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Africa > Mauritius

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International Monetary Fund. African Dept.
Weaker Macroeconomic Conditions and Policy Challenges. Mauritius continues to benefit from resilient economic activity, supported by tourism and financial services, but is now operating under weaker macroeconomic conditions amid a more adverse and uncertain external environment. High public debt, widening external imbalances, rising age-related spending pressures, substantial climate-adaptation and infrastructure needs, and weak productivity underscore the need to recalibrate the macroeconomic policy mix to rebuild buffers and strengthen macroeconomic resilience.
International Monetary Fund. African Dept.
Selected Issues
International Monetary Fund. Statistics Dept.
This paper presents report on the Observance of Standards and Codes—Data Module for Mauritius. The Response by the Authorities to this report and the Detailed Assessments Using the Data Quality Assessment Framework are also included. Mauritius’ Statistics Act provides a strong legal foundation for official statistics, but reforms underway will further enhance independence, transparency, and data integrity. Further enhancements are recommended to strengthen the professional independence of the Statistics Mauritius Director, modernize provisions for data sharing and access to administrative data. Mauritius’ macroeconomic statistics are broadly aligned with international statistical standards across all major domains. Mauritius has established a solid foundation for data accuracy and reliability, supported by long time series, regular publications, and broadly adequate source data, though some areas for improvement remain. Users of Mauritius Statistics expressed overall satisfaction with the quality of official statistics, while they emphasized the importance of strengthening the independence and governance of the statistical system to safeguard its credibility and transparency.
Steffi Schuster
and
David S Bailey
In September 2025, an assessment was undertaken of the data quality of the public sector debt statistics (PSDS) of Mauritius against the IMF’s Data Quality Assessment Framework (DQAF) for PSDS. The mission was undertaken as part of a project to strengthen the quality of public sector debt in select African countries, funded by the Government of Japan. The mission reviewed the PSDS compilation and dissemination practices against each element of the DQAF and presented a series of recommendations to improve the quality and transparency of the PSDS of Mauritius.
International Monetary Fund. Statistics Dept.
This report discusses the findings and recommendations of a diagnostic assessment of the quality of public sector debt statistics (PSDS) of Mauritius based on the IMF’s Data Quality Assessment Framework (DQAF) for PSDS. The assessment was undertaken in September 2025 as part of an initiative—funded by the Government of Japan—to strengthen the quality of public sector debt data in select African countries. Mauritius’ public debt is estimated to be 86 percent of GDP at the end of the 2024/25 fiscal year (end of June 2025), having risen significantly over the last five years. According to the PSDS reports of the Ministry of Finance (MOF), the consolidated gross public debt was 64 percent of GDP at the end of December 2019, just before the Covid pandemic. The high public debt levels of recent years have translated into a high risk of sovereign stress according to IMF’s latest debt sustainability analysis of June 2025. Mauritius subscribes to the IMF’s Special Data Dissemination Standard (SDDS) and submits quarterly debt data to the Joint IMF-World Bank Quarterly Public Sector Debt statistics database (QPSD). The quarterly debt data are disseminated in a regular and timely fashion through both the National Summary Data Page (NSDP) of the SDDS, and via the QPSD. In addition, the MOF publish a range of detailed quarterly public sector debt tables on their website. However, the mission found that debt reports could be more comprehensive through the inclusion of all debt instruments and more could be done to meet user needs by clearly presenting revisions, publishing stock-flow reconciliations, improving metadata and ensuring consistency with other macroeconomic statistics. In addition, the legislative and administrative arrangements could be further strengthened, including through the designation of PSDS as official statistics subject to the oversight and safeguards of the Statistics Act. The authorities have accepted the mission recommendations and developed an action plan to implement them in a phased manner.
Klakow Akepanidtaworn
and
Korkrid Akepanidtaworn
Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in nowcasting across simulation and six country cases, traditional econometric models tend to outperform ML algorithms. Among the ML algorithms, linear ML algorithm – Lasso and Elastic Net – perform best in nowcasting, even surpassing traditional econometric models in cases of long GDP data and rich high-frequency indicators. Among the traditional econometric models, the Bridge and Dynamic Factor deliver the strongest empirical results, while Three-Pass Regression Filter performs well in our simulation. Due to the relatively short length of GDP series, complex and non-linear ML algorithms are prone to overfitting, which compromises their out-of-sample performance.
International Monetary Fund

Abstract

Recognizing the increasing need for climate-responsive infrastructure investment, the IMF introduced the Climate-Public Investment Management Assessment (C-PIMA) in 2021 as an extension of the PIMA framework. The goal of the C-PIMA is to help governments identify potential improvements in public investment institutions and processes to build low-carbon and climate-resilient infrastructure. It has been conducted in more than 50 countries worldwide as of October 2024. The Climate-Public Investment Management Assessment Handbook (C-PIMA Handbook) outlines the importance of green resilient infrastructure investment for sustainable development and provides a detailed description of the C-PIMA framework, including discussions and explanations of all five institutions (and the 15 dimensions within them) with numerous examples from country practices. The handbook is aimed at anyone who is involved in a C-PIMA or has a practical interest in public investment management and climate change. It is intended to be useful to provide practical guidance to country authorities and development practitioners on how country systems are designed to incorporate climate considerations into public investment management and how they can be improved.

International Monetary Fund. Statistics Dept.
The Mauritius authorities requested IMF technical assistance to reconcile the statistical treatment of Global Business Corporations (GBCs) in the national accounts and the balance of payments. An IMF mission worked with Statistics Mauritius and the Bank of Mauritius to investigate significant GDP discrepancies, which were found to arise mainly from survey coverage gaps and methodological shortcomings in the measurement of output for the various types of GBCs. Following the discussions, both institutions agreed to the mission’s proposals to revise the methodology used to compile output and investment income of GBCs, in order to strengthen accuracy and ensure consistency across datasets.
International Monetary Fund. Finance Dept.
and
International Monetary Fund. Legal Dept.
This paper presents Resilience and Sustainability (RST) contribution agreements finalized with four contributors between March 2024 and September 5, 2025. The concluded agreements provide for contributions in a total amount of about SDR 3.4 billion across the three RST accounts – the loan account, deposit account, and reserve account. The new agreements with four members add critical resources that support the continued smooth operations of the RST.
Johanna Tiedemann
,
Olivier Bizimana
, and
Shant Arzoumanian
This paper assesses the stance of monetary policy in eleven Sub-Saharan African (SSA) emerging and frontier market economies. We estimate neutral real interest rates using a range of methodologies, and find a broadly declining trend in most economies since the Global Financial Crisis, consistent with patterns observed in advanced and major emerging market economies. We document significant heterogeneity in monetary policy stances—measured by the interest rate gap—even during common global shocks. We also examine the consistency between signals from the intended monetary policy stance and broader financial conditions. To this end, we construct financial conditions indices (FCIs) and analyze their relationship with interest rate gaps. We find that this relationship strengthens during periods of highly accommodative or restrictive monetary stances, particularly in economies that have adopted or are transitioning to inflation-targeting frameworks. Moreover, contractionary monetary shocks tighten financial conditions more in these economies than in those operating under other regimes.