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Topics in Advanced Econometrics

Topics in Advanced Econometrics

Topics in Advanced Econometrics

Estimation, Testing, and Specification of Cross-Section and Time Series Models
Herman J. Bierens, Southern Methodist University, Texas
April 2011
This ISBN is for an eBook version which is distributed on our behalf by a third party.
Adobe eBook Reader
9780511881114
$51.99
USD
Adobe eBook Reader
GBP
Paperback

    In this book Herman Bierens provides a mathematically rigorous treatment of a number of timely topics in advanced econometrics. His subjects include nonlinear estimation, maximum likelihood theory, ARMA and ARMAX models, unit roots and cointegration, and nonparametric regression, together with an extensive and thorough treatment of the necessary probability theory. Professor Bierens' study is uniquely self-contained, providing the reader with a selection of the latest developments in econometric theory, along with the required introductory material on each topic. It will be of great use to graduate students of econometrics and statistics, and is particularly suitable for self-tuition.

    • Offers a rigorous treatment of topical subjects in advanced econometrics, with all the necessary background; designed for self-tuition
    • Highly successful book, available in paperback for the first time
    • Bierens is a well-known econometrician, widely published in journals and a high-profile member of the Econometric Society

    Product details

    April 2011
    Adobe eBook Reader
    9780511881114
    0 pages
    0kg
    5 tables
    This ISBN is for an eBook version which is distributed on our behalf by a third party.

    Table of Contents

    • 1. Basic probability theory
    • 2. Convergence
    • 3. Introduction to conditioning
    • 4. Nonlinear parametric regression analysis and maximum likelihood theory
    • 5. Tests for model misspecification
    • 6. Conditioning and dependence
    • 7. Functional specification of time series models
    • 8. ARMAX models: estimation and testing
    • 9. Unit roots and cointegration
    • 10. The Nadaraya-Watson kernel regression function estimator.
      Author
    • Herman J. Bierens , Southern Methodist University, Texas