| 書目名稱 | Multivariate Modelling of Non-Stationary Economic Time Series |
| 編輯 | John Hunter,Simon P. Burke,Alessandra Canepa |
| 視頻video | http://file.papertrans.cn/642/641317/641317.mp4 |
| 概述 | Focuses on the multivariate nature of the problem of modelling non-stationary economic time series.Handles recent developments in Time Series Analysis.Has relevance for aspects of regulation and compe |
| 叢書名稱 | Palgrave Texts in Econometrics |
| 圖書封面 |  |
| 描述 | .This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction, volatility and the impact of different orders of integration. Models with expectations are considered along with alternate methods such as Singular Spectrum Analysis (SSA), the Kalman Filter and Structural Time Series, all in relation to cointegration. Using single equations methods to develop topics, and as examples of the notion of cointegration, Burke, Hunter, and Canepa provide direction and guidance to the now vast literature facing students and graduate economists.. |
| 出版日期 | Book 2017Latest edition |
| 關(guān)鍵詞 | econometrics; economics; modelling; stationary data; conventional time series; impulse responses; small sa |
| 版次 | 2 |
| doi | https://doi.org/10.1057/978-1-137-31303-4 |
| isbn_softcover | 978-0-230-24331-6 |
| isbn_ebook | 978-1-137-31303-4Series ISSN 2662-6594 Series E-ISSN 2662-6608 |
| issn_series | 2662-6594 |
| copyright | The Editor(s) (if applicable) and The Author(s) 2017 |
|Archiver|手機版|小黑屋|
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