Statistics, Econometrics and Forecasting

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.

[1]  A. Weigend,et al.  Time Series Prediction: Forecasting the Future and Understanding the Past , 1994 .

[2]  Rory A. Fisher,et al.  Statistical methods and scientific inference. , 1957 .

[3]  BAYESIAN MODELING OF ECONOMIES AND DATA REQUIREMENTS , 2001, Macroeconomic Dynamics.

[4]  M. Friedman,et al.  Theory of the Consumption Function , 1957 .

[5]  R. L. Winkler Combining Probability Distributions from Dependent Information Sources , 1981 .

[6]  H. Theil,et al.  Linear Aggregation of Economic Relations. , 1955 .

[7]  Pieter W. Otter,et al.  Canonical Correlation in Multivariate Time Series Analysis with an Application to One-Year-Ahead and Multiyear-Ahead Macroeconomic Forecasting , 1990 .

[8]  Jan Tinbergen,et al.  An econometric approach to business cycle problems , 1938 .

[9]  Peter B. Kahn Mathematical methods for scientists and engineers , 1990 .

[10]  C. Nelson,et al.  Trends and random walks in macroeconmic time series: Some evidence and implications , 1982 .

[11]  Arnold Zellner,et al.  To combine or not to combine? Issues of combining forecasts , 1992 .

[12]  M. West,et al.  Dynamic Generalized Linear Models and Bayesian Forecasting , 1985 .

[13]  Arnold Zellner,et al.  Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model , 2001 .

[14]  Philippe Jorion International Portfolio Diversification with Estimation Risk , 1985 .

[15]  Arnold Zellner,et al.  Macroeconomic Forecasting Using Pooled International Data , 1987 .

[16]  A. Zellner,et al.  Leading economic indicators: Bayesian methods for forecasting turning points in economic time-series: Sensitivity of forecasts to asymmetry of loss structures , 1991 .

[17]  A. Zellner CANONICAL REPRESENTATION OF LINEAR STRUCTURAL ECONOMETRIC MODELS, RANK TESTS FOR IDENTIFICATION AND EXISTENCE OF ESTIMATORS' MOMENTS , 1983 .

[18]  A. Zellner,et al.  Further Properties of Efficient Estimators for Seemingly Unrelated Regression Equations , 1962 .

[19]  H. Jeffreys,et al.  Theory of probability , 1896 .

[20]  Arnold Zellner,et al.  Information processing and Bayesian analysis , 2002 .

[21]  Jeffrey M. Perloff,et al.  Maximum entropy and Bayesian approaches to the ratio problem , 2001 .

[22]  Robert Fildes,et al.  Research on forecasting , 1989 .

[23]  Douglas J. Miller,et al.  Maximum entropy econometrics: robust estimation with limited data , 1996 .

[24]  K. Pearson “The Grammar of Science” , 1900, Nature.

[25]  J. M. Bates,et al.  The Combination of Forecasts , 1969 .

[26]  C. Nelson The Prediction Performance of the FRB-MIT-PENN Model of the U.S. Economy , 1972 .

[27]  James O. Berger,et al.  Bayesian Analysis: A Look at Today and Thoughts of Tomorrow , 2000 .

[28]  E. T. Jaynes,et al.  [Optimal Information Processing and Bayes's Theorem]: Comment , 1988 .

[29]  John L. Kling Predicting the Turning Points of Business and Economic Time Series , 1987 .

[30]  Arnold Zellner,et al.  Forecasting turning points in countries' output growth rates: A response to Milton Friedman , 1999 .

[31]  Bruce M. Hill [Optimal Information Processing and Bayes's Theorem]: Comment , 1988 .

[32]  S. James Press,et al.  The Subjectivity of Scientists and the Bayesian Approach: Press/The Subjectivity , 2001 .

[33]  Z. Griliches,et al.  Is aggregation necessarily bad , 1960 .

[34]  Arnold Zellner,et al.  Estimation of functions of population means and regression coefficients including structural coefficients : A minimum expected loss (MELO) approach , 1978 .

[35]  Inferring the Nutrient Content of Food With Prior Information , 1999 .

[36]  Arnold Zellner,et al.  Entry and empirical demand and supply analysis for competitive industries , 1985 .

[37]  Stephen K. McNees Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts , 1986 .

[38]  R. Hogarth,et al.  Order effects in belief updating: The belief-adjustment model , 1992, Cognitive Psychology.

[39]  L. Hurwicz,et al.  Measuring Business Cycles. , 1946 .

[40]  F. Diebold,et al.  Why Are Estimates of Agricultural Supply Response So Variable , 1996 .

[41]  Maurice Henry Quenouille,et al.  The analysis of multiple time-series , 1957 .

[42]  R. L. Cooper The Predictive Performance of Quarterly Econometric Models of the United States , 1972 .

[43]  M. Ghosh,et al.  On estimation with balanced loss functions , 1999 .

[44]  H. Ryu Maximum entropy estimation of density and regression functions , 1993 .

[45]  A. Zellner The Marshallian Macroeconomic Model , 2001 .

[46]  Irma Adelman,et al.  The Dynamic Properties of the Klein-Goldberger Model , 1959 .

[47]  C. Stein Inadmissibility of the Usual Estimator for the Mean of a Multivariate Normal Distribution , 1956 .

[48]  J. Muth Rational Expectations and the Theory of Price Movements , 1961 .

[49]  G. Orcutt,et al.  A new type of socio-economic system , 1957 .

[50]  Jean-Marie Dufour,et al.  Simulation-Based Finite and Large Sample Tests in Multivariate Regressions , 2002 .

[51]  H. B. Gamble,et al.  Systems simulation for regional analysis: an application to river-basin planning. , 1969 .

[52]  T. W. Anderson,et al.  Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations , 1949 .

[53]  Arnold Zellner,et al.  The finite sample properties of simultaneous equations' estimates and estimators Bayesian and non-Bayesian approaches , 1998 .

[54]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[55]  E. Soofi Principal Information Theoretic Approaches , 2000 .

[56]  Helmut Lütkepohl,et al.  Comparison of predictors for temporally and contemporaneously aggregated time series , 1986 .

[57]  Ehsan S. Soofi,et al.  Information Theory and Bayesian Statistics , 1996 .

[58]  Richard A. Highfield Forecasting Similar Time Series with Bayesian Pooling Methods: Application to Forecasting European Output Growth , 1992 .

[59]  Arnold Zellner,et al.  Turning points in economic time series, loss structures, and Bayesian forecasting , 2004 .

[60]  C. Stein Confidence Sets for the Mean of a Multivariate Normal Distribution , 1962 .

[61]  Justin L. Tobias,et al.  Forecasting Output Growth Rates and Median Output Growth Rates: A Hierarchical Bayesian Approach , 2001 .

[62]  A. Zellner,et al.  Forecasting turning points in international output growth rates using Bayesian exponentially weighted autoregression, time-varying parameter, and pooling techniques , 1991 .

[63]  Siddhartha Chib,et al.  Markov Chain Monte Carlo Simulation Methods in Econometrics , 1996, Econometric Theory.

[64]  A. Zellner Optimal Information Processing and Bayes's Theorem , 1988 .

[65]  R. Clemen Combining forecasts: A review and annotated bibliography , 1989 .

[66]  H. Markowitz Mean—Variance Analysis , 1989 .

[67]  A. Zellner,et al.  Posterior odds ratios for selected regression hypotheses , 1980 .

[68]  John S. J. Hsu,et al.  Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers , 1999 .

[69]  A. Zellner A Statistical Analysis of Provisional Estimates of Gross National Product and its Components, of Selected National Income Components, and of Personal Saving , 1958 .

[70]  Geoff Harcourt,et al.  Life and Work of John Richard Nicholas Stone 1913–1991 , 2000 .

[71]  A. Zellner,et al.  Real Balances and the Demand for Money: Comment , 1973, Journal of Political Economy.

[72]  A. Zellner An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias , 1962 .

[73]  Victor Zarnowitz,et al.  The Record and Improvability of Economic Forecasting , 1986 .

[74]  George E. P. Box,et al.  Time Series Analysis: Forecasting and Control , 1977 .

[75]  C. Christ,et al.  Judging the Performance of Econometric Models of the U.S. Economy , 1975 .

[76]  George G. Judge,et al.  Econometric foundations , 2000 .

[77]  S. Mittnik Macroeconomic Forecasting Using Pooled International Data , 1990 .

[78]  A. Zellner,et al.  Time series analysis and simultaneous equation econometric models , 1974 .

[79]  G. Barnard The Theory of Information , 1951 .

[80]  Arnold Zellner,et al.  THE BAYESIAN METHOD OF MOMENTS (BMOM) , 1997 .

[81]  Chan‐Fu Chen On Asymptotic Normality of Limiting Density Functions with Bayesian Implications , 1985 .

[82]  Arnold Zellner,et al.  Physics and Probability: Bayesian Analysis, Model Selection and Prediction , 1993 .

[83]  Arnold Zellner,et al.  Prediction and Decision Problems in Regression Models from the Bayesian Point of View , 1965 .

[84]  Soo-Bin Park,et al.  Some sampling properties of minimum expected loss (MELO) estimators of structural coefficients , 1982 .

[85]  A. Stuart,et al.  Portfolio Selection: Efficient Diversification of Investments , 1959 .

[86]  Josiah Royce,et al.  The psychology of invention. , 1898 .

[87]  A. Zellner An Introduction to Bayesian Inference in Econometrics , 1971 .

[88]  Robert B. Litterman Forecasting with Bayesian Vector Autoregressions-Five Years of Experience , 1984 .

[89]  Arnold Zellner,et al.  Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates , 1993 .

[90]  J. Berger Statistical Decision Theory and Bayesian Analysis , 1988 .

[91]  I. Johnstone,et al.  On Asymptotic Posterior Normality for Stochastic Processes , 1979 .

[92]  W. E. Wecker,et al.  Predicting the Turning Points of a Time Series , 1979 .

[93]  Richard Startz,et al.  Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator , 1988 .

[94]  John Geweke,et al.  Federal Reserve Bank of Minneapolis Research Department Staff Report 249 Using Simulation Methods for Bayesian Econometric Models: Inference, Development, and Communication , 2022 .

[95]  Antoni Espasa,et al.  Underlying inflation in the spanish economy: estimation and methodology , 1991 .

[96]  A. Zellner,et al.  A Note on Aggregation, Disaggregation and Forecasting Performance , 2000 .