Topics in Advanced Econometrics
Estimation, Testing, and Specification of Cross-Section and Time Series Models
Published on 7. July 1994
Book
Hardback
270 pages
978-0-521-41900-0 (ISBN)
Description
In this book Herman Bierens provides a mathematically rigorous treatment of a number of timely topics in advanced econometrics. His subjects include nonlinear estimation, maximum likelihood theory, ARMA and ARMAX models, unit roots and cointegration, and nonparametric regression, together with an extensive and thorough treatment of the necessary probability theory. Professor Bierens' study is uniquely self-contained, providing the reader with a selection of the latest developments in econometric theory, along with the required introductory material on each topic. It will be of great use to graduate students of econometrics and statistics, and is particularly suitable for self-tuition.
More details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Illustrations
5 Tables, unspecified
Dimensions
Height: 235 mm
Width: 158 mm
Thickness: 21 mm
Weight
529 gr
ISBN-13
978-0-521-41900-0 (9780521419000)
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Schweitzer Classification
Other editions
New editions
Herman J. Bierens
Topics in Advanced Econometrics
Estimation, Testing, and Specification of Cross-Section and Time Series Models
Book
02/1996
Cambridge University Press
€59.40
Shipment within 15-20 days
Additional editions
Herman J. Bierens
Topics in Advanced Econometrics
Estimation, Testing, and Specification of Cross-Section and Time Series Models
Book
02/1996
Cambridge University Press
€59.40
Shipment within 15-20 days
Person
Content
1. Basic probability theory; 2. Convergence; 3. Introduction to conditioning; 4. Nonlinear parametric regression analysis and maximum likelihood theory; 5. Tests for model misspecification; 6. Conditioning and dependence; 7. Functional specification of time series models; 8. ARMAX models: estimation and testing; 9. Unit roots and cointegration; 10. The Nadaraya-Watson kernel regression function estimator.