We now have data for 219 countries and territories for 1800-2007, although the data for the 19th century are largely based on rough assumptions. For a couple of countries the revisions mean substantial changes. You can still find the old version of the indicator, under “For advanced users”.
See the new indicator here. Note that the revisions also apply to all the “gaps within countries” graphs.
A new international comparison in math achievement has just been released. Here we have plotted the average achievement for children in the 8th grade against Income per person in each country. Here we have the same graph but with the results for 4th graders. As can be seen, the top five achievers are all East Asian countries.
You find the indicators under the heading “Education” -> “Achievement”. A higher score means better achievements in the test. The data is based on an international math test for children in 4th and 8th grade, from the TIMSS (Trends in International Mathematics and Science Study).
Income per person (i.e. GDP per capita) has been updated to 2007.
Here is one example for 2007 where income per person is plotted against Life expectancy at birth.
Note that the GDP data will be revised in a near future, taking into account the latest round of PPP from the ICP.
At the new documentation page you will find the documentation for the indicators compiled by Gapminder, including population. There you can also download an Excel-file that includes not only all the data, but also information on sources and estimation methods for each observation.
To the extent possible we have also used this information to give each observation one of these “data quality ratings”:
Continue reading “"Data quality" & documentation for Population added”
We have updated the indicator “population, total” so that it covers all countries and territories from 1800 to 2008. Population is by default used for the size of the bubbles in Gapminder World.
With “all countries and territories” we mean all the 192 UN-member plus 61 other entities (e.g. semi-autonomous territories, former countries and disputed territories). This gives a total of 253 countries and territories.
This work rests heavily on the work of Angus Maddison and is, to our knowledge, the most complete data set for population, containing over 20.000 observations. To the extent possible, we have also included meta-data for each observation with information on sources and estimation methods. Where possible, we have also included a quality rating of the observations, of which more of in the following blog-post.
Note: some of the observations, especially the earlier ones, are based on very rough estimates or extrapolations. Please check the data quality rating of the observations, described in the next blog-post.
At request we added a new indicator for consumption of sugar and sweeteners per day and person, i.e. it measures how many grams sugar and sweeteners does each person consume in one day.
In this graph we plotted sugar consumption against income per person.
It is of course tempting to plot this indicator against “bad teeth per child”.
In this graph we have done precisely that. However, the link between the two indicators seems to be relatively weak.
NOTE: the figures for 2004 is based on a very rough extrapolation (i.e. we use the data for 2003) and this was only done to allow a comparison with “bad teeth per child”.
We have updated the map in gapminder world. We removed all “former countries” and “ad-hoc” areas, but included all small countries and territies. We included even the smallest countries and territories, such as Pitcairn (where the mutineers of bounty settled) and Canada’s somewhat less known neighbour St.Pierre-et-Miquelon.
You find the map under the tab “map” in Gapminder World. You can also follow this link which takes you directly there, although it should be noted that the direct link is slower than normal since additional map-related data has to be loaded.
We have added a menu to the right of the Gapminder World to improve the usability. This new feature allows you to directly from the graph access information about the graph, find relevant links, watch tutorials, participate in discussions about the data, get tips on how to use the graph, and much more.
Go to the graph to see the new feature.
We have just started to experiment with this feature so for now we only have included a few points, but more will be added with time. Comments and suggestions are warmly welcome.
We have added a new indicator: “bad teeth per person” (you find it under “health” in the Gapminder World).
Here we have plotted “bad teeth per person” against “income per person”. Is dental problems worst in the richest or the poorest countries? There actually seem to be a tendency for the dental problems to be larger in the middle income countries, while the population in the richest and poorest countries have somewhat better teeth.
“Bad teeth per person” show how many decayed, missing or filled teeth an average 12 year old has in each country. The technical term of the indicator is DFMT for 12-years old and the data is taken from the WHO. We have unfortunatly only data for one year. Note that the data in many cases are actually based on estimates for earlier years.
There are some interesting discussions concerning this indicator over at Chris Blattman’s blog as well as at the meaningfullness of little things.
We have added a new page where we explain some of the principles we used for the countries & territories in Gapminder World (e.g. how we try to handle changes in country borders). You can find the page among the links on the right-hand side.
A new indicator called “year 1950-” has been added (you find it under “other”).
It simply shows the year, i.e. when we look at data for 1960 the indicator will be 1960 for all countries.
By using this indicator for the color of the bubbles (which you do in the top right corner of the graph) and using “trails” for a selection of countries you can more easily compare the development over time of these countries.
Here you see an example of this (opens in a new window). The development of China, USA, Botswana and South Africa between 1950 and 2005 is compared. The blue bubbles show the situation in the 50’s, the green bubbles show the situation in the 70’s and so on.
Note: the indicator only starts at 1950 so obervations before 1950 will be without colors.
Here is a link to the spreadsheet of the indicator.
On request we now add the new indicator “Public & private health expenditure (% of GDP)”.
It shows how big share of the average person’s income is being spent on health care, whether it is through the tax they pay, the health insurance they have or through out-of pocket expenses.
Here the indicator is compared with Infant Mortality in Gapminder World.
Here is a link to the spreadsheet of the indicator.
Unfortunatly the indicator only covers the years 2000-2004 (with three exceptions), so any tips on where we can find data covering more years are most welcomed.
On request we now add the new indicator “Growth in income per person (% per year)”, defined as the annual growth in Gross Domestic Product per person (percent increase from one year to next). It covers the period 1961-2005.
Note: this indicator is not necessary fully consistent with the “Income per person” indicator since different sources has been used.
Here “Growth in income per person” has been displayed against the level of “Income per person” in Gapminder World.
Here is a link to the spreadsheet of the indicator.
The indicator population has been updated and expanded to cover more countries and territories and a longer time span. It now covers 251 countries and territories, including all of the 192 UN member states. 205 of them have data going back to at least 1820 (and 51 goes back as far as 1600).
Furthermore, the documentation has been more systematic (the full documentation will be available in a few weeks).
NOTE: the unit has been changed from “1000 persons” to “number of persons”.
NOTE 2: some of the observations (particulary the earlier ones) is based on very rough estimates. See the (coming) documentation for details.
The data for Iceland after 1975 was incorrect for “income per person (fixed PPP$)”. This has now been corrected. Thanks to Björn Helgason for pointing out the error.
