Public Sector Debt Statistics - Fundamental (PDS-F)
Apply online by April 27, 2025 Deadline extended
Session No.: JV 25.23
Location: Vienna, Austria
Date: August 4-8, 2025 (1 week)
Delivery Method: In-person Training
Primary Language: English
Interpretation Language: Russian
Apply NowTarget Audience
Public sector officials whose main responsibility is compiling and disseminating public sector debt statistics.
Qualifications
Participants are expected to have a degree in economics, public financial management, statistics, or equivalent experience.
Course Description
This course, conducted by the Statistics Department, focuses on the conceptual framework of public sector debt statistics as presented in the Public Sector Debt Statistics: Guide for Compilers and Users 2011 (PSDSG 2011), as well as on the practical aspects of public sector debt data compilation. Basic concepts, accounting principles, and detailed classifications are dealt with in the context of the methodology that is harmonized with the Government Finance Statistics Manual 2014 (GFSM 2014) and the System of National Accounts (SNA 2008). The course examines coverage and accounting rules of the public sector debt statistics framework, valuation, classification, selected methodological issues, and the sources and methods used for compiling the statistics. It also deals with debt data reporting to the IMF and World Bank. The course is organized around a series of case studies.
Course Objectives
Upon completion of the course, participants should be able to:
- Define gross and net debt and explain the basic concepts and accounting principles for the compilation of public sector debt statistics.
- Classify public sector debt positions according to the PSDSG 2011 classifications.
- Apply general principles to classify an entity in the public sector, as well as in the relevant subsectors of the public sector, such as the general government and public corporations.
- Report quarterly public sector debt statistics covering—at a minimum—the central government, to the IMF and World Bank.
- Meeting data users’ needs to ensure relevancy.
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