Seasonal Adjustment
Over the year, the size of the Nation's labor force, the levels of
employment and unemployment, and other measures of labor market activity
undergo sharp fluctuations due to seasonal events including changes in
weather, harvests, major holidays, and the opening and closing of schools.
Because these seasonal events follow a more or less regular pattern each
year, their influence on statistical trends can be eliminated by adjusting
the statistics from month to month. These adjustments make it easier to
observe the cyclical, long term trend and other nonseasonal movements in
the series. In evaluating changes in a seasonally adjusted series, it is
important to note that seasonal adjustment is an approximation and initial
adjustment must be based on experience.
Beginning in 1992, BLS introduced publication of seasonally adjusted
labor force data for the 50 States, the
District of Columbia, and Puerto Rico. Beginning in 1996, seasonal
adjustment was extended to estimates for the Los Angeles-Long Beach
metropolitan area and New York City. In 1998, seasonally
adjusted data for census regions and divisions were first published.
With the introduction of the LAUS Redesign in 2005, seasonal
adjustment occured within the model estimation process through the removal
of the seasonal component. This modeling approach is used in developing
labor force estimates for Census divisions, States, the Los Angeles-Long
Beach-Glendale metropolitan division, and New York City. It was extended to
six substate areas in 2005. One of these areas was the New
Orleans-Metarie-Kenner, LA metropolitan area, which was subsequently
removed due to various technical problems following Hurricane Katrina.
The remaining five areas are:
- Chicago-Joliet-Naperville, IL metropolitan division
- Cleveland-Elyria-Mentor, OH metropolitan area
- Detroit-Warren-Livonia, MI metropolitan area
- Miami-Miami Beach-Kendall, FL metropolitan division
- Seattle-Bellevue-Everett, WA metropolitan division
In 2010, a smoothed-seasonally adjusted (SSA) series was introduced
to reduce the number of spurious turning points in the former estimates.
The estimates are smoothed using the Henderson Trend Filter (H13) that suppresses
irregular variation in real time. The H13 uses a filtering procedure, based on
moving averages, to remove the irregular fluctuations from the seasonally-adjusted
series, leaving the trend. Symmetric moving averages are used to smooth the
historical series while asymmetrical averages are used in real time. This new approach
addresses longstanding issues related to end-of-year revision and enhances the
analytical utility of the estimates.
For more information on Smoothed-Seasonal Adjustment, see
Smoothed-Seasonally-Adjusted Estimates (SSA) Questions and Answers.
Last Modified Date: March 03, 2010
