%compute the steady state
function [ys,params,check] = giowithouttax_steadystate(ys,exo,M_,options_)

NumberOfParameters = M_.param_nbr;
for ii = 1:NumberOfParameters
  paramname = M_.param_names{ii};
  eval([ paramname ' = M_.params(' int2str(ii) ');']);
end
% initialize indicator
check = 0;

%% THIS BLOCK IS MODEL SPECIFIC.
%%
%% Here the user has to define the steady state.

%%
R_1=[0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01];
fun = @(c) fun_megabe(c,mu,sigma,beta_e,beta_u,etaa,chi,gammaa,theta,vepsilon,nu,Te);
options=optimset('MaxFunEvals',10000,'MaxIter',10000,'Display','off');
c=fsolve(fun,R_1,options);

C = c(1);
Ce= c(2);
Cu= c(3);
W= c(4);
He= c(5);
H= c(6);
MC= c(7);
Y= c(8);
Lu= c(9);
L= c(10);
De= c(11);
D= c(12);
N= c(13);
xd= c(14);
zl= c(15);
Phi= c(16);
% Tu= c(17);
Ue= c(17);
welf_e= c(18);
Uu= c(19);
welf_u= c(20);
cons_ee= c(21);
cons_eu= c(22);
welf = c(23);
%%
Pi=0;
A=A_ss;
Rl= 1/beta_u -1;
R=1/beta_e - 1;
vsigma=Rl-R;
Lambda= beta_e;
Tu=Te;
%% DO NOT CHANGE THIS PART.
%%
%% Store model parameters
params=NaN(NumberOfParameters,1);
for iter = 1:length(M_.params) %update parameters set in the file
  eval([ 'params(' num2str(iter) ') = ' M_.param_names{iter} ';' ])
end

NumberOfEndogenousVariables = M_.orig_endo_nbr; %auxiliary variables are set automatically
for ii = 1:NumberOfEndogenousVariables
  varname = M_.endo_names{ii};
  eval(['ys(' int2str(ii) ') = ' varname ';']);
end

end                                                  % End of the loop.
%%                                                         % End of the loop.