Spurious Inference in the GARCH(1,1) Model When It Is Weakly Identified
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.
Year of publication: |
2007-03
|
---|---|
Authors: | Ma, Jun ; Nelson, Charles ; Startz, Richard |
Institutions: | Department of Economics, University of Washington |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
The Zero-Information-Limit-Condition and Spurious Inference in Weakly Identified Models
Nelson, Charles, (2007)
-
The Zero-Information-Limit Condition and Spurious Inference in Weakly Identified Models
Nelson, Charles, (2004)
-
Improved Inference for the Instrumental Variable Estimator
Startz, Richard, (1999)
- More ...