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Time Series and Dynamic Models by Christian Gourieroux,Alain Monfort
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    • Product code: 10928
    • ISBN: 0521423082, ISBN13: 9780521423083, 688 pages, paperback
      Published by Cambridge University Press on 1997 , 1st
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    Description of Time Series and Dynamic Models

    In this book Christian Gourieroux and Alain Monfort provide an up-to-date and comprehensive analysis of modern time series econometrics. They have succeeded in synthesising in an organised and integrated way a broad and diverse literature. While the book does not assume a deep knowledge of economics, one of its most attractive features is the close attention it pays to economic models and phenomena throughout. The coverage represents a major reference tool for graduate students, researchers and applied economists. The book is divided into four sections. Section one gives a detailed treatment of classical seasonal adjustment or smoothing methods. Section two provides a thorough coverage of various mathematical tools. Section three is the heart of the book, and is devoted to a range of important topics including causality, exogeneity shocks, multipliers, cointegration and fractionally integrated models. The final section describes the main contribution of filtering and smoothing theory to time series econometric problems.

    Contents of Time Series and Dynamic Models

    Preface
    Notation

    SECTION I. Traditional Methods
    1. Introduction
    2. Seasonal adjustment by regression methods
    3. Moving averages for seasonal adjustment
    4. Exponential smoothing methods

    SECTION II. Probabilistic and Statistical Properties of Stationary Processes
    5. Some results on the univariate processes
    6. The Box and Jenkins approach to forecasting
    7. Multivariate time series
    8. Time series representations
    9. Estimation and testing (stationary case)

    SECTION III. Time Series Econometrics: Stationary and Nonstationary Models
    10. Causality, exogeneity and shocks
    11. Trend components
    12. Expectations
    13. Specification analysis
    14. Non-stationary processes

    SECTION IV. State Space Models
    15. State space models and the Kalman filter
    16. Applications of the state space model

    Statistical tables
    Bibliography
    Index


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