Date of this Version Previous research has shown that seasonal
factors provide one of the most important ways to improve
forecast accuracy. For example, in forecasts over an 18-month
horizon for 68 monthly economic series from the M-Competition,
Makridakis et al. (1984, Table 14) found that seasonal
adjustments reduced the MAPE from 23.0 to 17.7 percent, an error
reduction of 23%. On the other hand, research has also shown
that seasonal factors sometimes increase forecast errors (e.g.,
Nelson, 1972). So, when forecasting with a data series measured
in intervals that represent part of a year, should one use
seasonal factors or not? Statistical tests have been devised to
answer this question, and they have been quite useful. However,
some people might say that the question is not fair. Why does it
have to be either/or? Shouldn’t the question be "to what extent
should seasonal factors be used for a given series?" Date
Posted: 14 June 2007 This document has been peer reviewed.