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MDG2: Accelerating progress towards universal primary education

Hiroko Maeda's picture

This is the second in a series of posts on data related the Millennium Development Goals based on the 2015 Edition of World Development Indicators.

Millennium Development Goal 2 is to "Achieve universal primary education" and is measured against a target to “ensure that, by 2015, children everywhere, boys and girls alike, will be able to complete a full course of primary schooling”

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After modest movement toward universal primary education in the poorest countries during the 1990s, progress has accelerated considerably since 2000. Achieving the MDG 2 target appeared within reach only a few years ago, but the primary school completion rate has been stalled at 91 percent for developing countries since 2009.

Only two regions, East Asia and Pacific and Europe and Central Asia, have reached or are close to reaching universal primary education. The Middle East and North Africa has steadily improved, to 95 percent in 2012, the same rate as Latin America and the Caribbean. South Asia reached 91 percent in 2009, but progress since has been slow. The real challenge remains in Sub-Saharan Africa, which lags behind with a 70 percent primary completion rate as of 2012.

MDG 1: Uneven progress in reducing extreme poverty, hunger and malnutrition

Juan Feng's picture

This is the first in a series of posts on data related the Millennium Development Goals based on the 2015 Edition of World Development Indicators.

Millennium Development Goal 1 is to "Eradicate extreme poverty and hunger" and is assosciated with three targets to: a) Halve, between 1990 and 2015, the proportion of people whose income is less than one dollar a day; b) Achieve full and productive employment and decent work for all; and to c) Halve, between 1990 and 2015, the proportion of people who suffer from hunger. 

The latest estimates show that the proportion of people living on less than $1.25 a day fell from 43.6 percent in 1990 to 17.0 percent in 2011. Forecasts based on country-specific growth rates in the past 10 years indicate that the extreme poverty rate will fall to 13.4 percent by 2015, a drop of more than two-thirds from the 1990 baseline.

The number of people worldwide living on less than $1.25 a day is also forecast to be halved by 2015 from its 1990 level. Between 1990 and 2011 the number of extremely poor people fell from 1.9 billion to 1 billion, and according to forecasts, another 175 million people will be lifted out of extreme poverty by 2015.

This means that based on current trends, nearly half of developing countries have already achieved the Millennium Development Goal 1 (MDG1) target of halving the proportion of the population in extreme poverty five years ahead of the 2015 deadline.

Much of the world is deprived of poverty data. Let’s fix this.

Umar Serajuddin's picture
Cross posted from the Let's Talk Development Blog
 
Data Deprivation

The availability of poverty data has increased over the last 20 years but large gaps remain

About half the countries we studied in our recent paper, Data Deprivation, Another Deprivation to End are deprived of adequate data on poverty. This is a huge problem because the poor, who often lack political representation and agency, will remain invisible unless objective and properly sampled surveys reveal where they are, and how they’re faring. The lack of data on human and social development should be seen as a form of deprivation, and along with poverty, data deprivation should be eradicated.

New 2015 edition of World Development Indicators shows 25 years of progress, but much left to do

Neil Fantom's picture
Also available in: 中文 | العربية | Français | Español

We’re pleased to announce that the 2015 edition of World Development Indicators (WDI)  has been released.  WDI is the most widely used dataset in our Open Data Catalog and it  provides high-quality cross-country comparable statistics about development and people’s lives around the globe. As usual you can download or query the database, read the publication and  access the online tables.

While the seasoned WDI user will know that the database is updated quarterly and historical versions are also available, for those new to the WDI, the annual release of a new edition is an opportunity to review the trends we’re seeing in global development and to take stock of what’s been achieved.

2015: the year of (data) time travel

Neil Fantom's picture
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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!

Have your say: what do you want from a development data revolution?

Haishan Fu's picture

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If you’ve been reading anything related to international development in the last year, you will have seen rich conversations around the the idea of a “data revolution”. What exactly would a data revolution look like? What would its aims be? Is it about data collection, use, analysis, all of the above, or something else entirely?

To answer these and other questions, the United Nations Secretary General recently formed an Independent Expert Advisory Group (IEAG) on the “Data revolution for development”. I’m part of this group: we’ve been tasked with making recommendations on how to achieve a data revolution. We have to do it quickly - and we want to get your inputs too!

Open Data for economic growth: the latest evidence

Andrew Stott's picture
Also available in: Español

One of the key policy drivers for Open Data has been to drive economic growth and business innovation. There's a growing amount of evidence and analysis not only for the total potential economic benefit but also for some of the ways in which this is coming about. This evidence is summarised and reviewed in a new World Bank paper published today.

There's a range of studies that suggest that the potential prize from Open Data could be enormous - including an estimate of $3-5 trillion a year globally from McKinsey Global Institute and an estimate of $13 trillion cumulative over the next 5 years in the G20 countries.  There are supporting studies of the value of Open Data to certain sectors in certain countries - for instance $20 billion a year to Agriculture in the US - and of the value of key datasets such as geospatial data.  All these support the conclusion that the economic potential is at least significant - although with a range from "significant" to "extremely significant"!

New Metadata Query Feature in DataBank

Paige Morency-Notario's picture

DataBank is a data retrieval, analysis, and visualization tool that allows users to create, save, and share custom charts, tables, and maps. We launched the tool two years ago and have been making improvements based on user feedback ever since. Last year we released a multilingual version of the tool, and today we're pleased to announce a new feature that allows users to query country, series, time, and footnote metadata.

What can DataBank do?

  • It enables users to easily create custom queries on data drawn from 52 databases
  • It lets users create and customize charts, tables, and maps
  • It makes it easy to select, save and share data and visualizations
  • It's available on both computers and mobile devices
  • DataBank and selected data are available in English, Spanish, French, Arabic, and Chinese
  • It now allows users to create custom metadata queries
  • Watch the tutorial and read the FAQs to learn more about the basics of DataBank 

Spicing up research on sub-national development through open data: Indonesia Data for Policy and Economic Research (INDO-DAPOER)

Also available in Bahasa

It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts. – Sherlock Holmes.
It's a game changer for those working on Indonesia's sub-national development issues. Comprehensive data at the sub-national level is now available to the public through INDO-DAPOER (Indonesia Data for Policy and Economics Research) at data.worldbank.org. DAPOER, which means ‘kitchen’ in Indonesian, is intended to be a ‘place’ where various data are blended, like spices, and cooked to produce analytical works, research papers, and policy notes.

INDO-DAPOER is the first World Bank sub-national database consisting of both province and district level data to be publicly accessible from anywhere in the world. The database provides access to around 200 indicators from almost 500 districts and 34 provinces in Indonesia, which in general go back to the early 1990s and even 1980s for some. The indicators are grouped into four main categories: fiscal, economic, social demographic, and infrastructure. Indicators range from sub-national government revenue and expenditure, sub-national GDP, to specific education, health, and infrastructure indicators such as net enrollment rate for junior secondary, immunization rate, and household access to safe sanitation.

From open data to development impact – the crucial role of the private sector

Prasanna Lal Das's picture

Can open data lead to reduced energy consumption (and therefore slow down climate change)? Can open data help improve maternal health services (and thus improve facets of public delivery of services)? Can open data help farmers and crop insurers make better crop predictions (and thus lead to smarter investment decisions in agriculture)? Can open data empower citizens to fight back against police corruption (and thus help promote the rule of law)?

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