Can anyone suggest a good source on how to calibrate parameters in a model, particularly when parameters are novel and have no guidance in terms of reference to other good papers. For example,

I am currently struggling to understand how Lin in her paper ‘Rating Systems and Procyclicality:an Evaluation in a DSGE Framework’ has calibrated the pecuniary and non-pecuniary default penalties (page 16). Further, Wont there be any identification issues if the model is estimated?

The paper is attached for your reference.

To pinpoint matters, in my model, I have a FOC which reads

(c_p-a_p*c_p(-1)) / ((1-a_p)*eps_z_p)=w_p*n_p/eps_l_p; which boils down to

c_p /eps_z_p = alpha*y/(x*eps_l_p) (the LHS comes from firms optimisation) in steady state

I calibrated alpha as 0.5 and x (goods mkt mark up) as 1.2. Then I calibrated eps_z_p (preference par as 1) and then worked out the value of eps_l_p as 0.83 as I fixed the share of consumption to income as 0.5. Is this the right way to do it. Or is there a better way? Wont this lead to collinearity issues while estimating the model? The model solves and gets steady state and impulses but I am having issues estimating it.

RatingSystemsAndProcyclicalityAnEv_preview (1).pdf (665 KB)