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Business and Economics > Information Management

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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 Working Papers
Big Data on Vessel Traffic: Nowcasting Trade Flows in Real Time
Mr. Serkan Arslanalp
,
Mr. Marco Marini
, and
Ms. Patrizia Tumbarello
Vessel traffic data based on the Automatic Identification System (AIS) is a big data source for nowcasting trade activity in real time. Using Malta as a benchmark, we develop indicators of trade and maritime activity based on AIS-based port calls. We test the quality of these indicators by comparing them with official statistics on trade and maritime statistics. If the challenges associated with port call data are overcome through appropriate filtering techniques, we show that these emerging “big data” on vessel traffic could allow statistical agencies to complement existing data sources on trade and introduce new statistics that are more timely (real time), offering an innovative way to measure trade activity. That, in turn, could facilitate faster detection of turning points in economic activity. The approach could be extended to create a real-time worldwide indicator of global trade activity.
Keywords:
WP; AIS data; trade statistics; cargo load indicator; trade activity; trade data; port call data; Trade balance; Trade in goods; Imports; Big data; Exports; Global; Europe
Cover IMF Working Papers
The Measurement and Macro-Relevance of Corruption: A Big Data Approach
Sandile Hlatshwayo
,
Anne Oeking
,
Mr. Manuk Ghazanchyan
,
David Corvino
,
Ananya Shukla
, and
Mr. Lamin Y Leigh
Corruption is macro-relevant for many countries, but is often hidden, making measurement of it—and its effects—inherently difficult. Existing indicators suffer from several weaknesses, including a lack of time variation due to the sticky nature of perception-based measures, reliance on a limited pool of experts, and an inability to distinguish between corruption and institutional capacity gaps. This paper attempts to address these limitations by leveraging news media coverage of corruption. We contribute to the literature by constructing the first big data, cross-country news flow indices of corruption (NIC) and anti-corruption (anti-NIC) by running country-specific search algorithms over more than 665 million international news articles. These indices correlate well with existing measures of corruption but offer additional richness in their time-series variation. Drawing on theory from the corporate finance and behavioral economics literature, we also test to what extent news about corruption and anti-corruption efforts affects economic agents’ assessments of corruption and, in turn, economic outcomes. We find that NIC shocks appear to negatively impact both financial (e.g., stock market returns and yield spreads) and real variables (e.g., growth), albeit with some country heterogeneity. On average, NIC shocks lower real per capita GDP growth by 3 percentage points over a two-year period, illustrating persistence in the effect of such shocks. Conversely, there is suggestive evidence that anti-NIC efforts appear to have a sustained positive macro impact only when paired with meaningful institutional strengthening, proxied by capacity development efforts.
Keywords:
WP; NIC shock; anti-corruption effort; NIC country; corruption; anti-corruption; capacity development; big data; text analysis; event study; reform program; NIC measure; NIC level; Auditing; 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 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
Cover IMF Working Papers
The Adjustment to Commodity Price Shocks in Chile, Colombia, and Peru
Mr. Francisco Roch
This paper presents a comparative analysis of the macroeconomic adjustment in Chile, Colombia, and Peru to commodity terms-of-trade shocks. The study is done in two steps: (i) an analysis of the impulse responses of key macroeconomic variables to terms-of-trade shocks and (ii) an event study of the adjustment to the recent decline in commodity prices. The experiences of these countries highlight the importance of flexible exchange rates to help with the adjustment to lower commodity prices, and staying vigilant in addressing depreciation pressures on inflation through tightening monetary policies. On the fiscal front, evidence shows that greater fiscal space, like in Chile and Peru, gives more room for accommodating terms-of-trade shocks.
Keywords:
WP; commodity price; commodity; Chile; Peru; Commodity Prices; Fiscal Policy; Flexible Exchange Rates; Colombia; Peru t; commodity exporters' emerging economies; oil price decline; large commodity price shock; shock to commodity price; country-specific commodity price index; propagation mechanism of commodity price shock; contribution of commodity price; effects of commodity-price fluctuation; Colombia t; adjustment to commodity price; Commodity price shocks; Current account; Technology transfer; Current account deficits; Sub-Saharan Africa
Cover Staff Discussion Notes
Big Data: Potential, Challenges and Statistical Implications
Cornelia Hammer
,
Ms. Diane C Kostroch
, and
Mr. Gabriel Quiros-Romero
Big data are part of a paradigm shift that is significantly transforming statistical agencies, processes, and data analysis. While administrative and satellite data are already well established, the statistical community is now experimenting with structured and unstructured human-sourced, process-mediated, and machine-generated big data. The proposed SDN sets out a typology of big data for statistics and highlights that opportunities to exploit big data for official statistics will vary across countries and statistical domains. To illustrate the former, examples from a diverse set of countries are presented. To provide a balanced assessment on big data, the proposed SDN also discusses the key challenges that come with proprietary data from the private sector with regard to accessibility, representativeness, and sustainability. It concludes by discussing the implications for the statistical community going forward.
Keywords:
SDN; big data data source; strategy action plan; innovation challenge; big data application; big data classification; big data project; IMF big data; private sector; project inventory; Big Data; Macroeconomic and Financial Statistics; Official Statistics; Data Quality; Surveillance; statistics big data strategy action plan; big data data analysis; big data network; big data revolution; big data use; Social networks; Financial statistics; Global