  We consider a semiparametric partly linear model identified by instrumental
variables. We propose an estimation method that does not smooth on the
instruments and we extend the Landweber-Fridman regularization scheme to the
estimation of this semiparametric model. We then show the asymptotic normality
of the parametric estimator and obtain the convergence rate for the
nonparametric estimator. Our estimator that does not smooth on the instruments
coincides with a typical estimator that does smooth on the instruments but
keeps the respective bandwidth fixed as the sample size increases. We propose a
data driven method for the selection of the regularization parameter, and in a
simulation study we show the attractive performance of our estimators.
