Nonparametric Estimation of Triangular Simultaneous Equations Models

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Abstract
This paper presents a simple two-step nonparametric estimator for a triangular simultaneous equation model. The authors use series approximations that exploit the additive structure of the model. The first step comprises the nonparametric estimation of the reduced form and the corresponding residuals. The second step is the estimation of the primary equation via nonparametric regression with the reduced form residuals included as a regressor. The authors derive consistency and asymptotic normality results for their estimator, including optimal convergence rates. An empirical example, on the relationship between the hourly wage rate and hours worked, illustrates the utility of the authors' approach. (This abstract was borrowed from another version of this item.)
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