*
* Examples of spectral analysis from pp 167-170
* Note that these examples go through all the steps required for computing an
* estimate of the spectral density. These can be done more simply using the
* procedure SPECTRUM which combines these steps into a single procedure call.
*
cal(m) 1947
open data indprod.rat
data(format=rats) 1947:1 1989:10 ipmfg6
graph(footer="Federal Reserve Board's IP Index, Not Seasonally Adjusted")
# ipmfg6
compute nobs=1989:10-1947:1+1
diff(center) ipmfg6 / demean
freq 1 nobs
rtoc
# demean
# 1
fft 1
cmult(scale=1.0/(2*%pi*nobs)) 1 1
ctor
# 1
# periodogram
graph(nodates,footer="Sample Periodogram for IP Data")
# periodogram 2 nobs/2
*
*
set lgrowth = 100*log(ipmfg6/ipmfg6{1})
clear demean
diff(center) lgrowth / demean
stats demean
compute nobs=1989:10-1947:2+1
stats lgrowth
rtoc
# demean
# 1
fft 1
cmult(scale=1.0/(2*%pi*nobs)) 1 1
window(type=tent,width=25) 1
ctor
# 1
# spectrum
graph(nodates,footer="Figure 6.5 Estimate of the Spectrum for Monthly Growth Rate of IP")
# spectrum 1 nobs/2
*
set ygrowth = 100*log(ipmfg6/ipmfg6{12})
clear demean
diff(center) ygrowth / demean
compute nobs=1989:10-1948:1+1
rtoc
# demean
# 1
fft 1
cmult(scale=1.0/(2*%pi*nobs)) 1 1
window(type=tent,width=25) 1
ctor
# 1
# spectrum
graph(nodates,footer="Figure 6.6 Estimate of the Spectrum for Year to Year Growth Rate of IP")
# spectrum 1 nobs/2