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.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.