PL EN


2010 | 2 | 4 | 279-314
Article title

Estimation Methods Comparison of SVAR Models with a Mixture of Two Normal Distributions

Content
Title variants
Languages of publication
EN
Abstracts
EN
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 designed 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 problem 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.
Year
Volume
2
Issue
4
Pages
279-314
Physical description
Dates
received
2011-03-13
accepted
2011-08-04
Contributors
References
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-1d6c6e20-e729-48b3-bdeb-1c4baa89a8ca
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