A Comparison of Short and Medium Range Statistical Forecasting Methods

Robert M. Kirby
Additional contact information
Robert M. Kirby: The Singer Company, 30 Rockefeller Plaza, New York, New York 10020

Management Science, 1966, vol. 13, issue 4, B202-B210

Abstract: Exponential Smoothing, Moving Average, and Least Squares forecasting models were tested by simulating their operation on seven years of actual data for various sewing machine product groups. The relative accuracy of the forecasts varied according to the length of the period being forecasted and the characteristics of the data. Tests were also conducted on synthetic series designed to isolate the cyclical, trend and noise components. For the series tested, the Exponential Smoothing and Moving Average methods were about equal in overall performance for intermediate range forecasts (next six months' demand). For the short range (next month's demand), the Exponential Smoothing gave slightly better over-all results. The difference in relative performance between the Exponential Smoothing and Moving Average methods for intermediate versus short range forecasts appears to be due to a subcomponent identified as "caused noise."

Date: 1966
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.13.4.B202 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:13:y:1966:i:4:p:b202-b210

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().