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Time Series Econometrics
Learning Through Replication
Buch von John D. Levendis
Sprache: Englisch

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Beschreibung
In this book, the author rejects the theorem-proof approach as much as possible, and emphasize 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 and Newbold, and Nelson and Plosser. Readers will learn about structural breaks by replicating papers by Perron, and Zivot and Andrews. They then turn to models of conditional volatility, replicating papers by Bollerslev. Finally, students estimate multi-equation models such as vector autoregressions and vector error-correction mechanisms, replicating the results in influential papers by Sims and Granger.

The book contains many worked-out examples, and many data-driven exercises. While intended primarily for graduate students and advanced undergraduates, practitioners will also find the book useful.

In this book, the author rejects the theorem-proof approach as much as possible, and emphasize 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 and Newbold, and Nelson and Plosser. Readers will learn about structural breaks by replicating papers by Perron, and Zivot and Andrews. They then turn to models of conditional volatility, replicating papers by Bollerslev. Finally, students estimate multi-equation models such as vector autoregressions and vector error-correction mechanisms, replicating the results in influential papers by Sims and Granger.

The book contains many worked-out examples, and many data-driven exercises. While intended primarily for graduate students and advanced undergraduates, practitioners will also find the book useful.

Inhaltsverzeichnis
Chapter 1: Introduction.- Chapter 2: ARMA (p,q) Processes.- Chapter 3: Non-Stationary and ARIMA (p,d,q) Processes.- Chapter 4: Unit Root and Stationarity Tests.- Chapter 5: Structural Breaks and Non-Stationairty.- Chapter 6: ARCH, GARCH and Time-Varying Variance.- Chapter 7: Multiple Time Series and Vector Autoregressions.- Chapter 8: Multiple Time Series and Cointegration.
Details
Erscheinungsjahr: 2019
Fachbereich: Allgemeines
Genre: Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Buch
Inhalt: Einband - fest (Hardcover)
ISBN-13: 9783319982816
ISBN-10: 3319982818
Sprache: Englisch
Herstellernummer: 978-3-319-98281-6
Autor: Levendis, John D.
Auflage: 1st ed. 2018
Hersteller: Springer
Springer, Berlin
Springer International Publishing
Abbildungen: XIII, 409 p. 403 illus.
Maße: 242 x 158 x 35 mm
Von/Mit: John D. Levendis
Erscheinungsdatum: 18.02.2019
Gewicht: 0,798 kg
Artikel-ID: 114093574
Inhaltsverzeichnis
Chapter 1: Introduction.- Chapter 2: ARMA (p,q) Processes.- Chapter 3: Non-Stationary and ARIMA (p,d,q) Processes.- Chapter 4: Unit Root and Stationarity Tests.- Chapter 5: Structural Breaks and Non-Stationairty.- Chapter 6: ARCH, GARCH and Time-Varying Variance.- Chapter 7: Multiple Time Series and Vector Autoregressions.- Chapter 8: Multiple Time Series and Cointegration.
Details
Erscheinungsjahr: 2019
Fachbereich: Allgemeines
Genre: Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Buch
Inhalt: Einband - fest (Hardcover)
ISBN-13: 9783319982816
ISBN-10: 3319982818
Sprache: Englisch
Herstellernummer: 978-3-319-98281-6
Autor: Levendis, John D.
Auflage: 1st ed. 2018
Hersteller: Springer
Springer, Berlin
Springer International Publishing
Abbildungen: XIII, 409 p. 403 illus.
Maße: 242 x 158 x 35 mm
Von/Mit: John D. Levendis
Erscheinungsdatum: 18.02.2019
Gewicht: 0,798 kg
Artikel-ID: 114093574
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