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LICs, LMICs, UMICs, and HICs: classifying economies for analytical purposes

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Also available in: 中文

Two previous posts outlined plans to review the World Bank's analytical income classification, here and here. Since we are updating this classification with new data soon (July 1, 2014), we wanted to let users know where this work stands.

Every year, the analytical classification groups all economies into four categories: low income countries (LICs); lower middle income countries (LMICs); upper middle income countries (UMICs); and high income countries (or HICs). This year we will update the classification using 2013 data, but we will not make any change to the methodology.

How we do Open Data: #1 - choosing development indicators

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Also available in: 中文

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

There are sometimes gaps in the data


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.

Data, Differences, and Digging Deeper

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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.

International Debt Statistics: three changes for 2014

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Also available in: Français | Español | 中文 | العربية

The World Bank has been collecting statistics on the debt of its borrowing countries since 1951, through the Debtor Reporting System. Published for many years as World Debt Tables (see, for example, the 1982 edition here) and then as Global Development Finance (initially as Volume 2), the 2013 dataset - which contains data for 2011 - was published in a renamed publication as International Debt Statistics, with expanded coverage of Quarterly External Debt Statistics and Public Sector Debt.

Last year we reviewed our dissemination strategy for World Development Indicators (WDI), and made some improvements to improve the quality and accessibility of the statistical indicators, tables and analyses. This year we’ve looked at debt statistics, and are planning some changes here as well; while the 2014 dataset - which contains data for 2012 - has been released in mid-December as usual, we’ll be releasing the redesigned data products in mid-February.

A conversation with Zoellick about Open Data

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A couple of weeks ago some of the original members of the team that helped make the World Bank's data freely accessible and open had an opportunity to meet with the outgoing President of the World Bank, Bob Zoellick; his enthusiasm and commitment to modernizing the World Bank and making it more open has been a key factor in the success of the Bank's Open Data Initiative – and some regard it as a hallmark of his tenure.

He was keen to thank the many people that came together behind the common objective of making the Bank's data easier to find and easier to use. And he had a question for us: what's next? We've posted some thoughts about that before, but what did we tell the President?

Open Data team June 2012