An Adversarial Approach to Identification, Computation, and Inference in Models with a Linear-in-Measures Representation

We develop a framework for identification, computation, and inference in econometric models with a linear-in-measures representation. These models express maintained restrictions as moment conditions linear in the joint probability measure of observed and latent inputs, and map that measure linearly