For vectors x and w, let r(x,w) be a function that can be nonparametrically estimated consistently and asymptotically normally. We provide consistent, asymptotically normal estimators for the functions g and h, where r(x,w) = h[g(x),w], g is linearly homogeneous and h is monotonic in g. This...

A positive Lyapunov exponent is one practical definition of chaos. We develop a formal test for chaos in a noisy system based on the consistent standard errors of the nonparametric Lyapunov exponent estimators. For international real output series, the hypothesis of the positive Lyapunov...

We examine the higher order asymptotic properties of semiparametric regression estimators that were obtained by the general MINPIN method described in Andrews (1989, Semiparametric Econometric Models: I. Estimation, Discussion paper 908, Cowles Foundation). We derive an order <italic>n</italic>⁻¹ stochastic...

We construct efficient estimators of the identifiable parameters in a regression model when the errors follow a stationary parametric ARCH(<italic>P</italic>) process. We do not assume a functional form for the conditional density of the errors, but do require that it be symmetric about zero. The estimators of...

We propose a nonparametric empirical distribution function based test of an hypothesis of conditional independence between variables of interest. This hypothesis is of interest both for model specification purposes, parametric and semiparametric, and for non-model based testing of economic...