I am looking for some clarification regarding when multicollinearity (btw i hate spelling that word) is a problem. I understand the, not individual significant but collectively significant t-test/ F-test logic, but I just encountered a QBANK question that only gave info on independant variable correlation coefficients (i.e. no info to calculate an F-test). The highest magnitude rho was 0.43 and the answer implied that due to the high rho of 0.43 multicollinearity was a problem. Not sure if the QBANK question was simply bad, but is a rho of 0.43 indicative of multicollineraity (strikes me as a bit too low to indicate existence of a linear relationship)? Mike
can you please post the entire question… in absence of more info… what do u expect us to respond?
i cant give more due to copyrights. but, i think you have what you need to answer.
many of us have QBank - you can provide the Qbank ID. and what are you talking about? Lot’s of folks do post QBank questions here - for asking questions…
Question ID#: 86547 3rd question. thanks for looking into this.
Regression 1: R^2 was 0.2244 t-stat for T-bill = 1.98 t-stat for S&P 500 Return −0.0161 / 0.032 = 0.5031 t-stat Global index return = 0.0037 / 0.034 = 0.1088 Neither of these is significant for t 0.05,16 so one of these related variables was dropped - which looks like the standard case for Multicollinearity.