by xuz » Tue Aug 23, 2016 11:20 pm
Hi all,
I have a similar problem as in the old posts. In my DSGE model, x and y are two forward looking endogenous variables, and v is the only shock. Instead of computing IRFs, I'm interested in a simulation, where a series of shock v could generate a certain path for variable y. I want to know how variable x behaves during this simulation. That certain path for variable y will match the features from real life, e.g. if y is inflation, the path could be the inflation goes down by 1%, goes back to steady state for 5 periods, goes up by 2% and then goes back to the usual dynamic rule.
inflation_1 =-0.01;
inflation_2 =0;
inflation_3 =0;
inflation_4 =0;
inflation_5 =0;
inflation_6 =0;
inflation_7 =0.02;
inflation_8 =function of state variables; etc.....
I want to see what kinds of series of shock v could generate this path, and more importantly, how the other variables respond.
The model is log linearized, and perfect foresight is assumed. (one side question, if I say the model is log-linearized, does it mean perfect foresight? how about vice versa?) The path I impose won't be an extreme case. The model could be solved using backward conduction. I wonder whether there're any commands or any parameter matrices that I can use to compute the size of the shocks in each period. It might be cases that there're multiple solutions for the shock series.
After I get the shock series, i can use the stimuli_ to generate the path for variable x.
Thanks very much!