Midlands State University Library
Image from Google Jackets

Second-order refinement of empirical likelihood for testing overidentifying restrictions created by by Yukitoshi Matsushita and Taisuke Otsu

By: Contributor(s): Material type: TextTextSeries: Econometric Theory ; Volume 29, number 2Cambridge: Cambridge University Press, 2013Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISSN:
  • 02664666
Subject(s): LOC classification:
  • HB139.T52 ECO
Online resources: Abstract: This paper studies second-order properties of the empirical likelihood overidentifying restriction test to check the validity of moment condition models. We show that the empirical likelihood test is Bartlett correctable and suggest second-order refinement methods for the test based on the empirical Bartlett correction and adjusted empirical likelihood. Our second-order analysis supplements the one in Chen and Cui (2007, Journal of Econometrics141, 492–516) who considered parameter hypothesis testing for overidentified models. In simulation studies we find that the empirical Bartlett correction and adjusted empirical likelihood assisted by bootstrapping provide reasonable improvements for the properties of the null rejection probabilities.
Reviews from LibraryThing.com:
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Call number Vol info Copy number Status Notes Date due Barcode
Journal Article Journal Article Main Library - Special Collections HB139.T52 ECO (Browse shelf(Opens below)) Vol. 29, no.2 (pages 324-353) SP17542 Not for loan For In House Use Only

This paper studies second-order properties of the empirical likelihood overidentifying restriction test to check the validity of moment condition models. We show that the empirical likelihood test is Bartlett correctable and suggest second-order refinement methods for the test based on the empirical Bartlett correction and adjusted empirical likelihood. Our second-order analysis supplements the one in Chen and Cui (2007, Journal of Econometrics141, 492–516) who considered parameter hypothesis testing for overidentified models. In simulation studies we find that the empirical Bartlett correction and adjusted empirical likelihood assisted by bootstrapping provide reasonable improvements for the properties of the null rejection probabilities.

There are no comments on this title.

to post a comment.