Regional Seasonal Adjustment (RSA)

Course Details

Start: June 25, 2018

End: June 29, 2018

Course Number: SA18.25

Course Name: Regional Seasonal Adjustment (RSA)

Language: English

Location: New Delhi, India

Application Process: Apply Online

 

 

Application Deadline

May 25, 2018

 

 

 

Target Audience

This workshop is intended for government officials from SARTTAC Member Countries, who are integrally engaged in the compilation and dissemination of gross domestic product (GDP) statistics, especially quarterly GDP statistics.


Qualifications

Participants are expected to be a current member of a GDP compilation team—typically at a statistics bureau. It will be favorable for participants to have completed an undergraduate degree in economics, statistics, mathematics, or accounting.
 

Course Description

This one-week workshop will be presented primarily by an expert from INSEE. The workshop will feature use of JDemetra Plus seasonal adjustment computer software. It will cover the following topics:

1. fundamental theories, concepts, and methods underlying seasonal adjustment;

2. the mathematics of seasonal adjustment;

3. special issues in seasonal adjustment, including calendar effects in seasonal adjustment; and

4. hands-on operationalization of seasonal adjustment processes.

The workshop will entail interactive lectures and hands-on exercises that enable participants to perform the seasonal adjustment process.


Course Objectives

By the end of the workshop, participants should be able to:

1. Describe fundamental components of time series data.

2. Convey the type of analysis that should be performed on time series on a pre-seasonal adjustment basis.

3. Describe how to determine the seasonal adjustment parameters that should be adopted for specific time series.

4. Explain how to develop calendars for seasonal adjustment that account for national specificities: moving and fixed holidays, and other calendar effects.

5. Explain how to assess seasonal adjustment statistics to determine whether time series have been seasonally adjusted properly.

6. Highlight how to determine the level at which data should be seasonally adjusted when there are aggregate and subaggregate series.

7. Describe how seasonal adjustment efforts affect revision policies.