In this work, we analyze the performance of production units using the directional distance function which allows to measure the distance to the frontier of the production set along any direction in the inputs/outputs space. We show that this distance can be expressed as a simple transformation...

We propose a quasi-Bayesian nonparametric approach to estimating the structural relationship φ among endogenous variables when instruments are available. We show that the posterior distribution of φ is inconsistent in the frequentist sense. We interpret this fact as the ill-posedness of the...

We design a data-dependent metric in Rd and use it to define the k-nearest neighbors of a given point. Our metric is invariant under all affine transformations. We show that, with this metric, the standard k-nearest neighbor regression estimate is asymptotically consistent under the usual...

Suppose that U=(U1,…,Ud) has a Uniform([0,1]d) distribution, that Y=(Y1,…,Yd) has the distribution G on R+d, and let X=(X1,…,Xd)=(U1Y1,…,UdYd). The resulting class of distributions of X (as G varies over all distributions on R+d) is called the Scale Mixture of Uniforms class of...

This paper extends the nonparametric structural method to estimate labor supply developed by Blomquist and Newey (2002) to handle cases in which there are individuals who do not work. The method is then applied to married women in Sweden from 1973 to 1999. I find an uncompensated wage elasticity...

This paper deals with the estimation of continuous-time diffusion processes which model the dynamics of a well diversified world stock index (WSI). We use the nonparametric kernel-based estimation to empirically identify a square root type diffusion coefficient function in the dynamics of the...

In nonparametric function estimation, the inclusion of shape constraints can confer several advantages, including improved estimation accuracy, reduced sensitivity to smoothing parameters, and control over the qualitative appearance of the estimate. Finding shape-restricted estimates may require...

In this paper we provide a new nonparametric estimator of the joint distribution of two lifetimes under random right censoring and left truncation which can be seen as a bivariate extension of the Kaplan–Meier estimator. We derive asymptotic results for this estimator, including uniform...

This paper studies the influence of educational innovations on school performance. We apply a tailored, fully nonparametric conditional efficiency model to study secondary school efficiency in the Netherlands. The application uses official school data and a self-collected questionnaire on recent...