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Journal of Forecasting

Volume 1, Issue 2

Article

The accuracy of extrapolation (time series) methods: Results of a forecasting competition

INSEAD, 77305 Fontainebleau, France

A. Andersen, Department of Economic Statistics, The University of Sydney, New South Wales 2006, Australia

R. Carbone, Faculté des Sciences de l'Administration, Université Laval, Quebec, Canada G1K 7P4

R. Fildes, Manchester Business School, University of Manchester, Manchester M15 6PB, England

R. Lewandowski, Marketing Systems GMBH, Postfach 230109, Hunsruckstraße 9a, D‐4300 ESSEN 1 (Bredeney), West Germany

J. Newton and E. Parzen, Institute of Statistics, Texas A&M University, College Station, Texas 77843, U.S.A.

R. Winkler, Indiana University, Graduate School of Business, Bloomington, IN 47405, U.S.A.

Spyros Makridakis is Professor of Management Science at INSEAD, France. He received his degree from the School of Industrial Studies in Greece and his M.B.A. and Ph.D. from New York University. He has published extensively in the areas of general systems and forecasting and has co‐authored Computer‐Aided Modeling for Managers (Addison‐Wesley, 1972), Forecasting Methods for Management, Third Edition (Wiley, 1979), Interactive Forecasting, Second Edition (Holden‐Day, 1978), and Forecasting: Methods and Applications (Wiley‐Hamilton. 1978). He has also been the co‐editor of TIMS Studies, Vol. 12, in Management Science. After his first degree in Statistics. Allan Andersen completed a Ph.D. in the Faculty of Economics at the University of Queensland. At present, he is a lecturer at the University of Sydney in the Department of Statistics. Allan's research interests lie in the general field of forecasting; in particular the time‐series approaches to the subject. He has published more than ten articles, and has co‐authored a book on non‐linear time‐series methods.

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INSEAD, 77305 Fontainebleau, France

A. Andersen, Department of Economic Statistics, The University of Sydney, New South Wales 2006, Australia

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INSEAD, 77305 Fontainebleau, France

Robert Carbone is the chairman of the Department of Management Sciences at La Faculte des Sciences de l'Administration de l'Université Laval. His Ph.D. is in urban and public affairs from Carnegie‐Mellon University. He is a member of AIDS, TIMS, and ORSA. His papers have appeared in The Journal of Environmental Systems, Management Science, IN FOR, Atmospheric Environment, and other journals. His principal current research interest is in data analysis and forecasting.

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INSEAD, 77305 Fontainebleau, France

R. Carbone, Faculté des Sciences de l'Administration, Université Laval, Quebec, Canada G1K 7P4

Robert Fildes is a lecturer in business forecasting at the Manchester Business School, University of Manchester. He received a Bachelor's degree (mathematics) from Oxford and a Ph.D. (statistics) from the University of California. He is co‐author of Forecasting for Business (Longmans, 1976) and an editor of Forecasting and Planning (Teakfield, 1978). He has also authored several articles on forecasting and applied statistics and served as a consultant in these fields. During 1978 he taught at the University of British Columbia and the University of California Berkeley.

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INSEAD, 77305 Fontainebleau, France

Michèle Hibon is currently a research assistant at INSEAD. For the last several years she has been working on various studies dealing with forecasting accuracy of time‐series methods. Before INSEAD, she was associated with the Ecole Polytechnique (Laboratoire de Recherche de Mecanique des Solides) as a computer specialist. She holds a degree in science and a diploma in advanced studies in physics.

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INSEAD, 77305 Fontainebleau, France

Rudolf Lewandowski, born 1938 in Valencia/Spain, studied mathematics and economics at the Sorbonne in Paris, and the universities of Bochum and Bonn and obtained degrees in both subjects. He came to the Federal Republic of Germany in 1962 as a mathematical adviser for a big French company. In 1966 he became the manager of the operations research, economics and marketing department in a leading software firm in West Germany, and founded in 1973‘MARKETING SYSTEMS’, and has been its general manager since. In 1973, he obtained a doctoral degree in economics at the Sorbonne. He has published papers on Markov processes, forecasting methodology and forecast systems, and is author of Prognose und Informationssysteme und ihre Anwendungen, 2 vols. (De Giuyter‐Verlag, Berlin 1974 and 1980), and La Prévision à Court Terme (Dunod, Paris 1979). He has lectured at various European universities, and is a member of several European Marketing Associations.

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INSEAD, 77305 Fontainebleau, France

Joseph Newton is an authority on the theory and algorithms of time series analysis particularly in the area of multivariate time series. His dissertation was written in 1975 at SUNY at Buffalo in the area of estimating the parameters of vector valued autoregressive moving average time series. His publications range from work on the asymptotic distribution of maximum likelihood estimators in multiple time series to the development of efficient algorithms for the prediction of time series. He has been a research assistant professor at SUNY at Buffalo and is currently an assistant professor in the Institute of Statistics at Texas A&M University.

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INSEAD, 77305 Fontainebleau, France

Emanuel Parzen is Distinguished Professor of Statistics at Texas A&M University. He has made research contributions to probability limit theorems, statistical spectral analysis by kernel methods, statistical communication theory, time series analysis by reproducing kernel Hilberg space methods, probability density estimation, multiple time series analysis, statistical spectral analysis by autoregressive methods, order determination criteria for autoregressive schemes, forecasting, and non‐parametric statistical data modelling using quantile and density‐quantile functions. He is the author of two widely used books: Modern Probability Theory and Its Applications (1960) and Stochastic Processes (1962).

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INSEAD, 77305 Fontainebleau, France

Robert Winkler is a distinguished professor of Quantitative Business Analysis in the Graduate School of Business, Indiana University, Bloomington, Indiana. For the 1980‐81 academic year he was a Visiting Professor at INSEAD, Fontainebleau, France. He received a B.S. from the University of Illinois and a Ph.D. from the University of Chicago, and he has held visiting positions at the University of Washington, the International Institute for Applied Systems Analysis, and Stanford University. He is the author of two books and numerous journal articles. His primary research interests involve probability forecasting, Bayesian inference, and statistical decision theory. He is a member of Tl MS and is currently serving as a Departmental Editor for Management Science.

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INSEAD, 77305 Fontainebleau, France

A. Andersen, Department of Economic Statistics, The University of Sydney, New South Wales 2006, Australia

R. Carbone, Faculté des Sciences de l'Administration, Université Laval, Quebec, Canada G1K 7P4

R. Fildes, Manchester Business School, University of Manchester, Manchester M15 6PB, England

R. Lewandowski, Marketing Systems GMBH, Postfach 230109, Hunsruckstraße 9a, D‐4300 ESSEN 1 (Bredeney), West Germany

J. Newton and E. Parzen, Institute of Statistics, Texas A&M University, College Station, Texas 77843, U.S.A.

R. Winkler, Indiana University, Graduate School of Business, Bloomington, IN 47405, U.S.A.

Spyros Makridakis is Professor of Management Science at INSEAD, France. He received his degree from the School of Industrial Studies in Greece and his M.B.A. and Ph.D. from New York University. He has published extensively in the areas of general systems and forecasting and has co‐authored Computer‐Aided Modeling for Managers (Addison‐Wesley, 1972), Forecasting Methods for Management, Third Edition (Wiley, 1979), Interactive Forecasting, Second Edition (Holden‐Day, 1978), and Forecasting: Methods and Applications (Wiley‐Hamilton. 1978). He has also been the co‐editor of TIMS Studies, Vol. 12, in Management Science. After his first degree in Statistics. Allan Andersen completed a Ph.D. in the Faculty of Economics at the University of Queensland. At present, he is a lecturer at the University of Sydney in the Department of Statistics. Allan's research interests lie in the general field of forecasting; in particular the time‐series approaches to the subject. He has published more than ten articles, and has co‐authored a book on non‐linear time‐series methods.

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INSEAD, 77305 Fontainebleau, France

A. Andersen, Department of Economic Statistics, The University of Sydney, New South Wales 2006, Australia

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INSEAD, 77305 Fontainebleau, France

Robert Carbone is the chairman of the Department of Management Sciences at La Faculte des Sciences de l'Administration de l'Université Laval. His Ph.D. is in urban and public affairs from Carnegie‐Mellon University. He is a member of AIDS, TIMS, and ORSA. His papers have appeared in The Journal of Environmental Systems, Management Science, IN FOR, Atmospheric Environment, and other journals. His principal current research interest is in data analysis and forecasting.

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INSEAD, 77305 Fontainebleau, France

R. Carbone, Faculté des Sciences de l'Administration, Université Laval, Quebec, Canada G1K 7P4

Robert Fildes is a lecturer in business forecasting at the Manchester Business School, University of Manchester. He received a Bachelor's degree (mathematics) from Oxford and a Ph.D. (statistics) from the University of California. He is co‐author of Forecasting for Business (Longmans, 1976) and an editor of Forecasting and Planning (Teakfield, 1978). He has also authored several articles on forecasting and applied statistics and served as a consultant in these fields. During 1978 he taught at the University of British Columbia and the University of California Berkeley.

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INSEAD, 77305 Fontainebleau, France

Michèle Hibon is currently a research assistant at INSEAD. For the last several years she has been working on various studies dealing with forecasting accuracy of time‐series methods. Before INSEAD, she was associated with the Ecole Polytechnique (Laboratoire de Recherche de Mecanique des Solides) as a computer specialist. She holds a degree in science and a diploma in advanced studies in physics.

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INSEAD, 77305 Fontainebleau, France

Rudolf Lewandowski, born 1938 in Valencia/Spain, studied mathematics and economics at the Sorbonne in Paris, and the universities of Bochum and Bonn and obtained degrees in both subjects. He came to the Federal Republic of Germany in 1962 as a mathematical adviser for a big French company. In 1966 he became the manager of the operations research, economics and marketing department in a leading software firm in West Germany, and founded in 1973‘MARKETING SYSTEMS’, and has been its general manager since. In 1973, he obtained a doctoral degree in economics at the Sorbonne. He has published papers on Markov processes, forecasting methodology and forecast systems, and is author of Prognose und Informationssysteme und ihre Anwendungen, 2 vols. (De Giuyter‐Verlag, Berlin 1974 and 1980), and La Prévision à Court Terme (Dunod, Paris 1979). He has lectured at various European universities, and is a member of several European Marketing Associations.

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INSEAD, 77305 Fontainebleau, France

Joseph Newton is an authority on the theory and algorithms of time series analysis particularly in the area of multivariate time series. His dissertation was written in 1975 at SUNY at Buffalo in the area of estimating the parameters of vector valued autoregressive moving average time series. His publications range from work on the asymptotic distribution of maximum likelihood estimators in multiple time series to the development of efficient algorithms for the prediction of time series. He has been a research assistant professor at SUNY at Buffalo and is currently an assistant professor in the Institute of Statistics at Texas A&M University.

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INSEAD, 77305 Fontainebleau, France

Emanuel Parzen is Distinguished Professor of Statistics at Texas A&M University. He has made research contributions to probability limit theorems, statistical spectral analysis by kernel methods, statistical communication theory, time series analysis by reproducing kernel Hilberg space methods, probability density estimation, multiple time series analysis, statistical spectral analysis by autoregressive methods, order determination criteria for autoregressive schemes, forecasting, and non‐parametric statistical data modelling using quantile and density‐quantile functions. He is the author of two widely used books: Modern Probability Theory and Its Applications (1960) and Stochastic Processes (1962).

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INSEAD, 77305 Fontainebleau, France

Robert Winkler is a distinguished professor of Quantitative Business Analysis in the Graduate School of Business, Indiana University, Bloomington, Indiana. For the 1980‐81 academic year he was a Visiting Professor at INSEAD, Fontainebleau, France. He received a B.S. from the University of Illinois and a Ph.D. from the University of Chicago, and he has held visiting positions at the University of Washington, the International Institute for Applied Systems Analysis, and Stanford University. He is the author of two books and numerous journal articles. His primary research interests involve probability forecasting, Bayesian inference, and statistical decision theory. He is a member of Tl MS and is currently serving as a Departmental Editor for Management Science.

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First published: April/June 1982

https://doi.org/10.1002/for.3980010202

Citations: 812

Abstract

In the last few decades many methods have become available for forecasting. As always, when alternatives exist, choices need to be made so that an appropriate forecasting method can be selected and used for the specific situation being considered. This paper reports the results of a forecasting competition that provides information to facilitate such choice. Seven experts in each of the 24 methods forecasted up to 1001 series for six up to eighteen time horizons. The results of the competition are presented in this paper whose purpose is to provide empirical evidence about differences found to exist among the various extrapolative (time series) methods used in the competition.

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Volume1, Issue2

April/June 1982

Pages 111-153

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