In a multiple linear regression model, the presence of perfect multicollinearity among the explanatory variables will primarily result in which of the following issues?

Solution: · Multicollinearity refers to a high linear correlation among two or more independent variables. · Perfect Multicollinearity means one explanatory variable is an exact linear function of one or more others (e.g., X2=2X1+5). · Mathematical Result: OLS requires calculating (X′X)−1, the inverse of the matrix of sums of squares and cross-products of the regressors. Perfect multicollinearity makes the X′X matrix singular (its determinant is zero), meaning its inverse (X′X)−1 does not exist. Without this inverse, the OLS estimators (β^=(X′X)−1X′y) cannot be computed or are undefined.