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• W241917 abstract "Abstract Vector autoregressive moving average (VARMA) models have certain advantages over pure vector autoregressive (VAR) models because they may permit more parsimonious representations of data generation processes. Moreover for many economic data, for instance, temporal and contemporaneous aggregation leads directly to mixed VARMA models. The major problems in VARMA modelling are related to specification unique representation. To solve these problems, we consider a VARMA model in echelon form, which is automatically identified. To specify the orders of the model, we propose an algorithm which selects a maximal set of linearly independent rows of the Hankel matrix of the estimated covariances. This set is obtained by sequentially testing the smallest singular value of the Hankel matrix and yields estimates of Kronecker indices which characterise the echelon form. Using the matrix perturbation theory, the asymptotic distribution of the test statistic is seen to be chi-squared. An example based on economic data series illustrates the procedure and demonstrates its feasibility in practice. Its performance is compared with other existing methods." @default.
• W241917 created "2016-06-24" @default.
• W241917 creator A5025445026 @default.
• W241917 date "2001-09-01" @default.
• W241917 modified "2023-09-25" @default.
• W241917 title "Specification of Varma Echelon form Models" @default.
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• W241917 doi "https://doi.org/10.1016/s1474-6670(17)33052-5" @default.
• W241917 hasPublicationYear "2001" @default.
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