Dear Professor Pfeifer,
I use the follow lines in the code (thanks to your code example in the github which helps a lot) and get irf plots as bellow.
initial_condition_states = repmat(oo_.dr.ys,1,M_.maximum_lag);
shock_matrix = zeros(options_.irf,M_.exo_nbr); %create shock matrix with number of time periods in columns
// set news shock
shock_matrix(1+4,strmatch(‘e_tauh’,M_.exo_names,‘exact’)) = 0.02;
y2 = simult_(initial_condition_states,oo_.dr,shock_matrix,1);
y_IRF = y2(:,M_.maximum_lag+1:end)-repmat(oo_.dr.ys,1,options_.irf); %deviation from steady state
plot(y_IRF(strmatch(‘GDPU’,M_.endo_names,‘exact’),:)); % use strmatch to select values
I have got a few questions when seeing the plot. Would you please give some guidance?
(1)How should I interpret this kind of fluctuation in the red rectangle?
(2) It seems the permanent new tax shock is unanticipated according to the results as the variables in the model are not impacted between 1-4 periods (as shown in the red circle). I thought the variables might change before the new tax was implemented at t=5 if it’s anticipated. Did I make anything wrong?
(3) I intend to get irf plots with mixed shocks, for example, the model is impacted by a stochastic technology shock at t=0 and meanwhile people know a new tax shock will arrive at t=5. I want to compare the irf plots under technology shock with and without this new tax shock. Does it possible to be realized?
Thank you for your time.