Econometric Modeling and Inference
Econometric Modeling and Inference
Velayoudom Marimoutou, Université d'Aix-Marseille
Anne Peguin-Feissolle, GREQAM, Aix-Marseille
Josef Perktold
Marine Carrasco
$78.99
USDThe aim of this book is to present the main statistical tools of econometrics. It covers almost all modern econometric methodology and unifies the approach by using a small number of estimation techniques, many from generalized method of moments (GMM) estimation. The work is in four parts: Part I sets forth statistical methods, Part II covers regression models, Part III investigates dynamic models, and Part IV synthesizes a set of problems that are specific models in structural econometrics, namely identification and overidentification, simultaneity, and unobservability. Many theoretical examples illustrate the discussion and can be treated as application exercises.
- 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
Reviews & endorsements
"...an updated and well-balanced bird's-eye view of the basic econometric concepts and analyses with informative references on the respective topics for the benefit of readers' further study, covering the traditional simultaneous-equation approach as well as the recent parametric and semiparametric time-series analyses."
Yuzo Hosoya, Mathematical Reviews
"... May make a great contribution to teaching the next generation of theoretical econometricians. For the statistician comfortable with formal mathematics, Econometric Modeling and Inference provides an excellent, low-cost opportunity to catch up with what the econometrics subfield has been doing."
Richard Startz, University of Washington for Journal of the American Statistical Association
Product details
July 2007Paperback
9780521700061
518 pages
228 × 152 × 25 mm
0.682kg
Temporarily unavailable - available from TBC
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.
