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Dynamic Model Analysis

Advanced Matrix Methods and Unit-Root Econometrics Representation Theorems

  • Book
  • © 2009

Overview

Editors:
  1. Mario Faliva

    1. Faculty of Economics Department of Mathematics and Econometrics, Catholic University of Milan, Largo Gemelli, 1, Italy

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  2. Maria Grazia Zoia

    1. Faculty of Economics Department of Mathematics and Econometrics, Catholic University of Milan, Largo Gemelli, 1, Italy

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    You can also search for this editor in PubMed   Google Scholar

  • Innovative algebraic toolkit for dynamic econometric model analysis
  • Self-contained design providing basic and advanced algebraic technicalities
  • Step by step guidance to a thorough understanding
  • Includes the latest research by the authors
  • Includes supplementary material: sn.pub/extras

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Table of contents (3 chapters)

  1. Front Matter

    Pages i-x
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  2. The Algebraic Framework of Unit-Root Econometrics

    Pages 1-125

  3. The Statistical Setting

    Pages 127-160

  4. Econometric Dynamic Models: From Classical Econometrics to Time Series Econometrics

    Pages 161-211

  5. Back Matter

    Pages 213-218
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About this book

This second edition sees the light three years after the first one: too short a time to feel seriously concerned to redesign the entire book, but sufficient to be challenged by the prospect of sharpening our investigation on the working of econometric dynamic models and to be inclined to change the title of the new edition by dropping the “Topics in” of the former edition. After considerable soul searching we agreed to include several results related to topics already covered, as well as additional sections devoted to new and sophisticated techniques, which hinge mostly on the latest research work on linear matrix polynomials by the second author. This explains the growth of chapter one and the deeper insight into representation theorems in the last chapter of the book. The rôle of the second chapter is that of providing a bridge between the mathematical techniques in the backstage and the econometric profiles in the forefront of dynamic modelling. For this purpose, we decided to add a new section where the reader can find the stochastic rationale of vector autoregressive specifications in econometrics. The third (and last) chapter improves on that of the first edition by re- ing the fruits of the thorough analytic equipment previously drawn up.

Reviews

From the reviews of the second edition:

“Researchers and postgraduate students in time series econometrics, statistics, matrix mathematics and other related areas. … provide an insightful analysis of dynamic modelling in econometrics by a self-contained and analytic setting to guide formulation and solution in closed form of vector autoregressive models with unit roots. … The presentation of the book is given in theorem-proof style with definitions, lemmas, theorems … . The book is very welcome, as it (again) proves that matrix results … are applicable and useful in dealing with real-world issues.” (Shuangzhe Liu, International Statistical Review, Vol. 78 (1), 2010)

Editors and Affiliations

  • Faculty of Economics Department of Mathematics and Econometrics, Catholic University of Milan, Largo Gemelli, 1, Italy

    Mario Faliva, Maria Grazia Zoia

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