28 October 2012

EFA Global Monitoring Report 2012

The Education for All Global Monitoring Report 2012 - Youth and skills: Putting education to work was published by UNESCO on 16 October 2012. As all previous reports, the 2012 edition describes progress towards the six Education for All goals.

  • Goal 1: Expanding and improving comprehensive early childhood care and education, especially for the most vulnerable and disadvantaged children.
  • Goal 2: Ensuring that by 2015 all children, particularly girls, children in difficult circumstances and those belonging to ethnic minorities, have access to, and complete, free and compulsory primary education of good quality.
  • Goal 3: Ensuring that the learning needs of all young people and adults are met through equitable access to appropriate learning and life-skills programmes.
  • Goal 4: Achieving a 50 per cent improvement in levels of adult literacy by 2015, especially for women, and equitable access to basic and continuing education for all adults.
  • Goal 5: Eliminating gender disparities in primary and secondary education by 2005, and achieving gender equality in education by 2015, with a focus on ensuring girls’ full and equal access to and achievement in basic education of good quality.
  • Goal 6: Improving all aspects of the quality of education and ensuring excellence of all so that recognized and measurable learning outcomes are achieved by all, especially in literacy, numeracy and essential life skills.

The Global Monitoring Report 2012 also takes a closer look at skills and skill development programs for urban and rural youth.

Reference

  • UNESCO. 2012. EFA Global Monitoring Report 2012 - Youth and skills: Putting education to work. Paris: UNESCO. (Download in PDF format, 8.8 MB)

External links

Related articles

Friedrich Huebler, 28 October 2012 (edited 9 March 2014), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2012/10/gmr.html
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09 September 2012

Blog translation

Articles on the International Education Statistics blog can now be translated into more than 60 languages, including Arabic, Chinese, French, Russian and Spanish. To translate an article, select a language from the "Translate" drop-down menu in the sidebar, above the search box.

The translations are provided by Google Translate. They are not always perfect and the formatting of articles is not always preserved. Even so, the translations may be useful for readers who prefer a language other than English.

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Friedrich Huebler, 9 September 2012, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2012/09/translation.html
Posted by on Sunday, September 09, 2012 0 comments
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31 August 2012

Guide to creating maps with Stata

Most charts and maps on this site were created with the Stata statistical software package. This guide explains how maps like those with adult and youth literacy rates in 2010 can be created with Stata. The article supersedes an earlier version from 2005 and introduces updated maps with current country borders. For example, South Sudan, which seceded from Sudan in 2011, is shown as a separate country on the new maps. The instructions below are for Stata version 9 or later. Users of Stata 8 are referred to the guide from 2005. The creation of maps is not supported in older versions of Stata.

Requirements

  • Stata version 9.2 or later.
  • spmap: Stata module for drawing thematic maps, by Maurizio Pisati. spmap can be installed in Stata with this command:
      ssc install spmap
  • shp2dta: Stata module for converting shapefiles to Stata format, by Kevin Crow. shp2dta can be installed in Stata with this command:
      ssc install shp2dta
  • Shapefile: A shapefile is a data format for geographic information systems. For the maps in Figures 1 and 2, please download this public domain shapefile from Natural Earth:
    ne_110m_admin_0_countries.zip (184 KB, world map with country borders, scale 1:110,000,000)
  • Note: The instructions are accurate for Natural Earth maps version 2.0.0, the most recent version of the maps available in April 2014.

Step 1: Convert shapefile to Stata format

  • Unzip ne_110m_admin_0_countries.zip to a folder that is visible to Stata, for example the current working directory of Stata. The archive contains six files:
    ne_110m_admin_0_countries.dbf
    ne_110m_admin_0_countries.prj
    ne_110m_admin_0_countries.shp
    ne_110m_admin_0_countries.shx
    ne_110m_admin_0_countries.README.html
    ne_110m_admin_0_countries.VERSION.txt
  • Start Stata and run this command:
      shp2dta using ne_110m_admin_0_countries, data(worlddata) coor(worldcoor) genid(id)
  • Two new files will be created: worlddata.dta (with the country names and other information) and worldcoor.dta (with the coordinates of the country boundaries).
  • If you plan to superimpose labels on a map, for example country names, run the following command instead, which adds centroid coordinates to the file worlddata.dta:
      shp2dta using ne_110m_admin_0_countries, data(worlddata) coor(worldcoor) genid(id) genc(c)
  • Please refer to the spmap documentation to learn more about labels.
  • The DBF, PRJ, SHP, and SHX files are no longer needed and can be deleted.

Step 2: Draw map with Stata

  • Open worlddata.dta in Stata.
  • For the example maps, create a variable with the length of each country's name. The Stata command for this is:
      generate length = length(admin)
  • Draw a map that indicates the length of all country names with this command:
      spmap length using worldcoor.dta, id(id)
  • The default map (Figure 1) is grayscale, it shows Antarctica, there are four classes for the length of the country names, the legend is very small, and the legend values are arranged from high to low.

Figure 1: Length of country names (small scale map, default style)

Click image to enlarge.

  • A second map without Antarctica, with a blue palette, five classes, and with a bigger legend with values arranged from low to high (Figure 2) can be drawn with this command:
      spmap length using worldcoor.dta if admin!="Antarctica", id(id) fcolor(Blues) clnumber(5) legend(symy(*2) symx(*2) size(*2)) legorder(lohi)
  • Darker colors on the map indicate longer country names, ranging from 4 (for example Cuba and Fiji) to 35 characters (French Southern and Antarctic Lands).
  • Please read the Stata help file for spmap to learn about the many additional options for customization of maps.

Figure 2: Length of country names (small scale map, blue palette)

Click image to enlarge.

Alternative maps with more detail

The shapefile that was used for Figures 1 and 2 was designed for small maps. It contains the borders for 177 countries and territories and does not include smaller geographic units like Hong Kong, Monaco, or St. Vincent and the Grenadines. As an alternative to the small scale map in Figures 1 and 2, Natural Earth offers shapefiles with more detail that were designed for larger maps.

  • To create the map in Figure 3, download this shapefile from Natural Earth, which has information for 241 countries and territories:
    ne_50m_admin_0_countries.zip (799 KB, world map with country borders, scale 1:50,000,000)
  • Unzip ne_50m_admin_0_countries.zip to a folder that is visible to Stata.
  • Run this Stata command to convert the shapefile to Stata format:
      shp2dta using ne_50m_admin_0_countries, data(worlddata2) coor(worldcoor2) genid(id)
  • If you need Stata files with centroids, run this command instead:
      shp2dta using ne_50m_admin_0_countries, data(worlddata2) coor(worldcoor2) genid(id) genc(c)
  • Open worlddata2.dta in Stata.
  • Create a variable with the length of each country's name:
      generate length = length(admin)
  • Draw the map in Figure 3:
      spmap length using worldcoor2.dta if admin!="Antarctica", id(id) fcolor(Blues) clnumber(5) legend(symy(*2) symx(*2) size(*2)) legorder(lohi)
  • The map takes longer to draw than the map in Figures 1 and 2 because it is more detailed and shows more geographic units. The names of the countries and territories on the map have a length up to 40 characters (South Georgia and South Sandwich Islands).

Figure 3: Length of country names (medium scale map)

Click image to enlarge.

  • To create the map in Figure 4, download this shapefile from Natural Earth, which has information for 255 countries and territories, including small islands like the Ashmore and Cartier Islands:
    ne_10m_admin_0_countries.zip (5.1 MB, world map with country borders, scale 1:10,000,000)
  • Unzip ne_10m_admin_0_countries.zip to a folder that is visible to Stata.
  • Run this Stata command to convert the shapefile to Stata format:
      shp2dta using ne_10m_admin_0_countries, data(worlddata3) coor(worldcoor3) genid(id)
  • If you need Stata files with centroids, run this command instead:
      shp2dta using ne_10m_admin_0_countries, data(worlddata3) coor(worldcoor3) genid(id) genc(c)
  • Open worlddata3.dta in Stata.
  • Create a variable with the length of each country's name:
      generate length = length(ADMIN)
  • Draw the map in Figure 4:
      spmap length using worldcoor3.dta if ADMIN!="Antarctica", id(id) fcolor(Blues) clnumber(5) legend(symy(*2) symx(*2) size(*2)) legorder(lohi)
  • The map takes longer to draw than the maps in Figures 1, 2 and 3 because it has the largest amount of detail. The differences between the maps in Figures 3 and 4 can be seen by clicking on the images to enlarge them. Figure 4 has more islands and more detailed shorelines. The names of the countries and territories on the map in Figure 4 have a length up to 40 characters (South Georgia and South Sandwich Islands).

Figure 4: Length of country names (large scale map)

Click image to enlarge.

Software used in this guide

  • Stata: statistical software package
  • spmap: Stata module for drawing thematic maps, by Maurizio Pisati
  • shp2dta: Stata module for converting shapefiles to Stata format, by Kevin Crow
  • ne_110m_admin_0_countries.zip: small scale (1:110,000,000) Natural Earth world map with country borders (184 KB)
  • ne_50m_admin_0_countries.zip: medium scale (1:50,000,000) Natural Earth world map with country borders (799 KB)
  • ne_10m_admin_0_countries.zip: large scale (1:10,000,000) Natural Earth world map with country borders (5.1 MB)

Related articles

External links

Friedrich Huebler, 31 August 2012 (edited 18 April 2015), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2012/08/stata-maps.html
Posted by on Friday, August 31, 2012 32 comments
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31 July 2012

61 million out-of-school children in 2010

61 million children of primary school age were out of school in 2010, down from a high of over 110 million out-of-school children in the mid-1990s, according to new estimates by the UNESCO Institute for Statistics (UIS). 32 million or 53% of the 61 million out-of-school children were girls.

The trend in out-of-school numbers since 1990 is illustrated in Figure 1. Much of the global progress over the past 15 years is due to developments in South and West Asia, where the number of out-of-school children fell from a high of 41 million in 1998 to 13 million in 2010.

Progress in sub-Saharan Africa, another region with a historically large number of out-of-school children, has been much more modest, by comparison. Here, the number of children out of school decreased from a high of 43 million in 1996 to 31 million in 2010. As a result, sub-Saharan Africa today is home to half of all out-of-school children worldwide.

In relative terms, the global out-of-school rate fell from 18% in the early 1990s to 9% in 2010, in spite of a large increase in the number of children of primary school age over the same period. However, the estimates by UIS also show that the out-of-school rate and the number of out-of-school children have stagnated over the past three years, partly because sub-Saharan Africa is struggling to increase enrolment rates in primary education while being confronted with continued strong population growth. At this rate, the world is unlikely to reach the Millennium Development Goal and Education for All goal of universal primary education by 2015.

Figure 1: Global number of out-of-school children of primary school age, by region and sex, 1990-2010
Global number of children out of school from 1990 to 2010
Source: UNESCO Institute for Statistics, July 2012. - Click image to enlarge.

The regional distribution of children in and out of school is illustrated in Figure 2. The width of each region in the graph indicates the size of the population of primary school age. The height of the bars indicates which proportion of children in each region is in or out of school.

In absolute terms, Sub-Saharan Africa has the highest number of children out of school (31 million), although its primary school-age population (132 million) is smaller than that of two other regions: South and West Asia, and East Asia and the Pacific. In relative terms, Sub-Saharan Africa also has the highest out-of-school rate of all regions. 23% of all primary school-age children have either never attended school or left school without completing primary education.

In South and West Asia, the proportion of out-of-school children (8%) is smaller than in sub-Saharan Africa and the Arab States, but in absolute terms, the region is home to 13 million out-of-school children, second only to sub-Saharan Africa. More than half of all out-of-school children in South and West Asia live in only two countries: India (2.3 million) and Pakistan (5.1 million).

East Asia and the Pacific has 168 million children of primary school age, nearly as many as South and West Asia, but only 4% are out of school. Still, due to the large primary school-age population in the region, this means that 7 million children are excluded from education.

The remaining regions have significantly fewer children out of school: Arab States (5.0 million), Latin America and the Caribbean (2.7 million), North America and Western Europe (1.3 million), Central and Eastern Europe (0.9 million), and Central Asia (0.3 million).

Figure 2: Global distribution of children of primary school age in and out of school, 2010
Distribution of children in and out of school, by region, 2010
Source: UNESCO Institute for Statistics, July 2012. - CA = Central Asia, CEE = Central and Eastern Europe, LAC = Latin America and the Caribbean, NAWE = North America and Western Europe. - Figure 2 was created with the spineplot add-on for Stata (Cox 2008). - Click image to enlarge.

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External links

Friedrich Huebler, 31 July 2012 (edited 2 August 2012), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2012/04/oos.html
Posted by on Tuesday, July 31, 2012 0 comments
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21 June 2012

Merger of huebler.info and huebler.blogspot.com

As announced in January, the huebler.info website was shut down in June 2012. As of 21 June, all requests for pages at huebler.info are redirected to huebler.blogspot.com.

huebler.info was mainly a mirror of articles posted on the International Education Statistics blog and nearly all content from the old huebler.info site is available at huebler.blogspot.com. Please use the blog search in the right sidebar, under "Search this site", or the blog archive to find content from the old site. The most popular pages from huebler.info, identified through access statistics collected between January and June 2012, are listed below with the corresponding huebler.blogspot.com URL.

Please replace any huebler.info links in your bookmarks and on your website by the corresponding huebler.blogspot.com links. If you are unable to find content from huebler.info with the blog search, blog archive or the list below, you can contact the author by email at fhuebler@gmail.com. I apologize for any inconvenience caused by the shutdown of the old site.

Education statistics

Stata

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Friedrich Huebler, 21 June 2012, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2012/06/blog.html
Posted by on Thursday, June 21, 2012 0 comments
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