* Simulation of Stern runs

* Run with low discounting
 ELASMU   = 1.0001;
 PRSTP    = 0.001;
RR(t)=1/((1+prstp)**(10*(ord(T)-1)));

partfract(t) = 1;
partfract('1')=1;

miu.up(t)=1;
miu.lo(t)=.001;

model co2stern / all /
solve CO2stern maximizing UTILITY using nlp ;
solve CO2stern maximizing UTILITY using nlp ;
solve CO2stern maximizing UTILITY using nlp ;

display damages.l;
Parameters
miustern(t)   Result for run without damages;
miustern(t) = miu.l(t);

* Then do the run with Stern mius and our damages
 ELASMU   = b_elasmu;
 PRSTP    = b_prstp;
RR(t)=1/((1+prstp)**(10*(ord(T)-1)));  

miu.up(t)= miustern(t);
miu.lo(t)= miustern(t);

model co2stern1 /all/
solve CO2stern1 maximizing UTILITY using nlp ;
solve CO2stern1 maximizing UTILITY using nlp ;
solve CO2stern1 maximizing UTILITY using nlp ;

display miustern, miu.l;

* Output

Parameters
Year(t)         Date
stern_y(t)
stern_cpc(t)
stern_s(t)
stern_indem(t)
stern_sigma(t)
stern_tatm(t)
stern_mat(t)
stern_tax(t)
stern_ri(t)
stern_rr(t)
stern_al(t)
stern_forcoth(t)
stern_l(t)
stern_etree(t)
stern_yy(t)
stern_cc(t)
stern_miu(t)
stern_wem(t)
stern_ri(t)
stern_dam(t)
stern_abate(t)
stern_mcemis(t)
stern_utility   ;

Year(t)         = 2005 +10*(ord(t)-1);
stern_y(t)=y.l(t);
stern_cpc(t)=cpc.l(t);
stern_s(t)=s.l(t)     ;
stern_indem(t)= e.l(t)-etree(t);;
stern_sigma(t)=sigma(t) ;
stern_tatm(t)=tatm.l(t)  ;
stern_mat(t)=mat.l(t)     ;
stern_tax(t)=-1*ee.m(t)*1000/(kk.m(t)+.0000001)       ;
stern_ri(t)=ri.l(t);
stern_rr(t)=rr(t)   ;
stern_al(t)=al(t)    ;
stern_forcoth(t)=forcoth(t);
stern_l(t)=l(t);
stern_etree(t)=etree(t);
stern_yy(t)=yy.m(t)     ;
stern_cc(t)=cc.m(t)      ;
stern_miu(t)=miu.l(t)     ;
stern_wem(t)= e.l(t);
stern_ri(t)=ri.l(t)         ;
stern_dam(t)= damages.l(t);
stern_abate(t) = abatecost.l(t);
stern_utility=utility.l        ;
stern_mcemis(t)= expcost2*cost1(t)*miu.l(t)**(expcost2-1)/sigma(t)*1000;

miu.up(t)= 1;
miu.lo(t)= 0;

display stern_tax, stern_mcemis;