Endogeniety simply means that a parameter or variable is correlated with the error term. There are many reasons why this would happen:
- Measurement error
- This happens when we do not have an accurate measure of the independent variables.
- Omitted variables
- This happens when the model does not include all the variables it should, and thus we have an uncontrolled variable.
- This happens when two variables are each affecting the other.
To address endogeniety, there are a few options:
- Use instrumental variables address omitted variables
- Heckman correction models address the sampling bias and unobservable variables
- If the data is not a panel, then propensity score matching could help a small sample
- Run a 2SLS or 3SLS
(Adapted from course notes)
(Flashcards and other resources here)