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June 2018

Q2 2018 update of World Development Indicators available

World Bank Data Team's picture

The World Development Indicators database has been updated. This is a regular quarterly update to 1,600 indicators and includes both new indicators and updates to existing indicators. 

Data for population and national accounts, including GDP and GNI-related indicators, have been released for countries and aggregates.

The methodology for presenting value added for the services sector has been revised, and financial intermediary services indirectly measured (FISIM) are presented separately. Historically, FISIM was used in the calculation of the “Services, etc” indicator. Starting with July 2018 update of the WDI, FISIM is presented as a separate series, where available. In addition, the “Final consumption expenditure, etc” and “Household consumption expenditure, etc” data included any existing statistical discrepancy between GDP according to production methodology and GDP according to expenditure methodology. Starting with this update, these two series will no longer be published. Instead, indicators for final consumption expenditure and household consumption expenditure are now available. Users can find the statistical discrepancy listed as a separate indicator. You can access the latest list of indicator additions, deletions, descriptions and code changes here. The methodology for calculating value added shares has also been updated.  
 
Other data that have been updated include FDI, tariffs, monetary and prices indicators, balance of payments, trade, health, military expenditure, air traffic, CPIA ratings, and fisheries. Purchasing Power Parities (PPP) have been updated for OECD and Eurostat countries to show the latest release. The country classification hierarchies and group aggregate data reflect the new fiscal year 2019 income classifications. Historical data have been revised as necessary.

Data can be accessed via various means including:

- The World Bank’s main multi-lingual and mobile-friendly data website, http://data.worldbank.org 
- The DataBank query tool: http://databank.worldbank.org which includes archived versions of WDI
Bulk download in XLS and CSV formats and directly from the API
 

Applications open for third round of funding for collaborative data innovation projects

World Bank Data Team's picture
Photo Credit: The Crowd and The Cloud


The Global Partnership for Sustainable Development Data and the World Bank Development Data Group are pleased to announce that applications are now open for a third round of support for innovative collaborations for data production, dissemination, and use. This follows two previous rounds of funding awarded in 2017 and earlier in 2018.

This initiative is supported by the World Bank’s Trust Fund for Statistical Capacity Building (TFSCB) with financing from the United Kingdom’s Department for International Development (DFID), the Government of Korea and the Department of Foreign Affairs and Trade of Ireland.

Scaling local data and synergies with official statistics

The themes for this year’s call for proposals are scaling local data for impact, which aims to target innovations that have an established proof of concept which benefits local decision-making, and fostering synergies between the communities of non-official data and official statistics, which looks for collaborations that take advantage of the relative strengths and responsibilities of official (i.e. governmental) and non-official (e.g.,private sector, civil society, social enterprises and academia) actors in the data ecosystem.

Official Statistics in a Post-Truth World

Haishan Fu's picture
Photo Credit:  2018 Edelman Trust Barometer Report

I've been thinking about the role of data and digital technology in today's information landscape. New platforms and technologies have democratized access to much of the world’s knowledge, but they’ve also amplified disinformation that affects public discourse. In this context, the official statistics community plays a critical role in bringing credible, evidence-based information to the public.
 
A “post-truth” society is not an inevitable state of affairs that we must accept; it's an unacceptable state of affairs that we must address. To do so, we need reliable data that are trusted by the public. Institutions like national statistical offices must go beyond their traditional data production remit to become a trusted, visible force for reason in people’s lives by building trust, embracing relevance, and communicating better.

If development data is so important, why is it chronically underfinanced?

Michael M. Lokshin's picture

Few will argue against the idea that data is essential for the design of effective policies. Every international development organization emphasizes the importance of data for development. Nevertheless, raising funds for data-related activities remains a major challenge for development practitioners, particularly for research on techniques for data collection and the development of methodologies to produce quality data.

If we focus on the many challenges of raising funds for microdata collected through surveys, three reasons stand out in particular: the spectrum of difficulties associated with data quality; the problem of quantifying the value of data; and the (un-fun) reality that data is an intermediate input.

Data quality

First things first – survey data quality is hard to define and even harder to measure. Every survey collects new information; it’s often prohibitively expensive to validate this information and so it’s rarely done. The quality of survey data is most often evaluated based on how closely the survey protocol was followed.

The concept of Total Survey Error sets out a universe of factors which condition the likelihood of survey errors (Weisbeg 2005). These conditioning factors include, among many other things: how well the interviewers are trained; whether the questionnaire was tested and piloted and to what degree; whether the interviewers’ individual profiles could affect the respondent answers, etc. Measuring some of these indicators precisely is effectively impossible—most of the indicators are subjective by nature. It may be even harder to separate the individual effects of these components in the total survey error.

Imagine you are approached with a proposal to conduct a cognitive analysis of your questionnaire. - How often were you bothered by the pain in the stomach over the last year? A cognitive psychologist will tell you that this is a badly formulated question: the definition of stomach varies drastically among the respondents; last year could be interpreted as last calendar year, 12 months back from now, or from January 1st until now; one respondent said: it hurt like hell, but it did not bother me, I am a Marine... (from a seminar by Gordon Willis)