Nonparametric estimation of triangular simultaneous equations models

This paper presents a simple two-step nonparametric estimator for a triangu lar simultaneous equation model. Our approach employs series approximations that exploit the additive structure of the model. The first step comprises the nonparametric estimation of the reduced form and the corresponding res iduals. The second step is the estimation of the primary equation via nonpa rametric regression with the reduced form residuals included as a regressor . We derive consistency and asymptotic normality results for our estimator, including optimal convergence rates. Finally we present an empirical examp le, based on the relationship between the hourly wage rate and annual hours worked, which illustrates the utility of our approach.