Gender

[Please note this report is only available in French] This technical assistance report documents the key phases of the scoping mission for the development of a macroeconomic model based on financial programming, conducted in Libreville from May 5 to 15, 2025, on behalf of the Ministry of Economy and Participations of Gabon. The mission undertook a comprehensive assessment of existing analytical tools and data quality, alongside delivering targeted training on financial programming and debt analysis. The exercise highlighted various areas to strengthen the current tools as well as organizational constraints to be addressed to improve performance. Building on these findings, a series of recommendations were formulated, endorsed by the authorities, and subsequently integrated into the project’s action plan. These recommendations propose a step-by-step strategy for the development of a customized macroeconomic model, fully integrated with a Debt Dynamics Tool (DDT), and supported by continuous capacity building and strengthened inter-institutional coordination, aimed at enhancing the robustness of economic analysis and fostering improved evidence-based decision-making processes.

In line with the framework for addressing excessive delays in the completion of Article IV consultations, the following table lists the IMF members for whom the Article IV consultation has been delayed by more than 18 months as of December 31, 2025.

Mozambique’s economy has slowed sharply since 2016 with two-thirds of the population below the poverty line. While over half a million young people enter the job market annually, job creation remains weak, as structural transformation has favored extractive industries (in particular, capital-intensive LNG projects) over manufacturing. Agriculture, employing three-quarters of the population, suffers from low productivity and limited access to inputs and finance. Informality dominates, accounting for about 95 percent of jobs. Human development indicators are among the world’s lowest, with fiscal pressures constraining social and development spending. To tackle Mozambique’s growth challenges, reforms must promote economic diversification, job-rich growth, agricultural modernization, improved governance, and expanded access to finance.

This paper describes the Quarterly Macro Forecasting Framework (QMFF), which is a novel approach to macroeconomic policy analysis and forecasting. At the core of this framework is a Quarterly Projection Model, with main behavioral equations quantified as deviations of real variables from their trends. The model comprises a simultaneous system of calibrated equations that cover the main sectors of the Financial Programming and Policies framework, as well as key accounting restrictions within and across sectors. By explicitly accounting for trends observed in real variables and relative prices, the framework ensures a balanced growth path and constant expenditure shares relative to nominal GDP. The QMFF is sufficiently flexible to be adapted to different monetary frameworks and exchange rate regimes. After describing the framework, the paper illustrates its implementation for policy analysis and forecasting on the case of Bosnia and Herzegovina. The empirical work with the model includes not only calibration but also testing the model’s dynamic and in-sample simulation properties.

Malaysia’s economy has shown notable resilience against global trade tensions and policy uncertainty, supported by strong domestic demand, a global tech-sector upcycle, and sound economic policies. Given the heightened global uncertainty, policy discussions centered on how Malaysia can sustain its resilience through enhancing macroeconomic buffers, navigating potential shocks, and advancing structural reforms to bolster domestic-driven and inclusive growth.

Selected Issues

This paper empirically evaluates the ability of current Large Language Models (LLMs) to analyze macrofinancial coverage in IMF Article IV staff reports, using human economists' assessments as a benchmark. We test several GPT models on reports from 2016-2024, assessing their performance on both qualitative ratings and binary questions. Our findings indicate that the latest models can meaningfully assist economists, achieving an average accuracy of 71-75% on ratings and an average exact match rate of 76-81% on binary questions in 2024 across advanced GPT models. However, we find that LLMs tend to assign higher, less-dispersed ratings than human experts and struggle with open-ended questions that require deep contextual judgment. The paper provides quantitative evidence on current LLM accuracy in this domain, explores the drivers of its performance, and discusses key limitations such as optimistic bias.

Following a request to the Caribbean Regional Technical Assistance Centre (CARTAC), a mission was held from July 7 to 10, 2025, in Belmopan and Belize City to assist the Belize Financial Services Commission (FSC) with prudential regulation and supervision of securities firms. The mission provided training on the prudential framework, potential supervisory approaches, and international standards concerning leveraged derivative contracts offered to retail investors. Supervisory materials were also developed. The mission found the prudential framework conceptually sound but identified opportunities for technical refinements. Key recommendations include developing a risk appetite for the securities sector, establishing conduct requirements for firms offering over-the-counter (OTC) derivative products to retail investors, enhancing compliance assessments, and strengthening staff training on technical matters. Subject to risk appetite and risk assessments, the report explores options for effective framework implementation.

Cadasters—records of land and property ownership—constitute an important pillar of a country’s institutional landscape by enabling the assignment of property rights. This paper examines the impact of cadasters on long-term economic growth by identifying a specific channel in this link: asset tangibility. It hypothesizes that the more a firm’s assets are tangible, the more relevant cadasters become. The analysis uses a cross-country dataset on cadasters together with granular data from industry panels over the last six decades. The results show that the development of cadasters fosters long-term growth, particularly in industries with high asset tangibility. Higher investment in those industries, resulting from stronger cadasters, contributes to this pattern. The growth impact of cadasters is more pronounced in (i) countries that lack strong cadasters, such as in Sub-Saharan Africa; and (ii) countries with typically more investment-conducive legal systems. The findings suggest that cadastral reforms can help stimulate investment and sustain long-term growth in many developing economies.