Fewer Consumers Are Raising Eyebrows at Prices as Inflation Cools
![](/_next/image?url=https%3A%2F%2Fpro-assets.morningconsult.com%2Fwp-uploads%2F2023%2F11%2FEcon-Report-FI-US-Inflation.jpg&w=1920&q=100)
Key Takeaways
Fewer adults were surprised by prices of goods and services in June, suggesting another month of cooler inflation.
Category price surprise scores track closely with inflation, though price changes for infrequently purchased goods and services take longer for consumers to notice.
A linear regression model combining price surprise scores for categories with the strongest associations with inflation has been predictive of overall monthly inflation; for June, this model estimates that prices overall stayed essentially flat.
The Price Surprise index measures the prevalence of consumers seeing higher than expected prices when purchasing various goods and services. In effect, it is tracking how quickly consumers recognize price increases. At the aggregate level, the price surprise has a strong correlation with the Bureau of Labor Statistics’ measure of annual inflation. The index declined in June, suggesting another month of cooling price growth.
Aggregate Price Surprise Has .9 Correlation With Topline Inflation
![](/_next/image?url=https%3A%2F%2Fpro-assets.morningconsult.com%2Fwp-uploads%2F2024%2F07%2Fprice-surprise-1.png&w=1920&q=100)
At the category level, however, dynamics are more complicated, as different purchasing patterns for various goods and services result in different relationships between price changes and consumers’ awareness of their own price surprise.
Consumers are quick to notice shifts in gas or food prices
For certain frequently purchased categories for which consumers have a strong awareness of current prices, like gas or food, monthly changes in price surprise track closely with changes in the associated consumer price index category.
A shift in gas price levels, for example, will immediately trigger price surprise among consumers: Gas price surprise has maintained a .93 correlation with the corresponding consumer price index. In June, gas price surprise declined, previewing a likely fall in monthly inflation for the category.
Consumers Register Changes in Gas Prices Right Away
![](/_next/image?url=https%3A%2F%2Fpro-assets.morningconsult.com%2Fwp-uploads%2F2024%2F07%2Fprice-surprise-2.png&w=1920&q=100)
Food price changes are also among the most likely to quickly garner attention from consumers. Both grocery and restaurant price surprise scores show a close relationship with monthly fluctuations in consumer prices, though with a slightly longer lag compared with gas. Price surprise scores converted to two- or three-month averages for groceries and restaurants correlate more strongly with monthly inflation movements than the raw monthly values. Furthermore, particularly for groceries, consumers’ awareness of price changes seems to peak a couple months after prices change. The delay in recognizing grocery price changes may be due in part to the nonuniformity that exists within the food category; for example, consumers may buy milk and eggs every week, but steak or watermelon might be more of an occasional treat.
Food Price Growth Elicits Consumers’ Notice Within a Few Months
![](/_next/image?url=https%3A%2F%2Fpro-assets.morningconsult.com%2Fwp-uploads%2F2024%2F07%2Fprice-surprise-3.png&w=1920&q=100)
Items bought just a couple times per year take longer to trigger price surprise
Among less frequently purchased categories such as durable goods or vacations, monthly price changes take even longer to capture consumers’ attention. A buyer’s frame of reference for how much an item not purchased for several months “should” cost will likely not be as current as the frame of reference for something purchased weekly or monthly. Consequently, it may take a few months of cumulative price changes for price changes to penetrate consumers’ consciousness. Correlation patterns between category price surprise data and corresponding price changes for those categories data bears this out. For example, price surprise scores for infrequently purchased categories, like home repairs and vacations, show a stronger relationship with 6-month or annual inflation rates.
Price Changes For Infrequently Purchased Items Take Longer to Trigger Consumer Awareness
![](/_next/image?url=https%3A%2F%2Fpro-assets.morningconsult.com%2Fwp-uploads%2F2024%2F07%2Fprice-surprise-4.png&w=1920&q=100)
The housing component: Constantly paid for but infrequently bought
Housing is a tricky category in that it is one of the least frequently purchased items (people don’t move very often), yet rents or mortgages are typically the single largest monthly expense for households. The component carries a large weight in the consumer price index (rent and owners’ equivalent rent make up about a third of the CPI), but prices for newly purchased homes or apartments make up a relatively small share of the housing units sampled each month. Current home prices therefore are digested on a lag by the consumer price index.
For price surprise, the housing index is tracking only consumers who made a home or apartment purchase each month. Residents living in place with long-term leases and mortgages–in other words, most consumers–are left out of this index.
The sampling and timing dynamics impacting the housing CPI and price surprise scores result in a unique relationship between the two indexes. Because housing is rarely purchased, the longer-term frame of reference for evaluating prices likely applies: It takes several months for consumers’ level of price surprise to respond to changes in actual prices. However, the delayed manner in which the housing CPI incorporates current home prices means price surprise may in fact lead the CPI to an extent, since Morning Consult’s index is capturing only consumers encountering current market prices. Perhaps as a result of these complicating factors, the six month moving average of housing price surprise, leading by one period, results in the strongest correlation with monthly housing inflation (.8).
Price Surprise for Homes and Apartments May Help Preview Shelter CPI
![](/_next/image?url=https%3A%2F%2Fpro-assets.morningconsult.com%2Fwp-uploads%2F2024%2F07%2Fprice-surprise-5.png&w=1920&q=100)
Using categories with strongest links to CPI to nowcast inflation
Identifying the categories with the strongest links to monthly price changes–and the specific transformations of those categories that maximizes their respective correlations–results in a set of ingredients that may be useful for estimating monthly topline inflation. Morning Consult’s survey runs several weeks ahead of the Bureau of Labor Statistics’ CPI release pertaining to the same month, so a model combining these price surprise variables could theoretically be used to “nowcast” inflation. A multiple linear regression model combining the price surprise indexes for most of the categories discussed above–gas, groceries, restaurants, home improvement supplies and housing–along with the lagged monthly CPI value, appears historically predictive of monthly changes in the topline consumer price index.
Morning Consult’s Data Suggests June Inflation Remained Subdued
![](/_next/image?url=https%3A%2F%2Fpro-assets.morningconsult.com%2Fwp-uploads%2F2024%2F07%2Fprice-surprise-6.png&w=1920&q=100)
The model has relatively short history to work with, as price surprise data has only been collected since early 2022. While the preliminary findings are promising, it will take time and potentially further refinement of the variables to establish whether the model has long-term predictive usefulness. Keeping those caveats in mind, the price surprise-based model projects that prices overall grew just 0.03% in June, slightly below the 0.1% consensus forecast and the 0.07% Cleveland Fed Nowcast for topline monthly CPI growth.
![A headshot photograph of Kayla Bruun](/_next/image?url=https%3A%2F%2Fpro-assets.morningconsult.com%2Fwp-uploads%2F2022%2F09%2F21094823%2FKayla-Brunn.jpg&w=96&q=75)
Kayla Bruun is the lead economist at decision intelligence company Morning Consult, where she works on descriptive and predictive analysis that leverages Morning Consult’s proprietary high-frequency economic data. Prior to joining Morning Consult, Kayla was a key member of the corporate strategy team at telecommunications company SES, where she produced market intelligence and industry analysis of mobility markets.
Kayla also served as an economist at IHS Markit, where she covered global services industries, provided price forecasts, produced written analyses and served as a subject-matter expert on client-facing consulting projects. Kayla earned a bachelor’s degree in economics from Emory University and an MBA with a certificate in nonmarket strategy from Georgetown University’s McDonough School of Business. For speaking opportunities and booking requests, please email [email protected]