Introduction to Multiple Time Series Analysis

Introduction to Multiple Time Series Analysis

Description

This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This 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 this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.


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Available Format

Details

Author(s)
Helmut L├╝tkepohl
Format
Paperback | 545 pages
Dimensions
170 x 244 x 29.21mm | 1,970g
Publication date
13 Aug 1993
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Publication City/Country
Berlin, Germany
Language
English
Edition
Revised
Edition Statement
2nd ed. 1993
Illustrations note
XXI, 545 p.
ISBN10
3540569405
ISBN13
9783540569404