Wednesday, April 14

Dalai Lama blames inequality for suffering

His Holiness the Dalai Lama tweeted a thought-provoking sentence on Twitter yesterday: "Economic inequality, especially that between developed and developing nations, remains the greatest source of suffering on this planet."

It's a loaded statement for 140 characters or less, and I was left pondering whether the Dalai Lama is correct. Certainly it's easy to accept that poverty — a lack of being able to afford basic necessities — can cause suffering. But it's not clear to me that economic inequality — a big variance in individual incomes — also causes suffering. I decided to try and test the Dalai Lama's theory.

A common way to measure economic inequality is with the Gini coefficient. A coefficient of zero indicates complete equality, whereas coefficients close to 100 indicate high levels of inequality. The CIA World Factbook provides a list of Gini coefficients by country for household income. It also provides data on GDP per capita, which is a half-decent measure for suffering (or lack thereof). We'd expect that the higher a country's GDP per capita, the less suffering its people experience.

I combined the Gini coefficient data with GDP per capita data to create a data set for 134 countries. Plotting the data, there doesn't appear to be any obvious link between a country's Gini coefficient and its GDP per capita.


However, when I run a simple regression using the data, it turns out there is a statistically significant correlation. Each one-point increase in a country's Gini coefficient can be expected to reduce its GDP per capita by $603.

I did another regression, replacing GDP per capita with life expectancy (we'd expect people with shorter life expectancies to suffer more). It again appears that more income inequality is correlated with shorter lives. I observe that a one-point increase in the Gini coefficient reduces life expectancy by almost half a year.

I can't say definitively that income inequality causes poverty. It may be other factors that are actually causing the results. For example, perhaps countries with high Gini coefficients tend to have corrupt governments, and it is having a corrupt government that is actually causing the lower GDP per capita or lower life expectancies. My analysis doesn't control for possibilities like that. I'd be more convinced of the Dalai Lama's statement if I could observe how countries' Gini coefficients and GDP per capita or life expectancy changed over time, since it would allow me to control for some of these unobservable differences between countries.

This is by no means a perfect test of the Dalai Lama's theory. Life expectancy and GDP per capita aren't perfect measures of suffering. And more importantly, the Dalai Lama emphasizes that it's inequality between countries that is particularly responsible for suffering; I tested inequality within countries. To test inequality between countries I'd need multiple years of data, which was not readily available.

But it does seem (much to my surprise) that the Dalai Lama's theory is consistent with what we observe in the real world.