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Econometric Modelling with Time Series
Specification, Estimation and Testing



Part of Themes in Modern Econometrics

  • Date Published: March 2013
  • availability: Available
  • format: Hardback
  • isbn: 9780521196604
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About the Authors
  • This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments estimation, nonparametric estimation and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

    • The principle of maximum likelihood is adopted as the unifying framework for this comprehensive time series text for econometricians, statisticians and applied mathematicians
    • Uniquely, it demonstrates econometric methods by means of a suite of programs written in GAUSS and MATLAB, and R
    • The text's computer code enables reproduction of theoretical and empirical results published in recent journal articles
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    Reviews & endorsements

    'This book will be an excellent text for advanced undergraduate and postgraduate courses in econometric time series. The statistical theory is clearly presented and the many examples make the techniques readily accessible and illustrate their practical importance.' Andrew Harvey, University of Cambridge

    'This book takes an important step forward relative to existing time-series econometrics texts, with, for example, significant coverage of numerical optimization, quasi-maximum-likelihood estimation, nonparametric and simulation-based estimation, latent-factor models, and volatility models. In addition, readers will benefit immensely from the complete sets of included R and Matlab routines. Well done!' Francis X. Diebold, University of Pennsylvania

    'This book is exceptionally well done. The blending of theory, application and computation is sublimely done throughout. [It] will be a must-have for advanced graduate students working with economic and financial time series data, and will also form a definitive and up-to-date reference source for both academic and academic-related researchers in the field.' Robert Taylor, University of Nottingham

    'This book gave me excitement and sensations similar to visiting Australian wineries: tantalizing vitality, pronounced yet balanced flavours, exposing exhilarating progressive developments, produced by excellent and tasteful craftsmanship, and well-matured and extremely consumer-friendly with its many recipes in various computer codes, thus it is strongly recommended to both young graduates and experienced connoisseurs.' Jan F. Kiviet, Nanyang Technological University and University of Amsterdam

    'This textbook strikes an excellent balance between explaining the underlying concepts and intuition, containing the requisite amount of rigor, and providing sufficient guidance for students to be able to apply the methods described to a variety of time-series situations. It is extremely clearly written and should instantly find a wide audience. The book's emphasis on maximum-likelihood as a unifying guiding principle is well-justified, and provides the right context for students to understand how seemingly disparate econometric methods are fundamentally related.' Yacine Ait-Sahalia, Princeton University

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    Customer reviews

    01st Aug 2013 by Tebogo1992

    I rate this book 9/10, Its interesting.

    Review was not posted due to profanity


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    Product details

    • Date Published: March 2013
    • format: Hardback
    • isbn: 9780521196604
    • length: 924 pages
    • dimensions: 229 x 152 x 48 mm
    • weight: 1.39kg
    • contains: 104 b/w illus. 97 tables
    • availability: Available
  • Table of Contents

    Part I. Maximum Likelihood:
    1. The maximum likelihood principle
    2. Properties of maximum likelihood estimators
    3. Numerical estimation methods
    4. Hypothesis testing
    Part II. Regression Models:
    5. Linear regression models
    6. Nonlinear regression models
    7. Autocorrelated regression models
    8. Heteroskedastic regression models
    Part III. Other Estimation Methods:
    9. Quasi-maximum likelihood estimation
    10. Generalized method of moments
    11. Nonparametric estimation
    12. Estimation by stimulation
    Part IV. Stationary Time Series:
    13. Linear time series models
    14. Structural vector autoregressions
    15. Latent factor models
    Part V. Non-Stationary Time Series:
    16. Nonstationary distribution theory
    17. Unit root testing
    18. Cointegration
    Part VI. Nonlinear Time Series:
    19. Nonlinearities in mean
    20. Nonlinearities in variance
    21. Discrete time series models
    Appendix A. Change in variable in probability density functions
    Appendix B. The lag operator
    Appendix C. FIML estimation of a structural model
    Appendix D. Additional nonparametric results.

  • Resources for

    Econometric Modelling with Time Series

    Vance Martin, Stan Hurn, David Harris

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  • Instructors have used or reviewed this title for the following courses

    • Business Cycles and Forecasting
    • Empirical Methods in Finance
    • Time Series Analysis
    • Using the Yield Curve
  • Authors

    Vance Martin, University of Melbourne
    Vance Martin is Professor of Econometrics at the University of Melbourne, Australia, a position he has held since 2000. He graduated with a PhD from Monash University in 1990. He was appointed Lecturer at the University of Melbourne in 1985 and became a Senior Lecturer in 1990.

    Stan Hurn, Queensland University of Technology
    Stan Hurn is Professor of Economics and Finance at Queensland University of Technology, Australia, a position he has held since 1998. He graduated with a DPhil in Economics from St Edmund Hall, Oxford, in 1992. He was appointed Lecturer at the University of Glasgow in 1988 and became a Senior Lecturer in 1993 before being named Official Fellow in Economics at Brasenose College, Oxford, in 1996.

    David Harris, Monash University, Victoria
    David Harris is Professor of Econometrics at Monash University, Australia. He was awarded his PhD in Econometrics from Monash University in 1995. He was lecturer in econometrics from 1995 to 1997 at Monash University and from 1998 to 2010 at the University of Melbourne.

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