A comparison of estimation methods for vector autoregressive moving-average models

Recently, there has been a renewed interest in modeling economic time series by vectorautoregressive moving-average models. However, this class of models has been unpopularin practice because of estimation problems and the complexity of the identication stage.These disadvantages could have led to the dominant use of vector autoregressive modelsin macroeconomic research. In this paper, several simple estimation methods for vectorautoregressive moving-average models are compared among each other and with purevector autoregressive modeling using ordinary least squares by means of a Monte Carlostudy. Dierent evaluation criteria are used to judge the relative performances of the algorithms