| 書目名稱 | Model Reduction Methods for Vector Autoregressive Processes |
| 編輯 | Ralf Brüggemann |
| 視頻video | http://file.papertrans.cn/636/635791/635791.mp4 |
| 叢書名稱 | Lecture Notes in Economics and Mathematical Systems |
| 圖書封面 |  |
| 描述 | 1. 1 Objective of the Study Vector autoregressive (VAR) models have become one of the dominant research tools in the analysis of macroeconomic time series during the last two decades. The great success of this modeling class started with Sims‘ (1980) critique of the traditional simultaneous equation models (SEM). Sims criticized the use of ‘too many incredible restrictions‘ based on ‘supposed a priori knowledge‘ in large scale macroeconometric models which were popular at that time. Therefore, he advo- cated largely unrestricted reduced form multivariate time series models, unrestricted VAR models in particular. Ever since his influential paper these models have been employed extensively to characterize the underlying dynamics in systems of time series. In particular, tools to summarize the dynamic interaction between the system variables, such as impulse response analysis or forecast error variance decompo- sitions, have been developed over the years. The econometrics of VAR models and related quantities is now well established and has found its way into various textbooks including inter alia Llitkepohl (1991), Hamilton (1994), Enders (1995), Hendry (1995) and Greene (2002). The u |
| 出版日期 | Book 2004 |
| 關(guān)鍵詞 | Cointegration; Model Reduction; Structural VAR Models; Time Series Econometrics; Time series; Vector Auto |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-642-17029-4 |
| isbn_softcover | 978-3-540-20643-9 |
| isbn_ebook | 978-3-642-17029-4Series ISSN 0075-8442 Series E-ISSN 2196-9957 |
| issn_series | 0075-8442 |
| copyright | Springer-Verlag Berlin Heidelberg 2004 |
|Archiver|手機(jī)版|小黑屋|
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