We establish the validity of higher order asymptotic expansions to the distribution of a version of the nonlinear semiparametric instrumental variable considered in Newey (1990) as well as to the distribution of a Wald statistic derived from it. We employ local polynomial smoothing with variable...

We derive the asymptotic distribution of a new backfitting procedure for estimating the closest additive approximation to a nonparametric regression function. The procedure employs a recent projection interpretation of popular kernel estimators provided by Mammen, Marron, Turlach and Wand...

Assume that we have two populations (X <Subscript>1</Subscript>,Y <Subscript>1</Subscript>) and (X <Subscript>2</Subscript>,Y <Subscript>2</Subscript>) satisfying two general nonparametric regression models Y <Subscript> j </Subscript>=m <Subscript> j </Subscript>(X <Subscript> j </Subscript>)+ε <Subscript> j </Subscript>, j=1,2, where m(⋅) is a smooth location function, ε <Subscript> j </Subscript> has zero location and the response Y <Subscript> j </Subscript> is possibly right-censored. In this paper, we propose...</subscript></subscript></subscript></subscript></subscript></subscript></subscript></subscript></subscript></subscript>

This paper is concerned with estimating the mean of a random variable Y conditional on a vector of covariates X under weak assumptions about the form of the conditional mean function. Fully nonparametric estimation is usually unattractive when X is multidimensional because estimation precision...

This paper develops a new estimation procedure for characteristic-based factor models of security returns. We treat the factor model as a weighted additive nonparametric regression model, with the factor returns serving as time-varying weights, and a set of univariate non-parametric functions...

In this paper we introduce the nonparametric AR(1)–ARCH(1) model and show weak consistency of the Nadaraya–Watson estimators for the model. We propose a residual and a wild bootstrap method and prove weak consistency of the bootstrap estimators.

This paper develops a new estimation procedure for characteristic-based factor models of security returns. We treat the factor model as a weighted additive nonparametric regression model, with the factor returns serving as time-varying weights, and a set of univariate nonparametric functions...