On causal and non‐causal cointegrated vector autoregressive time series
Previous‐30 treatments of multivariate non‐causal time series have assumed stationarity. In this article, we consider integrated processes in a non‐causal setting. We generalize the Johansen–Granger representation for causal vector autoregressive (VAR) models to allow for dependence on future errors...
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| Published in: | Journal of time series analysis Vol. 43; no. 2; pp. 178 - 196 |
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| Format: | Journal Article |
| Language: | English |
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Oxford, UK
John Wiley & Sons, Ltd
01.03.2022
Blackwell Publishing Ltd |
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| ISSN: | 0143-9782, 1467-9892 |
| Online Access: | Get full text |
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| Abstract | Previous‐30 treatments of multivariate non‐causal time series have assumed stationarity. In this article, we consider integrated processes in a non‐causal setting. We generalize the Johansen–Granger representation for causal vector autoregressive (VAR) models to allow for dependence on future errors and discuss how the parameters can be estimated. The asymptotic distribution of the trace statistic is also considered. Some Monte Carlo simulations are presented. |
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| AbstractList | Previous‐30 treatments of multivariate non‐causal time series have assumed stationarity. In this article, we consider integrated processes in a non‐causal setting. We generalize the Johansen–Granger representation for causal vector autoregressive (VAR) models to allow for dependence on future errors and discuss how the parameters can be estimated. The asymptotic distribution of the trace statistic is also considered. Some Monte Carlo simulations are presented. |
| Author | Rygh Swensen, Anders |
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| Copyright | 2021 The Authors. published by John Wiley & Sons Ltd. 2021. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| References | 2013; 29 1987; 55 2012; 80 2006; 97 1991; 36 2006; 77 1998 2020; 38 1995 2005 1970 1991 2012; 15 2016; 37 2014; 178 2009; 28 2019; 81 2010; 26 2000 2005; 8 2017; 79 2020; 216 2016 1982 2013 2017; 200 1988 e_1_2_10_23_1 e_1_2_10_24_1 e_1_2_10_21_1 e_1_2_10_22_1 e_1_2_10_20_1 e_1_2_10_2_1 e_1_2_10_4_1 e_1_2_10_18_1 e_1_2_10_3_1 e_1_2_10_19_1 e_1_2_10_6_1 e_1_2_10_16_1 e_1_2_10_5_1 e_1_2_10_17_1 e_1_2_10_8_1 e_1_2_10_14_1 e_1_2_10_7_1 e_1_2_10_9_1 e_1_2_10_13_1 e_1_2_10_10_1 e_1_2_10_11_1 Horn RA (e_1_2_10_15_1) 2013 Swensen AR (e_1_2_10_28_1) 2006; 77 Hannan EJ (e_1_2_10_12_1) 1988 der Wart AW (e_1_2_10_29_1) 1998 R Core Team (e_1_2_10_25_1) 2016 e_1_2_10_27_1 e_1_2_10_26_1 |
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| SubjectTerms | Autoregressive models Causal models Causality cointegration Errors non‐causal models Time series Treatment methods Vector autoregressive models |
| Title | On causal and non‐causal cointegrated vector autoregressive time series |
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