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.
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.
Over 1.25 million people are killed each year on the road. And 20-50 million others are seriously impacted by road traffic injuries. While most regions have seen a decrease in road-traffic related death rates, Sub-Saharan Africa and Middle East and North Africa still see over 20 deaths per 100,000 people every year.
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.
This year marks the fifth anniversary of the World Bank’s efforts to help countries launch their own open data initiatives, and harness the power of open data to benefit their citizens. A new report provides insights into how open data is benefitting countries, what strategies are working well, what could be improved.
The report provides the most comprehensive snapshot of Bank-funded open data activities to date. In the last five years, the Bank has provided technical assistance and funding for open data activities in over 50 countries, conservatively estimated at more than $50 million from a variety of sources. In many cases Bank funding has leveraged support from other partners or co-sponsorship by countries and other institutions. Within the Bank, the Trust Fund for Statistical Capacity Building (TFSCB) has been the most significant source of funding for open data. The TFSCB has financed over 20 projects in 16 countries, as well as 6 grants for regional and global activities.
Supporting over 45 countries with national and sector-specific open data
Support for open data has taken a variety of forms. To date, 45 Open Data Readiness Assessments (ODRAs) have been completed at national and sub-national levels, which have helped raise awareness and catalyze public and private efforts to advance open data within countries. There are now sector-specific ODRA tools for business, energy, and transport. The Bank has invested in a range of open data learning and knowledge products, including data literacy courses and the Open Data Toolkit, and collaborated with its global partners to support academic research, a series of regional conferences, and open data implementation. The report also found that these initial efforts have catalyzed longer-term project investments, i.e., IBRD loans and IDA credits, with open data implementation components in at least 14 countries.
Over the last 15 years, the Doing Business project has recorded nearly 3,200 reforms in 186 economies around the world. The area that's seen the greatest number of reforms is starting a business. Today, the time taken to start a new small or medium business has less than halved to an average of 20 days worldwide, compared with 52 in 2003. Read more in Doing Business 2018
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:
View the “about the data” section for a full description of the concepts and definitions in IDS.
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.
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”:
Official Development Assistance (ODA), which contains a grant element of 25% or more and is primarily intended for development.
Other Official Flows (OOF), where the grant element is under 25% and the the financing more commercial in nature.
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.
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.
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.
Africa has the world’s least developed weather, water, and climate observation network, with half of its surface weather stations not reporting accurate data. Hydrological and meteorological (“hydromet”) hazards are responsible for 90% of total disaster losses worldwide. Being able to understand, predict, and warn citizens about natural hazards and disasters drives the ability of governments to reduce economic risks and save lives.