When you hear the words “top tourist destination,” do sandy beaches and national parks come to mind? Perhaps places with historical significance like the Egyptian pyramids or the temples of Angkor Wat in Cambodia? When we take a close look at the tourism data, we see that some of the top tourist destinations in the world are in low- and middle-income countries, specifically, in the East Asia and Pacific region.
A recent question from Lorenz Noe caught our eye - how do we choose which indicators to publish in World Development Indicators (WDI), a major part of our Open Data Initiative? It’s a good question, so I thought I’d write a post about that - and we’ll also post something similar in the data help desk.
1. There’s no perfect indicator
Like many things in life, selecting indicators for the WDI is not an exact science. The intention is to provide good coverage of key development issues, but many of the countries that we work with do not have the quantity - or quality - of data that exists in countries like the United States, for example.
Explaining the differences in today’s global society is a topic that clearly captures the interest of many: as I write this blog, the hardback version of Thomas Piketty’s new book “Capital in the Twenty-First Century” is second on Amazon’s best-seller list. That’s not bad for a pretty hefty book about economics and the distribution of wealth!
Another publication – the 2014 edition of World Development Indicators (WDI) 2014 – was also released in the last few weeks: it’s not likely to reach the bestseller list on Amazon, but it does also reveal some startling differences in the lives of people around the world, and the challenges they face. Here’s one statistic: a newborn child born in Sierra Leone will be 90 times more likely to die before her fifth birthday than a newborn child born in Luxembourg. And the estimated probabilities of dying before five? In Sierra Leone, in 2012, it was 18%, or just under 1 in 5 – the highest in the world. In Luxembourg, that probability was just 0.2%, or about 1 in 500 – the lowest in the world. Since it really is quite shocking, maybe I should repeat it: almost 1 in 5 children born in Sierra Leone will die before they reach the age of five.
Their offense? Going to school.
This grim story highlights the pressing issue of education in the developing world.
So I thought I’d look at the stats. First: primary completion rate, which is the number of students in the last year of primary compared to the number of children of the correct age for that year – and one of the measures that is used to assess progress to “MDG2” – to achieve universal primary education. As of 2010, the estimate for Nigeria was 76%, higher than the Sub-Saharan Africa average of 69%, but well below the world average of 91%. And Nigerian girls were almost 10 percentage points behind Nigerian boys’ primary completion rate in that year. Interestingly, in 2006, the primary completion rate was as high as 90%, putting Nigeria slightly above the world average. The rate has since declined, possibly due to a steady increase in the size of Nigeria’s youth population, which can put a strain on resources linked to education. About 44% of the population was under 14 years of age in 2012.
In the developing world, one way to reduce maternal mortality is to train professional midwives for both health facility and home deliveries. But what does the bigger picture of maternal mortality look like today?
The global maternal mortality ratio has fallen by 45% between 1990 and 2013, according to new estimates released today. This means that the world went from 380 maternal deaths per 100,000 live births in 1990 to 210 deaths per 100,000 live births in 2013. While this decline represents substantial progress, the actual rate of decline is insufficient to reach Millennium Development Goal 5 (MDG 5) – a three-quarter reduction in 1990 levels by 2015. To truly reach the target, an annual average reduction of 5.5% would be needed between 1990 and 2015.
Data scientist may be the sexiest job of the current century, and everybody in the world may be crying hoarse over the growing shortage of data scientists, but if you are leading an international development project or an international development agency, chances are you don’t have a data scientist on your team and you likely aren’t looking for one. That’s a problem.
Where can you find the top trading partners for your country? Where can you find the top products exported to and imported from Indonesia? Where can you find just about any type of trade data?
The answers to these questions (and more) are available at our recently revamped World Integrated Trade Solution (WITS) site: wits.worldbank.org. In previous versions of the site, users needed to login and query the data themselves. You still can. And many still do to conduct much more detailed and sophisticated research and analysis on trade. But if you want to quickly look up or browse trade statistics like total exports, tariffs applied, top export, and import partners, the data has been pre-calculated and made available as Open Data.
“Thanks to the data I found on WITS, I successfully completed my PhD. Really easy-to-use site and great upgrades.”
– User in India
Although the World Bank collaborates with international agencies that work with external debt and debt-related statistics (the Bank for International Settlements (BIS), the International Monetary Fund (IMF), the Organisation for Economic Co-operation and Development (OECD) and others), the World Bank has the international mandate to collect external debt data, and we maintain comprehensive external debt information.
What sparks a revolution? And what helps keep the transformational power of a revolution alive? When Jim Yong Kim became World Bank Group president less than two years ago, he stated that one of his first priorities was to position the World Bank Group as a “solutions bank.” Most recently, during his speech last Tuesday at the Council on Foreign Relations, Kim discussed the Bank’s efforts to invest in effective infrastructure, including data systems and social movements to empower the poor.
These three words – solutions, data and the poor – from my perspective, point to this: the data revolution needs to be transformational and we must act now. Unless we fully embrace this data revolution as a bold, timely opportunity to engage citizens, identify successful case studies, leverage global partnerships and technology, strive to learn from the private sector and truly aim to be innovative, we just may miss out on keeping this revolution alive. And while it is good news that the UN High Level Panel Report on the post-2015 development agenda confirms that the data revolution is high on the political agenda, we must also gather evidence and vigorously commit to an inclusive plan to meet this goal.