I need a help to find out reasonable explanation for my model specification.
After running simple linear regression using OLS, ROBUST standard errors(due to
heteroskadasticty) and SUR, it turned out that log linear regression:
log(y)=a1+a2log(x1)+a3log(x2)+a4log(x3)+...e
seems to be fit so well in any cases rather than level or other transformation
regressions:
y=a1+a2x1+a3x2+a4x3+.....+e
in terms of lower standard errors and higher R squares.
I am looking some explanations why this happens and also want to know how tell
whether the log linear regression method is my best specification
Mostly y x2 x3 are ratio and x1 is level( but x1 is not a denominator of other
ratios)
Within my knowledge, the log transformation would be helpful for multiplicative
data set. I don't know it would be applied to my case
Any comments and suggestions will be welcomed and helpful
Thanks
WT
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