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Econometric Modeling and Inference

Econometric Modeling and Inference

£78.99

Part of Themes in Modern Econometrics

  • Date Published: August 2007
  • availability: In stock
  • format: Hardback
  • isbn: 9780521876407

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About the Authors
  • Presents the main statistical tools of econometrics, focusing specifically on modern econometric methodology. The authors unify the approach by using a small number of estimation techniques, mainly generalized method of moments (GMM) estimation and kernel smoothing. The choice of GMM is explained by its relevance in structural econometrics and its preeminent position in econometrics overall. Split into four parts, Part I explains general methods. Part II studies statistical models that are best suited for microeconomic data. Part III deals with dynamic models that are designed for macroeconomic and financial applications. In Part IV the authors synthesize a set of problems that are specific to statistical methods in structural econometrics, namely identification and over-identification, simultaneity, and unobservability. Many theoretical examples illustrate the discussion and can be treated as application exercises. Nobel Laureate James A. Heckman offers a foreword to the work.

    • A graduate text in econometrics and statistics, emphasizing theory and methods, not applications
    • Links teaching and recent approaches in research: nonparametric techniques and simulation methods, game theory and treatment effects
    • Contains numerous theoretical examples that are solved in the discussion
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    Reviews & endorsements

    'This book is invaluable to researchers and all who are interested in the statistical analysis of time series, microeconomic data, financial and econometric models.' Journal of Applied Statistics

    '… this book … make[s] a great contribution to teaching the next generation of theoretical econometricians. … Econometric Modeling and Inference provides an excellent, low- cost opportunity to catch up with what the econometrics subfield has been doing.' Journal of the American Statistical Association

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    Product details

    • Date Published: August 2007
    • format: Hardback
    • isbn: 9780521876407
    • length: 518 pages
    • dimensions: 235 x 152 x 29 mm
    • weight: 0.802kg
    • availability: In stock
  • Table of Contents

    Part I. Statistical Methods:
    1. Statistical models
    2. Sequential models and asymptotics
    3. Estimation by maximization and by the method of moments
    4. Asymptotic tests
    5. Nonparametric methods
    6. Simulation methods
    Part II. Regression Models:
    7. Conditional expectation
    8. Univariate regression
    9. Generalized least squares method, heteroskedasticity, and multivariate regression
    10. Nonparametric estimation of the regression
    11. Discrete variables and partially observed models
    Part III. Dynamic Models:
    12. Stationary dynamic models
    13. Nonstationary processes and cointegration
    14. Models for conditional variance
    15. Nonlinear dynamic models
    Part IV. Structural Modeling:
    16. Identification and over identification in structural modeling
    17. Simultaneity
    18. Models with unobservable variables.

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

    • Demand Analysis
    • Econometrics 1
    • Elements of Econometrics
    • Empirical Analysis in Economics
  • Authors

    Jean-Pierre Florens, Université de Toulouse I (Sciences Sociales)
    Jean-Pierre Florens is Professor of Mathematics at the University of Toulouse I, where he holds the Chair in Statistics and Econometrics, and a senior member of the Institut Universitaire de France. He is also a member of the IDEI and GREMAQ research groups. Professor Florens' research interests include: statistics and econometrics methods, applied econometrics, and applied statistics. He is coauthor of Elements of Bayesian Statistics with Michel Mouchart and Jean-Marie Rolin (1990). The editor or co-editor of several econometrics and statistics books, he has also published numerous articles in the major econometric reviews, such as Econometrica, Journal of Econometrics, and Econometric Theory.

    Velayoudom Marimoutou, Université d'Aix-Marseille
    Vêlayoudom Marimoutou is Professor of Economics at the University of Aix-Marseille 2 and a member of GREQAM. His research fields include: time series analysis, non-stationary processes, long range dependence, and applied econometrics of exchange rates, finance, macroeconometrics, convergence, and international trade. His articles have appeared in publications such as the Journal of International Money and Finance, Oxford Bulletin of Economics and Statistics, and the Journal of Applied Probability.

    Anne Peguin-Feissolle, GREQAM, Aix-Marseille
    Anne Peguin-Feissolle is Research Director of the National Center of Scientific Research (CNRS) and a member of the GREQAM. She conducts research on econometric modelling, especially nonlinear econometrics, applications to macroeconomics, finance, spatial economics, artificial neural network modelling, and long memory problems. Professor Peguin-Feissolle's published research has appeared in Economics Letters, Economic Modelling, European Economic Review, Applied Economics, and the Annales d'Economie et de Statistique, among other publications.

    Translators

    Josef Perktold

    Marine Carrasco

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