Hi.
I am doing two time-series regressions, both regressions contain 3 mutual variables with several other variables in them.
Set 1: A B C D E F G
Set 2: A B C H I J K L M
I am running covariance matrix (looking at the correlation amongst variables for both regressions). However, since the 3 mutual variables are present for both regressions, do I still include these 3 variables in the covariance matrices for both regression? I am not sure because the correlation coefficients for the same mutual variables are different.
For instance,
Set 1: A-B = 0.5678
Set 2: A-B = -0.4892
Any helps will be greatly appreciated.
Thank you!
Of course, you do otherwise how would you know cor(F,M) for example. you didn't specify the models but I am assuming that this coefficient is of some value somewhere. Even if it is not how does running the full matrix hurt anything?
D. Booth
You need the correlation matrix to check the relation between the response variable and explanatory variables and investigate the multicollinearity among explanatory variables. If your data is time series I think you need to check ARIMA with exogenous variables.
CODING for your two sets of data may cause confusion. You AB in the first set and AB in the second set are not the same. You need to rename the second set to avoid confusion. Note that you first AB and second AB are not in the same direction; one is positive and another is negative.
This is what you have:
Set 1: A B C D E F G
Set 2: A B C H I J K L M
Suggest to recode:
Set 1: A B C D E F G
Set 2: Aa Bb Cc Hh Ii Jj Kk Ll Mm
Now re-rum your matrix, you will not have confused reading. Now you should have A-B; A-Bb
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