Exploring the Wealth of Nations
Highlighting relationships between national wealth and various socio-economic indicators
Explaining the wealth of nations has been a topic of discussion and research since Adam Smith published his “Wealth of Nations” in 1776. The US Congress introduced the metric of Gross Domestic Product to measure national wealth in 1937 and since then it has become the ultimate yardstick in this regard. Simply put the Gross Domestic Product (GDP) is the total value of all goods and services produced in a country in a given year. The measure though elaborate does suffer from some weaknesses and some economists will highlight drawbacks like income inequality not being represented in it etc. Still GDP remains the most commonly used measure for quantifying and comparing national wealths. To normalize for the effect population, the metric of GDP per Capita is used which is just the GDP figure divided by the total population of the country. To further neutralize the effects of different currency exchange rates, the concept of Purchasing Power Parity (PPP) is used. GDP per Capita using PPP is the standard yardstick for comparing the wealth of nations.
The wealth of nations like the wealth of individuals can have quite complex relationships with different factors. Let us first study the rhetorical question i.e. “can money buy happiness?” in the context of nations. At the national level the data does suggests a clear ‘Yes’ as the answer. I took data from the the World Happiness Report 2020 published by the Sustainable Development Solutions Network, New York [1] for this analysis. This report uses Gallup World Poll and Lloyd’s Register Foundation’s World Risk Poll to directly calculate happiness scores for nations. The report itself identifies GDP per Capita using PPP as the single biggest factor that can explain the variations in national happiness scores. To explore this further, I have plotted below the happiness score and the GDP per capita using PPP. The two variables have a very strong correlation (Pearson’s correlation coefficient of 0.75). In fact amongst all the variables that I considered for this analysis, the correlation of national wealth was strongest with the happiness score for the country. Wealthy nations have a happier populace or may be happier nations are wealthier. Correlations don't predict causality so we have some food (data) for further thought here.
I also looked at other variables that have strong correlations with the wealth of nations. One comprehensive indicator recently launched by the World Bank is the ‘Ease of Doing Business Score’ [2]. The score considers a variety of legal, regulatory and economic indicators to rank nations on their ease of starting and running a business. The plot below shows the relationship. The ‘GDP per Capita’ and ‘Ease of Business Score’ also have a strong correlation coefficient of 0.64. Its easier to start businesses in wealthier nations. Low income countries need to pay special consideration to this. National wealth primarily comes from booming private businesses. Ease of doing business reforms promote private businesses and thereby leads to higher national wealth.
There are other indicators like urban population percentage that also have a strong positive correlations with the GDP per capita (Pearson’s coefficient of 0.65). Cities act as engines of economic growth in a modern economy and therefore urbanization should be promoted and properly managed. There are some indicators that have a significant negative relationship with national wealth. One of them is the national population growth rate, as can be seen in the plot below.
This analysis is by no means exhaustive. The selection of indicators is arbitrary and new indicators may be selected for future studies. The heatmap below map shows the correlations between the various national socio-economic indicators. In addition to the correlations with national wealth, there are other interesting relationships which can be seen in this heatmap.
For example, average life expectancy of country is highly correlated with electricity access. It also has a very high negative correlation with the national population dependency ratio that is defined as the number of dependents per 100 members of active labor force. Most likely this effect is due to a high number of children per family and higher infant mortality rates. Similarly, population growth rates and population dependence ratios have negative correlations with most indicators of economic development. This underlines the need for proper human resource development in low income countries. In conclusion, there is ample data available for exploration in the public sector domain. The best resource in this regard is the World Bank Open Data API [3].
Note: The code for this analysis is available for public use at :
https://github.com/janjuatest/Public-Sector/blob/main/GDP.ipynb
- Helliwell, John F., Richard Layard, Jeffrey Sachs, and Jan-Emmanuel De Neve, eds. 2021. World Happiness Report 2021. New York: Sustainable Development Solutions Network.
- Doing Business,
https://www.doingbusiness.org/en/rankings - The data for the indicators was obtained from the World Bank Open Data API:
https://datahelpdesk.worldbank.org/knowledgebase/topics/125589
