Downloading the data is easy. At the microdata library, you'll see a screen that looks like this:
The World Development Indicators (WDI) is the World Bank’s premier compilation of international statistics on global development. Drawing from officially recognized sources and including national, regional, and global estimates, the WDI provides access to almost 1,600 indicators for 217 economies, with some time series extending back more than 50 years. The database helps users—analysts, policymakers, academics, and all those curious about the state of the world—to find information related to all aspects of development, both current and historical.
An annual World Development Indicators report was available in print or PDF format until last year. This year, we introduce the World Development Indicators website: a new discovery tool and storytelling platform for our data which takes users behind the scenes with information about data coverage, curation, and methodologies. The goal is to provide a useful, easily accessible guide to the database and make it easy for users to discover what type of indicators are available, how they’re collected, and how they can be visualized to analyze development trends.
So, what can you do on the new World Development Indicators website?
The indicators in the WDI are organized according to six thematic areas: Poverty and Inequality, People, Environment, Economy, States and Markets, and Global Links. Each thematic page provides an overview of the type of data available, a list of featured indicators, and information about widely used methodologies and current data challenges.
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.
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 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
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.
This blog is part of a series based on International Debt Statistics 2018.
The 2018 edition of International Debt Statistics (IDS 2018) which presents statistics and analysis on financial flows (debt and equity) for 123 low-and middle-income countries has just been released. One of the key observations of IDS 2018 is that net financial flows in 2016 to all developing countries witnessed a more than threefold increase over their 2015 level. This was driven entirely by net debt flows, which increased by $542 billion in 2016. Consequently, total external debt outstanding of all developing countries went up to $6.9 trillion, an increase of 4.1 percent over 2015. Interestingly, South Asia seems to deviate from this norm of IDS 2018.
South Asia is the only region that has shown a contraction in the total external debt outstanding in 2016. The total external debt stock of South Asia contracted by almost 2 percent as net debt flows into the region turned negative ($-7.7) for the first time in a decade. More specifically, this is the result of net long-term external debt flows turning negative (-$12.5 billion) implying that principal repayments by South Asia, on long-term external debt far exceeded disbursements.
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.
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:
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.
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.
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.
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.
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.
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”:
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.
Since 1970, the electricity generation capacity of Turkey has increased more than 30-fold to reach 70,000 MW in March 2015. In a country of nearly 80 million people, demand for electricity has risen about 7 percent annually in recent years, requiring steady efforts to expand the sources of reliable and clean power. Starting in the early 2000s, through a series of interlinked measures supported by the World Bank Group, the country has worked to meet this growing demand, while spurring private-sector investment and innovation. Read more.
The World Bank forecasts that global economic growth will strengthen to 2.7 percent in 2017 as a pickup in manufacturing and trade, rising market confidence, and stabilizing commodity prices allow growth to resume in commodity-exporting emerging market and developing economies. Growth in advanced economies is expected to accelerate to 1.9 percent in 2017, and growth in emerging market and developing economies as will rise to 4.1 percent this year from 3.5 percent in 2016. Read more and download Global Economic Prospects.
Now that the 2017 edition of International Debt Statistics (IDS) has been released, as a member of the team who put these statistics together, I thought I would look back at what the data tells us about financial flows into the Middle East and North Africa (MENA) region.
According to IDS 2015 data, net financial flows (debt and equity) to all low and middle income countries were only one third of their 2014 levels ($1,159 billion). In particular net debt flows turned negative (-$185 billion) for the first time since the 2008 financial crisis, while foreign direct investment (FDI) showed a marginal increase of $7 billion from $536 billion in 2014. These phenomena were observed in all regions but MENA.
The net debt inflows into the MENA region diverged from global trends. The inflows increased 84 percent from 2014. On the other hand, FDI recorded its lowest level since 2010.