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.
Preview |
Text
Download (530kB) | Preview |
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 Classification: | C12 - Hypothesis Testing C14 - Semiparametric and Nonparametric Methods |
Subjects: | B- ECONOMIE ET FINANCE |
Divisions: | TSE-R (Toulouse) |
Site: | UT1 |
Date Deposited: | 09 Jul 2014 17:39 |
Last Modified: | 02 Apr 2021 15:48 |
OAI Identifier: | oai:tse-fr.eu:27678 |
URI: | https://publications.ut-capitole.fr/id/eprint/15755 |
Available Versions of this Item
-
Smooth Minimum Distance Estimation and Testing with Conditional Estimating Equations: Uniform in Bandwidth Theory. (deposited 09 Jul 2014 17:36)
- Smooth Minimum Distance Estimation and Testing with Conditional Estimating Equations: Uniform in Bandwidth Theory. (deposited 09 Jul 2014 17:39) [Currently Displayed]