Questions about Ramsey optimal policy

Dear all,

I have some questions about Ramsey optimal policy.

My model is a standard model with habit formation consumption. It works fine if I put Taylor rule as the monetary policy rule. But there’s a problem when I try to get the results under Ramsey optimal policy. The planner objective is a function of consumption expenditure and labour hours which I wrote it s follows:

planner_objective log(c-hc)-psi(((wl^(lambdaw*(1+v)/(1-lambdaw)))(w_star^(lambdaw(1+v)/(1-lambdaw)))*(l_star^(1+v)))/(1+v));
ramsey_policy(planner_discount=0.9976,order = 1,instruments=®);

When I try to run the code, Dynare returns the following error message:

Error using dynare_solve (line 60)
An element of the Jacobian is not finite or NaN
Error in evaluate_steady_state (line 66)
[ys,check] = dynare_solve([M.fname 'static’],…
Error in steady
(line 54)
[steady_state,params,info] =
Error in steady (line 81)
[steady_state,M_.params,info] = steady_(M_,options_,oo_);
Error in Ikeda_main10_ramsey (line 822)
Error in dynare (line 180)
evalin(‘base’,fname) ;

I need help to solve the errors. Any help would be much appreciated!

Best Regards,
Sahar Bashiri

You are most probably going to need a steady state file for this exercise that provides the analytical steady state values conditional on the value of the instrument.

Dear Professor,

Thank you very much for your help in advance.

I check the steady state values. The code works fine after eliminating some shocks. I have another questions, too.
Is writing the planner objective with habit persistence in consumption as follows correct?

planner_objective log(c-hc)-psi(((wl^(lambdaw*(1+v)/(1-lambdaw)))(w_star^(lambdaw(1+v)/(1-lambdaw)))*(l_star^(1+v)))/(1+v));

Best regards,
Sahar Bashiri

No, you are missing the lagged consumption term. To deal with this, define a new variable


and define the part of the planner objective as

planner_objective log(c-h*c_lag)
1 Like

I regard your reply for my questions. I would like to express my deepest appreciation for your help. .

Best regards,
Sahar Bashiri