We show how to construct bounds on counterfactual choice probabilities in semiparametric discrete-choice models. Our procedure is based on cyclic monotonicity, a convex-analytic property of the random utility discrete-choice model. These bounds are useful for typical counterfactual exercises in...

Using data from "WebsiteX", one of the largest online marketplaces in the world, we estimate a structural model of sponsored search auctions where bidders have heterogeneous click-through curves. Unlike earlier studies, our model accommodates two stylized empirical facts: the advertiser...

We propose an inference procedure for estimators defined by mathematical programming problems, focusing on the important special cases of linear programming (LP) and quadratic programming (QP). In these settings, the coefficients in both the objective function and the constraints of the...

We propose two Mathematical Programming with Equilibrium Constraints (MPEC) formulations: the MPEC-Sparse and the MPEC-Dense to estimate a class of separable matching models. We compare MPEC with the Nested Fixed-Point (NFXP) algorithm -- a well-received method in the literature of structural...

A data-cloning SMC² method is proposed as a general purpose optimization routine for estimating latent variable models by maximum likelihood. The latent variables are first marginalized out by SMC at any fixed parameter value, and the model parameters are then estimated by density tempered SMC....