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Lennart Brandt, Natalie Burr and Krisztian Gado

The Financial institution of England has a 2% annual inflation charge goal within the ONS’ shopper costs index. However taking a look at its 700 merchandise classes, we discover that only a few costs ever change by 2%. Actually, on a month-on-month foundation, solely about one fifth of costs change in any respect. As an alternative, we observe what economists name ‘sticky costs’: the value of an merchandise will stay fastened for an prolonged period of time after which regulate in a single giant step. We doc the time-varying nature of stickiness by trying on the share of worth modifications and their distribution within the UK microdata. We discover a seen discontinuity in price-setting within the first quarter of 2022, which has solely partially unwound.
Idea of sticky costs and associated literature
Understanding price-setting dynamics is important for central banks. Most structural fashions within the literature use a type of time-dependent pricing, underneath which companies maintain costs the identical for fastened quantities of time (Taylor (1980)), or for random quantities of time such that there’s uncertainty in regards to the exact size of the value spell (Calvo (1983)). One other means of modelling sticky costs emphasises that companies is not going to simply have a look at the time that has handed since they final adjusted its worth, but in addition at how far their worth is from some desired worth stage. That is known as state-dependent pricing. Macroeconomic fashions don’t sometimes enable for time-variation within the diploma of stickiness or switching between pricing methods. Lately, nevertheless, companies within the Choice Maker Panel inform us that they’ve moved more and more away from time-dependent in the direction of state-dependent pricing. On this case, when there’s a giant shock affecting many companies, the shock results in an elevated frequency of worth modifications and so extra fast pass-through to total inflation.
So as to higher perceive the pricing behaviour of companies in instances of enormous inflationary shocks, we discover the pricing dynamics on the micro stage utilizing CPI microdata revealed by the ONS. We’re after all not the one ones who’ve been fascinated by one of these information. Financial institution authors have been utilizing this information set for a variety of years. For instance, Bunn and Ellis (2011) doc stylised information about pricing behaviour from the UK microdata and the August 2020 Financial Coverage Report used CPI microdata to tell coverage. Elsewhere, Karadi et al (2020) use US microdata to analyse companies’ price-setting in response to modifications in credit score situations and financial coverage. Nakamura et al (2018) analyse the societal value of excessive inflation utilizing microdata from the Nineteen Seventies and Eighties, and Montag and Villar (2023) analyse the impact of extra frequent price-changes on mixture inflation throughout Covid. Relatedly, Davies (2021) finds that the distinction between the share of worth rises and worth cuts within the UK microdata is said to mixture inflation, specializing in price-setting in the course of the pandemic. And eventually, authors of the FT’s Alphaville weblog have additionally been trying into these information (see right here and right here).
The information
The microdata spanning from 1996 till September 2023 is publicly accessible and up to date month-to-month after every CPI launch. It incorporates the month-to-month worth quote information underpinning the ONS’ CPI sequence for over 700 gadgets with identifiers on the store, store kind, and area ranges. We clear the info which works out to about 30 million observations. When figuring out a worth change within the information, which is in the end what issues for inflation, we attempt to be as exact as potential close to the product and the timing of the change. To that finish we solely depend the change if we discover the identical merchandise, in the identical area, in the identical store, in two precisely neighbouring months. For instance, if a bag of potatoes value £2 in January and £3 in March however was not recorded in February, relatively than imputing a worth we discard the commentary since we can’t be certain through which month the change really occurred.
Stylised information from the microdata
A short have a look at the info lets us set up some stylised information. Chart 1 exhibits a decomposition of those month-on-month worth actions over all gadgets within the information set. 4 key observations stand out:
- Costs rise and fall on a regular basis, however the overwhelming majority of costs don’t change between months. In any given month, on common since 1996, round 80% of costs stay unchanged relative to the earlier month (blue line).
- The share of costs rising (in inexperienced) has elevated notably since 2021 to an extent that has not occurred in earlier inflationary episodes within the pattern (excluding VAT modifications).
- The share of costs falling (in pink) has fallen considerably however stays steady since 2021, relative to historic common. The primary margin of adjustment has been within the share of worth will increase.
- However, in latest months, whereas the share of costs rising has tapered off, it stays elevated relative to its historic common.
Chart 1: Decomposition of worth actions month-on-month

Notes: The share of costs rising and falling mirror month-on-month modifications. Shares are seasonally adjusted utilizing the R bundle seasonal. Spikes in 2008, 2010 and 2011 are a consequence of UK VAT modifications (17.5% to fifteen% in 2008, improve to 17.5% in 2010 and improve to twenty% in 2011). The gray shaded space covers the time between March 2020 and July 2021 when the economic system (and information assortment) was most affected by the Covid pandemic. Dashed strains present the 2011–19 averages. Newest commentary: September 2023.
Sources: ONS and authors’ calculations.
To be clear, this chart isn’t saying that 80% of merchandise by no means change costs. If the value of an merchandise remained fixed between December and January, and rose between January and February, it might transfer from the blue into the inexperienced class throughout this era. Equally, it might fall out of the inexperienced, into the blue or pink, if from February to March the value once more remained fixed, or fell, respectively.
So, maybe surprisingly, this chart exhibits that month-to-month worth dynamics within the economic system are pushed by solely a comparatively small fraction of roughly 20% of all items and companies within the consumption basket. Additionally, we see that in the newest episode, the shift into rising costs has been largely out of the ‘no change’ class. Therefore, fewer costs are staying fastened, and extra are rising. It’s value noting that the latest up-tick within the shares of costs rising is barely matched traditionally by these attributable to VAT modifications in 2008, 2010 and 2011, which nevertheless seem as one-off worth spikes relatively than a persistently larger share of worth rises, as in 2022.
If it’s a minority of whole merchandise whose worth modifications, it is very important take a better look. Chart 2 exhibits the distribution of costs modifications from 2019 by quarter (truncated at zero to exclude no-change observations). Consistent with the rise within the inexperienced line in Chart 1, we observe that over 2021 and 2022 a number of mass moved into the appropriate aspect of the distribution, that’s the share of worth will increase, with the share of worth decreases being comparatively steady.
Chart 2: Evolution of the distribution of worth modifications by quarter 2019–23

Notes: The share of costs that didn’t change is excluded from these densities. The truncated densities are estimated in R by way of the Bounded Density Estimation bundle utilizing the boundary kernel estimator. Darker colors correspond to quarters through which year-on-year CPI inflation was comparatively excessive, lighter colors to quarters through which it was low. Every distribution represents month-on-month modifications inside the similar quarter. Newest commentary: 2023 Q3.
Sources: ONS and authors’ calculations.
A observe on the chart: the distribution of worth modifications, when mixture inflation is at or shut to focus on, is roughly symmetric in logarithms. On this scale, a doubling (+100%) is equally distant from zero as a halving of the value (-50%). On account of gross sales, the doubling and halving of costs really occurs usually within the information, which explains the bunching round these factors. Whereas these could also be a supply of seasonality within the information, which can obscure the underlying dynamics, we don’t imagine they’re necessary for the general form of the distribution which we present right here.
In Chart 3, we zoom in on a few these densities to higher see variations of their form. They’re the densities corresponding to cost modifications within the third quarter of 2022 and 2023 alongside a median density over the pre-Covid interval.
Chart 3: Comparability of densities from 2022 and 2023 towards a pre-Covid common

Notes: The share of costs that didn’t change is excluded from these densities. The truncated densities are estimated in R by way of the Bounded Density Estimation bundle utilizing the boundary kernel estimator. To match densities throughout time, they’re normalised to sum to the typical share of costs falling and rising respectively inside the quarter. The yellow line exhibits the pointwise common density over the third quarters of the years 2011–19.
Sources: ONS and authors’ calculations.
We are able to see how, in comparison with this historic common – which we use as a stand-in for pricing behaviour when inflation was near the two% inflation goal – 2022 noticed an enormous variety of costs improve whereas there was little change within the behaviour of the decrease a part of the distribution. Within the newest information, this mass of will increase has begun to subside, and, on the similar time, there’s a rising variety of costs outright falling on the month. Nonetheless, the modal worth improve (that’s, probably the most possible) continues to be elevated at about 6%, in comparison with roughly 3% on common throughout 2011–19).
Conclusion
To summarise, trying on the micro stage of worth modifications, we discover a seen discontinuity in price-setting within the first quarter of 2022. A wide range of components, akin to the massive rise in power costs in early 2022, in addition to supply-chain points following Covid lockdowns, seemingly contributed to this important change in price-setting dynamics within the UK (relative to any latest historic precedent at the very least). On the micro stage, companies’ pricing choices led to the emergence of a big rebalancing within the distribution of worth modifications. Out of the blue, extra costs for a lot of completely different merchandise have been rising on the similar time. In comparison with the accessible historical past for these information, the latest interval is exclusive. Extra analysis can be wanted on the causes of this marked shift within the distribution of worth modifications, each at a micro and at a macro stage.
Within the very newest information, there may be some proof that the distribution of worth modifications has certainly begun to return within the course of its historic common, although it’s too quickly to determine a development.
Lennart Brandt and Natalie Burr work within the Financial institution’s Exterior MPC Unit, and Krisztian Gado is a PhD candidate at Brandeis College.
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