Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Studies in Nonlinear Dynamics & Econometrics

Ed. by Mizrach, Bruce

5 Issues per year


IMPACT FACTOR 2016: 0.649

CiteScore 2016: 0.63

SCImago Journal Rank (SJR) 2016: 0.546
Source Normalized Impact per Paper (SNIP) 2016: 0.793

Mathematical Citation Quotient (MCQ) 2016: 0.03

Online
ISSN
1558-3708
See all formats and pricing
More options …
Volume 11, Issue 1 (Mar 2007)

Issues

Spurious Inference in the GARCH (1,1) Model When It Is Weakly Identified

Jun Ma
  • 1University of Washington,
/ Charles R Nelson
  • 2University of Washington,
/ Richard Startz
  • 3University of Washington,
Published Online: 2007-03-01 | DOI: https://doi.org/10.2202/1558-3708.1434

This paper shows that the Zero-Information-Limit-Condition (ZILC) formulated by Nelson and Startz (2006) holds in the GARCH (1,1) model. As a result, the GARCH estimate tends to have too small a standard error relative to the true one when the ARCH parameter is small, even when sample size becomes very large. In combination with an upward bias in the GARCH estimate, the small standard error will often lead to the spurious inference that volatility is highly persistent when it is not. We develop an empirical strategy to deal with this issue and show how it applies to real datasets.

About the article

Published Online: 2007-03-01


Citation Information: Studies in Nonlinear Dynamics & Econometrics, ISSN (Online) 1558-3708, DOI: https://doi.org/10.2202/1558-3708.1434.

Export Citation

©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston. Copyright Clearance Center

Comments (0)

Please log in or register to comment.
Log in