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An example: unbiased and consistent estimate. new; format /m1 /rd 9,3; T=30; @ the number of observations@ n=10000; @ the number of sampling times@ beta1=1; beta2=2.0; Beta_e=zeros(n,2); x1=1*Rndn(T,1); x2=2*Rndn(T,1); X=x1~x2;. i=1; do until i>n;
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new; • format /m1 /rd 9,3; • T=30; @ the number of observations@ • n=10000; @ the number of sampling times@ • beta1=1; beta2=2.0; • Beta_e=zeros(n,2); • x1=1*Rndn(T,1); • x2=2*Rndn(T,1); • X=x1~x2;
i=1; • do until i>n; • @ Data Gerneration Process: Y=beta1*X1+beta2*X2+e@ • e=Rndn(T,1); • Y=beta1*x1+beta2*x2+e;
@ Parameter Estimation Process: Y=beta1*X1+beta2*x2+u @ • Beta_e[i,.]=olsqr(Y,X)'; • i=i+1; • endo; • print " the average value of the beta1 estimates"; • print meanc(Beta_e[.,1]); • print " the average value of the beta2 estimates"; • print meanc(Beta_e[.,2]);