OPEN DATA "Sign6.xls" CALENDAR(D) 2000:1:1 DATA(FORMAT=XLS,ORG=COLUMNS,COMPACT=AVERAGE) 2000:01:03 2002:09:26 DYS PIS RS DY PI R DE * system(model=varmodel) variables DYS PIS RS DY PI R DE lags 1 to 4 deterministic constant end(system) estimate(noprint) dec vect[strings] vl(7) compute vl=||'Gap US','CPI US','Interest Rate us',$ 'GAP vn','cpi vn','Interest Rate vn','Real Effective Exchange Rate'|| compute n1=100000 compute n2=100000 compute nkeep=1000 compute nvar=7 compute nstep=60 compute KMAX=1 * This is the standard setup for MC integration of an OLS VAR * dec symm s(7,7) dec vect v1(7) ;* For the unit vector on the 1st draw dec vect v2(6) ;* For the unit vector on the 2nd draw dec vect v3(5) ;*For the unit vector on the 3rd draw dec vect v4(4) ;* For the unit vector on the 4th draw dec vect v5(3) ;* For the unit vector on the 5th draw dec vect v6(2) ;*For the unit vector on the 6th draw dec vect v(7) ;* Working impulse vector compute sxx =%decomp(%xx) compute svt =%decomp(inv(%nobs*%sigma)) compute betaols=%modelgetcoeffs(varmodel) compute ncoef =%rows(sxx) compute wishdof=%nobs-ncoef dec rect ranc(ncoef,nvar) * * Most draws are going to get rejected. We allow for up to 1000 * good ones. The variable accept will count the number of accepted * draws. GOODRESP will be a RECT(nsteps,nvar) at each accepted * draw. * declare vect[rect] goodresp(1000) declare vect[rect] goodrespa(1000) declare vect[rect] goodrespb(1000) declare vect[rect] goodrespc(1000) declare vect[rect] goodrespd(1000) declare vect[rect] goodrespe(1000) declare vector ik a(nvar) source forcedfactor.src * compute accept=0 infobox(action=define,progress,lower=1,upper=n1) 'Monte Carlo Integration' do draws=1,n1 * * Make a draw from the posterior for the VAR and compute its impulse * responses. * compute sigmad =%ranwisharti(svt,wishdof) compute p =%decomp(sigmad) compute ranc =%ran(1.0) compute betau =sxx*ranc*tr(p) compute betadraw=betaols+betau compute %modelsetcoeffs(varmodel,betadraw) * * This is changed to unit shocks rather than orthogonalized shocks. * impulse(noprint,model=varmodel,decomp=%identity(7),results=impulses,steps=nstep) * * Do the subdraws over the unit sphere. These give the weights on the * orthogonal components. * do subdraws=1,n2 ************************************************ * First Set of Restrictions - Domestic Demand ************************************************ compute v1=%zeros(3,1)~~%ransphere(nvar-3) compute i1=p*v1 do k=1,KMAX+1 compute ik=%xt(impulses,k)*v1 if ik(4)<0.or.ik(5)<0.or.ik(6)<0 branch 105 end do k * * @forcedfactor(force=column) sigmad i1 f compute v2=%zeros(3,1)~~%ransphere(nvar-4) compute i2=%xsubmat(f,1,7,2,7)*v2 compute v2=inv(p)*i2 ***************************************************** * Second Set of Restrictions - Domestic productivity ***************************************************** do k=1,KMAX+1 compute ik=%xt(impulses,k)*v2 if ik(4)<0.or.ik(5)>0.or.ik(6)>0 branch 105 end do k * * @forcedfactor(force=column) sigmad i1~i2 f compute v3=%zeros(3,1)~~%ransphere(nvar-5) compute i3=%xsubmat(f,1,7,3,7)*v3 compute v3=inv(p)*i3 ***************************************************** * Third Set of Restrictions - Domestic monetary policy ***************************************************** do k=1,KMAX+1 compute ik=%xt(impulses,k)*v3 if ik(4)>0.or.ik(5)>0.or.ik(6)<0 branch 105 end do k * * @forcedfactor(force=column) sigmad i1~i2~i3 f compute v4=%ransphere(nvar-3) compute i4=%xsubmat(f,1,7,4,7)*v4 compute v4=inv(p)*i4 ***************************************************** * Fourth Set of Restrictions - Foreign Demand ***************************************************** do k=1,KMAX+1 compute ik=%xt(impulses,k)*v4 if ik(1)<0.or.ik(2)<0.or.ik(3)<0 branch 105 end do k * * @forcedfactor(force=column) sigmad i1~i2~i3~i4 f compute v5=%ransphere(nvar-4) compute i5=%xsubmat(f,1,7,5,7)*v5 compute v5=inv(p)*i5 ***************************************************** * Fifth Set of Restrictions - Foreign Productivity ***************************************************** do k=1,KMAX+1 compute ik=%xt(impulses,k)*v5 if ik(1)<0.or.ik(2)>0.or.ik(3)>0 branch 105 end do k * * @forcedfactor(force=column) sigmad i1~i2~i3~i4~i5 f compute v6=%ransphere(nvar-5) compute i6=%xsubmat(f,1,7,6,7)*v6 compute v6=inv(p)*i6 ***************************************************** * Sixth Set of Restrictions - Foreign Monetary policy ***************************************************** do k=1,KMAX+1 compute ik=%xt(impulses,k)*v if ik(1)>0.or.ik(2)>0.or.ik(3)<0 branch 105 end do k * * Meets all restrictions * compute accept=accept+1 dim goodresp(accept)(nstep,nvar) dim goodrespa(accept)(nstep,nvar) dim goodrespb(accept)(nstep,nvar) dim goodrespc(accept)(nstep,nvar) dim goodrespd(accept)(nstep,nvar) dim goodrespe(accept)(nstep,nvar) ewise goodresp(accept)(i,j)=(ik=%xt(impulses,i)*i1),ik(j) ewise goodrespa(accept)(i,j)=(ik=%xt(impulses,i)*i2),ik(j) ewise goodrespb(accept)(i,j)=(ik=%xt(impulses,i)*i3),ik(j) ewise goodrespc(accept)(i,j)=(ik=%xt(impulses,i)*i4),ik(j) ewise goodrespd(accept)(i,j)=(ik=%xt(impulses,i)*i5),ik(j) ewise goodrespe(accept)(i,j)=(ik=%xt(impulses,i)*i6),ik(j) if accept>=nkeep break :105 end do subdraws if accept>=nkeep break infobox(current=draws) end do draws infobox(action=remove) * * Post-processing. Graph the mean of the responses along with the 16% and 84%-iles * clear upper lower resp * spgraph(vfields=3,hfields=3,hlabel='Impulse Responses with Pure-Sign Approach',subhea='VN') do i=1,nvar compute minlower=maxupper=0.0 smpl 1 accept do k=1,nstep set work = goodresp(t)(k,i) compute frac=%fractiles(work,||.16,.84||) compute lower(k)=frac(1) compute upper(k)=frac(2) compute resp(k)=%avg(work) end do k * smpl 1 nstep graph(pattern,ticks,number=0,picture='##.##',header='Impulse Responses for '+vl(i)) 3 # resp # upper / 2 # lower / 2 end do i * spgraph(done)