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Business and Economics > Information Management

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Cover FinTech Notes
The Rise of Payment and Contracting Platforms
Mr. Tobias Adrian
and
Mr. Tommaso Mancini Griffoli
This Note explores the design and governance of platforms to enhance cross-border payments in line with public policy goals. While much innovation in recent years has more narrowly targeted end-user frictions, the vision in this paper is based on the mandate of the IMF, governed by the central banks and finance ministries of 190 member countries. Cross-border payments present the foundation for the global financial system, and its functioning is overseen by the IMF.
Keywords:
cross-border payments; platforms; central bank digital currencies; digital money; foreign exchange; settlement; programmability encryption; cross-border payment; note 2023/005; anatomy of payment; XC platform; platform operator; International reserves; Information and data management; Anti-money laundering and combating the financing of terrorism (AML/CFT); Global
Cover IMF Staff Country Reports
Solomon Islands: Selected Issues
International Monetary Fund. Asia and Pacific Dept
This Selected Issues paper on Solomon Island discusses big data and high frequency surveillance for Pacific Islands countries (PICs). Big data can be used to fill data gaps for PICs and the IMF can serve as a capacity-building and innovation hub. The estimators computed based on AIS data have been used as part of the surveillance dashboard by the Solomon Islands team and have been discussed with the authorities. Initiatives like the Arslanalp, Koepke, and Verschuur estimation exploit cross-country synergies and technical expertise available at the IMF to provide valuable inputs for both internal and external use. Other potential applications of the Automatic Identification System (AIS) can expand on this effort, for example, some single-country applications are monitoring of fishing vessels to estimate fishing rents from daily vessel schemes, monitoring export-related ships to monitor for piracy/exports misreporting, track tourism in real time, etc. Given the global nature of the AIS data, it can also be used to analyze global supply chains, trade disruptions from natural disasters, the effect of trade policies, etc.
Keywords:
Honiara port activity; export volume; D. trade flow; import volume; Island port activity; Imports; Exports; Trade balance; COVID-19; Agroindustries; Global; Pacific Islands
Cover IMF Working Papers
Derivative Margin Calls: A New Driver of MMF Flows
Maddalena Ghio
,
Linda Rousova
,
Dilyara Salakhova
, and
German Villegas Bauer
During the March 2020 market turmoil, euro area money-market funds (MMFs) experienced significant outflows, reaching almost 8% of assets under management. This paper investigates whether the volatility in MMF flows was driven by investors’ liquidity needs related to derivative margin payments. We combine three highly granular unique data sources (EMIR data for derivatives, SHSS data for investor holdings of MMFs and Refinitiv Lipper data for daily MMF flows) to construct a daily fund-level panel dataset spanning from February to April 2020. We estimate the effects of variation margin paid and received by the largest holders of EURdenominated MMFs on flows of these MMFs. The main findings suggest that variation margin payments faced by some investors holding MMFs were an important driver of the flows of EUR-denominated MMFs domiciled in euro area.
Keywords:
liquidity risk; money market funds; big data; interconnectedness; non-bank financial intermediaries.; EUR-denominated MMFs; derivative margin calls; MMF flow; variation margin payment; VM flow; Stocks; Liquidity; Mutual funds; Nonbank financial institutions; Pension spending; Global; IMF working paper research Department; derivatives reform; margin payment; Derivative markets
Cover IMF Working Papers
Building Statistical Capacity in Fragile and Conflict-Affected States
Yasmin Alem
and
Jacinta Bernadette Shirakawa
Based on internal data, this paper finds that the capacity development program of the IMF’s Statistics Department has prioritized technical assistance and training to fragile and conflict-affected states. These interventions have yielded only slightly weaker results in fragile states than in other states. However, capacity development is constantly needed to make up for the dissipation of progress resulting from insufficient resources that fragile and conflict-affected states allocate to the statistical function, inadequate inter-agency coordination, and the pervasive impact of shocks exogenous to the statistical system. Greater coordination with other capacity development providers and within the IMF can help partially overcome low absorptive capacity in fragile states. Statistical capacity development is more effective when it is tailored to countries’ level of fragility.
Keywords:
Capacity Development; Statistics; Data; Fragile States; Sta CD mission; government finance statistics manual; Sta CD delivery; Sta CD spending; World Bank methodology assessment; Income; Government finance statistics; External sector statistics; Information and data management; Middle East and Central Asia; Pacific Islands; Middle East; West Africa; Africa; Central Africa; Global
Cover IMF Working Papers
Using the Google Places API and Google Trends Data to Develop High Frequency Indicators of Economic Activity
Mr. Paul A Austin
,
Mr. Marco Marini
,
Alberto Sanchez
,
Chima Simpson-Bell
, and
James Tebrake
As the pandemic heigthened policymakers’ demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short—triggering stronger interest in real time data to provide early signals of turning points in economic activity. In this paper, we examine how data extracted from the Google Places API and Google Trends can be used to develop high frequency indicators aligned to the statistical concepts, classifications, and definitions used in producing official measures. The approach is illustrated by use of Google data-derived indicators that predict well the GDP trajectories of selected countries during the early stage of COVID-19. To this end, we developed a methodological toolkit for national compilers interested in using Google data to enhance the timeliness and frequency of economic indicators.
Keywords:
Reopening; COVID-19; High-Frequency Data; Business Register.; Google Trends data; Google data; high-frequency data; high frequency indicator; reopening Indicator; APIs; Big data; Manufacturing; Africa; Global
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 Staff Country Reports
Indonesia: Technical Assistance Report – Residential Property Price Statistics Capacity Development Mission
International Monetary Fund. Statistics Dept.
Technical Assistance Report – Residential Property Price Statistics Capacity Development Mission
Keywords:
ISCR; CR; price index; residential property price index; commercial property price index; mortgage data; rent price index; sales-price indexes; bank Indonesia CPPI; big data project; Price indexes; Land prices; Big data; Real estate prices; Real sector statistics
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
Cover IMF Working Papers
Productivity Growth, Technological Convergence, RandD, Trade, and Labor Markets: Evidence From the French Manufacturing Sector
Tehmina S. Khan
Total factor productivity (TFP) of 14 manufacturing sectors in France has kept up with that of the United States during 1980-2002 and remained well above that of the United Kingdom. Estimates using a dynamic panel equilibrium correction model indicate that sectors further behind the technological frontier experience faster productivity growth and that spending on research and development and trade with technologically advanced economies positively influences TFP growth, but not the speed of convergence. Conversely, TFP growth is negatively related to some key labor market variables, namely the replacement ratio and the ratio of the minimum wage to the median wage.
Keywords:
WP; replacement ratio; capital stock; Economic growth; Total factor productivity (TFP); Research and Development (R&D); Labor market institutions; Trade; Technological convergence; TFP level; TFP estimate; TFP easgrowth; TFP relative; TFP growth in the United States; Total factor productivity; Productivity; Labor markets; Technology transfer; Capacity utilization; Europe