Implications of multicollinearity:

There  are  two cases  as we mentioned earlier,  viz., perfect multicollinearity and less than perfect multicollinearity.

I.  'If multicollinearity is perfect  in the  sense  of  equation,  the  regression coefficients are indetemninate and their standard errors are  injnite.

2.  If multicollinearity is less than perfect  as  in  equation, the  regression coefficients  are determinate but possess  large standard errors (in relation to the  coeflcients themselves), which means  that  the coefficients cannot be estimated with great precision or accuracy.