Purpose:
Most of the data published by banks and government agencies consists of
time series. When using time series to make decisions, it is often useful
to look at time series that have been adjusted for seasonality. It is
important to recognize and understand the movements present in time series
and to understand the various components of a time series (such as the trend)
that are estimated during seasonal adjustment. The course covers the basic
concepts needed to understand the uses and mechanics of seasonal adjustment.
We will also discuss various software packages available for seasonal
adjustment, including how to read output files and diagnostics.
This class is only lecture, no computer work required.
Duration: 1 day
Target audience:
This course is intended for a broad audience:
managers, decision/policy makers, analysts, economists, and statisticians. No
background in time series or seasonal adjustment is required.
Prerequisites: None
Benefits to Participants:
Upon completion of the course, the participants will be able to
understand the language of seasonal adjustment, read the output from
X-12-ARIMA and/or X-13ARIMA-SEATS, and assess the results from X-12/X-13.
Outline:
The course examines the following topics:
The course will involve the practical application of concepts through the use of case studies, group discussion, and exercises.
Trademarks and Copyrights
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Last modified: 20 Mar 2021
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