Climate Change

This technical assistance assessed Uzbekistan’s public investment management practices and their climate sensitivity using the Public Investment Management Assessment (PIMA) with the Climate Module (C-PIMA). The assessment found that Uzbekistan has made important progress in strengthening public investment management since 2020, with the introduction of fiscal rules and improvements in project appraisal, selection, monitoring and management of PPP related fiscal risks. Uzbekistan’s public investment management institutions compare well with its peers, though there is room for improvement. In particular, planning and allocation processes remain fragmented with parallel investment procedures for domestic and externally financed projects. Implementing further reforms to improve strategic planning, align investment procedures across funding sources, enhance the PPP selection process and strengthen capital budgeting processes, including for maintenance, would be especially beneficial. Integrating climate considerations into existing processes would also enhance the resilience of public investment.

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.

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.

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.