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The Global State of Gender in 7 Charts

Tariq Khokhar's picture

This Sunday, International Women’s Day celebrates the achievements of women, while calling for greater gender equality. Ahead of several high-profile campaigns and initiatives launching this week and next, I thought I’d highlight some gender data and trends that you might not know about.

1) 91% of the world’s girls completed primary school

Chart 1

Data from UNESCO Institute of Statistics and World Development Indicators

In 2012, more girls completed primary school than ever before. Since 2000, there’s been progress across the world but large disparities remain between regions and countries. Only 66% of girls in Sub Saharan Africa completed primary school in 2012, and in three countries this figure was under 35%. Educating girls is one of the best investments we can make and by 2015, developing countries as a whole are likely to reach gender parity (about the same numbers of boys and girls) in terms of primary and secondary enrollment.

Can you visualize the structure of the world economy and population in one chart?

Morgan Brannon's picture
Also available in: Français | Español | العربية
Following the International Comparison Program (ICP) 2011 final report release from last October, there was particular interest in the charts presenting the results. To give a deeper explanation of one of the most popular charts, we’ve recently produced this video:
 
Real GDP Per Capita and Shares of Global Population, ICP 2011
Source:  ICP, http://icp.worldbank.org/

New data and research help measure a decade of urban expansion across East Asia

Chandan Deuskar's picture
Also available in: Français | العربية
How do you measure something when there’s no agreement on how to define an indicator?  How do you compare urban data when the word “urban” doesn’t have the same definition in every country? And what happens when cities stop counting the population that starts to spill over the municipal boundaries?
 

 

Big Data needs better questions

Elizabeth Sabet's picture

The term "big data" is much in the news lately – alternatingly touted as the next silver bullet potentially containing answers to myriad questions on natural and human dynamics, and dismissed by others as hype.  We are only beginning to discover what value exists in the vast quantities of information we have today, and how we are now capable of generating, storing, and analyzing this information. But how can we begin to extract that value?  More importantly, how can we begin to apply it to improving the human condition by promoting development and reducing poverty?
 
That is precisely the question that motivated the World Bank Group and Second Muse to collaborate on the recently released report Big Data in Action for Development. Interviews with big data practitioners around the world and an extensive review of literature on the topic led us to some surprising answers.

2015: the year of (data) time travel

Neil Fantom's picture
Delorean_DMC-12_Time_Machine_in_San_Francisco.JPG

Image Source: Wikimedia Commons

Time travel is, of course, the stuff of science fiction. H. G. Wells wrote about it in 1895, and it’s been fertile territory for film and television makers ever since. But the ability to store and retrieve digital records has at least made it possible to travel back in time with data...

For users of statistics, it turns out this can be a pretty handy thing to do: estimates and measures of many indicators get revised as methods improve, and as geographies and economies shift over time. A statistical data Time Machine can help answer questions like how much estimates been revised - and even whether different decisions might have been taken with the benefit of hindsight.

Now, 2015 is the year of the Data Revolution. So, let’s make a contribution by making a Time Machine using World Bank open data. We're pleased to announce that the World Development Indicators Database Archives are now available in the DataBank Application, read more below on how we got here!

The World Bank Group’s full project portfolio is now on the map

Philippa Sigl-Gloeckner's picture
Also available in: 中文 | العربية | Español | Français



We promise to add rich detail to our maps so that anyone will be able to go online, click on the maps, and immediately learn where we are working and what we are doing.” (Jim Yong Kim, Annual Meetings 2013)

For the first time, the World Bank Group’s (WBG) full portfolio, including IFC and MIGA is on the map (maps.worldbank.org). This accomplishment marks the completion of the geo-mapping target President Kim announced at the 2013 Annual Meetings. It is the result of a long collaboration across the WBG team’s to overcome numerous hurdles and successfully built on the foundation put down by the Mapping for Results team.

Which countries could be affected by plunging oil prices: a data perspective

Siddhesh Kaushik's picture
Tumbling oil prices continue to dominate the headlines. Although oil prices have started to rise earlier in the week, this issue is still of concern to many oil-exporting countries.
 


(Source: FRED Economic Data)

A recent World Bank Group feature story broke down country by country the potential regional consequences. And according to the Bank Group’s Global Economic Prospects report, the decline in oil prices will dampen growth prospects for oil-exporting countries.

There are various factors that can be used to assess the impact of falling oil prices on countries. One such factor is trade. Countries exporting mostly fuel products will lose export revenue as oil prices drop. The chart below shows the top 15 countries that exported fuel in 2012. You can visualize the data for other years and products using the World Integrated Trade Solution’s (WITS) product analysis visualization tool.

Tracking Urbanization: How big data can drive policies to make cities work for the poor

Axel van Trotsenburg's picture

Every minute, dozens of people in East Asia move from the countryside to the city.
The massive population shift is creating some of the world’s biggest mega-cities including Tokyo, Shanghai, Jakarta, Seoul and Manila, as well as hundreds of medium and smaller urban areas.

This transformation touches on every aspect of life and livelihoods, from access to clean water to high-speed trains that transport millions of people in and out of cities during rush hour each weekday.

Funding The Data Revolution

Claire Melamed's picture

A revolution starts with an idea, but to become real, it has to move quickly to a practical proposition about getting stuff done.  And getting things done needs money.  If the ideas generated last year, in the report of the UN Secretary General’s Independent Expert Advisory Group and elsewhere, about how to improve data production and use are to become real, then they will need investments.  It’s time to start thinking about where the money to fund the data revolution might come from, and how it might be spent.

Getting funding for investment in data won’t be easy.  As hard-pressed statistical offices around the world know to their cost, it’s tough to persuade governments to put money into counting things instead of, say, teaching children or paying pensions.  But unless the current excitement about data turn into concrete commitments, it will all fade away once the next big thing comes along, leaving little in the way of lasting change.

Next step for the Data Revolution: financing emerging priorities

Grant Cameron's picture
Also available in: 中文

Last August, the UN Secretary-General Ban Ki-moon asked an Independent Expert Advisory Group (IEAG) to make concrete recommendations on bringing about a Data Revolution in sustainable development.  In response, the IEAG delivered its report, and among other items, recommends, “a new funding stream to support the Data Revolution for sustainable development should be endorsed at the Third International Conference on Financing for Development,” in Addis Ababa in July 2015.

Three Issues Papers for Consultation

To support this request and to stimulate conversation, the World Bank Group has drafted issues papers that focus on three priority areas:

  1. Data innovation
  2. Public-private partnerships for data
  3. Data literacy and promotion of data use

The papers aim to flesh out the specific development needs, as well as financing characteristics needed to support each area. A fuller understanding of these characteristics will determine what kind of financing mechanism(s) or instrument(s) could be developed to support the Data Revolution.

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