non-linear model using exp()
Posted: Thu Feb 18, 2016 3:03 pm
Hi!
I have a simple question about the transformation of the variables from levels to logs.
Lets say that the original model has the following goods market clearing condition: Y1+Y2=C1+C2+I1+I2;
If I write:
The IRF will show absolute deviations from steady-state.
IF I wanted to obtained log-deviations, then I need to transform each variable with exp().
I have seen many models using the following transformation for this very specific equation ( which is originaly linear)
BUT, the exp(Y1+Y2)=exp(Y1)*exp(Y2), then the above transformation is wrong?
How should I do this transformation?
Many thanks in advance.
I have a simple question about the transformation of the variables from levels to logs.
Lets say that the original model has the following goods market clearing condition: Y1+Y2=C1+C2+I1+I2;
If I write:
- Code: Select all
model;
Y1+Y2=C1+C2+I1+I2;
end;
The IRF will show absolute deviations from steady-state.
IF I wanted to obtained log-deviations, then I need to transform each variable with exp().
I have seen many models using the following transformation for this very specific equation ( which is originaly linear)
- Code: Select all
model;
exp(Y1)+exp(Y2)=exp(C1)+exp(C2)+exp(I1)+exp(I2);
end;
BUT, the exp(Y1+Y2)=exp(Y1)*exp(Y2), then the above transformation is wrong?
How should I do this transformation?
Many thanks in advance.