Pairwise Collinearity Pattern.pdf (102.7 KB)
Dear Johannes,
First thank you very much for your previous help, I am grateful.
i have obtained pairwise collinearity pattern in identification/sensitivity analysis, please refer to lower graph (Collinearity patterns with 1 parameter(s)) in the PDF attachment,
In my DSGE model, the general structure of a shock is as follows:
lnU=(1-rhoU)Steady_State_U+rhoUlnU(-1)+e
e~N(0,sigma^2)
I find likelihood’s sensitivity to rhoU and likelihood’s sensitivity to sigma are highly correlated according to the graph (yellow spots)
the general measurement equation is as follows:
observed variable=constant+ln(state_variable/steady_state_variable)
I find likelihood’s sensitivity to observed production’s constant is highly correlated with likelihood’s sensitivity to other observables’ constants according to the graph (yellow spots)
Could you please have a look at the graph, do you think weak identification problem is serious according to my collinearity graph?
my model is identified according to the following output (also refer to upper graph in PDF attachment)
==== Identification analysis ====
Testing prior mean
All parameters are identified in the model (rank of H).
All parameters are identified by J moments (rank of J)
Monte Carlo Testing
Testing MC sample
All parameters are identified in the model (rank of H).
All parameters are identified by J moments (rank of J)
==== Identification analysis completed ====
Thank you very much and look forward to hearing from you.
Best wishes,
Jesse