In a number of semiparametric models, smoothing seems necessary in order to obtain estimates of the parametric … estimates of semiparametric index models. Approaches to bias-reduction are discussed. We also develop a higher order expansion … sample performance of the methods is investigated by means of Monte Carlo simulations from a Tobit model …

Local linear fitting is a popular nonparametric method in nonlinear statistical and econometric modelling. Lu and … nonparametric regression function under the condition of near epoch dependence. We further investigate the uniform consistency of … established under mild conditions. Furthermore, general results of uniform convergence rates for nonparametric kernel …

nonparametric long run component and a unit multivariate GARCH short run dynamic component. We suggest various kernel …-based estimation procedures for the parametric and nonparametric components, and derive the asymptotic properties thereof. For the … parametric part of the model, we obtain the semiparametric efficiency bound. Our method is applied to a bivariate stock index …

This paper develops methodology for nonparametric estimation of a polarization measure due to Anderson (2004) and …

We use local polynomial fitting to estimate the nonparametric M-regression function for strongly mixing stationary …

We propose a general two-step estimation method for the structural parameters of popular semiparametric Markovian …

Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, containing … unknown, nonparametric, form, where series nonparametric estimates of the score function are employed in adaptive estimates of …

Normal distribution with a faster rate of convergence than unrestricted nonparametric alternatives. Their small sample …