Purpose:
Seasonal adjustment is an important component of most published
monthly and quarterly economic time series and is usually done with
off-the-shelf software. Two such programs are X-12-ARIMA (from the
U.S. Census Bureau) and SEATS (developed by Agustin Maravall at the
Bank of Spain). They are the most widely used programs for seasonal
adjustment in the world.
The purpose of this course is to teach participants how to run X-13ARIMA-SEATS, the newest seasonal adjustment program that is now the official program for seasonal adjustments from the U.S. Census Bureau. The course focuses on the options used to produce X-11/X-12-type adjustments, the adjustments used for official adjustments from the U.S. Census Bureau. We also generally discuss SEATS-type adjustments.
Topics include writing input files, running the program, looking at the output, and assessing the results. We will also discuss the purpose of seasonal adjustment and the methods used for seasonal adjustment. The course is both practical and technical, and also discusses briefly some theoretical aspects. Involves in-class computer work.
Duration: 3 days
Target audience:
This course is intended for anyone interested in learning how to run
X-13ARIMA-SEATS. The course is limited to 10 persons.
Prerequisites:
None, only general prior knowledge of time series is assumed.
Some topics require some knowledge of statistics, for example,
the participants should understand terms like mean, covariance,
and linear regression.
Benefits to Participants:
Upon completion of the course, the participants will be able to
choose the most appropriate options in X-13ARIMA-SEATS,
run the program, and assess the results.
Topics Covered: The course examines the following topics:
The course will involve the practical application of concepts through the use of case studies, group discussion, and computer exercises.
Note: If time permits at the end of the course, participants will have the chance to work on sample series provided or on their own series. Participants are encouraged to bring sample time series with them to class as either text files or in Excel format.
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Last modified: 20 Mar 2021
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