Indicators… albeit very useful to synthesise concepts, they are also good at hiding variations and putting slightly different situations into just one bucket. Sometimes the devil is in the details, and when we look through these generalisations we risk an overly simplistic view of things. Many argue this is case with the Human Development Index (HDI).
The HDI aims to incorporate health and education measurements into a more balanced development metric. It has been traditionally measured at a country level and classifies nations in for levels of development. If we map the vaues for 2018, we have the below map (interactive version here).
Probably, this map conforms with a traditional view of the world: on one side we have highly developed, industrialised economies. African countries are situated on the other extreme of development, with Latin American and Asian countries covering the range in the middle.
As some people argue (for example here), reality is a more diverse than a clear division between “rich” and “poor” countries. Although useful as a rough idea, a single national HDI will hide this diversity. For examples, income extremes in Chile may make people feel they live in different countries. Increased urbanisation in developing countries may also create income disparity between urban an rural populations but will also have an impact on the access to education and health services.
To reflect this geographic differences, the people at Global Data Lab from Raboud University in the Netherlands have calculated a subnational Human Development Index for 1,765 regions across the world. Put on map, we then have something like this (interactive version here):
If you explore the map, it is possible to see a more nuanced version how development is generally no equal in each country. Even though almost all of the traditionally developed countries manage distribute this development more o less evenly across their territories. The only exception to this is France, with French Guiana (technically equal to the European departments) being less developed than the rest of the country. In the other countries, we can observe that:
- Countries like Chile or Malaysia have several regions lagging behind – Santiago or Kuala Lumpur may be highly developed but more rural areas are not. This is probably one of the factors that keeps them apart with other countries with comparable income levels.
- The previous statement seem to be valid for most of the other countries. Yes, there are large areas of Africa where HDI are low, but their big cities are areas of development.
- This is special through in some countries where key areas are already highly developed – like Lima, Mexico City, Brasilia and Bogotá in the Americas or Shanghai, Beijing, Bangkok and Ulan Baator in Asia. Most notably, there is already a very high HDI region in continental Africa, around Gaborone in Botswana.
The good news is that we consider urbanisation, 57% of the population already leave in areas with very high or high HDI. This is presented in the below chart:
Generally speaking, the above sounds like good news. If countries already have areas punching above their respective national indicators, is this a sign of good things to come for the rest of the country? If income keeps growing, will in mean that eventually all regions of a country will even out, as shown by the already developed economies? To try to see that, let’s have a look at the relation between the regional HDI gap (the difference between the highest and lowest HDIs in a country) and their national HDIs. This is presented in the below chart:
From this chart, it is possible to observe a very week correlation, where a higher HDI seems to come with lower regional gap. However, when we observe how this evolves over time for each country, we have a different picture, as shown by the animated chart below (please press play):
In those (arbitrarily) selected countries we actually have the whole range: for instance, in India progress in HDI brings a smaller gap; in Lybia and Australia response is rather flat; and in Chile and Malaysia national HDI improvements don’t have the same rate nationwide.
When trying to find a commonality between countries with the same behaviour, I couldn’t be able to find such. Political or administrative systems, continent, income brackets, etc. just don’t explain we this happens on their own. The only explanation I could find is that perhaps in the different countries there is a stronger will and more decisive actions from countries to make sure development happens across their territories, regardless their remoteness or low population. For instance, Australia spends intensely to bring medical and education services across remote communities, for instance investing in infrastructure and staff for remote clinics and schools and having an excellent aeromedical services. In Norway, there is an excellent network road and there is an excellent ferry service running throughout the year.
As they develop, countries should take note of this and not take for granted that progress will happen evenly – effort needs to be put (and money needs to be spent) to guarantee it spreads evenly.
The details / Notes
- This is just a personal opinion after exploring the data. I am not an expert on the field.
- As I mentioned in the start, indexes are reductive by nature.
- Data comes from the Global Data Lab at Raboud University.
- This has been created with RStudio, using Plotly and Leaflet.
- Map Layer by Stadia Maps.
- Country shapes have been created using shapefiles from Geoboundaries.
- The author does not take any responsibility on how this data is used. Don’t believe in everything you read on the Internet! The link to the source data has been provided, so you can check if I’ve made a mistake.
- R Notebook file available here