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International Monetary Fund
This Note provides guidance for staff on the treatment and use of allocations of Special Drawing Rights (SDRs). It presents a consistent framework for IMF country teams to assess the macroeconomic implications of the SDR allocation at the country level, covering the following areas: • Statistical and accounting treatment. • General macroeconomic implications and advice. • Debt sustainability analysis. • Transparency and accountability. • Reserve management. • Implications for Fund-supported programs.
International Monetary Fund. Finance Dept., International Monetary Fund. Strategy, Policy, &, Review Department, and International Monetary Fund. Statistics Dept.
This paper provides background for a further round of discussions on the Fifteenth General Review of Quotas (hereafter 15th Review). The paper builds on work presented in previous staff papers and Directors’ views expressed in three meetings of the Committee of the Whole in September 2017 and February 2018. No proposals are presented at this stage, pending further Board guidance on possible approaches to narrowing the current differences of views.
International Monetary Fund. Finance Dept. and International Monetary Fund. Statistics Dept.
This paper provides background for an initial discussion under the Fifteenth General Review of Quotas (15th Review) in line with the work plan agreed by the Executive Board. It discusses issues related to further reforms of the quota formula and realigning quota shares, based on updated quota data through 2015. A companion paper, to be discussed separately, will address issues related to the size of the Fund and mix of quota and borrowed resources. Both these papers seek to facilitate initial discussions on some of the key issues for the 15th Review. No proposals are made at this stage, recognizing that further deliberations will be needed before the issues under discussion can begin to be narrowed down.
Mr. George M Kabwe, Elie Chamoun, Riaan van Greuning, Mowele Mohlala, and Ms. Julia Cardoso
Safeguards assessments are a key pillar of the risk management arrangements for IMF lending. Safeguards assessments aim to mitigate the risks of misuse of Fund resources and misreporting of program monetary data under Fund arrangements. Safeguards assessment reports are confidential and therefore the IMF Executive Board is provided with a periodic report on safeguards activities on a biennial basis, in addition to high-level summaries in member country staff reports on key findings and recommendations. This update on safeguards activity covers the period May 2017 to end-April 2019 (the period).
International Monetary Fund. Strategy, Policy, &, Review Department, and International Monetary Fund. Statistics Dept.
This note provides guidance on use of third-party indicators (TPIs) in Fund reports, in line with the policy endorsed by the Board in November 2017.
International Monetary Fund. Strategy, Policy, & and Review Department
The first data and statistics strategy for the Fund comes at a critical time. A fast-changing data landscape, new data needs for evolving surveillance priorities, and persisting data weaknesses across the membership pose challenges and opportunities for the Fund and its members. The challenges emerging from the digital revolution include an unprecedented amount of new data and measurement questions on growth, productivity, inflation, and welfare. Newly available granular and high-frequency (big) data offer the potential for more timely detection of vulnerabilities. In the wake of the crisis, Fund surveillance requires greater cross-country data comparability; staff and authorities face the complexity of integrating new data sources and closing data gaps, while working to address the weaknesses noted by the IEO Report (Behind the Scenes with Data at the IMF) in 2016. The overarching strategy is to move toward an ecosystem of data and statistics that enables the Fund and its members to better meet the evolving data needs in a digital world. It integrates Fund-wide work streams on data provision to the Fund for surveillance purposes, international statistical standards, capacity development, and data management under a common institutional objective. It seeks seamless access and sharing of data within the Fund, enabling cloud-based data dissemination to support data provision by member countries (e.g., the “global data commons”), closing data gaps with new sources including Big Data, and improving assessments of data adequacy for surveillance to help better prioritize capacity development. The Fund also will work with policymakers to understand the implications of the digital economy and digital data for the macroeconomic statistics, including new measures of welfare beyond GDP.
International Monetary Fund
Fund staff use indicators developed by other organizations as input into analysis in surveillance and, to a lesser extent, in program work. While the Fund has been able to rely on data and statistics provided by member countries and compiled internally, continued efforts to foster global economic and financial stability require staff to work with indicators drawn from numerous third-party compilers. These indicators of varied qualities are used to measure concepts such as business environment, competitiveness, and quality of governance. It is anticipated that staff will continue to draw on other institutions’ expertise and estimates. This practice is consistent with the Executive Board’s guidance in areas where internal expertise is lacking or limited. It also puts a premium on staff’s understanding of the third-party indicators (TPIs) used to add analytical value, avoid flawed conclusions and presentation, and support traction with the membership. This paper outlines a framework to promote best practice with respect to use of TPIs in Fund reports. The framework will apply to all documents that are subject to the Fund’s Transparency Policy. Staff are encouraged to follow similar guidelines for other Fund documents. It draws on lessons from the current practice in the Fund and other selected international organizations (IOs), and insights from the application of an adapted data quality assessment framework (DQAF) to a subset of TPIs commonly used by Fund staff. Common good practices across IOs include the emphasis on staff judgment, review, and consultation with stakeholders.