Hi, this is the following code : please help me with your suggestions .

The data used in this example and the file.mod are here : https://drive.google.com/drive/folders/1pSTki0nJRLY24bE0VevP-mM99ayUbgmO?usp=sharing

Thanks in advance

% Super simple model

% - log-linearised variant using equations from the slides

% - includes observed variables that are stored in ‘imf_data.xlsx’

% - observed variables are y_obs pi_obs r_obs and treated as endogenous

% - measurement equations for variables are included in the model

% - allow for measurement error for output, but not the others

% - some of the parameters are estimated (starting with shocks)

% - includes a shock to technology and monetary policy

% - size of shock to technology is calibrated

% - steady-state block is not necessary (linearised around mean of zero)

% - estimation command includes very short Markov-chain

%%

close all;

var y_t c_t k_t a_t r_t pi_t y_obs pi_obs r_obs;

varexo eps_a eps_r eps_y_obs;

parameters beta_p delta_p alpha_p rhoa_p phi_pi_p;

alpha_p = 0.33; % capital share

delta_p = 0.025; % deprecation rate

beta_p = 0.99; % discount factor

phi_pi_p = 1.5; % central bank response to inflation

rhoa_p = 0.97; % TFP persistence

model(linear);

#k_ss = ((1/beta_p-(1-delta_p))/alpha_p)^(1/(alpha_p-1)); % used in budget constraint

#y_ss = k_ss^alpha_p; % used in budget constraint

#c_ss = y_ss-delta_p*k_ss; % used in budget constraint
-c_t = -c_t(+1) + beta_p*alpha_p

*k_ss^(alpha_p-1)*(a_t(+1)+(alpha_p-1)

*k_t); % Euler 1*

-c_t = -c_t(+1) + r_t - pi_t(+1); % Euler 2

y_ssy_t = c_ss

-c_t = -c_t(+1) + r_t - pi_t(+1); % Euler 2

y_ss

*c_t + k_ss*k_t - (1-delta_p)

*k_ss*k_t(-1); % Budget constraint

y_t = a_t + alpha_p

*k_t(-1); % Production function*

r_t = phi_pi_ppi_t + eps_r; % Monetary rule

r_t = phi_pi_p

a_t = rhoa_p*a_t(-1) + eps_a; % Technology shock

y_obs = y_t + eps_y_obs; % Output measurement equation

pi_obs = pi_t; % Inflation measurement equation

r_obs = r_t; % Interest rate measurement equation

end;

varobs y_obs pi_obs r_obs;

steady_state_model;

k_t=0;

y_t=0;

c_t=0;

r_t=0;

pi_t=0;

a_t=0;

end;

estimated_params;

phi_pi_p, gamma_pdf, 1.5, 0.005;

stderr eps_r, inv_gamma_pdf, 0.0005, inf;

stderr eps_y_obs, inv_gamma_pdf, 0.005, inf;

end;

shocks;

var eps_a; stderr 0.01;

end;

steady;

check;

estimation(datafile=‘imf_data.xlsx’, mh_replic=2000, mh_nblocks=1, mh_drop=0.45);

%stoch_simul(order=1, irf=20, periods=250);