We explore the identification of nonseparable models without relying on the property that the model can be inverted in the econometric unobservables. In particular, we allow for infinite dimensional unobservables. In the context of a demand system, this allows each product to have multiple...

We consider the invertibility of a nonparametric nonseparable demand system. Invertibility of demand is important in several contexts, including identification of demand, estimation of demand, testing of revealed preference, and economic theory requiring uniqueness of market clearing prices. We...

We develop an estimator for the parameters of a utility function that has interactions between the unobserved demand error and observed factors including price. We show that the Berry (1994)/Berry, Levinsohn, and Pakes (1995) inversion and contraction can still be used to recover the mean...

We show how to nonparametrically identify the distribution that characterizes heterogeneity among agents in a general class of structural choice models. We introduce an axiom that we term separability and prove that separability of a structural model ensures identification. The main strength of...

In this paper we introduce a new approach to estimating differentiated product demand systems that allows for products with zero sales in the data. Zeroes in demand are a common problem in product differentiated markets, but fall outside the scope of existing demand estimation techniques. Our...

We study the estimation of substitution patterns within the discrete choice framework developed by Berry (1994) and Berry, Levinsohn, and Pakes (1995). Our objective is to demonstrate the consequences of using weak instruments in this non-linear GMM context, and propose a new class of...

We study the estimation of substitution patterns within the discrete choice framework developed by Berry (1994) and Berry, Levinsohn, and Pakes (1995). Our objective, is to illustrate the consequences of using weak instruments in this non-linear GMM context, and propose a new class of...