In many low and middle income countries, out-of-pocket healthcare expenditures are high, and can be a significant financial risk to the poor. Universal health coverage (UHC) is about people having access to needed health care without suffering undue financial hardship.
Many rural households in low- and middle-income countries depend on livestock for their livelihoods. Sustainable livestock systems can contribute to reducing poverty, ending hunger, and improving health, and can also be key in addressing environmental degradation and climate change, and preserving biodiversity.
Measuring livestock systems—and the socioeconomic benefits they generate—remains a challenge due to a lack of high-quality, nationally representative data. Livestock is often neglected in many national statistical operations and, as a result, decision makers are unable to design evidence-based livestock sector policies and investments.
A new multi-partner publication provides guidance for effectively including livestock in multi-topic and agricultural household surveys. The livestock module template provided in this Guidebook can be used by survey practitioners and stakeholders to generate household-level statistics on livestock, its role in the household economy, and its contribution to livelihoods. It builds on a variety of multi-topic and agricultural/livestock household survey questionnaires implemented in low- and middle-income countries, and on lessons learned from the implementation of comprehensive livestock questionnaires, as part of multi-topic household surveys, in Niger, Tanzania, and Uganda.
The Guidebook is the result of collaboration between the World Bank's Living Standards Measurement Study (LSMS) team, the Food and Agriculture Organization of the United Nations (FAO), the Tanzania National Bureau of Statistics, and the Uganda Bureau of Statistics.
For practical advice on household survey design, visit the LSMS Guidebooks page: http://go.worldbank.org/0ZOAP159L0
People who look at the Doing Business report’s Trading Across Borders indicator and the Logistics Performance Index (LPI) often wonder why one country can perform well on one of the rankings but not so well on the other although they both measure trade and logistics. In fact, earlier this year, the Doing Business team organized a workshop at the World Bank Global Knowledge and Research Hub in Kuala Lumpur to clarify the differences between the two datasets.
Let’s start off with a few definitions:
The Doing Business report is a World Bank Group flagship publication, which covers 11 areas of business regulations. Trading Across Borders is one of these areas. It looks specifically at the logistical processes of exporting and importing. Data is updated annually and the latest edition covers 190 economies. Doing Business collects data from local experts and measures performance as reported by domestic entrepreneurs, while taking into consideration factual laws and regulations.
The Logistics Performance Index is a benchmarking tool which focuses on trade logistics. It is created to help countries identify the challenges and opportunities they face as they relate to customs, border management, transport infrastructure, and logistics services. Updated biennially, the latest data and report cover 160 economies. Data is collected from global freight forwarders and express carriers who provide feedback on the logistical “friendliness” of the countries they operate.
In less than a generation the Latin America and the Caribbean (LAC) region has made great progress in expanding the basic public services that are necessary for children to succeed later in life. The skills, knowledge and health accumulated by individuals by the time they reach adulthood are essential to get jobs, accelerate economic mobility, and reduce inequality in the long-run. The. But progress has also been uneven, both across countries and for different types of basic services.
, where we have seen gaps in coverage narrow the most. Figure 1 below shows how the typical performance in the region (the median) compares with the country in the region with the highest level of coverage (labeled “best in class”) in three basic services for children. The focus on children makes it possible to determine that any difference in access would be mostly due to circumstances out of their control. In the case of access to electricity the regional median has not only converged towards the best performing country but it has now reached a coverage of 99 percent.
In early November, nearly 200 countries came together at the UN climate change conference (COP22) in Marrakech to reaffirm their commitment to the historic “Paris Agreement.” If the COP21 was about signing this agreement, this year’s conference is about the critical next step of turning commitment into action.
To track overall opinions of thought leaders across the globe, including views toward climate change before and after the landmark deal, the World Bank Group’s Country Opinion Survey program annually surveys nearly 10,000 key influencers working in government, parliament, private sector, civil society, media, and academia in more than 40 development countries. The results help shed light on the overall public opinion environment where efforts to operationalize the Agreement will likely take place.
The following charts provide a snapshot view of global opinion leaders’ (in developing countries) attitudes toward climate change.
Overall, survey data suggest that concern about climate change among opinion leaders worldwide has increased significantly in the past four years. While the percentage of respondents considering addressing climate change a top development priority is relatively lower than that of education, governance, and food security in many countries, data clearly show an upward trend in the perceived importance of combatting climate change since 2015.
This month’s meeting of the International Comparison Program (ICP) Governing Board marked a new chapter in one of the world’s most far-reaching statistical operations. The release of the 2011 ICP round results in 2014 was met with some disagreement among scholars, but a dominant view emerged that they represent an improvement over the 2005 round. The release triggered a revision of the international poverty line which was updated from $1.25 / day in 2005 PPPs to $1.90 / day in 2011 PPPs. The IMF also uses the resulting PPPs in its Quota subscription allocation, as does the UNDP in the calculation of the Human Development Report’s Human Development Index (HDI), and a number of the SDGs involve PPPs in their measurement.
The ICP estimates purchasing power parities, or PPPs, for use as currency converters to compare the size and price levels of economies around the world. PPP-based measures are critical for assessing the real living conditions of individuals in different countries, and for establishing a common yardstick for measuring progress. Just as important as what it does is how it does it - the ICP is a partnership, and a great example of how working together can yield great benefits to all stakeholders.
The Global ICP Unit - part of the official statistical architecture
The World Bank is now home to the permanent Global ICP Unit, which has this year been instituted as a formal part of the global statistical program by the United Nations Statistical Commission (UNSC). This development puts the ICP on a stable long-term footing and is a testimony to the ICP’s collective efforts to ensure the success and continuity of the program.
Since its establishment in 1968, the ICP has grown to cover all regions of the world and become the world’s largest statistical initiative. The 2011 round of the ICP covered 199 economies from eight regions with the help of 15 regional and international partners.
In Sub-Saharan Africa and South Asia, there are more than twice as many students per teacher than in Europe and North America. The pupil-teacher ratio is different but related to class size, and is often used to compare the quality of schooling across countries.
Population density is one of the most important statistics for development efforts across many sectors, and since early 2016 we’ve been collaborating with Facebook on evaluating a new source of high-resolution population data that sheds light on previously unmapped populations.
As mentioned in the Living Standards Measurement Study (LSMS) team’s blog post, Facebook Connectivity Lab announced last week the public release of high-resolution population maps for Ghana, Haiti, Malawi, South Africa, and Sri Lanka, jointly produced with the Center for International Earth Science Information Network (CIESIN).
With the building footprints detected by artificial intelligence (AI) over high-resolution commercial satellite imagery, the data sets provide estimates of population at 30m spatial resolution, making these maps the highest-resolution population maps ever produced. This is only possible through recent breakthroughs in computer vision due to deep learning algorithms and technological development of computer processors, as well as the increasing availability of high-resolution commercial satellite imagery.
Image 1: Naivasha, Kenya.
DigitalGlobe satellite (upper left), gridded population of the world v4 from CIESIN (upper right), WorldPop (bottom left), output from Facebook model (bottom right).
Editor’s note: This is a guest blog from Jorn Berends and Wendy Carrara on behalf of the European Data Portal. The indicator “Open Data readiness” mentioned in the analysis below is unrelated to the Open Data Readiness Assessment tool developed by the World Bank.
The majority of European countries are improving their Open Data maturity
Open Data is taking off in Europe. Open Data – which refers to publicly available data that is free for all to use – is set to have a monumental impact on societies in the upcoming years, and has a potential market size for the European Union of 75.7 bn EUR by 2020. European countries seem to be on track to reap the potential of Open Data, although a lot of work remains to be done and substantial differences persist between countries. In 2016, with a 28.6% increase compared to 2015, the EU28 and Norway, Switzerland and Liechtenstein – referred to as EU28+ – completed over 55% of their Open Data journey. This shows that, by 2016, a majority of the EU28+ countries have successfully developed a basic approach to address Open Data. This is just one of the conclusions of the 2016 Open Data Maturity in Europe report, prepared by the European Data Portal. What can this report tell us on the countries that are doing particularly well in this regard, what is it that makes them European champions? Furthermore, what can other countries learn from them?
Spain and France are leading the way in Europe, but substantial differences persist
The measurement is built on two key indicators ‘Open Data Readiness’ and ‘Portal Maturity’, thereby covering the level of development of national activities promoting Open Data as well as the level of development of the country’s national data portal. Based on these indicators, the European countries are clustered into four different levels of Open Data maturity: Beginners, Followers, Fast Trackers and Trend Setters.
Facebook recently announced the public release of unprecedentedly high-resolution population maps for Ghana, Haiti, Malawi, South Africa, and Sri Lanka. These maps have been produced jointly by the Facebook Connectivity Lab and the Center for International Earth Science Information Network (CIESIN), and provide data on the distribution of human populations at 30-meter spatial resolution. Facebook conducted this research to inform the development of wireless communication technologies and platforms to bring Internet to the globally unconnected as part of the internet.org initiative.
Figure 1 conveys the spatial resolution of the Facebook dataset, unmatched in its ability to identify settlements. We are looking at approximately a 1 km2 area covering a rural village in Malawi. Previous efforts to map population would have represented this area with only a single grid cell (LandScan), or 100 cells (WorldPop), but Facebook has achieved the highest level of spatial refinement yet, with 900 cells. The blue areas identify the populated pixels in Facebook’s impressive map of the Warm Heart of Africa.
Facebook’s computer vision approach is a very fast method to produce spatially-explicit country-wide population estimates. Using their method, Facebook successfully generated at-scale, high-resolution insights on the distribution of buildings, unmatched by any other remote sensing effort to date. These maps demonstrate the value of artificial intelligence for filling data gaps and creating new datasets, and they could provide a promising complement to household surveys and censuses.
Beginning in March 2016, we started collaborating with Facebook to assess the precision of the maps and explore their potential uses in development efforts. Here, we describe the analyses undertaken to date by the Living Standards Measurement Study (LSMS) team at the World Bank to compare the high-resolution population projections against the ground truth data. Among the countries that were part of the initial release, Malawi was of particular interest for the validation exercise given the range of data at our disposal.