Multiple Time Series Models

Language: English

Published by SAGE Publications Inc, US, 2006

1412906563 / 9781412906562

Series: Book 110 of 194 - Quantitative Applications in the Social Sciences

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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 FeaturesOffers 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.

Seller Inventory # LU-9781412906562

Title
Multiple Time Series Models
Author
Patrick T. Brandt, John Taylor Williams
Publisher
SAGE Publications Inc, US
Publication year
2006
Condition
New
Binding
Paperback
Language
English
ISBN 10
1412906563
ISBN 13
9781412906562
Edition
1st.
Item weight
140 grams
Dimensions
13.97 x 0.66 x 21.59 cm
Series
Book 110 of 194: Quantitative Applications in the Social Sciences

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