Good morning everyone

I have two general questions that are confusing me for quite a while. Hopefully you can help me, i would really appreciate it. Thank you in advance!


1. I am wondering whether it is ok to use untransformed variables as dependent or independent variables in a panel data model (FE or RE)?
When looking at empirical papers, without any exception the variables are either logarithmized or ratios e.g. (Variable/Total assets, Variable/Net Income etc.) instead of the raw Variable.
I don´t have the feeling, that this even depends on the topic or the subject area. Thus, I feel like I have to transform variables before implementing them in a model.

Since my results are most often the best when using the raw variable, I am wondering whether this is a good sign, or whether the transformations are indeed necessary and the results for the raw variable are distorted. I can imagine, that such transformations reduce the threat of outliers, but in my case I have no outlier problems and in some rare cases I use winsorizing (cutting; I know its discussable if this is a good empirical practise).


2. My second question is also very broad. I wonder whether it is known, that growth rates in the dependent variable are leading to excessive insignificances for the independent variables?
All over my examinations, my results are clearly better when using variables in levels rather than in growth rates. And the difference is sometimes remarkably. Switching to a Growth rate DV sometimes take all significances of my IVs.

I am using a data Panel with N=33; T=7 (respectively T=6 in the regression since I use lagged IVs)

Greetings
Joan