Estimation methods comparison of SVAR model with the mixture of two normal distributions - Monte Carlo analysis

Katarzyna Maciejowska ()

No ECO2010/27, Economics Working Papers from European University Institute

Abstract: 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.

Keywords: Structural vetcor autoregression; Error correction models; Mixed normal; Monte Carlo (search for similar items in EconPapers)
JEL-codes: C32 C46 (search for similar items in EconPapers)
Date: 2010
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
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Citations: View citations in EconPapers (3)

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