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

By:

Matsushita, Yukitoshi [author]

Contributor(s):

Otsu, Taisuke [co author]

Material type: Text

TextSeries: 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:

Click here to access online

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.

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Item type	Current library	Call number	Vol info	Copy number	Status	Notes	Date due	Barcode
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

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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.

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