|
|
| Time series |
A sequence of measures of a given phenomenon taken at regular time intervals. For
the information to be useful for time series analysis, that data should be comparable over time.
That means 1) that the measurements should be taken over discrete consecutive periods, i.e.,
every month or every quarter, and 2) that the definition of the concept and the way it is measured
should be consistent over time. |
|
|
| Seasonal Adjustment |
The process of estimating and removing the seasonal effects from a time
series. The basic goal of seasonal adjustment is to decompose a time series into a several
different components including a seasonal component and an irregular component. |
|
|
| Trend or Trend-Cycle |
An estimate of the local level of the series for each month (quarter)
derived from the surrounding recent (a year or two) observations. |
|
|
| Seasonal Effects |
Effects that are reasonably stable in terms of annual timing, direction, and
magnitude. Possible causes include natural factors (the weather), administrative measures
(starting and ending dates of the school year), and social/cultural/religious traditions (fixed
holidays such as Christmas). Effects associated with the dates of moving holidays like Easter are
not seasonal in this sense, because they occur in different calendar months depending on the date
of the holiday. |
|
|
| Irregular Component |
Anything not included in the trend-cycle or the seasonal effects (or in
estimated trading day or holiday effects). Its values are unpredictable as regards timing, impact,
and duration. It can arise from sampling error, non-sampling error, unseasonable weather,
natural disasters, strikes, etc. |
|
|
| Trading Day Effects |
Recurring effects associated with individual days of the week. This
occurs because only non-leap-year Februaries have four of each day - four Mondays, four
Tuesdays, etc. All other months have an excess of some types of days. If an activity in higher
on some days compared to others, then the series can have a trading day effect. For example,
building permit offices are usually closed on Saturday and Sunday. Thus, the number of building
permits issued in a given month is likely to be higher if the month contains a surplus of
weekdays and lower if the month contains a surplus of weekend days. |
|
|
| Moving Holiday Effects |
Effects from holidays that aren't always on the same day of a month,
such as Labor Day or Thanksgiving. The most important moving holiday in the US is Easter, and
it not only moves between days, but can also move between months since it can occur in March
or April. |
|
|
| X-12-ARIMA |
The seasonal adjustment software used at the Bureau. This program is written and maintained
by staff at the Bureau. The primary programmer is Brian Monsell in the Statistical Research
Division at the US Census Bureau. |
Back to the Top