105 lines
3.0 KiB
Modula-2
105 lines
3.0 KiB
Modula-2
/* Mod file tests the correctness of the conditional_forecast command when used together with initval by
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* - checking whether the unconditional forecast from the conditional_forecast-command
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* coincides with the one from the forecast command
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* - checking whether the conditional forecast coincides with the path of
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* capital derived when simulating the model with simult_ and the computed exogenous instruments
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* - initval should not play a role as initial conditions need to be set with histval; with initval
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* the subsequently computed steady state is used
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*/
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var m P c e W R k d n l gy_obs gp_obs y dA;
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varexo e_a e_m;
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parameters alp bet gam mst rho psi del;
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alp = 0.33;
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bet = 0.99;
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gam = 0.003;
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mst = 1.011;
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rho = 0.7;
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psi = 0.787;
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del = 0.02;
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model;
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dA = exp(gam+e_a);
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log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
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-P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k^(alp-1)*n(+1)^(1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;
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W = l/n;
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-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
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R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
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1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)/(m*l*c(+1)*P(+1)) = 0;
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c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
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P*c = m;
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m-1+d = l;
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e = exp(e_a);
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y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
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gy_obs = dA*y/y(-1);
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gp_obs = (P/P(-1))*m(-1)/dA;
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end;
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initval;
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k = 6;
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m = mst;
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P = 2.25;
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c = 0.45;
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e = 1;
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W = 4;
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R = 1.02;
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d = 0.85;
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n = 0.19;
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l = 0.86;
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y = 0.6;
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gy_obs = exp(gam);
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gp_obs = exp(-gam);
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dA = exp(gam);
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end;
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shocks;
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var e_a; stderr 0.014;
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var e_m; stderr 0.005;
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end;
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steady(tolx=1e-10,tolf=1e-12);
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check;
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stoch_simul(irf=0);
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conditional_forecast_paths;
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var gy_obs;
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periods 1 2 3:5;
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values 0.01 -0.02 0;
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var gp_obs;
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periods 1 2 3:5;
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values 1 1.04 0.98;
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end;
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%set capital to non-steady state value
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initval;
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k = 6;
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end;
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conditional_forecast(periods=100,parameter_set=calibration,replic=10000, controlled_varexo=(e_m,e_a));
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plot_conditional_forecast(periods=100) gy_obs gp_obs k;
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forecast(periods=100);
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%compare unconditional forecasts
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cond_forecast=oo_.conditional_forecast;
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if max(abs(cond_forecast.uncond.Mean.k(2:end)-oo_.forecast.Mean.k))>1e-8
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error('Unconditional Forecasts do not match')
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end
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%compare conditional forecasts; initval should not play a role as initial
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%conditions need to be set with histval;
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initial_condition_states = oo_.dr.ys;
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shock_matrix = zeros(options_cond_fcst_.periods ,M_.exo_nbr); %create shock matrix with found controlled shocks
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shock_matrix(1:5,strmatch('e_a',M_.exo_names,'exact')) = cond_forecast.controlled_exo_variables.Mean.e_a; %set controlled shocks to their values
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shock_matrix(1:5,strmatch('e_m',M_.exo_names,'exact')) = cond_forecast.controlled_exo_variables.Mean.e_m; %set controlled shocks to their values
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y_simult = simult_(M_,options_,initial_condition_states,oo_.dr,shock_matrix,1);
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if max(abs(y_simult(strmatch('k',M_.endo_names,'exact'),:)'-cond_forecast.cond.Mean.k))>1e-8
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error('Unconditional Forecasts do not match')
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end
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