Hi all,
I've been working on a small open economy model with asymmetric adjustment costs of labour and I am trying to get the IRFs, which should display some degree of asymmetry given different positive/negative values of parameter zeta in the model (see code attached).
I have log-linearised the model by hand except there is one term that remains non-linear (i.e. if x=ln(X), then the non-linear term is exp(x-x(-1)))= X/X(-1)). This is the key feature of the model as it underlies the asymmetric nature of labour adjustment costs. The code "works", but the results for positive/negative zeta's are exactly identical, which can only be the case if the approximation exp(x)=1+x is applied by default. This however imposes an approximation error, which is non-negligible in my model. My question is, how can I avoid this approximation, because my key research interest is in analysing the non-linearity of the term exp(x-x(-1)).
I've tried to replace command exp with simply the Eulers constant. I've tried introducing a separate variable X=exp(x). I've also tried to use model(linear), but some of the variables have non-zero steady state - none of these change the results.
I thought that perhaps there are other algorithms for solving "non-linear" models instead (see Gomez (2014) attached, only it would be nice if someone could suggest some specific commands for those algorithms)? Perhaps there is a way how to disable Taylor-Series approximations by writing something instead of "order" in the stoch_simul command, given that all the other variables are log-linearised?
Thanks a lot for the comments in advance!
Justas