An Adversarial Approach to Structural Estimation

Understand

We propose a new simulation-based estimation method, adversarial estimation, for structural models.

• The estimator is formulated as the solution to a minimax problem between a generator (which generates simulated observations using the structural model) and a discriminator (which classifies whether an observation is simulated).
• The discriminator maximizes the accuracy of its classification while the generator minimizes it.
• We show that, with a sufficiently rich discriminator, the adversarial estimator attains parametric efficiency under correct specification and the parametric rate under misspecification.