Regression Models problem =_=
hi guys! i need your help here..
i have raw sugar data (dependent variable) and as for independent variables, i have white sugar, white sugar premium, crude oil, ethanol and corn.. all these data are in USD/Metric tonne..
basically i want to create the best regression model to predict future prices.. i took the data from 2007 till now.. (may 2010)
the problem that i have here is that, when i test the correlation between all the independent variables toward dependant variable, the correlations between ethanol and raw sugar is quite high (0.7) but when i used all the data from 2007-2010, the correlation is very very low.. (0.04)
in certain years, ethanol n crude oil affect raw sugar price quite strong.. but some times, it doesn't affect at all. should i include this variable in my model?
if what i did was wrong, could you suggest what should i do to create the best model to predict raw sugar price? thanks a lot..