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Inflation Update Glossary

Annualized rates: A change in a price index (or of the price of a particular item) from one month to the next can be expressed at a monthly rate (just the percentage change from one month to the next) or at an annualized rate—the percentage change we would obtain if the one-month change were repeated every month for a year. This is analogous to rates on credit card balances, which can be quoted in daily terms or as an annual percentage rate (APR). Even though you may not carry a balance for an entire year, you probably still use the APR to describe the rate you’re paying. In our Inflation Update, we like to put most numbers in the form of annualized rates, since this facilitates comparison of price changes over different horizons.

Components of personal consumption expenditures (PCE): In the Inflation Update, we often mention what fraction of items fell in price in a given month or what fraction had annualized price increases in a given range, say 0 percent to 2 percent. What are the underlying data these statements are based on? The data are for the 178 components used to construct the trimmed mean. From the Dallas Fed’s Trimmed Mean PCE web page, follow the link “Components included and excluded from this month’s trimmed mean” to see an Excel spreadsheet listing all 178 components.

Core goods and core services: Goods are items taking the form of a physical commodity, like a TV, a steak or a gallon of gasoline. Core goods are goods apart from food and energy items. Services are, well, services—like a haircut (the economist’s favorite example), a stay at a hotel, an airline trip or the electricity services you obtain from your utility provider. Core services are services other than energy services. In PCE, dining out at a restaurant is treated as a core service. This is not the case in the consumer price index (CPI), which groups meals at restaurants together with other food items—and thus excludes them from the core.

Department of Energy (DOE) weekly retail gasoline price data: The DOE’s Energy Information Administration collects and publishes weekly data on the average retail price of a gallon of gasoline. By the time PCE data covering a given month are released, we usually have three or more weeks worth of DOE price data for the subsequent month. Given the large weight gasoline carries in the headline PCE index (and the large volatility of gasoline’s price), the weekly retail price data are useful for getting a rough sense of what we can expect for headline PCE inflation when data for the subsequent month are released. The DOE data can be found at

Headline, core and trimmed mean PCE inflation: “Headline” PCE refers to the all-items PCE index (that is, the index including all items of personal consumption expenditure, excluding none). “Core” PCE refers to the index excluding food and energy items. This is the common usage, though some economists take core inflation to mean the underlying trend in headline inflation; for them, the “ex food and energy” inflation rate is one particular estimate of core inflation. The “trimmed mean” inflation rate is constructed by excluding the items that registered the biggest increases or decreases in a given month, regardless of whether those items are food, energy or something else. Taking core inflation in the sense of underlying trend inflation, the trimmed mean is an alternative estimate of that trend. The headline and core (ex food and energy) numbers are produced by the Bureau of Economic Analysis (BEA) and available at Using BEA’s data, the Dallas Fed produces a trimmed mean PCE inflation rate ( The Cleveland Fed produces a trimmed mean and median CPI inflation rate (, using data from the Bureau of Labor Statistics, the official source for CPI data.

More processed, less processed: Most current theoretical models of inflation (and monetary policy’s impact on inflation) suggest that central banks should focus their attention on prices that exhibit “stickiness”—that is, prices that don’t adjust instantaneously to changing supply and demand conditions. The price of a cup of coffee at Starbucks, for example, may be changed only once or twice in the course of a year, even though the price of one of the primary inputs—coffee beans—is perhaps changing on a daily basis. Economists would characterize the price of coffee beans as flexible and the price of the cup of coffee at Starbucks as sticky. In general, among food items, the less processed the item, the more likely its price is flexible (and conversely—the more-processed items probably exhibit more price stickiness). We thus might want to pay a bit more attention to what’s going on with the price of, say, snack foods or breakfast cereals, than with the price movements in a relatively unprocessed category like fresh fruit.

Owners' equivalent rent (OER): In the PCE (as well as the CPI), the cost of the housing services consumed by someone who owns his own home is measured by OER. In principle, OER answers the question: How much rent would I be paying to live here if I didn’t own this home? In practice, OER is not measured directly, but is imputed from data on rents paid by actual renters. OER is the single largest item in both the PCE (with a share of about 12 percent) and CPI (with a share of about 24 percent).

Seasonally adjusted: The prices of some items have a regular rhythm to them over the course of a year. Gasoline prices, for example, typically go up in March, April and May, and fall in July, August and September. Seasonal adjustment subtracts an estimate of the normal seasonal variation in an item’s price to isolate movements that are either higher or lower than we would normally expect, given the seasonal cycle. For example, based on the seasonal price pattern of the past few years, a roughly 5 percent increase in the price of gasoline in March is normal. If we then observe a 5 percent increase in price in March, the seasonally adjusted data would register “no change” (a 0 percent rate). If we observe a 7 percent increase, seasonal adjustment would count 5 percentage points of that as normal variation and just register a 2 percent increase. And if we saw only a 3 percent increase—2 percentage points short of what we would normally expect—the seasonally adjusted data would register a 2 percent decline.