Catherine Hood Consulting

Advanced Diagnostics: Case Studies

Purpose:
Many of the advances in seasonal adjustment in the past few years have been in the area of diagnostics. One of the benefits of using X-12-ARIMA for seasonal adjustment over its predecessors (X-11 and X-11-ARIMA) is the diagnostics available in X-12-ARIMA. New diagnostics have also been introduced for SEATS adjustments. The focus is on seasonal adjustment diagnostics that are useful in setting options in X-12-ARIMA or SEATS, with only some reference to ARIMA model diagnostics.

This course is not designed to teach the basics of seasonal adjustment or of running X-12-ARIMA or SEATS. Since there are more diagnostics available in X-12-ARIMA than in other seasonal adjustment programs, the course focuses on X-12-ARIMA diagnostics.

The course is both practical and technical, and we also discuss some of the theory behind the diagnostics. Involves in-class computer work.

Duration: 3 days

Target audience:
This course is intended for persons who are already X-12-ARIMA (and/or SEATS) users but who are interested in learning more about seasonal adjustment and diagnostics. The course is limited to 10 persons.

Prerequisites:
The "Running X-12-ARIMA" course or similar work experience is required. We assume that participants are already familiar with the basics of seasonal adjustment. Topics require some knowledge of statistics, and some theoretical topics are covered.

Benefits to Participants:
Upon completion of the course, the participants will have an in-depth understanding of the diagnsotics available in X-12-ARIMA and SEATS, knowing enough of the options available to be able to improve the seasonal adjustments of many kinds of series.

Topics Covered:
The course examines the following topics:

  • Review of the diagnostics available in X-12-ARIMA and SEATS, including theoretical background when appropriate
    • General graphical diagnostics
    • Spectral diagnostics
    • RegARIMA overview, tools, and diagnostics
    • Seasonal adjustment stability diagnostics
    • Other seasonal adjustment diagnostics
    • Diagnostics for composite series
  • Putting the diagnostics to work to improve the adjustment, including (but not limited to)
    • How to decide if a series is seasonal and/or adjustable
    • Strategies for dealing with residual spectral peaks
    • Strategies for deciding on ARIMA models and regression variables
    • Issues involving shortening the series or shortening the series for regARIMA modeling
    • Adjusting series that are a combination of smaller series (direct versus indirect adjustment of composite series)
    • Adjusting series with different variability in different months (or quarters)
  • Demonstration, looking at possible model and adjustment options for one series starting with only the data.
  • Computer work involving a wide range of sample series

The course will involve the practical application of concepts through the use of case studies, group discussion, and computer exercises.

Note: 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: 1 Apr 2013