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HIPC Debt Sustainability Analysis (DSA) Data
Data Science and Analytics
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About
This product tracks the evolution of external debt distress vulnerability among Sub-Saharan African nations designated as Heavily Indebted Poor Countries (HIPC). Following large-scale debt cancellations granted by institutions such as the World Bank, International Monetary Fund, and African Development Bank, the debt sustainability of these countries has been continuously scrutinised. The data provides annual classifications derived from the Debt Sustainability Analysis for Low-Income Countries (DSA for LIC) framework, offering critical insights into how debt risk has shifted over time, alongside related macroeconomic and governance metrics. It is an essential resource for monitoring post-relief fiscal health and development trajectory in the region.
Columns
The dataset contains 22 columns across governance, macroeconomics, and debt classification:
- ISO: The ISO 3166-1 alpha-3 code identifying the country.
- Year: The period for the classification, defaulting to the previous year’s classification if no DSA was conducted in that specific year.
- Risk.ext.debt.distress: The primary classification result from the Debt Sustainability Analysis for Low-Income Countries (DSA for LIC), with 'Moderate' being the most frequent category, representing 42% of the observations.
- Debt.Indicator: A binary variable where '0' signifies a Low or Moderate risk of external debt distress, and '1' indicates High risk or being currently in debt distress.
- Inflation: The annual percentage change of average consumer prices.
- Cur.acc.bal: Current account balance expressed as a percentage of GDP.
- Gen.gov.len.bor: General government net lending/borrowing as a percentage of GDP.
- Vol.Exp.Goods: Volume of exports in goods and services, expressed as a percentage change.
- GDP: Gross Domestic Product measured in current US dollars.
- GDP.per.cap: GDP per capita in US dollars.
- Gen.gov.rev: General government revenue as a percentage of GDP.
- US.int.rates: Real interest rates in the United States, measured as a percentage.
- Ext.Debt.Serv: Total debt service on external debt in current USD.
- Real.GDP.growth: Percentage change in real GDP growth.
- Exch.Rate: Official exchange rate (local currency unit per US dollar, period average).
- Control.of.Corruption: A score reflecting the control of corruption, sourced from the Worldwide Governance Indicators (WGI).
- Government.Effectiveness: A score from the WGI indicating Government Effectiveness.
- Pol.Stability.Absence.of.Violence: A WGI score for Political Stability and Absence of Violence.
- Regulatory.Quality: A WGI score measuring Regulatory Quality.
- Rule.of.Law: A WGI score for the Rule of Law.
- Voice.and.Accountability: A WGI score for Voice and Accountability.
Distribution
The product is available as a CSV file (
DSA_classifications.csv) and comprises 435 observations. It consists of 22 distinct columns, with no missing or mismatched data recorded across the valid observations. The file size is approximately 78.29 kB. Updates are anticipated to occur on an annual basis.Usage
This data product is suited for applications involving economic modelling, risk assessment, and policy analysis focused on low-income countries. Ideal uses include:
- Evaluating the long-term effectiveness of the HIPC initiative and its impact on debt sustainability.
- Predicting shifts in external debt risk classifications for Sub-Saharan African nations.
- Analysing correlations between macroeconomic indicators, governance metrics (such as the Rule of Law or Control of Corruption), and debt vulnerability.
- Developing early warning systems for emerging debt distress in developing economies.
Coverage
The dataset spans the time frame from 2005 to 2019, covering the period during which the Debt Sustainability Analysis for Low-Income Countries (DSA for LIC) framework has been consistently applied. Geographic coverage includes thirty Sub-Saharan African countries that benefited from the HIPC debt relief scheme, represented by 29 unique ISO codes.
License
CC0: Public Domain
Who Can Use It
The product is designed for use by:
- Economists and Researchers: For academic studies on African economic development and debt dynamics.
- International Financial Institutions: For monitoring the post-relief performance and sustainability of debtor nations.
- Policy Analysts: To inform government lending decisions and aid programmes targeting vulnerable economies.
- Data Scientists: For training machine learning models aimed at classifying sovereign debt risk.
Dataset Name Suggestions
- Africa HIPC Debt Vulnerability 2005-2019
- Sub-Saharan Africa External Debt Risk Classifications
- HIPC Debt Sustainability Analysis (DSA) Data
Attributes
Original Data Source: HIPC Debt Sustainability Analysis (DSA) Data
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