| 書目名稱 | Time Series Econometrics | | 副標題 | Learning Through Rep | | 編輯 | John D. Levendis | | 視頻video | http://file.papertrans.cn/926/925444/925444.mp4 | | 概述 | Revised and updated for the 2nd edition.Provides several worked-out examples that enable a more hands-on approach to learning the subject matter.Request lecturer material: | | 叢書名稱 | Springer Texts in Business and Economics | | 圖書封面 |  | | 描述 | .Revised and updated for the second edition, this textbook allows students to work through classic texts in economics and finance, using the original data and replicating their results. In this book, the author rejects the theorem-proof approach as much as possible, and emphasizes the practical application of econometrics. They show with examples how to calculate and interpret the numerical results..This book begins with students estimating simple univariate models, in a step by step fashion, using the popular Stata software system. Students then test for stationarity, while replicating the actual results from hugely influential papers such as those by Granger & Newbold, and Nelson & Plosser. Readers will learn about structural breaks by replicating papers by Perron, and Zivot & Andrews. They then turn to models of conditional volatility, replicating papers by Bollerslev. Students estimate multi-equation models such as vector autoregressions and vector error-correction mechanisms, replicating the results in influential papers by Sims and Granger. Finally, students estimate static and dynamic panel data models, replicating papers by Thompson, and Arellano & Bond..The book contains m | | 出版日期 | Textbook 2023Latest edition | | 關(guān)鍵詞 | econometrics; Stata; vector autoregression; volatility; time series analysis; financial econometrics; ARCH | | 版次 | 2 | | doi | https://doi.org/10.1007/978-3-031-37310-7 | | isbn_ebook | 978-3-031-37310-7Series ISSN 2192-4333 Series E-ISSN 2192-4341 | | issn_series | 2192-4333 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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