Hello all,
For those familiar with it, I seek to reproduce the work done in Matthes (2015)'s Figuring Out the Fed. This is 4-equation optimal policy NK model with an IS curve, a Phillips Curve, and their respective AR(1) error terms, which serves as a constraint in the optimization of a (matrix-form) quadratic loss function. This can be represented in state-space form, with predetermineds on top, forwards on the bottom, and i_t as the instrument.
Matthes uses St Louis Fed data from 1960-2005, and looks at commitment vs. discretion. There is a learning algorithm wherein private agents update beliefs on which regime is generating the interest rates they observe. For now, however, I would just like to solve the model and estimate its parameters. I know the priors I would like to test. I am curious if this can be done in dynare, and particularly, if somebody knew of an example that was along these lines? I was told that dynare may not be able to handle some specifics of the paper---namely, that the normal dynare likelihood function wouldn't work since, in the paper, agents use the observed shocks to update Lagrange multipliers, which are used to calculate optimal interest rates. Being a mere masters student, I can perhaps forget this problem momentarily while I try to understand the estimation procedure.
Anywho, thank you very much for your help. A simple link to an similar example would be very welcome!