的观点，并指出非线性是识别的重要来源。
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 nonparametrically identified from data on demand and supply in a single hedonic market. The empirical literature that claims that hedonic models estimated on data from a single market are fundamentally underidentified is based on arbitrary linearizations that do not use all the information in the model. The exact economic model that justifies linear approximations is unappealing. Nonlinearities are generic features of equilibrium in hedonic models and a fundamental and economically motivated source of identification.