Question

why does endogeneity lead to biased OLS estimates?

Answer 1

Endogeneity :

In econometrics, endogeneity broadly refers to situations in which an explanatory variable is correlated with the error term.

OLS estimates :

In statistics, ordinary least squares (OLS) is a type of linear least squares method for estimating the unknown parameters in a linear regression model

endogeneity problem when there is a correlation between your X variable and the error term in your model. What does this mean? the error term in your model is due to all of the stuff in your dependent variable that is not due to the variables you have in your model. So in the broadest sense an endogeneity problem arises when there is something that is related to your Y variable that is also related to your X variable, and you do not have that something in your model. Call that something Z, although notice that I have not claimed that Z is a variable – it is just a “something.”

Endogeneity problem arries example

Endogeneity are properties of variables in economic or econometric models.