Estimation of regression coefficients in the presence of high but not perfect multicollinearity may result in all of these except:

Correct option is B

Correct Option: B: Almost all the estimates are statistically significant
Explanation: High multicollinearity generally reduces t-statistics, making coefficients statistically insignificant, so it cannot result in “almost all estimates are statistically significant.”
Information Booster:
1. BLUE property is preserved under high multicollinearity as long as there is no perfect multicollinearity.
2. High multicollinearity inflates standard errors, widening confidence intervals.
3. R² can be high because correlated predictors jointly explain Y well.
Additional Knowledge:
1. Remedies for multicollinearity: Ridge regression, removing variables, PCA.
2. Variance Inflation Factor (VIF) > 10 indicates high multicollinearity.
3. Perfect multicollinearity violates Gauss–Markov assumptions and makes estimation impossible.