Let’s say that I am going to estimate my model and my steady state values are calculated like this

model;

# pk_ss=gamma/beta+delta-1;

# x_ss=pie;

# p_flex=1;

# inflation_ss=pie;

# mc_ss=(eta_p-1)/eta_p;

# Mw_ss=eta_w/(eta_w-1);

# R_ss=gamma*pie/beta;

# h=1;

# mu=0;

# PSI_ss=((1-alpha)/((pk_ss/alpha*gamma^(1/omega)*mc_ss)^(omega-1)-alpha/(gamma^((omega-1)/omega))))^(omega/(omega-1));

# TETHA_ss=1/(gamma^((1-xi)/xi));

# PHI_ss=(alpha*(PSI_ss/gamma)^((omega-1)/omega)+(1-alpha))^(1/(omega-1));

# w_ss=(1-alpha)*mc_ss*PHI_ss;

# OMEGA_ss=(TETHA_ss*Mw_ss*(1-theta)^sigma)*((PHI_ss^omega)*(1-sg)-(gamma-1+delta)*PSI_ss)^sigma;

# n_ss=(w_ss/OMEGA_ss)^(1/(sigma+phi));

# k_ss=n_ss*PSI_ss;

# investment_ss=k_ss*((gamma+delta-1)/gamma);

# y_ss=(alpha*(k_ss/gamma)^((omega-1)/omega)+(1-alpha)*n_ss^((omega-1)/omega))^(omega/(omega-1));

further assume that I have a Taylor rule in my model block that reacts on output deviations from its steady state according to

R=R_ss*(y/y_ss))^rho;

This means that I want to include my steady state value for y in my model block and I also want it to be updated as my parameters change during the estimation and as was evident from the steady state ekvations above my steady state value for y_ss depends on a lot of expression equations.

Then the problem is. What do I write under the “steady_state_model;” block? Because I can’t use the same expression names like THETA_ss and it seems a bit messy to have to define new expression variables just for the steady state block such as “THETA_ss2”. So does anyone have a clever way how to include all of this such that all steady state equations are updated during the estimation in a way that I can include “y_ss” directly in the model?