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!