Endogeniety simply means that a parameter or variable is correlated with the error term. There are many reasons why this would happen:

  1. Measurement error
    • This happens when we do not have an accurate measure of the independent variables.
  2. Omitted variables
    • This happens when the model does not include all the variables it should, and thus we have an uncontrolled variable.
  3. Simultaneity
    • 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)

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