var ne_D eta_D p_D csM_D csA_D G_D theta_D z_D cmM_D theta_g_D cmA_D A_m_D ;

varexo ch;

parameters A_t  A_n beta_n alpha eta0 gamma kg_bar delta_g delta_n e n g ca_bar rho;


 A_t=1;
%population
n=1;

%modern agriculture
A_n=2;

beta_n=.6;

%preference parameter
alpha=0.2;

%transportation costs function
eta0=1.2;

gamma=0.8;
kg_bar=1;
delta_g=0.03;

%education
%delta_n=0.03;
delta_n=0.06;

e=2;

%Government spending
g=0.1;

%subsistence food
ca_bar=0.6;


model; 
ne_D=(1-delta_n)*ne_D(-1)+theta_g_D*G_D/e;
(eta_D)^(-1/gamma)=eta0^(-1/gamma)*((1-theta_g_D)*G_D+delta_g*kg_bar)+(1-delta_g)*(eta_D(-1))^(-1/gamma);
 
 p_D=((1-beta_n)/(1+eta_D))^(1-beta_n)*A_n*A_m_D^(-beta_n)*beta_n^beta_n;
 csM_D=(A_t-ca_bar)/p_D/(1+alpha);
 csA_D=(ca_bar+alpha*A_t)/(1+alpha);
  
 G_D=g*(A_t*(n-ne_D)+p_D*ne_D*A_m_D*(theta_D/beta_n+1-theta_D));
 theta_D=(-(n-ne_D)*(A_t-csA_D)+ne_D*ca_bar+alpha*p_D*A_m_D*ne_D-alpha*p_D*(n-ne_D)*csM_D)/ne_D/(p_D*A_m_D*(alpha+1/beta_n)+alpha*p_D*(1+eta_D)*((p_D*A_m_D)/(beta_n*A_n))^(1/(1-beta_n)));
 
 z_D=(p_D*A_m_D/A_n/beta_n)^(1/(1-beta_n))*theta_D*ne_D;
cmM_D=A_m_D*(1-theta_D)-(n-ne_D)/ne_D*csM_D-z_D*(1+eta_D)/ne_D;
cmA_D=ca_bar+alpha*p_D*cmM_D;
A_m_D=ch;

 
end;

load steady_state_values.mat;

initval;

ne_D=ne_init;
eta_D= eta_init;
 p_D=p_init;
csM_D= csM_init;
csA_D= csA_init;
G_D= G_init;
theta_D= theta_init;
z_D= z_init;
cmM_D= cmM_init;
cmA_D=cmA_init;
theta_g_D= theta_g_init;
A_m_D=2;

end;

%CAN'T USE STEADY WITH RAMSEY PROBLEM
%steady;

%Import exogenous variables from Excel spreadsheet 

ch_read=xlsread('input.xlsx',1,'A1:A500');


shocks;
var ch;
periods 1:500;
values (ch_read);
end;


%end;



planner_objective (n-ne_D)*(alpha*log(csA_D-ca_bar)+log(csM_D))+ne_D*(alpha*log(cmA_D-ca_bar)+log(cmM_D));



ramsey_policy(planner_discount=0.95);

 
 %simul(periods=1000);