Dynamic Nonlinear Econometric Models
Subtitle: Asymptotic Theory
By: by Benedikt M. Pötscher, Ingmar R. Prucha
Contributors: Prucha, Ingmar R.
Publisher: Springer Berlin Heidelberg
Published: 1997
Place of publication: Berlin, Heidelberg
Language: eng
Format: [electronic resource] :
Number of pages: 312
ISBN-13: 9783642083099; 9783662034866
Subjects: Mathematical Economics; Mathematical statistics; Statistics; Mathematics; Economics; Econometrics
Description: The book provides an extensive discussion of asymptotic theory of M-estimators in the context of dynamic nonlinear models. The class of M-estimators contains least mean distance estimators (including maximum likelihood estimators) and generalized method of moments estimators. In addition to establishing the asymptotic properties of such estimators, the book provides a detailed discussion of the statistical and probabilistic tools necessary for such an analysis. The book also gives a careful treatment of estimators of asymptotic variance covariance matrices for dependent processes.
Notes: Online full text is restricted to subscribers.

Also available in print.

Mode of access: World Wide Web.
Table of contents: title: From the contents: Preface; title: Introduction; title: Models, Data Generating Processes, and Estimators; title: Basic Structure of the Classical Consistency Proof; title: Further Comments on Consistency Proofs; title: Uniform Laws of Large Numbers; title: Approximation Concepts and Limit Theorems; title: Consistency: Catalogues of Assumptions; title: Basic Structure of the Asymptotic Normality Proof; title: Asymptotic Normality under Nonstandard Conditions; title: Central Limit Theorems; title: Asymptotic Normality: Catalogues of Assumptions; title: Heteroskedasticity and Autocorrelation Robust Estimation of Variance Covariance Matrices; title: Consistent Variance Covariance Matrix Estimation: Catalogues of Assumptions; title: Quast Maximum Likelihood Estimation of Dynamic Nonlinear Simultaneous Systems; title: Concluding Remarks; title: References; title: Index.