2nd order linearized models: 2 questions on IRFs: SOLVED
Posted: Mon Oct 31, 2011 7:28 am
Hi,
I have 2 questions on IRFs for models linearized to the second order:
1) In DYNARE User Guide, it is written "if you instead linearize to a second order, impulse response functions will be the result of actual Monte Carlo simulations of future shocks."
I was wondering how many times the model is simulated. Can one change (increase/decrease) the number of simulations?
2) One of my equations has the following form: y_t=a*x_t+b*z_t . When t=0, x_t=0 and z_t=0, this would imply that y_t also should be equal to 0. But for 2nd order approximation, according to IRFs, y_t>0. Is this due to the shift effect of the variance of future shocks?
However, if model is linearized up to order 1, then y_t=0 if t=0, x_t=0 and z_t=0. This would suggest that 1st order approximation is able to produce more accurate results, wouldn't it?
Sigitas
I have 2 questions on IRFs for models linearized to the second order:
1) In DYNARE User Guide, it is written "if you instead linearize to a second order, impulse response functions will be the result of actual Monte Carlo simulations of future shocks."
I was wondering how many times the model is simulated. Can one change (increase/decrease) the number of simulations?
2) One of my equations has the following form: y_t=a*x_t+b*z_t . When t=0, x_t=0 and z_t=0, this would imply that y_t also should be equal to 0. But for 2nd order approximation, according to IRFs, y_t>0. Is this due to the shift effect of the variance of future shocks?
However, if model is linearized up to order 1, then y_t=0 if t=0, x_t=0 and z_t=0. This would suggest that 1st order approximation is able to produce more accurate results, wouldn't it?
Sigitas