% Project based on
% An and Schorfheide (2007), Bayesian Analysis of DSGE Models



%----------------------------------------------------------------
% (0.) Housekeeping
%----------------------------------------------------------------

close all;
clc;



%----------------------------------------------------------------
% (1.) Defining variables
%----------------------------------------------------------------



var c, r, z, pi, y, g, YGR, INFL, INT;

varexo e_r, e_g, e_z;

parameters beta, tao, rho_r, rho_z, rho_g, v, psi_1, psi_2, phi, pi_ss, gamma;


%----------------------------------------------------------------
% (2.) Model
%----------------------------------------------------------------



model(linear);
# kappa = tao*(1-v)/(v*pi_ss^2*phi);

# gamma_Q = 100*gamma-100;

# pi_A = 400*pi_ss-400;

# r_A = 400*(1-beta)/beta;

y = y(+1)+g-g(+1)-1/tao*(r-pi(+1)-z(+1));

pi = beta*pi(+1)+kappa*(y-g);

c = y-g;

r = rho_r*r(-1)+(1-rho_r)*psi_1*pi+(1-rho_r)*psi_2*(y-g)+e_r;

g = rho_g*g(-1)+e_g;

z = rho_z*z(-1)+e_z;

YGR = gamma_Q+100*(y-y(-1)+z);

INFL = pi_A+400*pi; 

INT = pi_A+r_A+4*gamma_Q+400*r;
end;



%----------------------------------------------------------------
% (3.) Estimation
%----------------------------------------------------------------



varobs YGR, INFL, INT;

estimated_params;
tao, gamma_pdf,  2.00, 0.50, 0.00;

kappa, gamma_pdf, 0.20, 0.10, 0.00;
 
psi_1, gamma_pdf, 1.50, 0.25, 0.00;

psi_2, gamma_pdf, 0.50, 0.25, 0.00;

rho_r, beta_pdf, 0.50, 0.20, 0.00, 1.00;
 
rho_g, beta_pdf, 0.80, 0.10, 0.00, 1.00;

rho_z, beta_pdf, 0.66, 0.15, 0.00, 1.00;

r_A, gamma_pdf, 0.50, 0.50, 0.00;

pi_A, gamma_pdf, 7.00, 2.00, 0.00;

gamma_Q, normal_pdf, 0.40, 0.20;

stderr e_r, inv_gamma_pdf, 0.40, 4.00;

stderr e_g, inv_gamma_pdf, 1.00, 4.00;

stderr e_z, inv_gamma_pdf, 0.50, 4.00;
end;


estimation(datafile=data_2,xls_sheet=sheet1,xls_range=A1:C232);