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New Introduction to Multiple Time Series Analysis

  • Textbook
  • © 2005

Overview

Authors:
  1. Helmut Lütkepohl

    1. Department of Economics, European University Institute, Firenze, Italy

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  • Profound 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
  • Based on the successful Introduction to Multiple Time Series Analysis by Helmut Lütkepohl, published in 1991/1993
  • Totally revised and with new chapters on cointegration analysis, structural vector autoregressions, cointegrated VARMA processes and multivariate ARCH models
  • Includes supplementary material: sn.pub/extras

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Table of contents (18 chapters)

  1. Front Matter

    Pages I-XXI
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  2. Introduction

    1. Introduction

      • Helmut Lütkepohl
      Pages 1-7

  3. Finite Order Vector Autoregressive Processes

    1. Front Matter

      Pages 9-11
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    2. Stable Vector Autoregressive Processes

      • Helmut Lütkepohl
      Pages 13-68

    3. Estimation of Vector Autoregressive Processes

      • Helmut Lütkepohl
      Pages 69-133

    4. VAR Order Selection and Checking the Model Adequacy

      • Helmut Lütkepohl
      Pages 135-192

    5. VAR Processes with Parameter Constraints

      • Helmut Lütkepohl
      Pages 193-231

  4. Cointegrated Processes

    1. Front Matter

      Pages 233-235
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    2. Vector Error Correction Models

      • Helmut Lütkepohl
      Pages 237-267

    3. Estimation of Vector Error Correction Models

      • Helmut Lütkepohl
      Pages 269-324

    4. Specification of VECMs

      • Helmut Lütkepohl
      Pages 325-352

  5. Structural and Conditional Models

    1. Front Matter

      Pages 353-355
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    2. Structural VARs and VECMs

      • Helmut Lütkepohl
      Pages 357-386

    3. Systems of Dynamic Simultaneous Equations

      • Helmut Lütkepohl
      Pages 387-413

  6. Infinite Order Vector Autoregressive Processes

    1. Front Matter

      Pages 415-417
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    2. Vector Autoregressive Moving Average Processes

      • Helmut Lütkepohl
      Pages 419-446

    3. Estimation of VARMA Models

      • Helmut Lütkepohl
      Pages 447-492

    4. Specification and Checking the Adequacy of VARMA Models

      • Helmut Lütkepohl
      Pages 493-514

    5. Cointegrated VARMA Processes

      • Helmut Lütkepohl
      Pages 515-529

    6. Fitting Finite Order VAR Models to Infinite Order Processes

      • Helmut Lütkepohl
      Pages 531-553
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Keywords

About this book

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.

Authors and Affiliations

  • Department of Economics, European University Institute, Firenze, Italy

    Helmut Lütkepohl

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