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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.

The 2018 Atlas of Sustainable Development Goals: an all-new visual guide to data and development

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Download PDF (30Mb) / View Online

“The World Bank is one of the world’s largest producers of development data and research. But our responsibility does not stop with making these global public goods available; we need to make them understandable to a general audience.

When both the public and policy makers share an evidence-based view of the world, real advances in social and economic development, such as achieving the Sustainable Development Goals (SDGs), become possible.” - Shanta Devarajan

We’re pleased to release the 2018 Atlas of Sustainable Development Goals. With over 180 maps and charts, the new publication shows the progress societies are making towards the 17 SDGs.

It’s filled with annotated data visualizations, which can be reproducibly built from source code and data. You can view the SDG Atlas online, download the PDF publication (30Mb), and access the data and source code behind the figures.

This Atlas would not be possible without the efforts of statisticians and data scientists working in national and international agencies around the world. It is produced in collaboration with the professionals across the World Bank’s data and research groups, and our sectoral global practices.
 

Trends and analysis for the 17 SDGs

Artificial intelligence for smart cities: insights from Ho Chi Minh City’s spatial development

Ran Goldblatt's picture
Zoning by Land Parcel (Source: https://thongtinquyhoach.hochiminhcity.gov.vn)

It’s amazing to see what technology can do these days! Satellites provide daily images of almost every location on earth, and computers can be trained to process massive amounts of data generated from them to produce insightful analysis/information. This is just one of the demonstrations of artificial intelligence (AI). AI can go beyond just reading images captured from space, it can help improve lives overall.

For urban governance, machine learning and AI are increasingly used to provide near real-time analysis of how cities change in practice – for example, through the conversion of green areas into built-up structures. By teaching computers what to look for in satellite images, rapidly expanding sources of satellite data (public and commercial), together with machine learning algorithms, can be leveraged to quickly reveal how actual city development aligns with planning and zoning or which communities are most prone to flooding. This provides insights beyond the basic satellite snapshots and time-lapse visualizations that can now be readily generated for any areas of interest.

But the barriers to applying these technologies can still seem daunting for many cities around the world. It’s not always clear how exactly to analyze this massive amount of satellite data, nor how to get access to it.

How many companies are run by women, and why does it matter?

Masako Hiraga's picture
Also available in: Español | العربية | Français

Happy International Women’s Day! This is an important year to celebrate – from global politics to the Oscars last weekend, gender equality and inclusion are firmly on the agenda.

But outside movies and matters of government, we see the effects on gender equality every day, in how we live and work. One area we have data on comes from companies: what share of firms have a female CEO or top manager?

Only 1 in 5 firms worldwide have a female CEO or top manager, and it is more common among the smaller firms. While this does vary by around the world – Thailand and Cambodia are the only two countries where the data show more women running companies than men.

Better representation of women in business is important. It ensures a variety of views and ideas are represented, and when the top manager of a firm is woman, that firm is likely to have a larger share of permanent female workers.

Announcing Funding for 12 Development Data Innovation Projects

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Also available in: Français | 中文

We’re pleased to announce support for 12 projects which seek to improve the way development data are produced, managed, and used. They bring together diverse teams of collaborators from around the world, and are focused on solving challenges in low and lower middle-income countries in Sub-Saharan Africa, East Asia, Latin America, and South Asia.

Following the success of the first round of funding in 2016, in August 2017 we announced a $2.5M fund to support Collaborative Data Innovations for Sustainable Development. The World Bank’s Development Data group, together with the Global Partnership for Sustainable Development Data, called for ideas to improve the production, management, and use of data in the two thematic areas of “Leave No One Behind” and the environment. To ensure funding went to projects that solved real people’s problems, and built solutions that were context-specific and relevant to its audience, applicants were required to include the user, in most cases a government or public entity, in the project team. We were also looking for projects that have the potential to generate learning and knowledge that can be shared, adapted, and reused in other settings.

From predicting the movements of internally displaced populations in Somalia to speeding up post-disaster damage assessments in Nepal; and from detecting the armyworm invasive species in Malawi to supporting older people in Kenya and India to map and advocate for the better availability of public services; the 12 selected projects summarized below show how new partnerships, new methods, and new data sources can be integrated to really “put data to work” for development.

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.

2018 Innovation Fund Recipients

Chart: 100 Million People Pushed into Poverty by Health Costs in 2010

Tariq Khokhar's picture
Also available in: 中文 | Español | العربية | Français



Universal health coverage (UHC) means that all people can obtain the health services they need without suffering financial hardship. A new report produced by the World Bank and the World Health Organization, finds that health expenditures are pushing about 100 million people per year into “extreme poverty,” those who live on $1.90 or less a day; and about 180 million per year into poverty using a $3.10 per day threshold.

You can access the report, data, interactive visualizations, and background papers at: http://data.worldbank.org/universal-health-coverage/

International Debt Statistics 2018 shows BRICs doubled bilateral lending commitments to low-income countries in 2016 to $84 billion

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The 2018 edition of International Debt Statistics (IDS) has just been published.

IDS 2018 presents statistics and analysis on the external debt and financial flows (debt and equity) of the world’s economies for 2016. It provides more than 200 time series indicators from 1970 to 2016 for most reporting countries. To access the report and related products you can:

This year’s edition is released less than 10 months after the 2016 reference period, making comprehensive debt statistics available faster than ever before. In addition to the data published in multiple formats online, IDS includes a concise analysis of the global debt landscape, which will be expanded on in a series of bulletins over the coming year.

Why monitor and analyze debt?

The core purpose of IDS is to measure the stocks and flows of debts in low- and middle-income countries that were borrowed from creditors outside the country. Broadly speaking, stocks of debt are the current liabilities that require payment of principal and/or interest to creditors outside the country. Flows of debt are new payments from, or repayments to, lenders.

These data are produced as part of the World Bank’s own work to monitor the creditworthiness of its clients and are widely used by others for analytical and operational purposes. Recurrent debt crises, including the global financial crisis of 2008, highlight the importance of measuring and monitoring external debt stocks and flows, and managing them sustainably. Here are three highlights from the analysis presented in IDS 2018:

Net financial inflows to low-and middle income countries grew, but IDA countries were left behind

In 2016, net financial flows into low- and middle-income countries grew to $773 billion - a more than three-fold increase over 2015 levels, but still lower than levels seen between 2012 and 2014.

However, this trend didn’t extend to the world’s poorest countries. Among the group of IDA-only countries, these flows fell 34% to $17.6 billion - their lowest level since 2011. This fall was driven by drops in inflows from bilateral and private creditors.

Where does Chinese development finance go?

Tariq Khokhar's picture

This post looks at the recently updated “Global Chinese Official Finance Dataset” from research group AidData. The post is also available here as an R Notebook which means you see the code behind the charts and analysis.

Credit: A city park in Tianjin, China. Photo: Yang Aijun / World Bank
Credit: A city park in Tianjin, China. Photo: Yang Aijun / World Bank

China has provided foreign assistance to countries around the world since the 1950s. Since it’s not part of the DAC group of donors who report their activities in a standard manner, there isn’t an official dataset which breaks down where Chinese foreign assistance goes, and what it’s used for.

A team of researchers at AidData, in the College of William and Mary have just updated their “Chinese Global Official Finance” dataset. This is an unofficial compilation of over 4,000 Chinese-financed projects in 138 countries, from 2000 to 2014, based on a triangulation of public data from government systems, public records and media reports. The team have coded these projects with over 50 variables which help to group and characterize them.

Activity-level data on an increasingly important donor

This dataset is interesting for two reasons. First, China and other emerging donors are making an impact on the development finance landscape. As the Bank has reported in the past (see International Debt Statistics 2016), bilateral creditors are a more important source of finance than they were just five years ago. And the majority of these increases are coming from emerging donors with China playing a prominent role.

Second, this dataset’s activity-level data gives us a look at trends and allocations in Chinese bilateral finance which can inform further analysis and research. Organizations like the World Bank collect data on financial flows directly from government sources for our operational purposes, but we’re unable to make these detailed data publicly available. We compile these data into aggregate financial flow statistics presented from the “debtor perspective”, but they’re not disaggregated by individual counterparties or at an activity-level. So there can be value added from sources such as AidData’s China dataset.

A detailed view, but only part of the picture of all financial flows

However, this dataset has limitations. It only presents estimates of “official bilateral credits”. These are flows between two governments, and are just one part of the total financial flows coming from China. By contrast, the World Bank is able to integrate the granular data it collects from countries into the full set of financial flows to and from its borrowing countries. This situates official bilateral credit among the broader spectrum of providers of long-term financing (such as bondholders, financial intermediaries, and other private sector entities), sources of short-term debt (including movements in bank deposits), and equity investments (foreign direct and portfolio investments). This data integration leads to better quality statistics.

In short, AidData’s China dataset provides more detail on one type of financial flow, but is likely to be less reliable for a number of low-income countries. With these caveats in mind, I’ve done a quick exploration of the dataset to produce some summary statistics and give you an idea of what’s inside. 

Looking at foreign assistance by type of flow

First, let’s see what the trends in different types of foreign assistance look like. AidData researchers code the projects they’ve identified into three types of “flow”:

  1. Official Development Assistance (ODA), which contains a grant element of 25% or more and is primarily intended for development.
  2. Other Official Flows (OOF), where the grant element is under 25% and the the financing more commercial in nature.
  3. Vague Official Finance, where there isn’t enough information to assign it to either category.

Here are the total financial values of the projects in AidData’s dataset, grouped by flow type and year:

It looks like more Chinese finance is classed as OOF ($216bn in the period above) than ODA ($81bn), and that 2009 is a bit of an outlier. With this dataset, we next can figure out which countries are the top recipients of ODA and OOF, and also which sectors are most financed.

A crisis in learning: 9 charts from the 2018 World Development Report

Tariq Khokhar's picture
Also available in: Español | العربية | Français | 中文

There’s a crisis in learning. The quality and quantity of education vary widely within and across countries. Hundreds of millions of children around the world are growing up without even the most basic life skills.

The 2018 World Development Report draws on fields ranging from economics to neuroscience to explore this issue, and suggests improvements countries can make. You can get the full report here and to give you a flavor of what’s inside, I’ve pulled out a few of the charts and ideas that I found most striking while reading through it.

Each additional year of schooling raises earnings by 8-10 percent

 

The report sets out several arguments for the value of education. The clearest one for me? It’s a powerful tool for raising incomes. Each additional year of schooling raises an individual’s earnings by 8–10 percent, especially for women. This isn’t just because more able or better-connected people receive more education: “natural experiments” from a variety of countries - such as Honduras, Indonesia, Philippines, the U.S., and the U.K. - prove that schooling really does drive the increased earnings. More education is also linked with longer, healthier lives, and it has lasting benefits for individuals and society as a whole.

If you know what stakeholders really think, can you engage more effectively?

Svetlana Markova's picture

The World Bank Group surveys its stakeholders from country governments, development organizations, civil society, private sector, academia, and media in all client countries across the globe. Building a dialogue with national governments and non-state partners based of the data received directly from them is an effective way to engage stakeholders in discussions in any development area at any possible level.

Let's take the education sector as an example to see how Country Survey data might influence the engagement that the Bank Group has on this highly prioritized area of work.

When Country Surveys ask what respondents identify as the greatest development priority in their country, overall, education is perceived as a top priority (31%, N=263) in India.1 However, in a large country, stakeholder opinions across geographic locations may differ, and the Country Survey data can be 'sliced and diced' to provide insight into stakeholders' opinions based on their geography, gender, level of collaboration with the Bank Group, etc. In India the data analyzed at the state level shows significant differences in stakeholder perceptions of the importance of education. The survey results can be used as a basis for further in-depth analyses of client's needs in education in different states and, therefore, lead to more targeted engagement on the ground. In the case of the India Country Survey, the Ns at the geographical level may be too small to reach specific conclusions, but this example illustrates the possibility for targeted analysis.

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