Barry Ritholtz uses the CRB "excluding food and energy" in a post today to show how high 'core' inflation is. I found the data in the post's chart at www.economagic.com. A bit of investigation into the data revealed the "ex food & energy" series to be the CRB Raw Industrials Index.
The Raw Industrials Index is composed of hides, tallow, copper scrap, lead scrap, steel scrap, zinc, tin, burlap, cotton, print cloth, wool tops, rosin, and rubber. All but hides, tallow, rosin, and rubber are contained in two other sub-groups:
- The "metals" sub-index (40% of the 'core' index) contains copper scrap, lead scrap, steel scrap, tin, and zinc.
- The "textiles and fibers" sub-index (30% of the 'core' index) is comprised of burlap, cotton, print cloth, and wool tops.
Therefore, this 'core' index is mainly composed of 5 metals and 4 textiles. Further, if you decompose the rise in the raw industrials index into its two main components - metals and textiles - you can see that the recent rise in metals prices is the main cause of the rise in its parent index (see chart - click to enlarge).
Barry has presented some good arguments against the use of core inflation in monetary policy. This is not one of them, however.
UPDATE: I should have guessed, Barry intended to be a bit over-the-top in his post...
For those interested, the R code used to create the chart is below.
require(fImport)
rawInd <- economagicImport("crb/crb12", freq="monthly")@data[-(1:7),]
rawInd$DATE <- as.Date(rawInd$DATE)
textiles <- economagicImport("crb/crb13", freq="monthly")@data[-(1:7),]
textiles$DATE <- as.Date(textiles$DATE)
metals <- economagicImport("crb/crb14", freq="monthly")@data[-(1:7),]
metals$DATE <- as.Date(metals$DATE)
plot( rawInd$DATE, rawInd$VALUE, type="l",
ylim = range( c( rawInd$VALUE, textiles$VALUE, metals$VALUE ) ),
main = "Selected CRB Indicies",
xlab = "Date", ylab = "Index Value",
lwd = 2 )
lines( textiles$DATE, textiles$VALUE, col="red" , lwd = 2 )
lines( metals$DATE, metals$VALUE, col="blue", lwd = 2 )
legend( "topleft",
legend = c("Raw Industrials","Textiles Sub Index","Metals Sub Index"),
col = c( "black", "red", "blue" ),
lty = c( 1, 1, 1 ),
lwd = c( 2, 2, 2 ),
bty = "n", inset = 0.05 )
savePlot( "Select_CRB_Indicies", type="png" )