Training Program

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National Accounts Statistics (NAS)

Invitation

Session No.: SA 24.29

Location: New Delhi, India

Date: July 22-26, 2024 (1 week)

Delivery Method: In-person Training

Primary Language: English

Target Audience

The workshop is intended for Indian subnational government officials who are integrally involved in the compilation of and dissemination of gross state domestic product statistics (GSDP).

Qualifications

Participants are expected to have a bachelor's degree, with backgrounds in economics, accounting, or related fields.

Course Description

This one-week workshop will be presented by experts from the International Monetary Fund's Statistics Department and a representative from India's Ministry of Statistics and Programme Implementation. The workshop will be based on the System of National Accounts 2008 (2008 SNA) and the Quarterly National Accounts Manual, 2017. The workshop will cover the following topics: (1) national accounts concepts and methods from the perspective of GSDP; (2) data sources and indicators (annual and quarterly), including use of benchmarking techniques; (3) price and volume measures; and (4) fundamental aspects of state/regional economic accounts. The workshop will feature interactive lectures and hands-on exercises that enable participants to operationalize what they learn.

Course Objectives

Upon completion of this workshop, participants should be able to: 

(i)    Describe fundamental aspects of a national accounts statistical system that is highly aligned with the international standard.
(ii)    Compilation of gross domestic product (GDP) estimates by economic activity and by expenditure from state perspective
(iii)    Highlight similarities and differences between processes for estimating GDP and GSDP. 
(iv)    Know how to identify statistically high-quality indicator series for estimating GDP and GSDP. 
(v)    Compile GDP and GSDP volume measures: using double deflation; volume extrapolation; and single extrapolation.
(vi)    Know topical areas where India plans to improve its estimates of GSDP.

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