Our full list of time series and seasonal adjustment courses:

• Introduction to Seasonal Adjustment
• Seasonal Adjustment with X-12-ARIMA in Windows®
• Seasonal Adjustment with TRAMO/SEATS for Windows®
• Seasonal Adjustment with X-12-ARIMA and TRAMO/SEATS in Windows®
• Advanced Diagnostics: Case Studies
• Advanced ARIMA Modeling for Forecasting and Seasonal Adjustment
• Advanced Seasonal Adjustment with X-12-ARIMA
• Advanced Seasonal Adjustment with X-12-ARIMA and Advanced ARIMA Modeling
• Advanced Seasonal Adjustment with TRAMO/SEATS
• Advanced Seasonal Adjustment with X-12-ARIMA and TRAMO/SEATS

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Introduction to Seasonal Adjustment

Purpose:
Most of the data published by banks and government agencies consists of time series. Time series data assist governments, businesses, and economists in making decisions. When comparing different economic indicators, 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: 2 days

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

Outline:
The course examines the following topics:

• Basic definitions – time series, seasonal adjustment, trend-cycle, trading day, moving holidays, and benchmarking
• The general mechanics of seasonal adjustment, such as various types of filters used and multiplicative versus additive adjustment
• Overview and demonstration of X-12-ARIMA and SEATS, including review of input and output files for each program
• An overview of concepts and the notation of regARIMA modeling, including the basic regressors used for seasonal adjustment
• A review of the diagnostics available, including spectral and stability diagnostics
• A discussion of various issues surrounding seasonal adjustment, including
• Issues with production, including publishing trend-cycles
• Direct versus indirect adjustment of aggregate series
• Possible sources of revisions or changes to the seasonal factors, including a discussion of outliers and extreme values
• Frequency of data collection and issues involved with time consistency and benchmarking
• Other policy issues related to seasonal adjustment

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

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Last update: 10 January 2007