Multiple Time Series Models

Multiple Time Series Models

Multiple Time Series Models introduces researchers and students to the different approaches to modeling multivariate time series data including simultaneous equations, ARIMA, error correction models, and vector autoregression. Authors Patrick T. Brandt and John T. Williams focus on vector autoregression (VAR) models as a generalization of these other approaches and discuss specification, estimation, and inference using these models.

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Publisher SAGE
Release Date
ISBN 1412906563
Pages 99 pages
Rating 4/5 (62 users)

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Multiple Time Series Models
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Type: BOOK - Published: 2007 - Publisher: SAGE

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Multiple Time Series Models introduces researchers and students to the different approaches to modeling multivariate time series data including simultaneous equ
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Type: BOOK - Published: 1993-08-13 - Publisher: Springer Science & Business Media

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This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. Th
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This book presents the numerous tools for the econometric analysis of time series. The text is designed with emphasis on the practical application of theoretica
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1. 1 Integrating results The empirical study of macroeconomic time series is interesting. It is also difficult and not immediately rewarding. Many statistical a
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