Tails or Average

When you read a blog using statistics you will be –mostly- reading about averages. Why? Because when researchers try to grasp a relationship between two variables, the best way to uncover this is through what economists call conditional expectation. What does conditional expectation mean? It means -in common parlance- (conditional) average. Let me explain this concept with an example.

Many economists have tried to find the relationship between years of completed education and earnings. The common sense would say that if you study more years you would earn more money. To find if this is true, however, is not trivial. For each year of schooling there can be enormous variation; while some people with 8 years of schooling earn $850 USD per month, other people with the same years of schooling earn $6,500 USD. This situation poses a problem to the researcher. How can she/he detect a relationship between schooling and earnings with that enormous variation? The answer to this question is using averages; if you estimate the average earnings per year of schooling, it will be easier (more likely) to detect this economic relationship. The following graph from the excellent book Mostly HarmlessEconometrics explains how this works.

Why I bring this to the blog? Because of something that caught my eye during my internship: the appalling situation of some (few) women in India. It interested me because when I read about Indian women, they almost never describe the lives of these women. Why? Because these women are a minority –they are on the tail of the distribution. Therefore, you will find it harder to detect an economic relationship by focusing on these women.

What exactly caught my eye?

1. That some women didn’t know their birthday.
2. That some women got married when they were between 8 and 12 years old.
3. That some women had their first child when they were 13 years old.
4. That some women didn’t know how to read, write or count.
5. That some women didn’t go to the hospital to deliver their baby because she didn’t understand the pain (they didn’t know that they were experiencing contractions and would soon be in labor).
6. That some women didn’t have a name: they were referred to as someone’s daughter, then someone’s wife, to end up as someone’s mom.
7.  That –unsurprisingly- these women were more likely to be stunted or underweight.  

These facts describe the lives of some women but not the average Indian women. The less unfortunate will have a name, will get married at a more reasonable age, and will know their birthday. That’s why I posed the question tails or average? Because sometimes it is important to design policies to help not the average women but the one’s in the tail of the distribution, those who are living a true nightmare.