Officials responsible for compiling national accounts statistics.
Participants should have a degree in economics, statistics, or the equivalent.
This course, presented by the IMF’s Statistics Department, aims at providing a thorough understanding of concepts, sources of data, and compilation techniques for producing quarterly national accounts statistics. The course is based on the IMF’s Quarterly National Accounts Manual and is oriented toward national accounts compilers from countries that are developing or planning to develop Quarterly National Accounts (QNA). The course covers both theoretical and practical issues in the compilation of QNA. It covers the following main topics:
- Scope and role of QNA.
- Data sources for compiling quarterly GDP estimates (mainly from production and expenditure approaches).
- Benchmarking techniques for combining quarterly indicators with the annual estimates.
- Seasonal adjustment.
- Price and volume measures.
- Chain-linking techniques for compiling QNA time series.
- Other specific QNA issues.
- Revision policy and dissemination practices.
The course is delivered through lectures, workshops, and small group discussions.
Upon completion of this course, participants should be able to:
- Describe the QNA, including its compilation, scope, role, and international standards and best practices.
- Describe data requirements and methods to compile the different sets of quarterly national accounts statistics, especially GDP and its valuation.
- Illustrate the relation of the QNA to other aggregates within the SNA.
- Develop a simple framework to compile a basic set of national accounts series, including the collection/development of source data to implementation of simple statistical methods to derive such 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, its potential analytical uses and some more advanced techniques to assess the economic activity more accurately.