New Introduction to Multiple Time Series Analysis

  • Helmut Lütkepohl

Table of contents

  1. Front Matter
    Pages I-XXI
  2. Introduction

    1. Helmut Lütkepohl
      Pages 1-7
  3. Finite Order Vector Autoregressive Processes

    1. Front Matter
      Pages 9-11
    2. Helmut Lütkepohl
      Pages 13-68
    3. Helmut Lütkepohl
      Pages 69-133
    4. Helmut Lütkepohl
      Pages 135-192
    5. Helmut Lütkepohl
      Pages 193-231
  4. Cointegrated Processes

    1. Front Matter
      Pages 233-235
    2. Helmut Lütkepohl
      Pages 237-267
    3. Helmut Lütkepohl
      Pages 269-324
    4. Helmut Lütkepohl
      Pages 325-352
  5. Structural and Conditional Models

    1. Front Matter
      Pages 353-355
    2. Helmut Lütkepohl
      Pages 357-386
    3. Helmut Lütkepohl
      Pages 387-413
  6. Infinite Order Vector Autoregressive Processes

    1. Front Matter
      Pages 415-417
    2. Helmut Lütkepohl
      Pages 419-446
    3. Helmut Lütkepohl
      Pages 447-492
    4. Helmut Lütkepohl
      Pages 515-529

About this book

Introduction

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.

Keywords

Analysis Dynamic Econometric Modeling Forecasting Multiple Time Series Multiple Time Series Analysis Regression Time Series Analysis model simulation statistics

Authors and affiliations

  • Helmut Lütkepohl
    • 1
  1. 1.Department of EconomicsEuropean University InstituteFirenzeItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-27752-1
  • Copyright Information Springer-Verlag Berlin Heidelberg 2005
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Business and Economics
  • Print ISBN 978-3-540-40172-8
  • Online ISBN 978-3-540-27752-1
  • About this book