As an integral part of the international community, the World Bank works closely with other international agencies, regional development banks, donors, and other partners to:
- Develop appropriate frameworks, guidance and standards of good practice for statistics.
- Build consensus and define internationally agreed indicators, such as indicators for the MDGs.
- Establish data exchange processes and methods.
- Help countries improve statistical capacity.
The World Bank offers technical assistance and financial support for statistical development to its member governments. Training and seminars are also provided. For more information on training, contact the Development Data Group or the World Bank Institute. Programs include:
The Virtual Statistical System (VSS) is an on-line resource that facilitates access to information on official statistics, including National Statistical Systems, specific statistical topics and learning modules. It functions as a portal by providing (a) reference materials on statistical themes, and (b) links to selected documents and organizations working on statistics. The VSS is a public good intending to reach people working on improving statistical capacity building of countries.
Alongside the creation of this knowledge platform, 10 e-Learning courses covering 100 topics with a total of about 200 lessons have been developed. they include management of statistical systems, labor market statistics and survey design, system of national accounts, business statistics and business registers.
The World Bank’s work to improve statistical capacity focuses on helping countries and the international community to better monitor Poverty Reduction Strategies and Millennium Development Goals, and enhance the Results Measurement System agreed for the 14th replenishment of the International Development Association. The overarching strategy is guided by a global action plan (commonly referred to as the Marrakech Action Plan for Statistics (MAPS) to improve national and international statistics. We provide financial and advisory services, in addition to tools to help our clients develop better statistical systems.
The Trust Fund for Statistical Capacity Building (TFSCB) was created in 1999 by the Development Data Group to provide grants to developing countries to support improvements in their statistical systems. This program is funded by several donors to provide small grants with a maximum implementation period of three years. Recently, emphasis has been placed on the preparation of national strategies for the development of statistics. As of 2008, the TFSCB has approved funding for more than 100 statistical projects, representing an investment in statistics of close to $22 million.
Through lending programs such as STATCAP, the World Bank helps developing countries finance investments to upgrade the capacity of their statistical systems. It is designed as a flexible instrument to meet the needs of countries at different levels of development. A key requirement for participation is that countries should have prepared a national strategy for the development of their statistical system.
International Comparison Program (ICP) is a global statistical initiative to collect internationally comparable price levels. These data are used to compute purchasing power parities (PPPs), which allow standards of living to be compared across countries. The 2005 round covered 146 economies, making it the largest international data collection exercise in the world.
At the beginning of each fiscal year, the World Bank Development Data Group provides a status report on the external debt of each country that is an active borrower. The report includes an assessment of the adequacy of debt-reporting arrangements and the nature of any inadequacies (e.g., lack of staff, data problems, inadequate administrative arrangements, simple neglect).
The Quarterly External Debt Database, jointly developed by the World Bank and the International Monetary Fund, brings together detailed external debt data that are published individually by countries that subscribe to the IMF’s Special Data Dissemination Standard (SDDS).
Jointly developed by the Bank for International Settlements, the International Monetary Fund (IMF), the Organization for Economic Cooperation and Development (OECD) and the World Bank, the Joint External Debt Hub (JEDH) brings together external debt data and selected foreign assets from international creditor/market and national debtor sources.
At the G8 Summit at Sea Island in 2004, heads of state recognized the important role remittances play in development, and they called for improvements in data on remittance flows in both sending and receiving countries. Since then, work has been ongoing to improve the data available to users, including data reported in the framework of balance of payments statistics. Since July 2008, improving data on international remittances has been included as a sub-theme within the framework of the Global Remittances Working Group set up by the World Bank. This page provides access to materials related to work to improve remittances data, including papers and presentations prepared for international meetings in Washington, D.C., in 2005 and 2009.
SDMX stands for Statistical Data and Metadata Exchange-the electronic exchange of statistical information. Its goal is to explore e-standards that could allow us to gain efficiency and avoid duplication of effort in our own work and possibly in the work of others in the field of statistical information.The BIS, ECB, EUROSTAT, IMF, OECD, UN, and the World Bank have joined together to focus on business practices in the field of statistical information that would allow more efficient processes for exchange and sharing of data and metadata within the current scope of our collective activities.
The Sponsoring Institutions created common (SDMX) technical and statistical standards and guidelines, together with an IT architecture and IT tools, to be used for the efficient exchange and sharing of statistical data and metadata.
Standardised file formats for data and metadata and standardised contents of these files are the pre-condition for the automated production, processing and exchange of SDMX data and metadata files between national and international statistical organisations.