Identifying Multidimensional Adverse Selection Models∗

In this paper, I study the nonparametric identification of a multidimensional adverse selection model. In particular, I consider the screening model of Rochet and Choné (1998), where products have multiple characteristics and consumers have private information about their multidimensional taste for these characteristics, and determine the data features and additional condition(s) that identify model parameters. The parameters include the nonparametric joint density of consumer taste, the cost function and the utility function, and the data includes individual level data on choices and prices paid from one market. When the utility is nonlinear in product characteristics, however, data from one market is not enough, but if data from at two markets, or over two periods is sufficient as long as they have different marginal prices. Therefore, it is sufficient to have data with exogenous and binary cost shifter that affects the marginal prices. I also characterize all (testable) restrictions imposed by the model on the data.