Statistics, Econometrics and Forecasting.

Zellner, Arnold:

ISBN 10: 0521540445 / ISBN 13: 9780521540445

Published by Cambridge University Press, 2004

About this Item

Series: The Stone Lectures in Economics 163p blue paperback, appears unused, some sunning to spine, binding tight, text clean and fresh, an excellent copy Language: English. Seller Inventory # 168580

Bibliographic Details

Title: Statistics, Econometrics and Forecasting.

Publisher: Cambridge University Press

Publication Date: 2004

Binding: Paperback

Condition: Very Good

About this title

Synopsis:

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.

About the Author:

Arnold Zellner is H. G. B. Alexander Distinguished Service Professor Emeritus of Economics and Statistics at the University of Chicago, and adjunct Professor at the University of California at Berkeley. He is one of the most important figures in the development of econometrics, in particular the use of Bayesian technique. He is co-founder of the Journal of Econometrics, and remains an active researcher in modeling, statistics and forecasting.