Evaluation of Extrapolative Forecasting Methods: Results of a Survey of Academicians and Practitioners
Journal of Forecasting, Vol. 1, pp. 215-1217, 1982
3 Pages Posted: 8 Feb 2005 Last revised: 26 Jul 2008
Abstract
There exists a large number of quantitative extrapolative forecasting methods which may be applied in research work or implemented in an organizational setting. For instance, the lead article of this issue of the Journal of Forecasting compares the ability to forecast the future of over twenty univariate forecasting methods. Forecasting researchers in various academic disciplines as well as practitioners in private or public organizations are commonly faced with the problem of evaluating forecasting methods and ultimately selecting one. Thereafter, most become advocates of the method they have selected. On what basis are choices made? More specifically, what are the criteria used or the dimensions judged important? If a survey was taken among academicians and practitioners, would the same criteria arise? Would they be weighted equally? Before you continue reading this note, write on a piece of paper your criteria in order of importance and answer the last two questions. This will enable you to see whether or not you share the same values as your colleagues and test the accuracy of your perception.
Keywords: Forecasting, extrapolcation model, forecasting academic and organizational practitioners
Suggested Citation: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Recommended Papers
-
By Fred Collopy and J. Scott Armstrong
-
Error Measures for Generalizing About Forecasting Methods: Empirical Comparisons
By J. Scott Armstrong and Fred Collopy
-
By J. Scott Armstrong and Fred Collopy
-
Causal Forces: Structuring Knowledge for Time-Series Extrapolation
By J. Scott Armstrong and Fred Collopy
-
Expert Opinions About Extrapolation and the Mystery of the Overlooked Discontinuities
By Fred Collopy and J. Scott Armstrong
-
Beyond Accuracy: Comparison of Criteria Used to Select Forecasting Methods
By Thomas Yokum and J. Scott Armstrong
-
Structuring Knowledge Retrieval: An Analysis of Decomposed Quantitative Judgments
By Donald G. Macgregor, Sarah Lichtenstein, ...
-
Identification of Asymmetric Prediction Intervals Through Causal Forces
By J. Scott Armstrong and Fred Collopy