We investigate the problem of optimal choice of the smoothing parameter (bandwidth) for the regression discontinuity estimator. We focus on estimation by local linear regression, which was shown to be rate optimal (Porter, 2003). Investigation of an expected-squared-error-loss criterion reveals...

In this paper a new method for monotone estimation of a regression function is proposed. The estimator is obtained by the combination of a density and a regression estimate and is appealing to users of conventional smoothing methods as kernel estimators, local polynomials, series estimators or...

The problem of selecting bandwidth for nonparametric regression is investigated. The methodology used here is a double-smoothing procedure with data-driven pilot bandwidths. After giving an extension of the asymptotic result of Hardle, Hall and Marron (1992) by transfering the ideas of Jones,...

We investigate the problem of optimal choice of the smoothing parameter (bandwidth) for the regression discontinuity estimator. We focus on estimation by local linear regression, which was shown to be rate optimal (Porter, 2003). We derive the optimal bandwidth. This optimal bandwidth depends on...

We consider the problem of choosing two bandwidths simultaneously for estimating the difference of two functions at given points. When the asymptotic approximation of the mean squared error (AMSE) criterion is used, we show that minimisation problem is not well-defined when the sign of the...

Causal effects of a policy change on hazard rates of a duration outcome variable are not identified from a comparison of spells before and after the policy change, if there is unobserved heterogeneity in the effects and no model structure is imposed. We develop a discontinuity approach that...

A comparison of hazard rates of duration outcomes before and after policy changes is hampered by non-identification if there is unobserved heteogeneity in the effects and no model structure is imposed. We develop a discontinuity approach that overcomes this by exploiting variation in the moment...

The problem of selecting bandwidth for nonparametric regression is investigated. The methodology used here is a double-smoothing procedure with data-driven pilot bandwidths. After giving an extension of the asymptotic result of Hardle, Hall and Marron (1992) by transfering the ideas of Jones,...

In this paper a new method for monotone estimation of a regression function is proposed. The estimator is obtained by the combination of a density and a regression estimate and is appealing to users of conventional smoothing methods as kernel estimators, local polynomials, series estimators or...

For the common binary response model we propose a direct method for the nonparametric estimation of the effective dose level ED? (0 ? 1). The estimator is obtained by the composition of a nonparametric estimate of the quantile response curve and a classical density estimate. The new method...