The Producer Price Index is one of two key market pricing series put out by the Bureau of Labor Statistics on a monthly basis. It is one of the oldest continuous data series collected by the Federal government, having begun in the 1890s. It consists of a weighted index of prices measured at the wholesale and production levels. The BLS releases an index for commodities (for example energy, natural gas, scrap metals), intermediate goods (like fuel, lumber, steel bar), and for finished goods. The PPI serves as a good indicator of medium term inflation prospects. It is not measuring consumer prices, and many producer prices are locked into longer term contracts. As such, it measures spot prices better than actual consumer inflation.
We presented the PPI last month, and The Producer Price Index for finished goods decreased 0.6 percent in March, the index for intermediate goods fell 0.9 percent, and the crude goods index declined 2.5 percent. This month, the index for finished goods decreased 0.7 percent. Prices received by manufacturers of intermediate goods declined 0.6 percent, and the crude goods index moved down 0.4 percent. This suggests that inflation is still very tame.
One of the interesting facts in economics is that there are a tremendous number of different statistics published on a regular basis. Indices such as the PPI contain literal hundreds of what economics call “series,” or individual pieces of data. For example, there is a producer price index number for baked goods, one for soft drinks, even one for toilet paper. An economist or analyst particularly interested in say the toilet paper industry can find out that producer prices are up by 0.1 percent over the past year.
While it is useful to have access to such a large amount of information, one problem is that researchers become lazy. Rather than taking the time to develop a theory to be tested and to produce the correct model for a hypothesis test, many people simply throw large amounts of data into an equation and try to generate statistically significant figures. We see this all of the time in studies that often receive a lot of press. In fact, nearly two thirds of bio-statistical studies which are the kind that often make headlines when they suggest that bacon leads to Alzheimer’s Disease, or that apples cause the clap, are developed simply by throwing large amounts of disjointed data into a regression analysis.
Other time, statistics are simply misinterpreted, like when the media touts that consumer spending generates 70 percent of GDP. In fact, spending generates none of GDP but is used as a measure of production. One reason that we are putting out this statistical release every three weeks or so is to make our clients aware of these problems and suggest other ideas as to why certain economic events are happening.