By: Janet Harrah
In analyzing the economy, economists and business analysts study a variety of data such as the number of jobs, number of new housing permits, number of home sales and total retail sales. Looking at these data at one point in time usually is not very informative. Most analysts track data over time to determine the extent to which individual industries or regions are contributing to or detracting from economic growth.
One problem with tracking trends over a few months or quarters is that many data series have movements that recur regularly. For example, over the course of a year, the size of the labor force, the levels of employment and unemployment, and other measures of labor market activity undergo fluctuations due to seasonal events, including changes in weather, harvests, major holidays, and school schedules. Because these seasonal events follow a more or less regular pattern each year, their influence on statistical trends can be eliminated by seasonally adjusting the statistics from month to month. These seasonal adjustments make it easier to observe the cyclical, underlying trend, and other non-seasonal movements in the series.
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