nonparametric sample covariances have different uniform convergence rates depending on direction, a result that differs …, we establish uniform consistency of nonparametric kernel estimators of the coefficient functions in nonlinear …

used in applied econometric work. Nonparametric and semiparametric estimation methods are proposed to estimate the varying … the conduct of semiparametric regression with nonstationary data. The results include some new asymptotic theory for …

nonparametric kernel methods. It is shown that the usual asymptotic methods of kernel estimation completely break down in this …-consistency apply in nonparametric kernel estimation of time-varying coefficient cointegration models. The higher rate of convergence (n … degenerate directions but is still super-consistent for nonparametric estimators. In addition, local linear methods are used to …

nonparametric kernel methods. It is shown that the usual asymptotic methods of kernel estimation completely break down in this …-consistency apply in nonparametric kernel estimation of time-varying coefficient cointegration models. The higher rate of convergence … degenerate directions but is still super-consistent for nonparametric estimators. In addition, local linear methods are used to …

nonparametric regression is consistent whereas parametric regression is inconsistent even when the true regression functional form … functional form is known, but interestingly does not do so in local nonparametric regression. We examine this example in detail … means of spatial bounding and bias correction using nonparametric estimation. Some simulations are reported illustrating the …

nonparametric regression and there is no need for nonparametric instrumental variable estimation. Instead, simple Nadaraya Watson … nonparametric estimation of a (possibly nonlinear) cointegrating regression equation is consistent with a limiting (mixed) normal … nonparametric regression with independent data when there are continuous location shifts in the regressor. In such cases, location …

parameter that plays a key role in determining the asymptotic properties of the standard errors and associated semi-parametric …

nonparametric estimation where the focus is the nonparametric quantity itself and the choice rule balances asymptotic variance with …

identified without the need for instrumentation. Second, in partially linear threshold models, both parametric and nonparametric … conventional parametric structural change tests to the nonparametric case. A wild bootstrap procedure is suggested to deliver …