Forecasting Principles

M. Lovric, International Encyclopedia on Statistical Science (2010)

9 Pages Posted: 18 Aug 2015

See all articles by Kesten C. Green

Kesten C. Green

University of South Australia - UniSA Business School; Ehrenberg-Bass Institute for Marketing Science

Andreas Graefe

Macromedia University of Applied Sciences

J. Scott Armstrong

University of Pennsylvania - Marketing Department

Date Written: October 5, 2011

Abstract

Forecasting is concerned with making statements about the as yet unknown. There are many ways that people go about deriving forecasts. This entry is concerned primarily with procedures that have performed well in empirical studies that contrast the accuracy of alternative methods.

Evidence about forecasting procedures has been codified as condition-action statements, rules, guidelines or, as we refer to them, principles. At the time of writing there are 140 principles. Think of them as being like a safety checklist for a commercial airliner — if the forecast is important, it is important to check all relevant items on the list. Most of these principles were derived as generalized findings from empirical comparisons of alternative forecasting methods. Interestingly, the empirical evidence sometimes conflicts with common beliefs about how to forecast.

Primarily due to the strong emphasis placed on empirical comparisons of alternative methods, researchers have made many advances in forecasting since 1980. The most influential paper in this regard is the M-competition paper (Makridakis et al. 1982). This was based on a study where different forecasters were invited to use what they thought to be the best method to forecast many times series. Entry into the competition required that methods were fully disclosed. Entrants submitted their forecasts to an umpire who calculated the errors for each method. This was only one in a series of M-competition studies, the most recent being Makridakis and Hibon (2000). For a summary of the progress that has been made in forecasting since 1980, see Armstrong (2006).

We briefly describe valid forecasting methods, provide guidelines for the selection of methods, and present the Forecasting Canon of nine overarching principles. The Forecasting Canon provides a gentle introduction for those who do not need to become forecasting experts but who nevertheless rightly believe that proper knowledge about forecasting would help them to improve their decision making. Those who wish to know more can find what they seek in Principles of Forecasting: A Handbook for Practitioners and Researchers, and at the Principles of Forecasting Internet site.

Keywords: forecasting, principles

JEL Classification: C53

Suggested Citation

Green, Kesten C. and Graefe, Andreas and Armstrong, J. Scott, Forecasting Principles (October 5, 2011). M. Lovric, International Encyclopedia on Statistical Science (2010). Available at SSRN: https://ssrn.com/abstract=1939340

Kesten C. Green

University of South Australia - UniSA Business School ( email )

GPO Box 2471
Adelaide, SA 5001
Australia
+61 8 83012 9097 (Phone)

HOME PAGE: http://people.unisa.edu.au/Kesten.Green

Ehrenberg-Bass Institute for Marketing Science ( email )

Australia

HOME PAGE: http://www.marketingscience.info/people/KestenGreen.html

Andreas Graefe

Macromedia University of Applied Sciences ( email )

Sandstrasse 9
Munich, Bavaria 80337
Germany

HOME PAGE: http://www.andreas-graefe.org

J. Scott Armstrong (Contact Author)

University of Pennsylvania - Marketing Department ( email )

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States
215-898-5087 (Phone)
215-898-2534 (Fax)

HOME PAGE: http://marketing.wharton.upenn.edu/people/faculty/armstrong.cfm

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