Search Results

No results found.

(refine search)
SORT BY: PREVIOUS / NEXT
Author:Harmon, Richard 

Working Paper
The simultaneous equations model with generalized autoregressive conditional heteroskedasticity: the SEM-GRACH model
In this paper I generalize the standard simultaneous equations model by allowing the innovations of the structural equations to exhibit Generalized Autoregressive Conditional Heteroskedasticity (GARCH). I refer to this new specification as the SEM-GARCH model. I develop two estimation strategies: LIM-GARCH, a limited information estimator, and FIM-GARCH, a full information estimator. I show that these estimators are consistent and asymptotically normal. Following Weiss (1986) I show that when the errors in the SEM-GARCH process are incorrectly assumed to be conditionally normal the likelihood function is still maximized at the true parameters, given certain regularity conditions. This results in the asymptotic variance-covariance matrix being more complex than the usual inverse of the information matrix.
AUTHORS: Harmon, Richard
DATE: 1988

FILTER BY Content Type

FILTER BY Author

FILTER BY Keywords

PREVIOUS / NEXT