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Which one of the following problems will not cause the endogeneity problem in a linear regression model? a. Errors-in-variables. b. Omitting relevant variables. c. Including irrelevant variables. d. Simultaneous equations.

Question

Which one of the following problems will not cause the endogeneity problem in a linear regression model?

a. Errors-in-variables.

b. Omitting relevant variables.

c. Including irrelevant variables.

d. Simultaneous equations.

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Solution

The answer is c. Including irrelevant variables.

Endogeneity problem in a linear regression model is caused when there is a correlation between the explanatory variable and the error term. This can be due to measurement errors (errors-in-variables, option a), omitted variables (option b), or simultaneous equations (option d) where the dependent variable in one equation is used as an independent variable in another.

However, including irrelevant variables (option c) does not cause endogeneity. It may reduce the efficiency of the estimator and increase the standard error, but it does not bias the estimator, hence it does not cause an endogeneity problem.

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