Jean-Pierre Florens, Velayoudom Marimoutou, Anne Peguin-Feissolle

Econometric Modeling and Inference

Übersetzer: Perktold, Josef; Carrasco, Marine

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Verlag: European Community
• Seitenzahl: 518
• Erscheinungstermin: 2. Juli 2007
• Englisch
• Abmessung: 232mm x 154mm x 32mm
• Gewicht: 684g
• ISBN-13: 9780521700061
• ISBN-10: 052170006X
• Artikelnr.: 22582981

Autorenporträt

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.

Inhaltsangabe

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.