Identification and Inference in Consumer Models

This paper provides new identification results for a large class of (static) consumer problems that contain (production) functions in the budget constraints. I show that the mere structure of the consumer problem is sufficient to nonparametrically identify the part of the production functions linked to preferences. In addition, I derive a nonparametric characterization of the class of models considered that operationalizes the identification strategy. Finally, I use a novel and easy-to-apply inference method for the estimation of the production functions. This method can be used to statistically test the model, can deal with any type of latent variables (e.g., measurement error), and can be combined with standard exclusion restrictions. A full-blown application to a general model of price search shows the feasibility and effectiveness of this approach