function [ys,params,check] = Model_steadystate(ys,exo,M_,options_)

check = 0;
options = optimset('Display','Final','TolX',1e-10,'TolFun',1e-10);

for ii = 1:M_.param_nbr
  eval([ M_.param_names{ii} ' = M_.params(' int2str(ii) ');']);
end

m=556.59;
c=9378.02;
r=5.89;
e0=0;
z0=0;
pi0=58.71;
y0=20449.01;
r0=5.89;
tau0=0.0046;
e=0;
lambd=-0.2977;
a=0;
in=1649.74;
k=496561.2;
x=0;
z=0;
v=0;
q=1/bet-1+delt;
lambd=(et+(1-alph)*((1+e*(r/(r-1))^(gamm-1))^(-1))*(thet/(thet-1)-delt*(alph/q))^(-1))/((1-alph)*z*((thet-1)/thet)^((1+alph)/(1-alph))*(alph/q)^(alph/(1-alph)));
c=((1+e*((r/(r-1))^(gamm-1))^(-1))*(1/lambd));
m=c*((r/(r-1))^(gamm))*c;
pi=58.71;
tau=pi;
r=pi/bet;
ksi=((thet-1)/thet)*lambd;
y=(1-delt*(alph/q)*((thet-1))/thet)^(-1);
k=(alph*q)*((thet-1)/thet)*y;
i=delt*k;
h=(1/z)*(y/k^alph)^(1/(1-alph));
w=(1-alph)*((thet-1)/thet)*(y/h);
d=y-w*h-q*k;
n=y/h;

params=NaN(M_.param_nbr,1);
for iter = 1:M_.param_nbr
  eval([ 'params(' num2str(iter) ') = ' M_.param_names{iter} ';' ])
end

for ii = 1:M_.orig_endo_nbr
  eval(['ys(' int2str(ii) ') = ' M_.endo_names{ii} ';']);
end