Dear Tom,

Thank you for your quick reply. The model is a standard Taylor rule (I know I could estimate it in a linear way but I don't want to for several reasons):

i(t) = (1-rho_i)*(mu + gamma_pi*pi(t) + gamma_y*Ygap(t)) + rho_i*i(t-1) + u(t), whereas u(t) = lambda*u(t-1) + epsilon(t).

My first idea was indeed to start with recursive frmls but I don’t see the trick. I tried

- Code: Select all
`set u = 0`

frml cfrml1 i = (u = lambda*u{1} + epsilon), ((1-rhoi)*(mu + gamma_pi*pi + gamma_y*Ygap) + rhoi*i{1}) + u

and

- Code: Select all
`declare real u`

frml cfrml1 i = (u = epsilon + lambda*%if(t==start,0,u)), ((1-rhoi)*(mu + gamma_pi*pi + gamma_y*Ygap) + rhoi*i{1}) + u

but lambda cannot be estimated in both cases.

Best,

Mike