Simulation-Based Two-Step Estimation with Endogenous Regressors

This paper considers models with latent/discrete endogenous regressors and presents a simulation-based two-step (STS) estimator. The endogeneity is corrected by adopting a simulation-based control function approacy. The first step consists of simulating the residuals of the reduced-form equation for endogenous regressors. The second step is a regression model (linear, latent or discrete) with the simulated residual as an additional regressor. In this paper we develop the asymptotic theory for the STS estimator and its rate of convergence.