nonparametric estimation. We further develop methods for automatic bandwidth selection. Finally, we discuss how to impose …Nonparametric estimators provide a flexible means of uncovering salient features of auction data. Although these … provide several suggestions for nonparametric estimation of first-price auction models. Specifically, we show how to impose …

We develop a nonparametric test to check whether a process can be represented by a stochastic differential equation …

approaches rely on restrictive parametric assumptions. This paper contributes to nonparametric approaches, with unknown frontier … and unknown variance of a normally distributed error. We propose a nonparametric method identifying and estimating both …

nonparametric instrumental regression. We propose a regularized Newton-type iteration and establish convergence and convergence rate …

estimator is often estimated using a nonparametric kernel method that involves a lag truncation parameter. Depending on whether … uses an F-distribution as the reference distribution. Finally, the paper develops a bandwidth selection rule that is … testing-optimal in that the bandwidth minimizes the type II error of the asymptotic F test while controlling for its type I …

In nonparametric instrumental variables estimation, the mapping that identifies the function of interest, g, is …

the scale parameter and the bandwidth parameter in the estimator. In Monte Carlo simulations, we compare the finite sample …