Anticipated and unanticipated permanent shock with linear_approximation

Perfect foresight simulations
1

Dear all,
I have a question on how shock is implemented in perfect foresight simulation.

I want to implement a permanent tax in my model. I know that there are many topics about this. However, due to the complexity of my model and I don’t need to preserve the nonlinearity of the model, I find out that there is an option stack_solve_algo=0, linear_approximation.

However, I am not sure if I use this, my shock is an unanticipated or anticipated shock. Secondly, I want to simulate a ‘transition dynamic’. I am not sure if this is the correct way to do it. Thirdly, will it give me a different results compared to more common way with initial, endval(with the value of tax) and perfect_foresight_solver ?

Thank you so much for all kinds of help.

2

The linear_approximation-option will preserve the characteristics of perfect foresight simulation, but simply use a linear approximation of the model instead of the full nonlinear one. All shocks will be perfectly anticipated as it’s still perfect foresight.

3

Thank you so much for your quick reply.
So if I understand correctly, whenever we use perfect foresight, the shock is anticipated.

Let’s say, I implement the shock from period 5:100. But this means the shock is anticipated from period 1. Do I understand correctly?

Is there any way to have permanent unanticipated shock?

4
  1. Yes, you understand that correctly.
  2. In the unstable version (Dynare 6), there is a perfect_foresight_with_expectation_errors_*-command to allow for that. See
1 Like
5

Many thanks, this surely helps a lot.