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…mehr
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.
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.
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.
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Shop der buecher.de GmbH & Co. KG Bürgermeister-Wegele-Str. 12, 86167 Augsburg Amtsgericht Augsburg HRA 13309