The nonparametric censored regression model is y = max[c, m(x) + e], where both the regression function m(x) and the … the derivatives of an uncensored nonparametric regression. We then estimate the regression function itself by solving the … usual estimators in uncensored nonparametric regression. We also provide root n estimates of weighted average derivatives of …

nonparametric treatment of regression errors is permitted so that it is not necessary to be explicit about the dynamic specification …

We propose a nonparametric empirical distribution function based test of an hypothesis of conditional independence …

We propose a nonparametric test of conditional independence based on the empirical distribution function. The …

allow for covariates to enter the unit root (or near unit root) model in a nonparametric fashion, so that our model is an …

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 …

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 …

We study the problem of nonparametric regression when the regressor is endogenous, which is an important nonparametric …