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Explain multicollinearity and the consequences one is likely to encounter in cases of near or high multicollinearity (3 marks) ii. Define Variance Inflation Factor and explain how it can be used to detect the presence of multicollinearity in a model. (3 marks) iii. Consider the following estimated Ordinary Least Square results where the sample size is 5 Yt = 1.2108 + 0.4014X2i + 0.0270X3i Se (0.7480) (0.2721) (0.1252) R 2 = 0.8143, r23 = 0.8285 (correlation between X2i and X3i) Is multicollinearity present in the model? Give reasons to support your answer. (3
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