The Wealth of Nations: income, cost of living, and purchasing power for 110 countries

Map of global wealth -- income vs. cost of living  

In this post, we’ll walk through a map of global wealth — with data on incomes, cost of living, and purchasing power across 110 countries.

The data is visualized below in three ways: a geographic map, scatterplot chart, and a tool to compare countries head-to-head.

Using this data, we can answer questions such as:

The data is sourced from WorldData.info based on the year of 2023.

All data is shown as a relative index, where the value for the United States equals 100. An index value of 120 means “20% higher than USA”, while an index value of 75 means “25% lower than USA”.

 

Map of Global Wealth (Income, Cost of Living, and Purchasing Power)

Use the map below to explore data across the globe. You can scroll and zoom to see more countries.

Hover/click on any country for more info.

The drop-down menu lets you choose between analysing cost of living, income, or purchasing power [1]. Countries are color-coded based on their index value (brighter colors = higher values).


 

Note [1]: “Purchasing Power” is a metric that takes into consideration both income and cost of living, to determine whether one country is richer/better off than another country.

For example, average income in Switzerland is 19% higher than average income in the USA. However, cost of living is 26% higher in Switzerland. Therefore, on a purchasing power basis, people in Switzerland are ~6% poorer (they can buy less goods and/or save less than the average American).

 

Scatterplot Chart — Income versus Cost of Living by Country

The scatterplot chart below compares incomes against cost of living for all 110 countries in the dataset. Each country is represented as a dot, where the dot is color-coded by world region and sized based on population.

Hover/click on any dot for more info.


 

The “average incomes” used in this analysis are calculated using an arithmetic mean.

The average income of a country is computed using gross national income (GNI) and the population of the country. Dividing all earnings/profits of the country (i.e., GNI) by the total population gives the average income per person.

Please note that this includes wages/salaries, but also other income, such as capital gains and dividends.

As many readers are probably thinking, “average income” is a flawed metric that doesn’t do a good job of adjusting for income inequality. I’m absolutely in agreement with that.

Median income would be a preferred metric to use for this. If you know of a reliable data source for median incomes across most countries in the world, please let me know and I will adjust accordingly. As it stands, this is the best data I was able to find.

 

Head-to-Head Country Comparison

Select any two countries below, and the table will provide a head-to-head comparison of the income, cost of living, and purchasing power in those countries.

Note: these are relative index values as of 2023, where USA = 100

A B A vs. B
Country
Cost of Living
Income
Purchasing Power

 

Full Data Table

The full dataset is presented below. Click on any of the column headers to sort by ascending or descending order.

Note: these are relative index values as of 2023, where USA = 100

 

Sources, Notes, and Closing Remarks

The data is sourced from WorldData.info based on the year of 2023. This has been compiled based on data from the OECD, World Bank, IMF, and Eurostat.

Mapping was done using the leaflet.js library, together with mapping tiles from OpenStreetMap.

The scatterplot chart was created using the d3.js data visualization library.

If you liked this post, you may be interested in some of my other tools and data essays:

That’s all for now! Thanks for joining me on this data deep dive 🧐. Feel free to leave any comments or questions below.




       

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Comment Section

4 Responses to “The Wealth of Nations: income, cost of living, and purchasing power for 110 countries”

  1. Sam says:

    This is an incredible data visualization! Makes it easy to pick out global outliers like Bermuda / Cayman Islands / Norway.

    Great work

  2. EWF says:

    Really beautiful presentation of the dataset — bravo.

    d3.js is a really great library for data viz

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