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New Introduction to Multiple Time Series Analysis
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Artikelzustand:
- Sofort-KaufenNew Introduction to Multiple Time Series Analysis
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eBay-Artikelnr.:397249843191
Artikelmerkmale
- Artikelzustand
- subject_code
- KJ
- target_audience
- General/trade
- is_adult_product
- false
- edition_number
- 1
- binding
- paperback
- edition
- 2005
- MPN
- 49 black & white illustrations, 36 black
- batteries_required
- false
- manufacturer
- Springer Berlin Heidelberg
- Brand
- Springer
- number_of_items
- 1
- pages
- 788
- ghs
- [object Object]
- genre
- Econometrics
- part_number
- 49 black & white illustrations, 36 black
- publication_date
- 2010-06-02T00:00:01Z
- unspsc_code
- 55101500
- batteries_included
- false
- ISBN
- 9783540262398
Über dieses Produkt
Product Identifiers
Publisher
Springer Berlin / Heidelberg
ISBN-10
3540262393
ISBN-13
9783540262398
eBay Product ID (ePID)
52748664
Product Key Features
Number of Pages
Xxi, 764 Pages
Language
English
Publication Name
New Introduction to Multiple Time Series Analysis
Subject
Engineering (General), Probability & Statistics / Time Series, Econometrics, Statistics
Publication Year
2006
Type
Textbook
Subject Area
Mathematics, Technology & Engineering, Business & Economics
Format
Trade Paperback
Dimensions
Item Weight
84.7 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Scholarly & Professional
Dewey Edition
22
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
519.5/5
Table Of Content
Finite Order Vector Autoregressive Processes.- Stable Vector Autoregressive Processes.- Estimation of Vector Autoregressive Processes.- VAR Order Selection and Checking the Model Adequacy.- VAR Processes with Parameter Constraints.- Cointegrated Processes.- Vector Error Correction Models.- Estimation of Vector Error Correction Models.- Specification of VECMs.- Structural and Conditional Models.- Structural VARs and VECMs.- Systems of Dynamic Simultaneous Equations.- Infinite Order Vector Autoregressive Processes.- Vector Autoregressive Moving Average Processes.- Estimation of VARMA Models.- Specification and Checking the Adequacy of VARMA Models.- Cointegrated VARMA Processes.- Fitting Finite Order VAR Models to Infinite Order Processes.- Time Series Topics.- Multivariate ARCH and GARCH Models.- Periodic VAR Processes and Intervention Models.- State Space Models.
Synopsis
When I worked on my Introduction to Multiple Time Series Analysis (Lutk ¨ ¨- pohl (1991)), a suitable textbook for this ?eld was not available. Given the great importance these methods have gained in applied econometric work, it is perhaps not surprising in retrospect that the book was quite successful. Now, almost one and a half decades later the ?eld has undergone substantial development and, therefore, the book does not cover all topics of my own courses on the subject anymore. Therefore, I started to think about a serious revision of the book when I moved to the European University Institute in Florence in 2002. Here in the lovely hills of ToscanyIhadthetimetothink about bigger projects again and decided to prepare a substantial revision of my previous book. Because the label Second Edition was already used for a previous reprint of the book, I decided to modify the title and thereby hope to signal to potential readers that signi'cant changes have been made relative to my previous multiple time series book., When I worked on my Introduction to Multiple Time Series Analysis (Lutk ] ]- pohl (1991)), a suitable textbook for this ?eld was not available. Given the great importance these methods have gained in applied econometric work, it is perhaps not surprising in retrospect that the book was quite successful. Now, almost one and a half decades later the ?eld has undergone substantial development and, therefore, the book does not cover all topics of my own courses on the subject anymore. Therefore, I started to think about a serious revision of the book when I moved to the European University Institute in Florence in 2002. Here in the lovely hills of ToscanyIhadthetimetothink about bigger projects again and decided to prepare a substantial revision of my previous book. Because the label Second Edition was already used for a previous reprint of the book, I decided to modify the title and thereby hope to signal to potential readers that signi'cant changes have been made relative to my previous multiple time series book., This is the new and totally revised edition of Lütkepohl's classic 1991 work. It provides a detailed introduction to the main steps of analyzing multiple time series, model specification, estimation, model checking, and for using the models for economic analysis and forecasting., This is the new and totally revised edition of Lütkepohl's classic 1991 work. It provides a detailed introduction to the main steps of analyzing multiple time series, model specification, estimation, model checking, and for using the models for economic analysis and forecasting. The book now includes new chapters on cointegration analysis, structural vector autoregressions, cointegrated VARMA processes and multivariate ARCH models. The book bridges the gap to the difficult technical literature on the topic. It is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it., This reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting multiple time series. The models covered include vector autoregressive, cointegrated,vector autoregressive moving average, multivariate ARCH and periodic processes as well as dynamic simultaneous equations and state space models. Least squares, maximum likelihood and Bayesian methods are considered for estimating these models. Different procedures for model selection and model specification are treated and a wide range of tests and criteria for model checking are introduced. Causality analysis, impulse response analysis and innovation accounting are presented as tools for structural analysis. The book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their tasks. It bridges the gap to the difficult technical literature on the topic.
LC Classification Number
HB139-141
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