Income per person for Democratic Republic of Congo has been revised. We have made an upward adjustment of the income for 2005 with 25%. We have also adjusted the growth rate from 1991 and on. Congo is still the poorest country in the world. The background and details of this adjustment are documented in our documentation, (p. 23-25).
The data for “Children per woman (total fertility)” has been updated to cover 195 countries from 1800-2008. It is now possible to see the entire “demographic transition” that most countries have followed: going from many children and short lives, too few children and long lives.
We have made a number of revisions of “Income per person”. Continue reading ““Income per person” revised”
The name of the main income indicator shown when Gapminder World is started has been revised for clarity, but the data remain the same. It is now called “Income per person (GDP/capita, inflation-adjusted $).
A new data set on the HIV epidemics in each country since 1979 is now available in Gapminder World. The dataset is an expansion of the excellent UNAIDS data, and illustrates several interesting points.
Here is a moving graph with the percent adults infected with HIV in each country plotted against the GDP per capita. The size of the bubbles shows the number of people infected with HIV in each country (not the total population, as is usual in the Gapminder graphs). Click Play to see the epidemic from 1979 to 2007, and to see new surprising trends.
We have made an update of the indicator Life expectancy at birth. To see this indicator together with Income per capita, follow this link.
The biggest change is that we now show this indicator for 155 countries back to 1800, although in most cases, the early estimates are based on a very rough model. This full dataset is not suitable for statistical analysis. Please consult the documentation for information about sources and data quality. A spreadsheet with detailed source information will be added later.
You can also see some tentative information about data quality in the graph, look for this under “For advanced users” -> “Data quality”, or use this link. Red is “very poor quality data” while blue is “very good quality data”. Read more about our data quality ranking in this previous blogpost.
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.
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.
Gapminder World now incorporates the latest update on carbon dioxide emissions from burning fossil fuels. This update adds more recent data and makes some corrections for earlier years. Data are now available from 1751-2005.
See this example graph which shows CO2 emissions per person against income per person, with the bubble size representing total CO2 emissions.
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.