Estimation methods comparison of SVAR model with the mixture of two normal distributions - Monte Carlo analysis
This paper addresses the issue of obtaining maximum likelihood estimates of parameters for structural VAR models with a mixture of distributions. Hence the problem does not have a closed form solution, numerical optimization procedures need to be used. A Monte Carlo experiment is design to compare the performance of four maximization algorithms and two estimation strategies. It is shown that the EM algorithm outperforms the general maximization algorithms such as BFGS, NEWTON and BHHH. Moreover simplification of the probelm introduced in the two steps quasi ML method does not worsen small sample properties of the estimators and therefore may be recommended in the empirical analysis.
|Date of creation:||2010|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.eui.eu/ECO/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:eui:euiwps:eco2010/27. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Rhoda Lane)
If references are entirely missing, you can add them using this form.