issued coupon bonds. Our approach is nonparametric and does not assume a particular functional form for the discount function … our estimation procedure is iterative, rather like the backfitting method of estimating additive nonparametric models. We … with declining coefficients. The rate of convergence is standard for one dimensional nonparametric regression. We …

to a nonparametric regression function. The procedure employs a recent projection interpretation of popular kernel …

nonparametric instrumental regression. We propose a regularized Newton-type iteration and establish convergence and convergence rate …

We investigate a class of semiparametric ARCH(∞) models that includes as a special case the partially nonparametric … likelihood. We establish the distribution theory of the parametric components and the pointwise distribution of the nonparametric … component of the model. We also discuss efficiency of both the parametric and nonparametric part. We investigate the performance …

We study a general class of semiparametric estimators when the infinite-dimensional nuisance parameters include a …

covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing … of the covariates and of the observations. Our procedure is based on iterative fits of the covariates and nonparametric … the estimator is used for testing parametric specifications of the mean function. Our leading example is a semiparametric …