Multiple Time Series Models 1st Edition by Patrick Brandt, John Williams 1412906563 9781412906562

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Product details:

ISBN 10: 1412906563 

ISBN 13: 9781412906562

Author: Patrick T. Brandt, John T. Williams

Many analyses of time series data involve multiple, related variables.  Multiple Time Series Models presents many specification choices and special challenges.  This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression.  The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned.  Specification, estimation, and inference using these models is discussed.  The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features Offers a detailed comparison of different time series methods and approaches. Includes a self-contained introduction to vector autoregression modeling. Situates multiple time series modeling as a natural extension of commonly taught statistical models.

Table of contents:

CHAPTER 1- INTRODUCTION TO MULTIPLE TIME SERIES MODELS

CHAPTER 2- BASIC VECTOR AUTOREGRESSION MODELS

CHAPTER 3- EXAMPLES OF VAR ANALYSES

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Tags: Patrick Brandt, John Williams, Multiple, Models