The structure of multivariate AR and ARMA systems: Regular and singular systems; the single and the mixed frequency case

被引:13
作者
Anderson, Brian D. O. [1 ,2 ]
Deistler, Manfred [3 ,4 ]
Felsenstein, Elisabeth [3 ]
Koelbl, Lukas [3 ]
机构
[1] Australian Natl Univ, Res Sch Engn, Canberra, ACT, Australia
[2] Natl ICT Australia Ltd, Canberra Res Lab, Sydney, NSW, Australia
[3] Vienna Univ Technol, Inst Stat & Math Methods Econ, A-1040 Vienna, Austria
[4] Inst Adv Studies, Vienna, Austria
基金
奥地利科学基金会;
关键词
FACTOR MODELS; IDENTIFICATION;
D O I
10.1016/j.jeconom.2016.02.004
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper is concerned with the structure of multivariate AR and ARMA systems. The emphasis is on two "non-standard" cases: We deal with the structure of singular AR and ARMA systems which generate singular spectral densities and with identifiability of ARMA systems from mixed frequency data. In the mixed frequency case we show that, for the case where the MA order is smaller than or equal to the AR order, identifiability can be achieved generically. Furthermore, we demonstrate that for a pure MA system identifiability cannot be achieved. The paper generalizes the results obtained in Anderson et al. (2015) for the AR case. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:366 / 373
页数:8
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