Consider the Multiple Regression Model with Two Regressors X₁ and X₂

Multiple Choice

Consider the multiple regression model with two regressors X₁ and X₂, where both variables are determinants of the dependent variable. You first regress Y on X₁ only and find no relationship. However when regressing Y on X₁ and X₂, the slope coefficient $\widehat { \beta 1 }$ changes by a large amount. This suggests that your first regression suffers from

A) heteroskedasticity
B) perfect multicollinearity
C) omitted variable bias
D) dummy variable trap