When I sat down to look at the income inequality index for Cameroon, I thought I would spend most of my time defending Cameroon for the poor performance it’s done relative to other countries. Instead, the joke’s on me. Before your mind is blown, let’s look at some basic data you probably already know comparing Cameroon and the United States:
Source: Cameroon & The United States
The Gini coefficient is a measure of the inequality of a distribution, a value of 0 expressing total equality and a value of 1 maximal inequality. To be clear, income distribution should not be confused for a quality of life ranking. Measuring inequality is just that–examining the divide, not the average. Inequality has more than individual implications. Broadly, it affects social mobility, infrastructure, political stability, and immigration/brain drain. A distorting factor of these values is that the gini coefficient does not take into account corruption and fraud.
When I was rifling around for Cameroon gini data, I thought to myself “Wait, Cameroonians don’t pay income tax. How do they calculate this?” Well, luckily I came across this paper from the University of Yaounde, where I found out there have been three large scale consumption surveys, the last two surveys reaching more than 10,000 households, that are representative of the total population. According to the 2011 UNHABITAT paper on urban inequality, the gini can be calculated two ways; consumption and income based inequality rankings. Both the income and consumption inequalities are linked to broader economic factors like labour markets, capital investment in public services, lack of pro-poor services etc. Using consumption based gini coefficients are a stronger indicator of inequality because high gini coefficients also denote unequal access to public goods, which may act as a hindrance to poverty reduction strategies and achievement of Millennium Development Goals.
My inspiration began with this error ridden article in the Atlantic, but I was still shocked to find that the States and Cameroon aren’t so different when looking at income distribution. There are multiple places to get your gini coefficients. Mr. Fisher of the Atlantic used the CIA World Factbook, but I prefer UNDP because of it’s international presence and intuitive presentation of data. When I was comparing his own maps and comments to the UNDP, they didn’t match up all of the time. So I made my own visual.
Below is a Venn Diagram, highlighting countries based on their gini coefficient. Conveniently in the middle, you will see Cameroon and the United States, who happen to have comparable levels of inequality. The countries in the purple, center section all fall between the narrow difference in coefficients for Cameroon and the United States. All countries were selected based on regional and economic diversity–it wouldn’t be helpful to only put Europe in Blue and Africa in Red.
Here are some of the major takeaways of the UNDP data:
- In terms of Human Development Index Rankings, the United States (no. 5) sticks out like a sore thumb when examining it’s gini coefficient. Aside, from Israel (no. 19) and Qatar (no. 31) there isn’t a lot of variance at the top. There are a lot of mid-20’s and low-30’s of almost exclusively Western European countries, indicating a higher level of income redistribution (tax, social welfare programs etc.) among classically “successful” nations. Most highly ranked countries have an average gini coefficient of 32.6, substantially lower than the United States–even when factoring an average that includes an outlier like the United States.
- The United States having a high gini coefficient could be indicative of low levels of income redistribution (low tax rates, etc.) compared to other highly ranked UNDP countries. The U.S. is a great place to be if you are extraordinary, but less so if you are average compared to other OECD countries.
- Latin America seems to struggle with inequality, Nicaragua was the only country in Latin America within the 38.9-40.8 window. As a group, they average a gini coefficient of about 47.4
- The base for countries that have a similar gini coefficient can have a huge variance. For example, a country like Norway, with a gini of 25.8 and Afghanistan with a gini of 27.8 have similar distribution levels of consumption, but the “Bottom” or starting points are worlds apart. The same could be said for the United States and Cameroon.
In my village, there are several “big men”, people with wealth. What is different about how wealth is handled here is that they build a 5,000 square-foot house along the road, next to shanties. I feel like, compared to my upbringing in metro Detroit, wealth is more visible here, andt also less segregated. It is not just during funeral season that the wealthy come out, they participate and sponsor most of the social events here informally. My friend Brittany asked me, how large are the elite class in the U.S. compared to Cameroon? I don’t know. My impression is that, as a percentage, there are more wealthy people in the United States, but the spread is also wider. The big question here seems to be is this a problem?