Eight in 10 people in the developing world own a mobile phone, but the cost of using mobiles varies significantly. The 2016 World Development Report explores the impact of the Internet and mobiles on human development.
If you're interested in exploring this data a bit further, I put together a dashboard using the original data source (Table 4.2 in the ITU's Measuring the Information Society 2015 - PDF link). Since extracting data from a PDF isn't always error free, I take responsibility for any "transcription errors" - but having looked it over a couple of times, I don't see anything obviously amiss.
The World Region
"The World By Income"
We’ve just released a working paper reviewing the Bank’s classification of countries by income. As Tariq Khokhar and Umar Serajuddin pointed out in their recent blog about whether we should call countries developing or not, there’s a strong appetite for classifying and ranking countries. Where is the best country to live, according to the OECD? (it depends, but it might be Australia, Norway or Sweden.) Which are making the most social progress, according to the Social Progress Imperative? (Norway and Sweden again.) Where is it easiest to do business, according to the World Bank? (Singapore.) Which countries have highest or lowest human development, according to the United Nations Development Program? (that’s Norway once more, and Niger is lowest.).
Using GNI per capita
The World Bank has used a specific measure of economic development - gross national income (GNI) per capita - for the purpose of ranking and classifying countries for over 50 years. The first compendium of these statistics was called the World Bank Atlas, published in 1966 - it had just two estimates for each country: its population, and its per capita gross national product in US dollars, both for 1964. Then, the highest reported average income per capita was Kuwait, with $3,290. In second place was the United States, with $3,020, third was Sweden, a fair way behind, with $2,040. The bottom three were Ethiopia, Upper Volta (now Burkina Faso), and Malawi, with GNP per capita estimates of $50, $45 and $40 respectively (GNI used to be called GNP). It probably comes as no surprise that today Norway is top. Malawi is still bottom.
The newly released 2016 edition of the International Debt Statistics (IDS) shows a rapid rise in sovereign bond issuance in some Sub-Saharan African countries. This includes those countries that have benefited from Heavily Indebted Poor Countries (HIPC) and Multilateral Debt Relief Initiative (MDRI) debt relief programs.
The chart above shows that sovereign bond issuance in certain Sub-Saharan African countries has risen substantially over the past 4 years. At the end of 2011, bond issuance totaled $1 billion and by the end of 2014, it amounted to $6.2 billion. Steady global market conditions and the potential for higher returns for investors have helped pave the way for more access to international markets, where the average return for these bond issuances is about 6.6%, with an average maturity of 10 years.
For these Sub-Saharan African countries, the proceeds from these sovereign bonds are used to benchmark for future government and corporate bond markets issues, to manage the public debt portfolio, and for infrastructure financing.
In a study of 137 countries, on average, firms reported that 14% of public transactions, such as dealing with utilities, permits, licenses, and taxes, involved the request of a gift or informal payment — a bribe. The Enterprise Surveys program collects data directly from firms to study an economy’s private sector. Read more.
Today is World Aids Day - an annual event to raise awareness about the global fight against HIV. Earlier this year, a report from UNAIDS declared that the Millennium Development Goal 6 target of “halting and reversing the spread of HIV” had been met, but that continued effort and financing would be needed to end the AIDS epidemic by 2030 as part of Sustainable Development Goal 3.
When it comes to international data about HIV and AIDS, the cross-organisational UNAIDS program publishes age and gender-disaggregated data on indicators such as prevalence, new infections and deaths. In turn, we incorporate some of these data into the World Development Indicators.
Here are some highlights from the most recently available data:
In 2014, there were an estimated 36.9 million adults and children living with HIV in the world. The majority of these people are in Sub-Saharan Africa and parts of Asia. As you can see from the decreasing slope of the “global” line - while people continue to become infected, the rate of new infections is going down.
Globally, the most common form of violence women experience is from an intimate partner. A recent report found that 127 out of 173 economies studied had laws on domestic violence, and in 72% of economies, protection orders can be used to limit an abuser's behavior. Read more.
On a brisk February morning in 2010, a small group of my World Bank colleagues, a few AidData partners, and I were in brainstorming mode. Our topic of discussion: how we could make a meaningful, measurable difference in making our development projects more open, transparent, and effective.
One idea lit us all up: putting development on a map. We envisioned an open platform that citizens around the world could use to look up local development projects and provide direct feedback. We were inspired by “open evangelists” like Beth Novek, Hans Rosling and Viveck Kundra.
Testing of the citizen feedback platform with local community members in rural Cochabamba, Bolivia
However, there was one challenge: how could we help make the World Bank’s data and numerous data sets fully open, free, shareable, and easily accessible to anyone? At the time, the large majority of these data sets were proprietary, and those who had access to key data sets were a relatively limited number of technical specialists.
In addressing this issue, we were fortunate. We worked closely as a small, creative, and highly committed team of innovators from different parts of the Bank to gradually open up the Bank’s data. To be honest, no one on our small team of incubators could have predicted that we would be able to scale up our early innovations so rapidly and that they would result in such important changes in the Bank’s approach to data and openness.
The use of big data to help understand the global economy continues to build momentum. Last week our sister institution, the International Monetary Fund, launched their own program in big data, with a slate of interesting speakers including Hal Varian (Google Chief Economist), Susan Athey (Professor at Stanford GSB and a former Microsoft Chief Economist) and DJ Patil (Chief Data Scientist of the United States).
The day's speakers grappled with the implications of big data for the Fund's bread-and-butter macroeconomic analysis--a topic of great interest to the World Bank Group too. Examples were presented in which big data is used to generate macroeconomic series that have traditionally been the preserve of national statistical offices (NSOs): for example, MIT's Billion Prices Project, which measures price inflation in a radically different way from traditional CPI statistics.
Comparing the classification of countries.
Humans, by their nature, categorize. Economists are no different. For many years, the World Bank has produced and used income classifications to group countries.
The low, lower-middle, upper-middle and high income groups are each associated with an annually updated threshold level of Gross National Income (GNI) per-capita, and the low and middle income groups taken together are referred to in the World Bank (and elsewhere) as the “developing world.”
This term is used in our publications (such as the World Development Indicators and the Global Monitoring Report) and we also publish aggregate estimates for important indicators like poverty rates for both developing countries as a group and for the whole world.
But the terms “developing world” and “developing country” are tricky: even we use them cautiously, trying to make it clear that we're not judging the development status of any country.