Quarterly National Accounts - Advanced
Source details
- Canonical URL
- Quarterly National Accounts - Advanced
Other formats
Bibliographic details
- Session: HQ 26.05
- Location: Washington, D.C., United States
- Dates: February 2-13, 2026 (2 weeks)
- Delivery method: Blended Training
- Primary language: English
- Status: Deadline passed
Training program and target audience
- Training Program: Targeted at officials responsible for compiling national accounts statistics.
- Qualifications: Participants are expected to have a degree in economics or statistics; or equivalent experience.
Course description
- Presented by: Statistics Department.
- Course duration: Two-week course.
- Basis: The course is based on the IMF Quarterly National Accounts Manual (2017 Edition).
- Orientation: Oriented to national accounts compilers from countries that are improving, developing, or planning to develop quarterly national accounts (QNA).
- Teaching methods: Lectures, workshops, and small group discussions.
- Main topics covered:
- The scope and role of QNA.
- Data sources for compiling quarterly GDP estimates (using production, expenditure and income approaches).
- Editing procedures and dealing with indicators.
- Benchmarking techniques for combining quarterly indicators with annual estimates.
- Seasonal adjustments.
- Price and volume measures.
- Chain-linking techniques for compiling QNA time series.
- Early estimates of quarterly GDP.
- Other specific QNA issues.
- Revision policy and dissemination practices.
Course objectives
Upon completion of the course, participants should be able to:
- Describe the QNA in terms of its compilation, scope, role, and international standards and best practices.
- Describe data requirements for and methods of compiling the different sets of QNA statistics, especially GDP and its valuation.
- Illustrate the relation of the QNA to other aggregates within the SNA. Draw up a simple framework to compile basic national accounts series, from collection and development of source data to application of simple statistical methods to derive aggregates.
- Gain practical experience dealing with specific issues relating to the compilation and use of quarterly data.
- Describe the analytical uses of quarterly information on GDP, other potential analytical uses, and some advanced techniques to assess economic activity more accurately.