Question

Suppose you are interested in estimating how health affects productivity. Specifically, you are interested in the following regression:

2)

where Yi is a variable representing the income earned by person i, and Xi is a variable representing the health of person i.

Income is a fairly straightforward concept to capture. Health, however, is a more complex concept that can be measured in many different ways. For example, body mass index (BMI - weight in kilograms, divided by height in meters squared) is one indicator of health. People with very low BMI are considered underweight (which is typically not healthy) and people with very high BMI are considered overweight (which is typically not healthy).

Answer 1

9) In this regression, an endogeneity problem might be created by the variable denoting the education level. The education level is an important determinant of income, it is also correlated with the health of the person. More educated person are more likely to be healthy and less likely to be infected with a diseases. This omitted variable would bias our estimate of beta. More specifically, our estimate of beta would be higher than the true beta since it also incorporates the education effect on income.

10) In these regression, there might be the problem of reverse causality since it is highly likely that our income level is going to effect our health level due to access to quality treatment or practicing of quality hygiene, etc.