Exclusion of a relevant variable from a multiple linear regression model leads to the problem of _____.
A)misspecification of the model
B)multicollinearity
C)perfect collinearity
D)homoskedasticity

Question

Quizplus · Accepted Answer

Exclusion of a relevant variable from a multiple linear regression model leads to misspecification of the model, also known as omitted variable bias. This can lead to incorrect estimates of the coefficients of other variables in the model and distorted predictions.

Exclusion of a Relevant Variable from a Multiple Linear Regression