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Statistics, Econometrics and Forecasting: The Stone Lectures in Economics

Autor Arnold Zellner
en Limba Engleză Paperback – 18 feb 2004
Based on two lectures presented as part of The Stone Lectures in Economics series, Arnold Zellner describes the structural econometric time series analysis (SEMTSA) approach to statistical and econometric modeling. Developed by Zellner and Franz Palm, the SEMTSA approach produces an understanding of the relationship of univariate and multivariate time series forecasting models and dynamic, time series structural econometric models. As scientists and decision-makers in industry and government world-wide adopt the Bayesian approach to scientific inference, decision-making and forecasting, Zellner offers an in-depth analysis and appreciation of this important paradigm shift. Finally Zellner discusses the alternative approaches to model building and looks at how the use and development of the SEMTSA approach has led to the production of a Marshallian Macroeconomic Model that will prove valuable to many. Written by one of the foremost practitioners of econometrics, this book will have wide academic and professional appeal.
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Specificații

ISBN-13: 9780521540445
ISBN-10: 0521540445
Pagini: 184
Ilustrații: 9 b/w illus. 13 tables
Dimensiuni: 139 x 217 x 14 mm
Greutate: 0.25 kg
Editura: Cambridge University Press
Colecția Cambridge University Press
Seria The Stone Lectures in Economics

Locul publicării:Cambridge, United Kingdom

Cuprins

List of figures; List of tables; Preface; Lecture 1. Bank of England; Lecture 2. National Institute of Economic and Social Research; Appendix: on the questionable virtue of aggregation; Notes; References; Indexes.

Recenzii

"I found it a stimulating book. It offers valuable insights on Arnold Zellner's approach to 'good' research, demonstrating how productive and novative research may emerge. Also entertaining were the various anecdotes." - Markus Leippold, University of Ziurich

Notă biografică


Descriere

Analysis and appreciation of the structural econometric, time series analysis approach to statistical and econometric modeling.