Quarterly External Debt Statistics (QEDS) Database

Quarterly External Debt Statistics (QEDS) is a joint initiative by the World Bank and the International Monetary Fund (IMF) that compiles, harmonises, and publishes quarterly external debt data for countries participating in the IMF’s Special Data Dissemination Standard (SDDS) and a subset of those in the General Data Dissemination System (GDDS). The goal is to provide timely, comparable, and disaggregated external debt data for analytical and policy use.

Purpose and Significance

• QEDS enables cross-country comparison of external debt positions using a harmonised framework.
• It supports macroeconomic analysis, debt sustainability assessments, and risk monitoring.
• It enhances transparency, helping markets, policymakers, and researchers see trends in external obligations with greater clarity.
• It complements other debt databases such as the Joint External Debt Hub (JEDH) by focusing on national debtor reporting.

Methodology and Standards

• QEDS is aligned with the 2013 External Debt Statistics: Guide for Compilers and Users (2013 EDS Guide), which is consistent with the Sixth Edition of the Balance of Payments and International Investment Position Manual (BPM6).
• Historical external debt data originally reported under earlier norms (2003 EDS Guide / BPM5) have been converted to the newer framework using generic conversion templates in consultation with reporting countries.
• The QEDS database offers both a prescribed core table (Table 1) and encouraged supplementary tables (Tables 2, 3, 4). These cover breakdowns by sector, instrument, maturity, currency composition, debt service schedules, and more.
• Some countries participating via the GDDS report a simplified set of public and publicly-guaranteed external debt statistics under QEDS.

Data Coverage and Frequency

• Data generally begin from first quarter 1998 (1998 Q1) for SDDS participants.
• QEDS covers quarterly frequency, with each entry reflecting the external debt stock and its attributes at the end of the quarter.
• It disaggregates debt by institutional sector (public, private, publicly-guaranteed), instrument type (loans, debt securities, trade credit, etc.), original maturity, remaining maturity, and currency of denomination.
• Debt service schedules (principal and interest payments due in one year or less) and breakdowns of short-term debt are also included where available.

Structure of Tables

• Table 1 (Core / Prescribed): Gross external debt position by sector, maturity, instrument.
• Table 2 (Encouraged): Currency composition (foreign-currency vs domestic linked) of external debt.
• Table 3 (Encouraged): Debt service payment schedule (principal and interest) for outstanding stock as of end-period.
• Table 4 (Encouraged): Principal and interest due within one year, by sector.
• Supplementary Tables: Reconciling nominal vs market values, arrears, net debt position, and sectoral breakdowns (e.g. public vs private).

Advantages and Limitations

Advantages:

• High-frequency data allows more timely monitoring of external liabilities.
• Standardised classifications increase comparability across countries.
• Detailed breakdowns help identify vulnerabilities (e.g. short-term debt exposure, currency mismatches).

Limitations:

• Participation is voluntary; not all countries report full series under QEDS.
• Some countries, especially in the GDDS group, may report only a limited data subset (e.g. public external debt).
• The process of converting historical data to the new standard may introduce measurement adjustments.
• Differences in national data collection practices and reporting lags may affect consistency.

Updates and Maintenance

• QEDS is quarterly updated, reflecting newly reported external debt positions (along with revised historical data where applicable).
• It is accessible via the World Bank’s Open Data portal under “Quarterly External Debt Statistics / SDDS (New)” and “/ GDDS (New)” interfaces.
• Metadata accompanying country reports document definitions, compilation practices, notes, and data revisions.