Smooth Minimum Distance Estimation and Testing with Conditional Estimating Equations: Uniform in Bandwidth Theory

Lavergne, Pascal and Patilea, Valentin (2013) Smooth Minimum Distance Estimation and Testing with Conditional Estimating Equations: Uniform in Bandwidth Theory. Journal of Econometrics, vol. 177 (n° 1). pp. 47-59.

This is the latest version of this item.

[img]
Preview
Text
Download (530kB) | Preview
Official URL: http://tse-fr.eu/pub/27678

Abstract

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.

Item Type: Article
Language: English
Date: November 2013
Refereed: Yes
Uncontrolled Keywords: Semiparametric Estimation, Conditional Estimating Equations, Smoothing Methods, Asymptotic Efficiency, Hypothesis Testing, Bootstrap
JEL codes: C12 - Hypothesis Testing
C14 - Semiparametric and Nonparametric Methods
Subjects: B- ECONOMIE ET FINANCE
Divisions: Toulouse School of Economics - TSE
Site: UT1
Date Deposited: 09 Jul 2014 17:39
Last Modified: 18 Oct 2017 15:13
OAI ID: oai:tse-fr.eu:27678
URI: http://publications.ut-capitole.fr/id/eprint/15755

Available Versions of this Item

Actions (login required)

View Item View Item