Calibration with pruning

Dear friends,

Sorry to post a trivial question. I am not familiar with higer-order approximation with pruning.
When I set “optPruning.computeIRF = 1” using MAndreason et.al(2013)'s package, IRFs for all volatility shocks shown up together. Actually, I hope there will be only desired IRFs for particular endogenous variables and shocks. May be it needs coding.
BP(2014)'s code is clear. But I am still confused how to replicate it even in calibration.

Besides, I also encountered the same problem as some users before:
dynare:k_order_perturbation: Caught Kord exception: NaN or Inf asserted in first order derivatives in FirstOrder::solve
??? Error using ==> print_info at 68
k_order_pert was unable to compute the solution
Error in ==> stoch_simul at 98
print_info(info, options_.noprint, options_);

I have tried but failed. Any tips or advice would be deeply appreciated! Thanks in advance.

Sorry, but I do not understand the question. Are you working with Dynare? Or Andreasen’s toolkit? And what exactly are the problems. Please state them systematically.

I finally realised that dynare itself has the power to do pruning.
I want to figure out whether there is a real difference between MAndreasen toolkit and dynare in pruning.
Thanks a lot!

Dynare implements Andreasen’s pruning. There is no difference (I coded that part up). What is different is the way to compute IRFs. He uses analytical GIRFs, while Dynare’s GIRFs are currently simulation based.

Dear professor, thanks for your help!

Hello Professor Pfeifer

We normally use oo_irfs.variablename_shock to plot irfs when we don’t want to use dynare’s default irfs graphs. Is there a similar way doing this for GIRFs when we use Andreasen Pruning toolbox ?

Thank you

You would have to check the toolbox documentation. I haven’t worked with it in a long time.