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Product Identifiers
PublisherSpringer Berlin / Heidelberg
ISBN-103540401725
ISBN-139783540401728
eBay Product ID (ePID)48248974
Product Key Features
Number of PagesXxi, 764 Pages
Publication NameNew Introduction to Multiple Time Series Analysis
LanguageEnglish
SubjectEngineering (General), Probability & Statistics / Time Series, Econometrics, Statistics
Publication Year2005
TypeTextbook
AuthorHelmut Lütkepohl
Subject AreaMathematics, Technology & Engineering, Business & Economics
FormatHardcover
Dimensions
Item Weight98.8 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2005-927322
ReviewsFrom the reviews: "The monograph is a substantial revision of the authora's previous successful book, Introduction to multiple time series analysis a? . As the previous book, the present one is meant to be an introductory exposition a? and it has been prepared with economic and business students in mind a? ." (Tom?!?! Cipra, Zentralblatt MATH, Vol. 1072, 2005) "The book is oriented towards econometric applications; the text was prepared with economics and business students in mind, and examples and exercises are chosen accordingly. The text presents a collection of many of the topics currently treated in the literature. a? this new version of a previous book by the author represents a timely addition to the time series and econometric literature. a? The selection of topics responds to current trends in the literature." (Ra'l Pedro Mentz, Mathematical Reviews, Issue 2006 f)
Dewey Edition22
Number of Volumes1 vol.
IllustratedYes
Dewey Decimal519.5/5
Table Of ContentFinite 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.
SynopsisWhen 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 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., 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 NumberHB139-141
