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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.

Announcing the launch of the Global Financial Inclusion (Global Findex) Microdata

Asli Demirgüç-Kunt's picture

It’s raining data. Financial inclusion data, that is. The Development Research Group has published the complete micro dataset of the Global Financial Inclusion (Global Findex) dataset on the Open Data Microdata Library. We’re talking over 150,000 individual-level observations, representing adults in 148 economies and 97 percent of the world’s adult population. Users can download the complete worldwide dataset, or datasets by country.

What has the World Bank done for your neighborhood lately?

Prasanna Lal Das's picture

Let’s say you are in the middle of what others may call ‘nowhere’ and need information on the Bank’s work in the vicinity before an upcoming meeting with local officials. Or you are a civil society organization rep and want to make sure that the numbers you have about a particular project are the same as what the Bank reports (and if not, you want to know why not).

Your laptop is no good because - it is the middle of nowhere after all! - and you can only rue your decision to leave your stack of papers behind.

What do you do? Well, the answer might be in your pocket.

It took longer than we'd hoped but it's finally here - the new World Bank Finances app answers many of the questions you asked after the release of the first version last year (click here to download the new version for Android; an updated iOS version will be out soon). 


How can the open government data toolkit help you?

Iulian Pogor's picture

We’ve recently released an Open Government Data Toolkit (OGD Toolkit), designed to provide staff at the World Bank and in country governments a basic set of resources for initiating and developing an open data program. The toolkit is a “work in progress” which we expect to revise and improve as we receive your feedback and real-world experience.

 

We developed the toolkit based on questions we’ve frequently heard from countries considering open data programs:

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.

A Review of the analytical income classification

Shaida Badiee's picture

This post originally appeared on Let's Talk Development.

The World Bank’s classification of economies as low-, lower-middle-, upper-middle-, or high-income has a long history. Over the years these groupings have provided a useful way of summarizing trends across a wide array of development indicators. Although the income classification is sometimes confused with the World Bank’s operational guidelines, which set lending terms and are determined only in part by average income, the classification is provided purely for analytical convenience and has no official status.

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