A new way of constructing efficient semiparametric instrumental variableestimators is proposed. The method involves the combination of a large number ofpossibly inefficient estimators rather than combining the instruments into anoptimal instrument function. The consistency and asymptotic...

We discuss a number of issues in the smoothed nonparametric estimation of kernel conditional probability density functions for stationary processes. The kernel conditional density estimate is a ratio of joint and marginal density estimates. We point out the different implications of leading...

We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard smoothness conditions and simultaneously depends on some nonparametric estimators that can...