The partially linear regression model: Monte Carlo evidence from the projection pursuit regression approach

In a partially linear regression model with a high dimensional unknown component we find an estimator of the parameter of the linear part based on projection pursuit methods to be considerably more efficient than the standard density weighted kernel estimator.