Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79507
Authors: 
Han, Heejoon
Kristensen, Dennis
Year of Publication: 
2013
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP18/13
Abstract: 
This paper investigates the asymptotic properties of the Gaussian quasi-maximum-likelihood estimators (QMLE.s) of the GARCH model augmented by including an additional explanatory variable - the so-called GARCH-X model. The additional covariate is allowed to exhibit any degree of persistence as captured by its long-memory parameter dx; in particular, we allow for both stationary and non-stationary covariates. We show that the QMLE.s of the parameters entering the volatility equation are consistent and mixed-normally distributed in large samples. The convergence rates and limiting distributions of the QMLE.s depend on whether the regressor is stationary or not. However, standard inferential tools for the parameters are robust to the level of persistence of the regressor with t-statistics following standard Normal distributions in large sample irrespective of whether the regressor is stationary or not.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
370.22 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.