@@ -2,14 +2,14 @@ function [ys,params,check] = NK_baseline_steadystate(ys,exo,M_,options_)
% function [ys,params,check] = NK_baseline_steadystate(ys,exo,M_,options_)
% computes the steady state for the NK_baseline.mod and uses a numerical
% solver to do so
% Inputs:
% Inputs:
% - ys [vector] vector of initial values for the steady state of
% the endogenous variables
% - exo [vector] vector of values for the exogenous variables
% - M_ [structure] Dynare model structure
% - options [structure] Dynare options structure
%
% Output:
% Output:
% - ys [vector] vector of steady state values for the the endogenous variables
% - params [vector] vector of parameter values
% - check [scalar] set to 0 if steady state computation worked and to
...
...
@@ -35,8 +35,8 @@ function [ys,params,check] = NK_baseline_steadystate(ys,exo,M_,options_)
% read out parameters to access them with their name
NumberOfParameters=M_.param_nbr;
forii=1:NumberOfParameters
paramname=M_.param_names{ii};
eval([paramname' = M_.params('int2str(ii)');']);
paramname=M_.param_names{ii};
eval([paramname' = M_.params('int2str(ii)');']);
end
% initialize indicator
check=0;
...
...
@@ -65,6 +65,7 @@ Lambdax=mu_z;
%set the parameter gammma1
gammma1=mu_z*mu_I/betta-(1-delta);
ifgammma1<0% parameter violates restriction; Preventing this cannot be implemented via prior restriction as it is a composite of different parameters and the valid prior region has unknown form