@ Below is an example of how your might call the Hodrick Prescott filer procedure below
In this example I filter logged series - to compute percentage standard deviations of variables
at business cycle frequencies I would then simply compute the standard deviations of the
columns in varhp  

horizon = 200;
lamda = 1600;

hpmat=hpf(horizon,lambda);

varhp = hpmat*(ln(consumption)~ln(GDP)~ln(investment));
@



proc hpf(n,l);

@ Calculates an n x n matrix that can be used to compute cyclical component.      
inputs:   n = number of observations in data set
          l = lambda (see Prescott, "Theory Ahead of Measurement..")
output:  hpfilt = n x n matrix    @

local nobs,a,i,ai;nobs=n;
a=zeros(nobs,nobs);
a[1,1]=1+l;a[1,2]=-2*l; a[1,3]=l;
a[2,1]=-2*l; a[2,2]=1+5*l;
a[2,3]=-4*l; a[2,4]=l;
a[nobs-1,nobs-3]=l;
a[nobs-1,nobs-2]=-4*l;
a[nobs-1,nobs-1]=1+5*l;
a[nobs-1,nobs]=-2*l;
a[nobs,nobs-2]=l;
a[nobs,nobs-1]=-2*l; 
a[nobs,nobs]=1+l;i=3;
do until i>(nobs-2);    
 a[i,i]=1+6*l;
 a[i,i+1]=-4*l;     
a[i,i+2]=l;     
a[i,i-1]=-4*l;     
a[i,i-2]=l;
 i=i+1;
endo;
ai=eye(nobs)-inv(a);
retp(ai);
endp;