Hurricanes Irma and Maria recently devastated the Caribbean region. Infrastructure in Dominica was severely damaged and the country suffered a total loss of its annual agricultural production. The entire population of Barbuda had to be evacuated to Antigua and other islands. Estimates by the World Bank indicate that Irma caused damages equivalent to 14 percent of GDP for Antigua and Barbuda, and up to 200 percent of GDP for Dominica. The increasing frequency of hurricanes poses a threat to the economic development and wellbeing of 40 million people living in the region.
The World Bank and other development institutions acted quickly by offering support to assess damages and losses, respond to the disaster, and assist with recovery by delivering financial packages and supporting emergency operations. However, in the longer term, the focus is on building the resilience of these small island states to natural disasters.
Data: critical for responding to disasters, but also vulnerable to them
Systems of national statistics can provide critical information about the extent of a disaster, help guide recovery operations, and assess the preparedness of countries to future shocks. At the same time, the reliance of National Statistical Offices (NSOs) on local IT infrastructure makes them highly vulnerable to natural disasters. Computers, servers, and networks cannot operate without power; flooding and high humidity destroys hardware and storage media; looting and breaking into abandoned buildings puts sensitive information at the risk of falling into the wrong hands. Fortifying NSO buildings to withstand Category 5 hurricanes and enabling the offices to continue functioning afterwards is prohibitively expensive. Even if such structures were built, staffing would remain an issue, particularly if the entire population of the country was evacuated (as in case of Barbuda).
Cloud computing provides a very effective way to resolve that problem at a small fraction of the cost.
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.
The importance of soil health in agrarian societies is indisputable – soil health has a direct relationship with agricultural productivity and sustainability. Yet, its highly complex nature renders it much more challenging to measure than other agricultural inputs, such as fertilizers or pesticides. Household surveys, particularly those in low-income contexts where agriculture is the primary means of livelihood, have generally relied on subjective assessments of soil health – and for good reason. Subjective assessment is relatively inexpensive, and alternative methodological options have historically been prohibitively expensive. Recent advances in rapid low-cost technologies, namely spectral soil analysis, however, have increased the feasibility of integrating objective plot-level soil health measurement in household surveys.
This new Guidebook provides practical guidance for survey practitioners aiming to implement objective soil health measurement via spectral analysis in household and farm surveys, particularly in low-income smallholder farmer contexts. Two methodological experiments, in Ethiopia and Uganda, provide the foundation for this Guidebook. In each study, plot-level soil samples were collected following best-practice protocols and analyzed using wet chemistry and spectral analysis methods at ICRAF’s Soil-Plant Diagnostics Laboratory, in addition to a subjective module of soil health questions asked of the plot manager. The Guidebook offers (i) a comparison of subjective farmer assessments of soil health with laboratory testing, and (ii) step-by-step guidance on how to implement spectral soil analysis in a household- or farm-level survey, from questionnaire design to soil sample collection, labeling, and processing.
The Guidebook is the result of collaboration between the World Bank's Living Standards Measurement Study (LSMS) team, the World Agroforestry Centre, the Central Statistical Agency of Ethiopia, and the Uganda Bureau of Statistics.
As Agriculture Economists who work on advancing the food and agriculture agenda, SDG 2 articulates much of our work in the Sustainable Development agenda and illustrates how food and agriculture are intertwined with poverty reduction. Goal 2 seeks to “End hunger, achieve food security and improve nutrition, and promote sustainable agriculture.”
Without making progress on Goal 2, we can’t achieve the Bank’s twin goals of ending poverty and boosting shared prosperity.
But what does Goal 2 mean, exactly? On the surface, it might seem to be a matter of producing more food in a sustainable way. But a deeper dive into this SDG reveals that it is not quite that simple.
There has been substantial progress in reducing child mortality in the past several decades. Between 1990 and 2016, the global under-five mortality rate dropped by 56 percent from 93 deaths per 1,000 live births to 41 deaths per 1,000 live births. Over the last sixteen years, the reduction in child mortality rates accelerated, compared to the previous decade. As a consequence, around 50 million more young children survived the first five years of life since 2000 who would have died had under-five mortality remained at the same level as in 2000.
But even in 2016, 15,000 children died every day (totaling 5.6 million a year). While a substantial reduction from the 35,000 deaths a day in 1990 (12.6 million a year), more needs to be done to meet target 3.2 of the Sustainable Development Goals, which aims for all countries fewer than 25 deaths of under-5s per 1,000 live births.
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.
As global demand for food rises, the halting of landscape degradation and the restoration of these areas is paramount. Sustainable Development Goal 15 recognizes that efforts to restore degraded areas also benefit livelihoods and biodiversity by reducing erosion, supplying clean water, and providing wildlife habitat and other forest products (targets 15.1 and 15.3). Forests and trees also help mitigate climate change, enhance soil fertility, conserve soil moisture, and boost food production (target 15.3). A restored landscape may accommodate a range of land uses such as agriculture, protected reserves, ecological corridors, regenerated forests, well-managed plantations, agroforestry systems, and riparian plantings to protect waterways.
Landscape degradation directly affects 1.5 billion people, many of which live in extreme poverty.Around half of all land used globally for agriculture is moderately or severely affected by soil degradation.
Worldwide, nearly 25 million square kilometers offer opportunities for restoration, many in tropical and temperate areas. Nearly 18 million square kilometers would ideally combine forests and trees with other land uses through "mosaic restoration," including smallholder agriculture, agroforestry, and community forestry. A further 5 million square kilometers would be suitable for wide-scale restoration of closed forests. Africa provides the largest restoration opportunity, followed by Latin America (figure 15h).
What kind of information do you need to assess progress of community projects that aim to improve livelihoods and biodiversity conservation in remote Conservation Areas in Mozambique? More importantly, how do you efficiently collect this type of data and guarantee the level of consistency and quality needed to make strategic improvements in project implementation?
These are the questions our team faced during our recently concluded Mid-Term Review (MTR) of the World Bank Conservation Areas Development Project (Mozbio). We learned that there was not more time to wait and by applying the free World Bank-designed Computer Assisted Personal Interviewing (CAPI) Platform Survey Solutions, we could improve data collection and get the Project’s monitoring and evaluation back on track.
The 5-year Mozbio project addresses some of the most pressing challenges to Conservation Areas (CAs) in Mozambique, which covers 25% of the country. Besides strengthening the legal and institutional framework for conservation and promoting nature-based tourism and infrastructure facilities, the cornerstone of the project is to improve livelihood alternatives to local communities that live in and around the CAs. These populations constitute some of Mozambique’s poorest and most vulnerable households. To address this, Mozbio finances small-scale community projects that equip communities with tools to sustainably manage natural resources, engage them in income generating activities and increase their contribution to biodiversity conservation.
Goal 3 of the Sustainable Development Agenda for 2030 – Good Health and Well-being - explores a myriad of causes of ill-health and mortality, and hopes to improve the lives of many through its targets. Two recent blogs by the authors have focused on health during pregnancy and childbirth, and the prevention of some communicable and non-communicable diseases.
This blog turns its attention to other factors that impact people: mental health, alcohol and tobacco, and road traffic injuries and deaths.
Suicide rates are falling gradually in many parts of the world
Mental health is a focus of target 3.4, alongside other non-communicable diseases. Suicide accounts for 8.2 percent of deaths among young adults ages 15-29 globally and is the second leading cause of death after road traffic injuries for that age group.[i] Suicide rates for all ages tend to be higher in Europe and Central Asia and in high-income countries. In middle- and low-income countries, there has been a decline in rates since 2000.