Quarterly National Accounts/High Frequency Indicators of Economic Activity

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Canonical URL: Quarterly National Accounts/High Frequency Indicators of Economic Activity

Course title: Quarterly National Accounts/High Frequency Indicators of Economic Activity (QNAx)
Session No.: OL 25.201
Location: Course conducted online
Date: May 1, 2025 - April 15, 2026 (50 weeks)
Delivery Method: Online Training
Primary Language: French
Status: Deadline passed
Target audience: Officials worldwide responsible for compiling quarterly national accounts (QNA) and/or high frequency indicators of economic activity (HFIEA)
Qualifications and technical requirements:
- Participants are expected to have a degree in economics or statistics; or equivalent experience.
- Access to a computer with a reliable Internet connection and a Google Chrome web browser are essential.

Purpose: Prepare participants to compile QNA and/or HFIEA by providing a thorough understanding of concepts, source data, and compilation techniques.
Coverage:
- Theoretical and practical compilation issues for QNA and HFIEA.
- Benchmarking techniques and seasonal adjustment techniques, as well as volume estimates.
- Application of benchmarking, seasonal adjustment, and volume-estimation techniques to time series data.
- Identification and assessment of available data sources for compiling QNA and HFIEAs.
- Use of related real-time series databases to assess the quality of QNA and HFIEAs.
- Implementation of a suitable revisions policy.

Recognize the role, scope, and uses of QNA and HFIEAs.
Describe the compilation framework for the QNA and the different compilation methods for HFIEAs (including composite leading indicators).
Review available data sources for compiling QNA by the income, expenditure and production approaches, and HFIEAs.
Explain the use of volume measures and the basic relation between value, quantity, and price—expanding on how to detect and address issues such as the need for updated weights; and recognizing the loss of additivity for chain-linked volume estimates.
Compile benchmarked series using the recommended techniques.
Apply basic techniques for filling data gaps.
Identify good seasonal adjustment practices and apply basic seasonal adjustment techniques to time series.
Formulate a balanced revisions policy taking account of how related real-time database can be used to assess the reliability of the QNA/HFIEA estimates.