Marketing Papers
Document Type
Book Chapter
Date of this Version
2001
Abstract
Ideally, forecasting methods should be evaluated in the situations for which they will be used. Underlying the evaluation procedure is the need to test methods against reasonable alternatives. Evaluation consists of four steps: testing assumptions, testing data and methods, replicating outputs, and assessing outputs. Most principles for testing forecasting methods are based on commonly accepted methodological procedures, such as to prespecify criteria or to obtain a large sample of forecast errors. However, forecasters often violate such principles, even in academic studies. Some principles might be surprising, such as do not use R-square, do not use Mean Square Error, and do not use the within-sample fit of the model to select the most accurate time-series model. A checklist of 32 principles is provided to help in systematically evaluating forecasting methods.
Recommended Citation
Armstrong, J. S. (2001). Evaluating Forecasting Methods. Retrieved from https://repository.upenn.edu/marketing_papers/146
Date Posted: 24 May 2011
This document has been peer reviewed.
Comments
Suggested Citation:
Armstrong, J.S. Evaluating Forecasting Methods. In Principles of Forecasting: A Handbook for Researchers and Practitioners (Ed. J. Scott Armstrong). Kluwer, 2001.
Publisher URL: http://www.springer.com/business+%26+management/business+for+professionals/book/978-0-7923-7930-0