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Understanding the alphabet soup of inflation indexes

January 12, 2022

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If there’s one business news story that affects everyone, it’s inflation. And the inflation figures announced January 12th by the U.S. Labor Department were stunning. The most commonly used gauge of inflation, the consumer price index (CPI-U), rose 7% in December from a year earlier, the fastest pace since 1982.

But as with all economic data, the trick for business journalists is to help readers and viewers put the abstract, and often confusing, numbers into context. It doesn’t help that the consumer price index comes in different flavors (core and non-core), can be adjusted statistically or left alone, and that the inflation picture can appear very different depending on whether you compare how prices changed from the previous month or from the previous year. Plus, CPI is only one of several ways to measure how prices change: there are also data sets on chained CPI, producer price inflation, and even the off-puttingly named “GDP deflator.” 

At its most basic, CPI measures how the total cost of a typical household’s shopping basket changes over time, and is calculated every month. Since these measurements are based on a survey, they take time to compile and thus CPI is a lagging indicator: Tuesday’s numbers are for December’s shopping basket. It’s a big basket – large enough to include not just meat and potatoes, but also gasoline, used cars, airfare, and school tuition. 

Most journalists tend to focus on a single measure of inflation in their reporting: the percentage change in the non-core CPI-U figure from the same month a year earlier.

This makes sense from an audience perspective, since “non-core” CPI includes prices for fuel and food – key products for most consumers but which are susceptible to sudden and dramatic price changes due to supply disruptions. As such, the non-core year-on-year comparison tends to present a bigger, and more headline-worthy, change than other inflation measures. For example, core CPI-U rose by 5.5% in December from the previous year, and by just 0.6% from the previous month on a seasonally adjusted basis (more on seasonally adjusted figures below). 

The volatility in non-core CPI also makes it less useful as an indicator of longer-term trends; when determining how to respond to inflation, economic-policy makers focus on core CPI data, which exclude food and energy prices, rather than non-core. So when reporting on the Fed’s interest-rate policies, it’s best to use the core figures in stories. 

The “U” in CPI-U represents an often-overlooked aspect of this data set: it only measures prices in urban areas. The BLS divides the urban areas of the United States into 32 geographic areas, which cover most of the population but omits wide geographic swaths of the country due to limitations in data-collection capacity. This indicator aims to track prices for the most common goods of the average U.S. consumer; a separate indicator, CPI-W, focuses just on the shopping basket for wage-earners – but is also limited to those living in urban areas. 

While a year-on-year comparison is the most common way to report inflation, a month-on-month percentage change can be more helpful in illustrating the near-term trend in price changes. That figure is also better able to highlight sudden changes that might be hidden in the yearly data. However, because consumer behavior is seasonal – consumption tends to increase in the run-up to the year-end holiday season, for example – any month-to-month comparison needs to be “seasonally adjusted” to present an accurate picture. This adjustment relies on a long-term look at typical seasonal trends and then increases or decreases the figures to remove the impact of those trends from the data series. Make sure that any month-to-month comparison for inflation data is based on these seasonally adjusted figures. 

One other factor that can lead to distortions in the picture of inflation as painted by CPI-U is how consumers change their purchasing habits in response to a sudden price hike for a particular product. For example, if a shopper finds that the supermarket price of beef has risen sharply since their last shopping trip, they might decide to buy pork or chicken instead. If many consumers make the same decision, then this will change the composition of the country’s typical shopping basket for that month – but the basket used to calculate CPI-U won’t be updated to reflect that change. So the inflation as measured by CPI-U will be higher than what’s actually experienced by consumers. This is where chained, or chain-weighted CPI (C-CPI-U), comes in: this data series is adjusted to account for changes in consumer behavior not picked up by CPI-U, and can often present a more accurate picture of inflation when prices are particularly volatile. 

In addition to measures of consumer-price inflation, it can be helpful to look at other measures of price changes in the economy. In particular, looking at price changes for manufacturers and other producers can sometimes help predict future trends in consumer prices, as for example manufacturers might raise the prices they charge in response to higher prices for their raw materials. The BLS produces a monthly data series called the producer price index that tracks prices in the domestic supply chain, a particularly helpful indicator now with all the disruption to the supply chain globally. 

Perhaps the most obscure measure of price changes in the economy, the GDP deflator, can also be the most useful as it measures the broadest possible range of prices, including the prices for all goods and services produced in the United States. While the main purpose of the GDP deflator is to adjust the calculation of gross domestic product to remove the effects of inflation, it can also serve as an overall measure of inflation and a helpful comparison to narrower indicators like CPI and PPI. The GDP deflator in the U.S. is calculated on a quarterly basis (corresponding to the release of GDP data) by the Bureau of Economic Analysis at the Department of Commerce.

For more information on the various ways to measure price changes and how they’re calculated, check out the Bureau of Labor Statistics’ website – it’s a fantastic resource for business journalists, and the general public.

Author

  • Jeffrey Timmermans

    Jeffrey Timmermans has more than two decades of experience as a financial journalist and journalism educator, having worked as a reporter in Tokyo for The Wall Street Journal and as a managing editor for Dow Jones Newswires in Hong Kong and Singapore...

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