This page is a collection of data visualizations from the World Bank using open data.
World Bank Blogs IBRD and IDA: Working for a World Free of Poverty. en Announcing Funding for 12 Development Data Innovation Projects <p> <img alt="" height="454" src="" title="" width="680" /></p> <p> 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.</p> <p> Following the <a href="" rel="nofollow">success of the first round of funding in 2016,</a> in August 2017 <a href="" rel="nofollow">we announced a $2.5M</a> fund to support <em>Collaborative Data Innovations for Sustainable Development.</em> 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.</p> <p> 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.</p> <p> <em>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. </em></p> <table> <tbody> <tr> <th> <img alt="" height="150" src="" title="" width="137" /></th> <th> <img alt="" height="150" src="" title="" width="383" /></th> <th> <img alt="" height="150" src="" title="" width="231" /></th> </tr> </tbody> </table> <h2> 2018 Innovation Fund Recipients</h2> <!--break--> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 1: Children on the Move: Using Satellite Data Analysis in Conflict/Famine-Affected Areas (Somalia &amp; Kenya)</h2> <p> This project aims to develop a scientifically tested method, based on the use of high resolution satellite data, to monitor and predict movements of Internally Displaced People (IDP) in Somalia and Kenya. It will seek to create standardized technical best practices for improving the identification, tracking, and assessment of IDPs with a particular focus on identifying at-risk and highly vulnerable women and children in famine and conflict-affected contexts.</p> <p> The team says: <em>“The flow, frequency and scale of how IDP households move around in Somalia is influenced by climate change and environmental degradation; violent conflict; and political, economic and food crises. Understanding these mobility patterns in real time, especially in mobile populations, can significantly improve our capacity to predict how and where people will move to and from enabling more efficient and effective interventions. “</em></p> <p> <strong>Collaborators</strong>: The Governance Lab at New York University (lead) and UNICEF.</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 2: Scale up of the Pastoral Early Warning System in the Sahel (Niger, Mali, Burkina Faso)</h2> <p> This project will scale up the Pastoral Early Warning System (PEWS) in the Sahel, which integrates satellite and weekly community survey data to track the impacts of climate change on pastoral conditions. Early warnings can help mitigate drought and inform decisions such as herders moving livestock during a long dry season.</p> <p> The team says: “<em>The West African Sahel is prone to droughts on an almost yearly basis. These droughts have devastating effects on communities: destroying livelihoods, exacerbating malnutrition and hunger. Pastoral herding communities are particularly vulnerable to these impacts since their livelihoods depend on grazing animals. In order to plan emergency responses or help make communities more resilient, decision-makers need access to fast and reliable information on droughts and their impact.”</em></p> <p> <strong>Collaborators:</strong> Action Contre la Faim (lead); Flemish Institute of Technology/ Vlaamse Instelling voor Technologisch Onderzoek (VITO); Regional Direction for Production of Animal Industries (DRPIA) (Gao, Mali); Regional Direction of Veterinary Services (DRSV) (Gao, Mali); Pastoral Development Direction, Ministry of Agriculture and Livestock (DDP) (Niger); Direction of Fish and Animal Resources (DRAH) (Burkina Faso); and Hoefsloot Spatial Solutions (HSS)</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 3 : Targeting Water Subsidies Based on New Data Generation Technologies (Angola)</h2> <p> This project will develop a tool that maps poverty by combining high resolution satellite and surveys in cost-effective and time-saving ways to better target water subsidies to those who need them most. The model will be calibrated using survey, geospatial, and other existing data. Such poverty mapping could have numerous other applications for resource allocation and service provision.</p> <p> The team says: <em>“What we see in our partner countries in Africa, is that subsides are equally distributed among wealthier and poorer households, and since funding is very limited, the lower income population doesn’t get enough subsidies (or doesn’t get it at all). At the end, we would expect to make water services for the poor—those identified using geostatistical data—affordable; while charging a non-subsidized price to the wealthier population”</em></p> <p> <strong>Collaborators:</strong> World Bank (lead); Government of Angola (Regulatory Institute for Water and Energy Services); and Global Water Challenge</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 4: Climate Change Mitigation Strategies for Dhaka (Bangladesh)</h2> <p> This project will generate recommendations for mitigating climate change impacts in the Dhaka mega-city by examining the association between land use change, population shift, and urban micro-climate through geospatial modeling. Policy implications will be assessed by analyzing the costs and benefits of introducing green space planning and reviewing existing land use regulations and planning codes and their implications for the urban micro-climate. In addition, the project will produce a methodology template so that it can be replicated elsewhere.</p> <p> The team says: “<em>A key project goal is the development of a new body of knowledge on urban microclimate, which will provide quality data and statistics to support necessary institutional and policy changes for mitigating climate change effects in urban environments.”</em></p> <p> <strong>Collaborators: </strong>Curtin University (Australia) (lead); Department of Meteorology, University of Dhaka; and Bangladesh Institute of International and strategic studies (BIISS)</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 5: Assessing Forest Functionality to Provide Water Services (New Caledonia, Wallis and Futuna, Vanuatu)</h2> <p> This project will assess the functioning levels of forest ecosystems in watersheds that supply water catchments to vulnerable island communities through an innovative and low-cost tool based on geospatial data. The team will scale up a new method that is replicable and relatively inexpensive in order to enable long-term monitoring and to produce outputs that are easily interpreted by users and decision-makers.</p> <p> The team says: <em>“Forests play a role in water regulation. Yes. That has been proven for many years now. But today, seeing the level of degradation of these forests and the effects of climate changes starting — are they still able to fulfill that role? For how long? How to ensure this for the upcoming decades? These are major issues for resources and land managers. So this diagnostic aims to give them some answers.”</em></p> <p> <strong>Collaborators: </strong>World Wide Fund for Nature (WWF) - France (lead); BLUECHAM SAS; New Caledonia Water Dept. (DAVAR); Wallis-et-Futuna Environment Service (SENV); and Govt. of Vanuatu Ministry of Lands and Natural Resources</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 6: Armyworm Research Using Remote-Sensing Methods ( Malawi)</h2> <p> The Fall Armyworm (FAW) are aggressive feeders that decimate crops, particularly maize and sorghum, potentially causing widespread food insecurity. This project will contribute to the efforts to eliminate the FAW threat by developing a tool that uses satellite imagery to detect FAW hotspots. The proposal is for a proof of concept, which if successful will be developed into a software tool to help public institutions, NGOs, and commercial farmers maximize the benefits of insecticide, manage yield losses, and adapt to climate change challenges.</p> <p> The team says: <em>“Fall Armyworm is an invasive pest, which was first recorded in West Africa in early 2016. Crop losses to date in Africa are estimated to be $13.3 billion, and maize yield losses are predicted at 30% in the 2017-18 season. As Fall Armyworm has only been present in Africa for a short period, its behaviour is not yet understood and research into management strategies is still at a very early stage.”</em></p> <p> <strong>Collaborators: </strong>Gorta-Self Help Africa (lead); Orbas Consulting, Training and Research Ltd; and University College Dublin School of Biosystems and Food Engineering</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 7: Bridging Development and Emergency Data Gaps for the Refugee Crisis (Uganda, Tanzania)</h2> <p> This project will engage refugees in mapping refugee camps, as well as non-camp communities, to capture data on population, built environment, and services, thereby allowing governments to improve service delivery and support to refugee communities. It will scale up a proven pilot and combine citizen-generated data with surveys and satellite imagery to address new sectors and locations.</p> <p> The team says: “<em>Over 1.4 million refugees from South Sudan have arrived in Uganda in the past two years, and more are arriving every day. Measuring access to key services (e.g. clean water sources) is nearly impossible to gauge, considering the rapid rate of cross-border forced migration into Uganda and Tanzania, and subsequent urban and rural growth. Our project bridges this critical data gap by increasing near real-time, comprehensive data production on base infrastructure and services where refugees reside. It can provide this data over large areas in Uganda and Tanzania, and does it in a sustainable way by building the capabilities of refugees and host communities to keep data up to date “</em></p> <p> <strong>Collaborators: </strong>Humanitarian OpenStreetMap Team (HOT) (lead); UNHCR Uganda; Uganda Office of the Prime Minister; MapUganda; YouthMappers; and MSF in Uganda</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 8: Participatory Mapping to Support Sustainable Energy for All in the Amazon (Ecuador)</h2> <p> This project will use earth observation data and citizen engagement to help deliver access to electricity to indigenous people in Ecuador and other remote areas of Amazonia. The project will consist of geospatial analysis of the study area, a participatory mapping approach, and the dissemination of results for transferability. Citizen participation will reduce costs and improve the accuracy of data production and dissemination, which benefits national statistics offices, but also planning offices in charge of electrification and development plans.</p> <p> The team says: <em>“Knowing the demand and technological choices of the indigenous population in the Amazon will help to accelerate energy supply and other basic services such as education and health. With our work we want to overcome obstacles which those who are left behind are facing but during all activities we also respect their opinions and needs.”</em></p> <p> <strong>Collaborators: </strong>Center for Remote Sensing of Land Surfaces (ZFL), University of Bonn (lead), AmazonGISnet, and Gov. of Ecuador Ministry of Electricity and Renewable Energy (MEER)</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 9: Geomapping Barriers to Urban Service Access in Older Age (Kenya and India)</h2> <p> This project aims to build a community data collection effort among older people in urban Kenya and India to better understand the spatial and social barriers to older residents in accessing services, particularly for the homeless or those living in informal settlements. Geotagged primary data will be collected at project locations on a range of older age-related spatial and social barriers. Data collection will be undertaken by data collectors, local organizations, and older people themselves.</p> <p> The team says: <em>“We know that older people are often marginalised from service provision and decision-making. To improve cities, service delivery and participatory decision-making, we must first understand the complex exclusion and marginalisation older people face. With this knowledge, we will train older people themselves to develop advocacy messaging based on data and to argue for tangible changes to service delivery and decision-making.”</em></p> <p> <strong>Collaborators: </strong>HelpAge International (lead); DataScience (Kenya); Karika Kenya; HelpAge India; and Humanitarian OpenStreetMap Team (HOT)</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 10: Digital Farm (Kenya, Tanzania, Uganda)</h2> <p> Digital Farm aims to help smallholder farmers respond to climate risks by integrating multiple sources of data and then presenting them with a personalized, accessible perspective on how to adapt and respond to specific challenges. The project intends to enable smallholders to engage with data in meaningful ways and transition from being passive recipients of data to active designers of the very data systems intended to benefit them.</p> <p> The team says:<em> “We are motivated by a commitment to collect, disseminate and use data in a different way – placing smallholder farmers at the center to create something with real value. Digital Farm empowers smallholder farmers with actionable data, enabling farmers to take action on their farms.”</em></p> <p> <strong>Collaborators: </strong>Producers Direct (previously known as Cafedirect Producers' Foundation) (lead); International Center for Tropical Agriculture (CIAT); Climate Edge; and WeFarm</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 11: Supporting Equitable Disaster Recovery Through Mapping (Nepal)</h2> <p> This project will create a new methodology for rapidly and accurately assessing post-disaster damage, shifting the current focus from the most damaged (disaster-induced losses) to the most in need (disaster-induced vulnerability). A reputable team of researchers and civil society organizations will integrate multiple remotely-sensed and crowd-sourced data sets into a comprehensive damage assessment. It will use the 2015 earthquake in Nepal as the case study.</p> <p> The team says: <em>“Everyone on the team was in some way involved or personally affected by the 2015 earthquake in Nepal. We want to make sure that the information used to make decisions – the prioritization of assistance, the allocations of funding, the reconstruction standards and process, properly reflects disaster-induced vulnerability and need.”</em></p> <p> <strong>Collaborators: </strong>Earth Observatory of Singapore (EOS), Nanyang Technological University (lead); Kathmandu Living Labs (KLL); Stanford Urban Resilience Initiative (SURI); Humanitarian OpenStreetMap Team (HOT); World Bank Global Facility for Disaster Risk Reduction (GFDRR) and World Bank Big Data Program; and NASA Jet Propulsion Lab and Advanced Rapid Imaging and Analysis Center (NASA-JPL/ARIA)</p> <h2 style="font-family: Sans-Serif; font-size: 120%; font-weight: bold;"> Activity 12: Estimating and Mapping Off-Grid Populations (Sierra Leone, Liberia)</h2> <p> This project seeks to increase the visibility of off-grid, hard-to-reach populations by providing information about the location and size of small settlements/villages through an online interface, taking advantage of high resolution satellite images, Volunteered Geographic Information (VGI), and modeling. The project will focus on small settlements within mangrove areas of six data-poor countries in West Africa that share similar landscape and livelihood characteristics and where there is an urgent need for locating and estimating coastal population in areas prone to sea-level rise. The project will subsequently establish partnerships in other regions (e.g. Amazon Basin).</p> <p> The team says: “<em>To date, there are no well-established methodologies to provide disaggregated information on hard-to-reach populations to governmental and non-governmental organizations. Addressing this gap through an easy-to-use, online interface could help in targeting development and adaptation planning for those populations”</em></p> <p> <strong>Collaborators:</strong> Center for International Earth Science Information Network (CIESIN), Columbia University (New York) (lead); Connectivity Lab at Facebook; and Wetlands International Africa</p> Mon, 29 Jan 2018 10:00:00 -0500 World Bank Data Team Over 1.25 Million People are Killed on the Road Each Year <p> <iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="400" id="datawrapper-chart-vnD6o" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["vnD6o"]={},window.datawrapper["vnD6o"].embedDeltas={"100":718,"200":503,"300":460,"400":443,"500":426,"600":400,"700":400,"800":400,"900":400,"1000":400},window.datawrapper["vnD6o"].iframe=document.getElementById("datawrapper-chart-vnD6o"),window.datawrapper["vnD6o"]["vnD6o"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["vnD6o"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("vnD6o"==b)window.datawrapper["vnD6o"]["datawrapper-height"][b]+"px"});</script></p> <p> 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.</p> <p> <a href="">A new report produced by the World Bank and funded by Bloomberg Philantrophies</a>&nbsp;estimates the social and economic benefits of reducing road traffic injuries&nbsp;in low- and middle-income countries​.</p> <!--break--> <p> <script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["vnD6o"]={},window.datawrapper["vnD6o"].embedDeltas={"100":744,"200":503,"300":460,"400":443,"500":426,"600":400,"700":400,"800":400,"900":400,"1000":400},window.datawrapper["vnD6o"].iframe=document.getElementById("datawrapper-chart-vnD6o"),window.datawrapper["vnD6o"]["vnD6o"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["vnD6o"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("vnD6o"==b)window.datawrapper["vnD6o"]["datawrapper-height"][b]+"px"});</script></p> <p> <iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="335" id="datawrapper-chart-s8M3Y" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe></p> <p> Low- and middle-income countries (LMICs) have the highest road-traffic related death rates. Despite having only about half the world’s motor vehicles, these countries now account for 90 percent of the worldwide road traffic deaths and non-fatal road crash injuries.</p> <p> <script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["s8M3Y"]={},window.datawrapper["s8M3Y"].embedDeltas={"100":594,"200":430,"300":404,"400":361,"500":361,"600":361,"700":335,"800":335,"900":335,"1000":335},window.datawrapper["s8M3Y"].iframe=document.getElementById("datawrapper-chart-s8M3Y"),window.datawrapper["s8M3Y"]["s8M3Y"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["s8M3Y"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("s8M3Y"==b)window.datawrapper["s8M3Y"]["datawrapper-height"][b]+"px"});</script></p> <p> <iframe id="datawrapper-chart-WZlIG" src="//" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="allowfullscreen" webkitallowfullscreen="webkitallowfullscreen" mozallowfullscreen="mozallowfullscreen" oallowfullscreen="oallowfullscreen" msallowfullscreen="msallowfullscreen" style="width: 0; min-width: 100% !important;" height="245"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["WZlIG"]={},window.datawrapper["WZlIG"].embedDeltas={"100":504,"200":340,"300":271,"400":271,"500":245,"600":245,"700":245,"800":219,"900":219,"1000":219},window.datawrapper["WZlIG"].iframe=document.getElementById("datawrapper-chart-WZlIG"),window.datawrapper["WZlIG"]["WZlIG"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["WZlIG"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("WZlIG"==b)window.datawrapper["WZlIG"]["datawrapper-height"][b]+"px"});</script></p> Mon, 08 Jan 2018 15:28:00 -0500 David Mariano Chart: 100 Million People Pushed into Poverty by Health Costs in 2010 <p> <iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="490" id="datawrapper-chart-C3fgS" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><br /> <br /> <script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["C3fgS"]={},window.datawrapper["C3fgS"].embedDeltas={"100":800,"200":619,"300":576,"400":533,"500":533,"600":533,"700":490,"800":490,"900":490,"1000":490},window.datawrapper["C3fgS"].iframe=document.getElementById("datawrapper-chart-C3fgS"),window.datawrapper["C3fgS"]["C3fgS"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["C3fgS"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("C3fgS"==b)window.datawrapper["C3fgS"]["datawrapper-height"][b]+"px"});</script></p> <p> Universal health coverage (UHC) means that all people can obtain the health services they need without suffering financial hardship. A <a href="">new report produced by the World Bank and the World Health Organization</a>, 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. </p> <p>You can access the report, data, interactive visualizations, and background papers at: <a href=" "></a> </p> <!--break--> Wed, 13 Dec 2017 12:00:00 -0500 Tariq Khokhar Chart: It's Never Been Faster to Start A Business <iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="415" id="datawrapper-chart-yXmDW" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["yXmDW"]={},window.datawrapper["yXmDW"].embedDeltas={"100":566,"200":482,"300":440,"400":440,"500":415,"600":415,"700":415,"800":415,"900":415,"1000":415},window.datawrapper["yXmDW"].iframe=document.getElementById("datawrapper-chart-yXmDW"),window.datawrapper["yXmDW"]["yXmDW"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["yXmDW"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("yXmDW"==b)window.datawrapper["yXmDW"]["datawrapper-height"][b]+"px"});</script> <p> 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 <a href="">Doing Business 2018</a></p> <!--break--> Tue, 31 Oct 2017 10:15:00 -0400 Tariq Khokhar International Debt Statistics 2018 shows BRICs doubled bilateral lending commitments to low-income countries in 2016 to $84 billion <div> <a href=""><img alt="" height="255" src="" style="float:right" title="" width="207" /></a></div> The <a href="">2018 edition of International Debt Statistics</a> (IDS) has just been published. <p> 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:</p> <ul> <li> Download the full publication (<a href="">PDF</a>)</li> <li> <a href="">Download or query the database</a></li> <li> Visit the <a href="">IDS 2018 Products Page</a></li> <li> Access the <a href="">statistical tables</a></li> <li> Visit <a href="">the debt portal</a> for a range of related content</li> <li> View the “<a href="">about the data</a>” section for a full description of the concepts and definitions in IDS.</li> </ul> <p> 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.</p> <h2 style="font-family: Sans-Serif; font-size: 140%; font-weight: bold;"> Why monitor and analyze debt?</h2> <p> 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.</p> <p> 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:</p> <h2 style="font-family: Sans-Serif; font-size: 140%; font-weight: bold;"> Net financial inflows to low-and middle income countries grew, but IDA countries were left behind</h2> <p> In 2016, net financial flows into low- and middle-income countries grew to $773&nbsp;billion - a more than three-fold increase over 2015 levels, but still lower than levels seen between 2012 and 2014.</p> <p> <iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="500" id="datawrapper-chart-wAR1x" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["wAR1x"]={},window.datawrapper["wAR1x"].embedDeltas={"100":919,"200":651,"300":567,"400":542,"500":525,"600":500,"700":500,"800":500,"900":500,"1000":500},window.datawrapper["wAR1x"].iframe=document.getElementById("datawrapper-chart-wAR1x"),window.datawrapper["wAR1x"]["wAR1x"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["wAR1x"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("wAR1x"==b)window.datawrapper["wAR1x"]["datawrapper-height"][b]+"px"});</script></p> <p> However, this trend didn’t extend to the world’s poorest countries. Among the <a href="">group of IDA-only</a> 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.</p> <!--break--> <p> Most IDA-only countries remain heavily dependent on official, concessional sources of financing. But in recent years, bond issuances and other private sources of financing have accounted for an important share of inflows. This largely came to a halt in 2016 as tighter market conditions and credit rating downgrades curtailed market access and deterred commercial bank lenders.</p> <p> Net inflows from private creditors collapsed, falling to $1.7&nbsp;billion from $7.7 billion in 2015. This downturn in financing from private creditors was exacerbated by a 24&nbsp;percent fall in inflows from bilateral creditors, but the increase in new bilateral loan commitments suggests this may only be temporary.</p> <p> <iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="459" id="datawrapper-chart-hNh0C" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["hNh0C"]={},window.datawrapper["hNh0C"].embedDeltas={"100":694,"200":543,"300":501,"400":501,"500":459,"600":459,"700":459,"800":459,"900":459,"1000":459},window.datawrapper["hNh0C"].iframe=document.getElementById("datawrapper-chart-hNh0C"),window.datawrapper["hNh0C"]["hNh0C"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["hNh0C"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("hNh0C"==b)window.datawrapper["hNh0C"]["datawrapper-height"][b]+"px"});</script></p> <h2 style="font-family: Sans-Serif; font-size: 140%; font-weight: bold;"> A doubling of bilateral lending, driven by BRICs, notably China</h2> <p> New loan commitments from bilateral creditors to low- and middle-income more than doubled in 2016 to $84 billion. This rise was driven by financing from other low- and middle-income countries, primarily the BRICs, and notably China with its “One Belt One Road” initiative to build an integrated international economic corridor encompassing more than 60 countries in various regions.</p> <h2 style="font-family: Sans-Serif; font-size: 140%; font-weight: bold;"> Foreign direct investment fell to its lowest level in 8 years</h2> <p> Traditionally, FDI has been the largest and least volatile component of external financial flows to low- and middle-income countries but 2016 showed that it is not immune to adverse developments in the global economy. FDI inflows fell 10&nbsp;percent to $481 billion - a level not seen since 2009.</p> <p> As widely reported, this decline reflected fragility of the global economy, persistent weak aggregate demand, sluggish growth in some commodity-exporting countries, and a slump in profits earned by multilateral enterprises; factors that outweighed the positive benefits from continued improvements in business and regulatory environments and burgeoning domestic markets in many low- and middle-income countries.</p> <h2 style="font-family: Sans-Serif; font-size: 140%; font-weight: bold;"> Compiling, curating and publishing comprehensive, high-quality debt statistics</h2> <p> While the dissemination format has changed over the years, the core purpose of these statistics continues to be the coordinated and comprehensive measurement of stocks and flows of the external debt of developing countries. They are used by client governments, economists, investors, financial consultants, academics, bankers, and a broad spectrum of the development community.</p> <p> The new IDS format includes aggregate tables detailing the debtor and creditor composition, maturity structure, and debt burden, in relation to GNI; export earnings for each country and relevant regional and income groups; and a user guide.</p> <p> You can look forward to more IDS 2018&nbsp;content here on the Data Blog over the coming months, and on <a href="">@worldbankdata</a> on Twitter. If you have any questions related to IDS or our other data products, please visit our <a href="">Data Helpdesk.</a></p> Tue, 24 Oct 2017 16:00:00 -0400 World Bank Data Team Where does Chinese development finance go? <script src=""></script><meta name="viewport" content="width=device-width, initial-scale=1" /> <link href="" rel="stylesheet" /><script src=""></script><script src=""></script><script src=""></script><script src=""></script><script src=""></script> <link href="" rel="stylesheet" /><script src=""></script> <link href="" rel="stylesheet" /><script src=""></script> <style type="text/css">code{white-space: pre;} </style> <style type="text/css">pre:not([class]) { background-color: white; } </style> <script type="text/javascript"> if (window.hljs && document.readyState && document.readyState === "complete") { window.setTimeout(function() { hljs.initHighlighting(); }, 0); } </script> <style type="text/css">h1 { font-size: 34px; } h1.title { font-size: 38px; } h2 { font-size: 30px; } h3 { font-size: 24px; } h4 { font-size: 18px; } h5 { font-size: 16px; } h6 { font-size: 12px; } .table th:not([align]) { text-align: left; } </style> <style type="text/css">.main-container { max-width: 940px; margin-left: auto; margin-right: auto; } code { color: inherit; background-color: rgba(0, 0, 0, 0.04); } img { max-width:100%; height: auto; } .tabbed-pane { padding-top: 12px; } button.code-folding-btn:focus { outline: none; } </style> <div class="container-fluid main-container"> <!-- tabsets --><script> $(document).ready(function () { window.buildTabsets("TOC"); }); </script><!-- code folding --> <style type="text/css">.code-folding-btn { margin-bottom: 4px; } </style> <script> $(document).ready(function () { window.initializeCodeFolding("hide" === "show"); }); </script> <p> <em>This post looks at the recently updated <a href="">“Global Chinese Official Finance Dataset”</a> from research group AidData. The post is&nbsp;<a href="">also available here</a> as an <a href="">R Notebook</a> which means you see the code behind the charts and analysis.</em></p> <div style="text-align:center"> <figure class="image" style="display:inline-block"> <img alt="Credit: A city park in Tianjin, China. Photo: Yang Aijun / World Bank" height="400" src="" title="" width="600" /> <figcaption> <em>Credit: A city park in Tianjin, China. Photo: Yang Aijun / World Bank</em></figcaption> </figure> </div> <p> China has provided foreign assistance to countries around the world since the 1950s. Since it’s not part of the <a href="">DAC group of donors</a> who report their activities in a <a href="">standard manner</a>, there isn’t an official dataset which breaks down where Chinese foreign assistance goes, and what it’s used for.</p> <p> A team of researchers at <a href="">AidData</a>, in the <a href="">College of William and Mary</a> have just updated their <a href="">“Chinese Global Official Finance”</a> 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.</p> <div class="section level4" id="activity-level-data-on-an-increasingly-important-donor"> <h4> Activity-level data on an increasingly important donor</h4> <p> 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 <a href=";isAllowed=y">International Debt Statistics 2016</a>), 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.</p> <p> 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.</p> </div> <div class="section level4" id="a-detailed-view-but-only-part-of-the-picture-of-all-financial-flows"> <h4> A detailed view, but only part of the picture of all financial flows</h4> <p> 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 <a href="">full set of financial flows</a> 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.</p> <p> 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.&nbsp;</p> </div> <div class="section level4" id="looking-at-foreign-assistance-by-type-of-flow"> <h4> Looking at foreign assistance by type of flow</h4> <p> 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”:</p> <ol style="list-style-type: decimal"> <li> <strong>Official Development Assistance (ODA)</strong>, which contains a grant element of 25% or more and is primarily intended for development.</li> <li> <strong>Other Official Flows (OOF)</strong>, where the grant element is under 25% and the the financing more commercial in nature.</li> <li> <strong>Vague Official Finance</strong>, where there isn’t enough information to assign it to either category.</li> </ol> <p> Here are the total financial values of the projects in AidData’s dataset, grouped by flow type and year:</p> <p> <img alt="" src="" style="display: block; margin: auto;" title="" width="1350" /></p> <p> 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.</p> <!--break--> <p> But first, let’s take advantage of the activity-level breakdown to see what accounts for the spike in 2009. At a guess, it’s going to be some large individual projects coded that year, so let’s look for OOF activities in 2009 which were &gt; $10bn:</p> <table class="table table-striped table-hover" style="margin-left: auto; margin-right: auto;"> <caption> OOF Projects in 2009 &gt; $10bn</caption> <thead> <tr> <th style="text-align:right;"> ID</th> <th style="text-align:left;"> Title/Description</th> <th style="text-align:right;"> Amount</th> </tr> </thead> <tbody> <tr> <td style="text-align:right;"> 43012</td> <td style="text-align:left;"> China Development Bank to offer loans totaling 25 billion USD in to Russian Roseneft and Transneft (linked to project #43069)</td> <td style="text-align:right;"> 13.6</td> </tr> <tr> <td style="text-align:right;"> 43069</td> <td style="text-align:left;"> Roseneft takes out loan of 10 billion USD out of available 15 from China Development Bank (linked to #43012)</td> <td style="text-align:right;"> 20.4</td> </tr> </tbody> </table> <p> <br /> It looks like part of the jump can be explained by two large projects involving Russian energy firms Transneft and Roseneft - they’re also referenced in this 2009 Reuters article about <a href="">China loaning Russia $25 billion to access to 20 years of oil.</a></p> </div> <div class="section level4" id="who-are-the-top-recipients-of-chinese-oda-and-oof"> <h4> Who are the top recipients of Chinese ODA and OOF?</h4> <p> Switching back to an aggregate view - which countries have received the most ODA and OOF in the 15 years the dataset covers? We can aggregate total project values by flow type and look at the top 10 countries for each type of flow:</p> <p> <img alt="" src="" style="display: block; margin: auto;" title="" /><img alt="" src="" style="display: block; margin: auto;" title="" /><br /> This again shows the relative difference in size of ODA vs OOF but also has me asking some more questions - what are the Chinese ODA flows to Cuba? When we list them out, it looks like the majority of the $6.7bn figure above is debt forgiveness recorded in 2011.</p> <table> <caption> ODA Projects Cuba 2000-2014</caption> <thead> <tr class="header"> <th align="right"> ID</th> <th align="left"> Title/Description</th> <th align="right"> Year</th> <th align="right"> Amount</th> </tr> </thead> <tbody> <tr class="odd"> <td align="right"> 36186</td> <td align="left"> China reschedules $7.2 million Cuban debt</td> <td align="right"> 2008</td> <td align="right"> 9.9</td> </tr> <tr class="even"> <td align="right"> 36187</td> <td align="left"> China donates cash and materials for Cuban hurricane relief</td> <td align="right"> 2008</td> <td align="right"> 11.0</td> </tr> <tr class="odd"> <td align="right"> 39195</td> <td align="left"> China forgives US$ 6 billion worth of Cuban Debt</td> <td align="right"> 2011</td> <td align="right"> 6659.9</td> </tr> <tr class="even"> <td align="right"> 39776</td> <td align="left"> China donates 400,000 USD for Hurricane Sandy Relief</td> <td align="right"> 2012</td> <td align="right"> 0.4</td> </tr> </tbody> </table> </div> <div class="section level4" id="which-sectors-receive-the-most-investment-via-oda-or-oof"> <h4> Which sectors receive the most investment via ODA or OOF?</h4> <p> Finally, let’s take a look by sector. The AidData team have coded projects using <a href="">DAC Sector Codes</a> and we can look at the relative allocation of resources across these by flow type:</p> <p> <img alt="" src="" style="display: block; margin: auto;" title="" /><img alt="" src="" style="display: block; margin: auto;" title="" /></p> <p> This exploration shows the kind of information in AidData’s <a href="">“Chinese Global Official Finance”</a> dataset. While offering only a partial, unofficial look at the country’s bilateral financial flows, it’s a detailed look at the activities of an increasingly prominent donor.</p> </div> </div> <!--break--><script> // add bootstrap table styles to pandoc tables function bootstrapStylePandocTables() { $('tr.header').parent('thead').parent('table').addClass('table table-condensed'); } $(document).ready(function () { bootstrapStylePandocTables(); }); </script><!-- dynamically load mathjax for compatibility with self-contained --><script> (function () { var script = document.createElement("script"); script.type = "text/javascript"; script.src = ""; document.getElementsByTagName("head")[0].appendChild(script); })(); </script> Wed, 18 Oct 2017 11:00:00 -0400 Tariq Khokhar Chart: An Over 30-Fold Increase in Turkey's Power Generation Capacity <iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="450" id="datawrapper-chart-S5gJ8" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//" style="width: 0; min-width: 100% !important;" webkitallowfullscreen="webkitallowfullscreen"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["S5gJ8"]={},window.datawrapper["S5gJ8"].embedDeltas={"100":696,"200":543,"300":518,"400":475,"500":475,"600":475,"700":450,"800":450,"900":450,"1000":450},window.datawrapper["S5gJ8"].iframe=document.getElementById("datawrapper-chart-S5gJ8"),window.datawrapper["S5gJ8"]["S5gJ8"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["S5gJ8"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("S5gJ8"==b)window.datawrapper["S5gJ8"]["datawrapper-height"][b]+"px"});</script> <p> 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. <a href="">Read more.</a><br /> &nbsp;</p> <!--break--> Fri, 06 Oct 2017 13:00:00 -0400 Tariq Khokhar Chart: Globally, The Number of People Without Access to Electricity is Falling <iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="500" id="datawrapper-chart-nTPBl" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//" webkitallowfullscreen="webkitallowfullscreen" width="100%"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["nTPBl"]={},window.datawrapper["nTPBl"].embedDeltas={"100":726,"200":592,"300":550,"400":525,"500":525,"600":525,"700":500,"800":500,"900":500,"1000":500},window.datawrapper["nTPBl"].iframe=document.getElementById("datawrapper-chart-nTPBl"),window.datawrapper["nTPBl"]["nTPBl"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["nTPBl"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("nTPBl"==b)window.datawrapper["nTPBl"]["datawrapper-height"][b]+"px"});</script> <p> Electrification has expanded in all regions and in both urban and rural areas. South Asia has driven global declines, with just 28 percent of rural dwellers lacking electricity in 2014. In most regions, electrification has outpaced population growth. An exception is Sub-­Saharan Africa: 134 million more people in rural areas lacked access in 2014 than in 1994.&nbsp;Read more in the&nbsp;<a href="">2017 Atlas of Sustainable Development Goals</a>&nbsp;and in a new feature on "<a href="">Solar Powers India's Clean Energy Revolution</a>"</p> <p> &nbsp;</p> <!--break--> Fri, 30 Jun 2017 16:00:00 -0400 Tariq Khokhar Chart: Globally, Over 1 Billion People Lack Access to Electricity <iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="450" id="datawrapper-chart-QFnbu" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//" webkitallowfullscreen="webkitallowfullscreen" width="100%"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["QFnbu"]={},window.datawrapper["QFnbu"].embedDeltas={"100":651,"200":517,"300":475,"400":475,"500":475,"600":450,"700":450,"800":450,"900":450,"1000":450},window.datawrapper["QFnbu"].iframe=document.getElementById("datawrapper-chart-QFnbu"),window.datawrapper["QFnbu"]["QFnbu"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["QFnbu"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("QFnbu"==b)window.datawrapper["QFnbu"]["datawrapper-height"][b]+"px"});</script> <p> In 2014, around 15 percent of the world’s population, or 1.1 billion had no access to electricity. Nearly half were in rural areas of Sub-Saharan Africa and around a third were rural dwellers in South Asia. Just four countries - India, Nigeria, Ethiopia and Bangladesh are home to about half of all people who lack access to electricity.&nbsp;Read more in the&nbsp;<a href="">2017 Atlas of Sustainable Development Goals</a>&nbsp;and in a new feature on "<a href="">Solar Powers India's Clean Energy Revolution</a>"</p> <p> &nbsp;</p> <!--break--> Fri, 30 Jun 2017 16:00:00 -0400 Tariq Khokhar Chart: Global Growth Forecast to Reach 2.7 Percent in 2017 <iframe allowfullscreen="allowfullscreen" allowtransparency="true" frameborder="0" height="400" id="datawrapper-chart-tXBpX" mozallowfullscreen="mozallowfullscreen" msallowfullscreen="msallowfullscreen" oallowfullscreen="oallowfullscreen" scrolling="no" src="//" webkitallowfullscreen="webkitallowfullscreen" width="100%"></iframe><script type="text/javascript">if("undefined"==typeof window.datawrapper)window.datawrapper={};window.datawrapper["tXBpX"]={},window.datawrapper["tXBpX"].embedDeltas={"100":596,"200":471,"300":427,"400":427,"500":427,"600":400,"700":400,"800":400,"900":400,"1000":400},window.datawrapper["tXBpX"].iframe=document.getElementById("datawrapper-chart-tXBpX"),window.datawrapper["tXBpX"]["tXBpX"].embedDeltas[Math.min(1e3,Math.max(100*Math.floor(window.datawrapper["tXBpX"].iframe.offsetWidth/100),100))]+"px",window.addEventListener("message",function(a){if("undefined"!=typeof["datawrapper-height"])for(var b in["datawrapper-height"])if("tXBpX"==b)window.datawrapper["tXBpX"]["datawrapper-height"][b]+"px"});</script> <p> The World Bank <a href="">forecasts that global economic growth will strengthen to 2.7 percent in 2017</a> 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. <a href="">Read more</a>&nbsp;and download <a href="">Global Economic Prospects</a>.</p> <!--break--> Mon, 05 Jun 2017 10:00:00 -0400 Tariq Khokhar