A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models
Title: A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models
Author: KASCHA, Christian
Publisher: European University Institute
Series/Report no.: EUI ECO; 2007/12
Classical Gaussian maximum likelihood estimation of mixed vector autoregressive moving-average models is plagued with various numerical problems and has been considered difficult by many applied researchers. These disadvantages could have led to the dominant use of vector autoregressive models in macroeconomic research. Therefore, several other, simpler estimation methods have been proposed in the literature. In this paper these methods are compared by means of a Monte Carlo study. Different evaluation criteria are used to judge the relative performances of the algorithms.
Subject: C32; C15; C63; VARMA Models; Estimation Algorithms; Forecasting
Type of Access: openAccess