%S TSE Working Paper
%A Pascal Lavergne
%A Valentin Patilea
%T Smooth Minimum Distance Estimation and Testing with Conditional Estimating Equations: Uniform in Bandwidth Theory
%X We study the influence of a bandwidth parameter in inference with conditional estimating equations. In that aim, we propose a new class of smooth minimum distance
estimators and we develop a theory that focuses on uniformity in bandwidth. We establish a vn-asymptotic representation of our estimator as a process indexed by a
bandwidth that can vary within a wide range including bandwidths independent of the sample size. We develop an efficient version of our estimator. We also study its behavior in misspecified models. We develop a procedure based on a distance metric statistic for testing restrictions on parameters as well as a bootstrap technique to account for the bandwidth’s influence. Our new methods are simple to implement, apply to non-smooth problems, and perform well in our simulations.
%K Semiparametric Estimation
%K Conditional Estimating Equations
%K Smoothing Methods
%K Asymptotic Efficiency
%K Hypothesis Testing
%K Bootstrap
%B TSE Working Paper
%V 13-404
%D 2013
%C Toulouse
%I TSE Working Paper
%L publications15629