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Business and Economics > Information Management

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Cover The IMF and Capacity Development: Evaluation Report 2022
The IMF and Capacity Development: Evaluation Report 2022
International Monetary Fund. Independent Evaluation Office

Abstract

Capacity development (CD) is a key function of the IMF, aiming to assist its member countries develop their institutional and human capacity to design and implement sound macroeconomic and financial policies. CD has been provided to all IMF member countries at some point, although it is directed mainly toward low- and middle-income countries. CD represents about one-third of the IMF’s administrative budget, having expanded substantially in the past decade. This evaluation assesses how effective the IMF has been in meeting the CD needs and expectations of recipient countries, and the Fund’s institutional objectives for CD, during 2012-20. It also provides an initial review of how IMF CD adapted to the challenges of the COVID-19 pandemic. The evaluation finds that IMF CD was relevant, valued, and broadly effective. Recipients, donors, and the wider membership saw IMF CD as being of the highest technical quality in the Fund’s core areas of expertise and generally perceived that it had become better tailored to recipient needs and circumstances. Overall, Fund CD has supported member countries in building the institutional capacity, in a very wide range of country circumstances. The IMF has also put substantial effort into integrating CD with surveillance and programs, which has in general enhanced its overall engagement with member countries. While recognizing these achievements, the evaluation also identifies a number of important shortcomings and challenges. The evaluation includes recommendations to enhance the strategic framework for, and prioritization of, CD; information available to Executive Directors and opportunities to exercise their oversight role; the integration of CD with surveillance and programs, particularly in the context of programs; CD ownership and delivery; the monitoring and evaluation framework; the sustainability of the CD funding model; and HR policies and incentives to maintain and develop the expertise in the Fund’s core and newly emerging CD topics.

Keywords:
Capacity Development; Technical Assistance; Training; Donors; Capacity Building; Institutional Capacity; IMF CD; CD strategy review; CD resource; CD ownership; CD work; COVID-19; Absorptive capacity; Climate change; Information and data management; Global; Middle East and Central Asia; Middle East; Central America; Southeast Asia; North Africa; Africa; Western Hemisphere; Europe; Asia and Pacific
Cover IMF Working Papers
Patterns in IMF Growth Forecast Revisions: A Panel Study at Multiple Horizons
Metodij Hadzi-Vaskov
,
Mr. Luca A Ricci
,
Alejandro Mariano Werner
, and
Rene Zamarripa
This paper investigates the performance of the IMF WEO growth forecast revisions across different horizons and country groups. We find that: (i) growth revisions in horizons closer to the actual are generally larger, more volatile, and more negative; (ii) on average, growth revisions are in the right direction, becoming progressively more responsive to the forecast error gap as horizons get closer to the actual year; (iii) growth revisions in systemic economies are relevant for growth revisions in all country groups; (iv) WEO and Consensus Forecast growth revisions are highly correlated; (v) fall-to-spring WEO revisions are more correlated with Consensus Forecasts revisions compared to spring-to-fall revisions; and (vi) across vintages, revisions for a given time horizon are not autocorrelated; within vintages, revisions tend to be positively correlated, suggesting perception of persistent short-term shocks.
Keywords:
growth revision; consensus forecast growth revision; WEO growth forecast; consensus forecasts revision; fall-to-spring WEO revision; Technology transfer; Terms of trade; Time series analysis; Vector autoregression; Europe; Caribbean
Cover IMF Working Papers
World Seaborne Trade in Real Time: A Proof of Concept for Building AIS-based Nowcasts from Scratch
Diego A. Cerdeiro
,
Andras Komaromi
,
Yang Liu
, and
Mamoon Saeed
Maritime data from the Automatic Identification System (AIS) have emerged as a potential source for real time information on trade activity. However, no globally applicable end-to-end solution has been published to transform raw AIS messages into economically meaningful, policy-relevant indicators of international trade. Our paper proposes and tests a set of algorithms to fill this gap. We build indicators of world seaborne trade using raw data from the radio signals that the global vessel fleet emits for navigational safety purposes. We leverage different machine-learning techniques to identify port boundaries, construct port-to-port voyages, and estimate trade volumes at the world, bilateral and within-country levels. Our methodology achieves a good fit with official trade statistics for many countries and for the world in aggregate. We also show the usefulness of our approach for sectoral analyses of crude oil trade, and for event studies such as Hurricane Maria and the effect of measures taken to contain the spread of the novel coronavirus. Going forward, ongoing refinements of our algorithms, additional data on vessel characteristics, and country-specific knowledge should help improve the performance of our general approach for several country cases.
Keywords:
port visit; machine-learning technique; data from the Automatic Identification System; port call; trade activity; Imports; Exports; Oil; Machine learning; Trade balance; Global
Cover IMF Research Bulletin
IMF Research Bulletin, Fall-Winter 2019
International Monetary Fund. Research Dept.
It has been two years since the trade tensions erupted and not only captured policymakers’ but also the research community’s attention. Research has quickly zoomed in on understanding trade war rhetoric, tariff implementation, and economic impacts. The first article in the December 2019 issue sheds light on the consequences of the recent trade barriers.
Keywords:
IRB; trade; debt measurement; exporter; policy session; firm; Mundell-Fleming Lecture; US-China trade tension; tariff factor; Exports; Tariffs; Infrastructure; Big data; Trade liberalization; Global; East Asia; North America; Sub-Saharan Africa; Europe; Africa; threshold ModelsHow; ship movement; TrajectoriesThe global financial crisis; Imports; Asia and Pacific
Cover IMF Research Bulletin
IMF Research Perspectives: Spring/Summer 2018
IMF Research Perspective (formerly published as IMF Research Bulletin) is a new, redesigned online newsletter covering updates on IMF research. In the inaugural issue of the newsletter, Hites Ahir interviews Valeria Cerra; and they discuss the economic environment 10 years after the global financial crisis. Research Summaries cover the rise of populism; economic reform; labor and technology; big data; and the relationship between happiness and productivity. Sweta C. Saxena was the guest editor for this inaugural issue.
Keywords:
IRB; big data wave; populism; product market reform; reform agenda; rise of populism; big data innovation; Big data; Global financial crisis of 2008-2009; Personal income; Output gap; Global; Europe
Cover Policy Papers
Overarching Strategy on Data and Statistics at the Fund in the Digital Age
International Monetary Fund. Strategy, Policy, &amp
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.
Keywords:
PP; director; data landscape; consumer sentiment; Fund staff estimate; data commons; data weakness; big data experiment; Big data; Data dissemination; Special Data Dissemination Standard (SDDS); Global