Buch, Englisch, 236 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 508 g
Buch, Englisch, 236 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 508 g
ISBN: 978-1-4398-3824-2
Verlag: CRC Press
Topics covered include:
- Well-established nonparametric and parametric approaches to estimation and conventional (asymptotic and bootstrap) frameworks for statistical inference
- Estimation of models based on moment restrictions implied by economic theory, including various method-of-moments estimators for unconditional and conditional moment restriction models, and asymptotic theory for correctly specified and misspecified models
- Non-conventional asymptotic tools that lead to improved finite sample inference, such as higher-order asymptotic analysis that allows for more accurate approximations via various asymptotic expansions, and asymptotic approximations based on drifting parameter sequences
Offering a unified approach to studying econometric problems, Methods for Estimation and Inference in Modern Econometrics links most of the existing estimation and inference methods in a general framework to help readers synthesize all aspects of modern econometric theory. Various theoretical exercises and suggested solutions are included to facilitate understanding.
Zielgruppe
Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Review of Conventional Econometric Methods: Standard Approaches to Estimation and Statistical Inference. Estimation of Moment Condition Models: Generalized Empirical Likelihood Estimators. Estimation of Models Defined by Conditional Moment Restrictions. Inference in Misspecified Models. Higher-Order and Alternative Asymptotics: Higher-Order Asymptotic Approximations. Asymptotics Under Drifting Parameter Sequences. Appendix: Results from Linear Algebra, Probability Theory and Statistics. Index.