Hello everyone,
Can you do model-implied regression based on simulated dynare results?
Thanks.
Hello everyone,
Can you do model-implied regression based on simulated dynare results?
Thanks.
Why not? But without context, it is hard to give a well-founded answer.
Thanks for your reply. For example, only state and exogenous variables are stored in oo_.dr.ghx and oo_.dr.ghu and presumably regressing impulse responses on oo_.dr.ghu is a bad specification?
Why would you want to run that particular type of regression?
I wanted to show that my model is consistent with data results. I have OLS regression and wanted to present an equivalent regression from the model.
Hi,
You need to simulate your model, setting periods
equal to a positive value in stoch_simul
. The simulated data will be in oo_.endo_simul
for the endogenous variables (each row is for a different endogenous variable, the variables are ordered as in M_.endo_names
) and oo_.exo_simul
for the exogenous variales (each column is for an exogenous variable, and the variables are ordered as in M_.exo_names
) but you don’t need them (unless you want to compare the true innovations with the OLS residuals). Using the data in oo_.endo_simul
, you can build the vector y and matrix X of the regression and compute the OLS estimator: \hat\beta = (X'X)^{-1}X'y.
We have developed codes to do that in dynare but they are not yet public. You can have a preview about the implementation in this post:
Best,
Stéphane.
Hi Stéphane,
This is very helfpul, many thanks for the information!