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Middle East and Central Asia > Qatar

You are looking at 1 - 10 of 12 items for :

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Cover IMF Staff Country Reports
Peru: Technical Assistance Report-Consumer Price Index Mission
International Monetary Fund. Statistics Dept.
This technical assistance mission collaborated with the National Institute of Statistics and Informatics in Peru to incorporate big data methods into compilation of the consumer price index (CPI). This includes both prices ingested from the websites of large retailers and data recorded through in-store checkout scanners.
Keywords:
consumer price index mission; scanner data; staff team of the International Monetary Fund; World Bank staff; data provider; Consumer price indexes; Data collection; Data processing; Big data
Cover IMF Staff Country Reports
Republic of Latvia: Selected Issues
International Monetary Fund. African Dept.
Selected Issues
Keywords:
term premium; premium in the Baltic; staff team of the International Monetary Fund; nominal NPLS; Latvia's lending rate; Loans; Credit; Big data; Nonperforming loans; Bank credit; Baltics
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
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