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Dataviz

Can our parents collect reliable and timely price data?

Nada Hamadeh's picture
Also available in: 中文 | Español | Français | العربية

During the past few years, interest in high-frequency price data has grown steadily.  Recent major economic events - including the food crisis and the energy price surge – have increased the need for timely high-frequency data, openly available to all users.  Standard survey methods lag behind in meeting this demand, due to the high cost of collecting detailed sub-national data, the time delay usually associated with publishing the results, and the limitations to publishing detailed data. For example, although national consumer price indices (CPIs) are published on a monthly basis in most countries, national statistical offices do not release the underlying price data.

 
Crowd sourced price data

What does World Development Indicators tell us about South-South trade?

Wendy Ven-dee Huang's picture

Merchandise trade has become an increasingly important contributor to a country’s gross domestic product (GDP), particularly for developing countries. Before the global financial crisis hit in 2008, merchandise trade as a percent of GDP for low- and middle-income economies was 57 percent, about 5% higher than for high-income economies. This is very evident in Europe and Central Asia (ECA) where merchandise trade accounts for 73 percent of the developing region’s GDP.  Many ECA countries including Hungary, Belarus, and Bulgaria have merchandise trade to GDP ratios above 100 percent (155, 136, and 114 percent respectively in 2011), meaning merchandise exports are a large contributor to their overall economy.

<1000 days to the MDGs: Data Dashboards to Monitor the last Stretch

Johan Mistiaen's picture
Also available in: Español | Français | العربية

Data on Millennium Development Goals (MDG) indicator trends for developing countries and for different groups of countries are curated in the World Development Indicator (WDI) database.  Each year we use these data in the Global Monitoring Report (GMR) to track progress on the MDGs.  Many colleagues, as well as non-Bank staff, approach us on a weekly basis with questions regarding where their region, or country, or sector stands in regard to achieving the core MDGs.  Oftentimes in the same breath, they will also ask us whether or when we expect that a particular country or region will meet a certain MDG.  

With less than 1,000 days remaining to the MDG deadline, work on the Post-2015 agenda is in full swing. In response to the growing demand for additional info about GMR analytics and the underlying data, we developed a suite of open and interactive data diagnostics dashboards available at: http://data.worldbank.org/mdgs.  Below is an extract which summarizes the progress status towards meeting various MDGs among countries in various regions, income and other groups.  Select different indicators and highlight categories of progress status to interact with the visualization.

 

The Fast Changing World of Information and Communications Technology

Buyant Erdene Khaltarkhuu's picture
Also available in: Français | العربية
Mobile phones and the Internet are increasingly seen as essential requirements for the exchange of information. Data from World Development Indicators 2013 illustrates the dramatic change in access across the world in the last decade.

Intersecting sources of education inequality

Elizabeth King's picture

Developing countries today have unprecedented numbers of schools, classrooms, teachers—and students.  Remarkable accomplishments have also been made towards achieving gender equality at all levels of education (see World Bank, 2010). Since 1999, girls’ gross enrollment rates have risen fastest in South Asia, especially at the primary level, by about 30 percentage points; in South Asia, girls’ enrollment rates at the secondary level rose almost as fast. In the other regions where girls’ enrollment rate at the primary level was already very high, girls’ enrollment rate at the secondary and tertiary levels showed impressive increases. 

International debt flows before and after the financial crisis

Evis Rucaj's picture

New debt statistics show that the composition of long term debt inflows in 2011 follows pre-crisis patterns.

Debt statistics are central to understanding the impact of the financial crisis; the World Bank's International Debt Statistics provides a detailed picture of debt flows of 128 developing countries. Now that the 2013 edition has been released, and as a member of the team that put it together, I thought I would look back at what the data tell us actually happened to international debt flows to developing countries before and after the recent financial crisis.

International Debt Statistics: Open Data on a wider scale

Ibrahim Levent's picture

For over three decades debt statistics published by the World Bank have provided the authoritative accounting of the external debt of developing countries. Governments, investors and bankers, academics, and journalists have relied on them to identify financial trends and vulnerabilities.

Seven things I learned about data visualization

Tariq Khokhar's picture

Last week, the World Bank Data team descended on New York City for Visualized - a two day event exploring the “evolution of communication at the intersection of big data, storytelling and design.”

It was awesome.

Here are seven things I learned:

1) Iteration is the path to perfection

By now you’ve heard of Nate Silver - the statistician behind FiveThirtyEight and a near-perfect prediction of the 2012 US elections. What you may have missed is the best interactive graphic of the year - the New York Times’ “Paths to the White House” built with Mike Bostock’s D3:

 Shan Carter from the NYT graphics team showed how newspapers have struggled to represent the potential scenarios and actual outcomes of US elections ever since the late 19th century. His team eventually came up with the graphic above, but see how many revisions they went through to get there:

That’s 257 revisions. As early as version 15, you can see the core idea. At version 81, it looks almost done, but it takes another 157 revisions and that extra attention to detail, high production values and pride in your work to be at the top of your game like this.

Lesson: Iterate and aim high: editors are your friends, they’ll make your work stand out. Also: this is the benchmark for what a good data visualization looks like - if you can’t honestly say what you’re doing is at least this good, iterate.

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