Arnold Zellner is Adjunct Professor in Econometrics at the Department of Agricultural and Resource Economics, University of California, Berkeley. He is also H.G.B. Alexander Distinguished Service Professor Emeritus of Economics and Statistics at the University of Chicago. He is considered as an Econometrics Superstar.
He gave an interview (34 pages long!) to Kathy Morrissey which is a fascinating journey throughout his life and modern econometrics:
"In talking with Arnold, I saw three themes in his professional career. The first is his efforts to bridge the disciplines of statistics, particularly Bayesian methods, economics and econometrics.
The second theme is furthering knowledge on important problems. Arnold is concerned about social and economic problems such as hunger, unemployment, the business cycle and economic stagnation.
The third theme is a commitment to his “customers,” his students, and helping them to achieve their dreams and goals. Arnold feels he was lucky to be born in America and have the opportunities he did."
His book Statistics, Econometrics and Forecasting is available in Cyberlibris.
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.
Helmut Lütkepohl is Professor of Econometrics at the European University Insitute in Firenze. He has published extensive research in the area of nonparametric time series analysis, multivariate time series analysis and money demand analysis.
The book he recently edited, Applied Time Series Analysis, (published by Cambridge University Press) is now available in Cyberlibris.
Time series econometrics is a rapidly evolving field. Particularly, the
cointegration revolution has had a substantial impact on applied
analysis. Hence, no textbook has managed to cover the full range of
methods in current use and explain how to proceed in applied domains.
This gap in the literature motivates the present volume. The methods
are sketched out, reminding the reader of the ideas underlying them and
giving sufficient background for empirical work. The treatment can also
be used as a textbook for a course on applied time series econometrics.
Topics include: unit root and cointegration analysis, structural vector
autoregressions, conditional heteroskedasticity and nonlinear and
nonparametric time series models. Crucial to empirical work is the
software that is available for analysis. New methodology is typically
only gradually incorporated into existing software packages. Therefore
a flexible Java interface has been created, allowing readers to
replicate the applications and conduct their own analyses.