1. Introduction
This analysis explores a sample international debt dataset using PostgreSQL. The goal is to understand the structure of the data, assess data quality, and generate insights about global debt distribution. The dataset contains information on countries, debt indicators, and debt value. It also includes missing values that must be handled carefully during analysis, if accurate meaning is to be drawn from the dataset.
2. Loading the Dataset
**Assuming there is an active connected postgresql.
Steps:
- Open PostgreSQL in Dbeaver
- Create a schema
create schema international_debt_analysis);
Set the search path
set search_path to international_debt_analysis);
- Right click on tables under your schema
Import data
Select the source file
Map the table to the schema
Confirm
Proceed
Open a new script
Confirm your table is in the right schema
select * from international_debt_with_missing_values;
3. SQL Queries and Findings
The data is analysed using SQL queries. Charts and tables are used for visualization.
3.1 The Total Amount of Debt Owed
select sum(debt) as total_debt
from international_debt_analysis;
The Total Amount of Debt Owed is 2,823,893,300,273
3.2 Number of Distinct Countries
select count(distinct country_name) as distinct_country
from international_debt_analysis;
Distinct Countries = 125
3.3 Distinct Types of Debt Indicators
select distinct indicator_code, indicator_name
from international_debt_analysis
where indicator_name is not null
and indicator_name <> ''
and indicator_code is not null
and indicator_code <> '';
Table1: Distinct Debt Indicators
| Serial | Code | Description |
|---|---|---|
| 1 | DT.INT.PRVT.CD | PPG, private creditors (INT, current US$) |
| 2 | DT.AMT.OFFT.CD | PPG, official creditors (AMT, current US$) |
| 3 | DT.INT.DLXF.CD | Interest payments on external debt, long-term (INT, current US$) |
| 4 | DT.INT.DPNG.CD | Interest payments on external debt, private nonguaranteed (PNG) (INT, current US$) |
| 5 | DT.DIS.PCBK.CD | PPG, commercial banks (DIS, current US$) |
| 6 | DT.AMT.PBND.CD | PPG, bonds (AMT, current US$) |
| 7 | DT.DIS.MLAT.CD | PPG, multilateral (DIS, current US$) |
| 8 | DT.DIS.PRVT.CD | PPG, private creditors (DIS, current US$) |
| 9 | DT.INT.MLAT.CD | PPG, multilateral (INT, current US$) |
| 10 | DT.INT.PBND.CD | PPG, bonds (INT, current US$) |
| 11 | DT.INT.PROP.CD | PPG, other private creditors (INT, current US$) |
| 12 | DT.DIS.OFFT.CD | PPG, official creditors (DIS, current US$) |
| 13 | DT.AMT.MLAT.CD | PPG, multilateral (AMT, current US$) |
| 14 | DT.INT.OFFT.CD | PPG, official creditors (INT, current US$) |
| 15 | DT.DIS.PROP.CD | PPG, other private creditors (DIS, current US$) |
| 16 | DT.AMT.PCBK.CD | PPG, commercial banks (AMT, current US$) |
| 17 | DT.DIS.BLAT.CD | PPG, bilateral (DIS, current US$) |
| 18 | DT.AMT.DLXF.CD | Principal repayments on external debt, long-term (AMT, current US$) |
| 19 | DT.AMT.PROP.CD | PPG, other private creditors (AMT, current US$) |
| 20 | DT.AMT.PRVT.CD | PPG, private creditors (AMT, current US$) |
| 21 | DT.AMT.BLAT.CD | PPG, bilateral (AMT, current US$) |
| 22 | DT.INT.PCBK.CD | PPG, commercial banks (INT, current US$) |
| 23 | DT.INT.BLAT.CD | PPG, bilateral (INT, current US$) |
| 24 | DT.DIS.DLXF.CD | Disbursements on external debt, long-term (DIS, current US$) |
| 25 | DT.AMT.DPNG.CD | Principal repayments on external debt, private nonguaranteed (PNG) (AMT, current US$) |
3.4 Country with Highest Total Debt, and the Amount
select country_name, sum(debt) as total_debt
from international_debt_analysis
where country_name is not null
and country_name <> ''
group by country_name
order by total_debt desc
limit 1;
The county is China with the debt of 283,748,948,518
3.5 The Average Debt Across Different Debt Indicators
select indicator_name, AVG(debt) AS avg_debt
from international_debt_with_missing_values
group by indicator_name
order by avg_debt desc;
Fig1: Average Debt per Indicator Category
3.6 Country with Highest Principal Repayment
select country_name, SUM(debt) AS total_principal_repayment
from international_debt_analysis
where indicator_name like '%Principal repayment%' and debt> 0
group by country_name
order by total_principal_repayment desc
limit 1;
The county is China with the principal repayment amount of 168,611,607,050
3.7 Most Common Debt Indicator
select indicator_name, COUNT(*) AS frequency
from international_debt_analysis
where indicator_name is not null
and indicator_name <> ''
group by indicator_name
order by frequency desc
limit 1;
the most common debt indicator is PPG, official creditors (AMT, current US$) with a total of 124
3.8 Other Key Debt Trends
3.8.1 Top 5 countries with the most debt
select country_name, sum(debt) as total_debt
from international_debt_with_missing_values
group by country_name
order by total_debt desc
limit 5;
Fig2: Average Debt per Indicator Category
3.8.2 Five Countries with the Least Debt
This excludes countries registering 0 debt
select country_name, sum(debt) as total_debt
from international_debt_analysis
where debt> 0
group by country_name
order by total_debt asc
limit 5;
Fig:5 Countries with the Lowest Debt
3.8.3 Number of countries with missing debt values or 0 debt
select count(distinct country_name) as countries_with_zero_or_missing_debt
from international_debt_analysis
where debt is null or debt = 0;
Total number of countries where debt is 0 or missing debt are 110
Conclusion
Overall, the data suggests a significant dependence on external financing, with repayment pressures concentrated in a few major economies and vulnerable groups. This underlines the importance of careful debt management policies, diversification of financing sources, and sustainable borrowing strategies to reduce long-term risks.
References and Further Reading
World Bank. (2023). International Debt Statistics. Washington, DC: World Bank. Available at: https://databank.worldbank.org/source/international-debt-statistics
International Monetary Fund (IMF). (2022). Global Debt Database. Washington, DC: IMF. Available at: https://www.imf.org/en/Data
Reinhart, C. M., & Rogoff, K. S. (2010). Growth in a Time of Debt. American Economic Review, 100(2), 573–578.
FAO & UNCTAD. (2021). Financing Sustainable Development in Developing Countries. Geneva: United Nations.
PostgreSQL Global Development Group. (2023). PostgreSQL Documentation. Available at: https://www.postgresql.org/docs/
IBM Developer. (2021). Best Practices in Data Analysis Using SQL. IBM Developer Portal.
O’Neil, P., & O’Neil, E. (2014). Database Principles, Programming, and Performance. Morgan Kaufmann.
DataCamp. (2022). SQL for Data Analysis: Concepts and Practice. Available at: https://www.datacamp.com
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