Botswana

This report presents the findings and recommendations from the 2025 assessment of Botswana’s public sector debt statistics (PSDS) in relation to the IMF’s Data Quality Assessment Framework (DQAF) for PSDS. The assessment was conducted as part of an initiative—funded by the Government of Japan—to strengthen public debt data quality and transparency in selected African countries. Botswana adopted the IMF’s enhanced General Data Dissemination System (e-GDDS) in January 2016, but the reporting of PSDS via the National Summary Data Page (NSDP) remains limited in scope. Since that time, Botswana has benefited from substantial capacity development support provided by the IMF’s Statistics Department to strengthen government finance statistics (GFS) and PSDS. Botswana has maintained a prudent and credible debt management strategy over the years, adhering to a public debt ceiling of below 40 percent of GDP, with an even split between external and domestic debt. However, due to shifting global economic conditions, Botswana has recently encountered increases in debt ratios, with public debt reaching 28 percent of GDP by March 2025—up from 20.2 percent in December 2023 (excluding other accounts payable). The report concludes that, while Botswana’s public debt statistics are generally reliable, further enhancements are needed to improve data coverage, timeliness, and transparency. Notably, it recommends strengthening the Ministry of Finance's debt management functions to align with best practices, incorporating dedicated front, middle, and back-office operations, and enhancing the legal framework to provide more comprehensive oversight of debt management. Compilation methods are largely in accordance with international statistical standards; however, the enhancement of IT resources is necessary to mitigate operational risks, facilitate integration with internal systems, and enable effective interfacing with the Bank of Botswana’s Central Securities Depository (CSDB) to promote efficient data exchange and ensure consistency in published data.