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

• Authors: Katarzyna Maciejowska
• 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.

Keywords

EN

Structural vector autoregression; error correction models; mixed normal distributions; Monte Carlo

• Publisher: Polska Akademia Nauk Oddział w Łodzi
• Journal: Central European Journal of Economic Modelling and Econometrics
• Year: 2010
• Volume: 2
• Issue: 4
• Pages: 279-314

Dates

received

2011-03-13

accepted

2011-08-04

Contributors

author

Katarzyna Maciejowska

• Wroclaw University of Technology