£56.38

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£56 today · all-time low £56 (Aug 2026) · usually £56

Cambridge University Press Cambridge Structural Vector Autoregressive Analysis Book

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Description

Master modern econometrics with this comprehensive guide to structural vector autoregressive (VAR) models. Published by Cambridge University Press, this text serves as an essential resource for empirical researchers working in macroeconomics, finance, and related fields. This book provides a deep review of the various structural VAR approaches found in academic literature. It goes beyond simple theory by highlighting the practical pros and cons of different models. You will find clear guidance on making the most appropriate modeling choices, as well as effective methods for estimating and evaluating your structural VAR models. By tracing the evolution of structural VAR methodology, the text helps you understand how these tools have developed over time. It also provides valuable context by contrasting these methods with other common approaches, such as dynamic stochastic general equilibrium models. Whether you are a student or a professional researcher, this book offers the practical insights needed to navigate complex econometric modeling.

Key Features

Comprehensive review of structural VAR approaches discussed in current literature to help you understand diverse modeling options.

Practical guidance on selecting the most appropriate modeling choices for your specific empirical research needs.

Detailed instruction on the methods used for estimating and evaluating structural VAR models in professional practice.

In-depth analysis of the pros and cons of various structural VAR approaches to aid in better decision-making.

Historical context regarding the evolution of structural VAR methodology and its development over time.

Comparative analysis that contrasts structural VAR with other common methodologies like dynamic stochastic general equilibrium.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
23 November 2017
Listed Since
15 February 2017

Barcode

No barcode data available

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