56 lines
1.3 KiB
Modula-2
56 lines
1.3 KiB
Modula-2
// Estimates the hall model using maximum likelihood. See hall1_estimateBayes.mod for Bayesian method
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periods 5000;
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var c k mu_c b d in;
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varexo e_d e_b;
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parameters R rho rho_b mu_b mu_d;
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R=1.05;
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rho=0.9;
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mu_b=30;
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mu_d=5;
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rho_b = 0.5;
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model(linear);
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c+k = R*k(-1) + d;
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mu_c = b - c;
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mu_c=mu_c(+1);
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d= rho*d(-1)+ mu_d*(1-rho) + e_d;
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b=(1-rho_b)*mu_b+rho_b*b(-1)+e_b;
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in = k - k(-1);
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end;
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// Michel says that in a stationary linear model, this junk is irrelevant.
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// But with a unit root, there exists no steady state. Use the following trick.
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// Supply ONE solution corresponding to the initial k that you named. (Michel is a gneius!! Or so he thinks -- let's see
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// if this works.)
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initval;
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d=mu_d;
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k=100;
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c = (R-1)*k +d;
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mu_c=mu_b-c;
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b=mu_b;
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end;
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shocks;
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var e_d;
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stderr 0.05;
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var e_b;
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stderr 0.05;
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end;
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estimated_params;
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// ML estimation setup
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// parameter name, initial value, boundaries_low, ..._up;
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// now we use the optimum results from csminwel for starting up Marco's
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rho, -0.0159, -0.9, 0.9;
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R, 1.0074, 0, 1.5;
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end;
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varobs c in;
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// declare the unit root variables for diffuse filter
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unit_root_vars k;
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estimation(datafile=data_hall,first_obs=101,nobs=200,mh_replic=0,mode_compute=4,mode_check);
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// Note: there is a problem when you try to use method 5. Tom, Jan 13, 2006 |