Cancelled - Quarterly National Accounts

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Cancelled - Quarterly National Accounts (QNA)

Cancelled

Session No.: CT 20.02

Location: Shenzhen, China

Date: February 24-28, 2020 (1 week)

Primary Language: English

Target Audience

Officials responsible for compiling national accounts statistics.

Qualifications

Participants are expected to have a degree in economics or statistics, or the equivalent.

Course Description

This course, presented by the Statistics Department, offers an opportunity for thorough understanding of concepts, sources of data, and compilation techniques for producing quarterly national accounts statistics. The course is based on the IMF Quarterly National Accounts Manual (2017 Edition) and oriented to national accounts compilers from countries that are improving, developing, or planning to develop quarterly national accounts (QNA). The course covers both theoretical and practical compilation issues, specifically the following main topics:

the scope and role of QNA;
data sources for compiling quarterly GDP estimates (mainly using production and expenditure 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; and
revision policy and dissemination practices.

The course consists of lectures, workshops, and small group discussions.

Course Objectives

Upon completion of this 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.

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