LAUSR

We propose a model averaging method to combine estimators from the generalized method of moments (GMM). Unlike other GMM-based model averaging procedures, this method allows all candidate models to be misspecified (not locally misspecified). We prove that when all candidate models are misspecified, the proposed method is optimal in the sense of minimizing estimation loss; when there exists at least one correctly specified model, the method can achieve the common root-n convergence rate. Simulation experiments and an application to the housing market show the superiority of our method with respect to other methods.