Identification and estimation of hedonic models
This paper considers the identification and estimation of hedonic models. We establish that technology and preferences in a separable version of the hedonic model are generically identified up to ane transformations from data on demand and supply in a single hedonic market. For a very general parametric structure, preferences and technology are fully identified from demand data. 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 the linear approximations has strange properties so the approximation is doubly poor. A semiparametric estimation method is proposed, and alternative estimators are considered. Instrumental variables estimators can be applied to identify technology and preference parameters from a single market even though there are no exclusion restrictions.
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