Every
month the U.S. Bureau of Labor Statistics (BLS) announces its latest estimate
of the cost of all consumer goods and services. These initial estimates are
then revised as additional data come in. One of the key drivers of the American
economy over the last few years has been the declining cost of information in
relation not only to other goods and services but occasionally also in nominal
prices. This blog reviews the current procedures for measuring information
costs, hopefully giving readers more context about the long-term trends.
We
examine seven discrete categories of goods and services that have the primary
purpose of collecting and processing information. Four of these goods are
members of the broader category of Information technology, hardware and
services. Two lie within the category of Telephone services. The
final one lies within the category of Video and audio.
Approximately
half of the index for telephone hardware, calculators, and other consumer
information items consists of cellphones (about 95 percent of which are smartphones)
with home-based phones, phone accessories and smartwatches making up the rest.
The Consumer Price Index (CPI) records the actual price of a smartphone, with
promotions deducted from the advertised price. The BLS also separates out the
price of hardware from accompanying services such as Internet access and
television subscriptions. These services are collected in a separate category
of spending.
One
of the most important information products is smart phones. These goods are
the only item in their broader category that are quality adjusted due to the
rapid rate of technological advancements and improved quality for consumers. For
the vast majority of products, BLS simply records the price without any
adjustment for quality. However, for smartphones BLS economists have developed a
hedonic regression
model
that allows them to identify how much of a price rise is due to specific improvements
in quality. Assuming some of a price increase was due to product improvements
such as better screen resolution, BLS would add the value of those improvements
to the previous price of the smartphone and compare it to the new price. If
both prices were the same, consumers would be paying more but also getting
more, as opposed to paying more for the same benefit due to general inflation. Wireless
telephone services and television services undergo similar adjustments.
CPI
also uses the concept of directed substitution for both smartphones and
computers because of the rapid quality improvements in each good. Basically,
twice a year BLS assumes that consumers are purchasing the newer version of a
product even if the older one is still available. The resulting data recognizes
that manufacturers are improving the cost and/or quality of the product even if
consumers are not purchasing it yet.
Another
key fact is that information services make up a growing share of consumers’
total spending. This multiplies the impact of cost restraint. A 50 percent
price reduction in housing, which currently accounts for more than 44 percent
of spending, has a much larger effect on living standards than a 50 percent cut
in furniture and bedding, which makes up less than 1 percent. Table 1 shows the
relative weights for selected categories of information spending for 2017-18 compared to 2024. Some items have
increased their share of the consumer’s budget while others have contracted.
Table
1: Relative Importance of Components in the CPI, 2017-18 and 2024
|
Spending
Category
|
2017-18
|
2024
|
|
Computers,
peripherals, and smart home assistants
|
0.285
|
0.293
|
|
Computer
software and accessories
|
0.016
|
0.027
|
|
Internet
services and electronic information providers
|
0.856
|
0.923
|
|
Telephone
hardware, calculators, and other consumer information services
|
0.066
|
0.461
|
|
Wireless
telephone services
|
1.824
|
1.340
|
|
Residential
telephone services
|
0.405
|
0.126
|
|
Cable,
satellite and live streaming television service*
|
1.145
|
0.606
|
*Was
Cable and satellite television service in 2017-18
It
is important to note that the CPI only collects data on consumer items. Price
and quality improvements on products purchased by businesses are not recorded.
This excludes a major source of innovation and productivity in the economy.
However, many of these changes are eventually captured as competition eventually
forces companies to pass most of the benefit on to consumers. Also excluded from
this table are subscriptions to on-line magazines, games, and music and video
downloads, which are treated just as if the consumer purchased them offline. Non-business
subscriber fees for residential television are included, but pre-recorded video-on-demand
subscription streaming services are not.
BLS
faces a constant problem separating out changes in general inflation from
changes in the quality and capacity of specific goods and services. Products
that seldom change from one period to another present little problem. However,
the true prices of products that change rapidly are more difficult to measure. A
current example is the rise in pay-per-view streaming which charges viewers fees
for a greater choice of programming content. If a replacement product is better
than its predecessors and BLS can measure the value of the difference in
quality, it will raise the price from the previous month to reflect that there
has been no change in the real price. In cases like this, nominal price
increases may simply reflect the fact that consumers are getting more for
their money. In this case the market is doing exactly what it should.
The
relationship between prices and growth is complex. Some experts argue that much
of the U.S. productivity boom in the 1990s and 2000s was due to statistical
agencies using hedonic measures to overestimate productivity gains. However,
others point to the large unincluded value of free services such as ChatGPT,
Facebook, Gmail, Google Maps, and YouTube. Although these services deliver
tremendous value to consumers, they are not counted in GDP. This debate will
not end soon. In the meantime, the important point is that technology does
increase our living standards even if the inherent level of data uncertainty
makes this hard to see.
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