*
* BOOTVAR.RPF
* RATS Version 8
* Bootstrapping example for VAR
*
compute lags=4				;*Number of lags
compute nvar=2				;*Number of variables
compute nstep=16			;*Number of response steps
compute ndraws=2500			;*Number of draws
*
open data haversample.rat
calendar(q) 1959
data(format=rats) 1959:1 2006:4 fm1 gdph
*
log gdph
log fm1
******************************************************************
*
* Set up the system
*
dec vect[series] udraws(nvar) resids(nvar) resample(nvar)
dec vect[equation] eqsample(nvar) eqbase(nvar)
*
system(model=varmodel)
variables gdph fm1
lags 1 to lags
det constant
end(system)
*
estimate(resids=resids)
compute rstart=%regstart(),rend=%regend()
*
* Set up the parallel system for the resampled data
*
system(model=bootvar)
variables resample
lags 1 to lags
det constant
end(system)
*
do i=1,nvar
   set resample(i) = %modeldepvars(varmodel)(i){0}
end do i
*
declare vect[rect] %%responses(ndraws)
declare rect[series] impulses(nvar,nvar)
*
infobox(action=define,progress,lower=1,upper=ndraws) "Bootstrap Simulations"
do draw=1,ndraws
   *
   * Draw a bootstrapped sample
   *
   boot entries rstart rend
   do i=1,nvar
      set udraws(i) = resids(i)(entries(t))
   end do i
   forecast(paths,model=varmodel,from=rstart,to=rend,results=resample)
   # udraws
   *
   * Estimate the model with resampled data
   *
   estimate(noprint,noftests,cvout=v)
   impulse(noprint,model=bootvar,cv=v,results=impulses,steps=nstep)
   *
   * Store the impulse responses
   *
   dim %%responses(draw)(nvar*nvar,nstep)
   ewise %%responses(draw)(i,j)=ix=%vec(%xt(impulses,j)),ix(i)
   infobox(current=draw)
end do draw
infobox(action=remove)
*
@MCGraphIRF(model=varmodel,page=all)