50 lines
1.3 KiB
Modula-2
50 lines
1.3 KiB
Modula-2
%% Mod-file tests interaction between estimation and shock_decomposition when dseries is used or not
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var hh nn log_nn;
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varexo eps_a;
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parameters alfa nbar lambda betta rho_a std_a nn_init;
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nn_init = -0.1;
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alfa = 0.05;
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lambda = 0.054;
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betta = 0.99;
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nbar = 1;
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rho_a = 0;
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std_a = 1;
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model(linear);
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hh = - alfa * nn + betta * ( hh(+1) + 0 * eps_a(+1) ) + eps_a;
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log_nn = log_nn(-1) + hh * lambda / (1-lambda);
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log_nn = ln(nbar) + nn;
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end;
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steady_state_model;
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log_nn = log(nbar);
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nn = 0;
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hh = 0;
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end;
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shocks;
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var eps_a; stderr 1;
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end;
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estimated_params;
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alfa, beta_pdf, 0.1, 0.05;
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std_a, inv_gamma_pdf, 0.05, 1;
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end;
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varobs log_nn;
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%reading Excel sheet from column A on creates quarterly dseries starting in
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%1950
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estimation(first_obs=2,datafile='data_uav.xlsx', xls_sheet=Tabelle1, xls_range=a1:b54, silent_optimizer,mh_replic=2, mh_nblocks=1, mh_jscale=1.1, mh_drop=0.8, plot_priors=0, smoother) log_nn nn hh ;
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shock_decomposition( parameter_set=posterior_median ) nn hh;
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%reading Excel sheet from column B on creates annual dseries starting with 1
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estimation(first_obs=2,datafile='data_uav.xlsx', xls_sheet=Tabelle1, xls_range=b1:b54, silent_optimizer, mh_replic=2, mh_nblocks=1, mh_jscale=1.1, mh_drop=0.8, plot_priors=0, smoother) log_nn nn hh ;
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shock_decomposition( parameter_set=posterior_median ) nn hh;
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