I’m trying to back out the policy function from a non-linear model solved using ‘order=2’. To do this efficiently, I gather that the go-to place is oo_.dr. However, I’m struggling to understand some of the internals relative to what is printed in the command window upon running stoch_simul. I’m assuming that the method to generate the approximation to the policy function follows Schmidt-Grohe & Uribe (2004, JEDC)? If so, then here is what I understand:
i) oo_.dr.ghs2 is the `correction’ term that appears in the print-out.
ii) oo_.dr.ghx and oo_.dr.ghu are the usual coefficients multiplying the vector of pre-determined (or exogenous state) variable deviation from the steady state and the vector of shocks (analogous to 1st order perturbation).
iii) oo_.dr.ghxx is a matrix of coefficients next to the covariance of state variables (expressed as deviations from the steady state).
iv) oo_.dr.ghuu is the matrix of coefficients next to the covariance of shocks.
Here is what I don’t understand:
i) How is the correction term computed? It should reflect the difference between the steady state and the non-ergodic mean upon repeatedly sampling shocks stored in oo_.endo_simul, right?
ii) Why is oo_.dr.ghxu not equal to zero? Theorem 1 in SGU (2004) states that setting them to zero ensures that a unique solution exists. Is this something to do with pruning?