64 lines
1.1 KiB
Modula-2
64 lines
1.1 KiB
Modula-2
// Estimates the Rosen schooling model by maximum likelihood
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// Rosen schooling model
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//
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// The model is the one Sherwin Rosen showed Sargent in Sargent's Chicago office.
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// The equations are
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//
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// s_t = a0 + a1*P_t + e_st ; flow supply of new engineers
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//
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// N_t = (1-delta)*N_{t-1} + s_{t-k} ; time to school engineers
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//
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// N_t = d0 - d1*W_t +e_dt ; demand for engineers
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//
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// P_t = (1-delta)*bet P_(t+1) + W_(t+k); present value of wages of an engineer
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periods 500;
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var s N P W;
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varexo e_s e_d;
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parameters a0 a1 delta d0 d1 bet ;
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a0=10;
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a1=1;
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d0=1000;
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d1=1;
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bet=.99;
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delta=.02;
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model(linear);
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s=a0+a1*P+e_s; // flow supply of new entrants
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N=(1-delta)*N(-1) + s(-4); // evolution of the stock
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N=d0-d1*W+e_d; // stock demand equation
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P=bet*(1-delta)*P(+1) + bet^4*(1-delta)^4*W(+4); // present value of wages
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end;
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initval;
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s=0;
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N=0;
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P=0;
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W=0;
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end;
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shocks;
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var e_d;
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stderr 1;
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var e_s;
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stderr 1;
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end;
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steady;
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estimated_params;
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a1, gamma_pdf, .5, .5;
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d1, gamma_pdf, 2, .5;
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end;
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varobs W N;
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estimation(datafile=data_rosen,first_obs=101,nobs=200,mh_replic=5000,mh_nblocks=2,mh_jscale=2,mode_compute=0,mode_file=rosen_estimateML_mode);
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