This paper provides a unified framework for partial identification of counterfactual parameters in a general class of discrete outcome models allowing for endogenous regressors and multidimensional latent variables, all without parametric distributional assumptions. Our main theoretical result...

This paper proposes a simple specification test for partially identified models with a large or possibly uncountably infinite number of conditional moment (in)equalities. The approach is valid under weak assumptions, allowing for both weak identification and non-differentiable moment conditions....

This paper examines various explanations for the increase in the degree of regulation of the auto industry in the last ten years. Using cross section data for the State of California, the paper confirms earlier findings for the State of Massachusetts that the demand for auto insurance is highly...