# Use preprocessor for variable transformation (e.g. exp for doing approximation in log variables instead of level variables)

An often heard request is a way to loglinearize a model instead of a linearization. Currently, the way to go is to put all variables in exp(). This is mechanic and error-prone work.

If it is easily doable, I would like to propose to use the preprocessor to make this substitution, similar to the predetermined_variables-command substituting the lag of the current period.
We could then add a command like
`model(loglinearize)`

to tell the preprocessor to loglinearize.

At the same time, we need a command like `non_logarithmic_variables`

similar to the `predetermined_variables`

command to exclude already logarithmic variables (like e.g. technology) or variables with a negative steady state. I think this is a better option than specifying explicitly which variables to substitute.

If possible, a design issue we would need to discuss is the behavior in steady state computation. I would suggest that the `model(loglinearize)`

automatically triggers taking the log of the corresponding initvals so that users can enter the model in nonlinear standard form and Dynare takes care of the rest.