Ever since Trump announced that former Fed Governor Kevin Warsh was his nominee to lead the central bank, there was a question: Would Trump now end his feud with current chairman Jerome Powell (whom he also nominated in 2017) to clear the path for a shiny, new face behind the podium?
It seems not.
The president told Fox News in an interview published yesterday that he wouldn’t be dropping a criminal probe into Powell over renovations to the Fed building. Powell announced in January that the Department of Justice had served subpoenas on the central bank, relating to his testimony about work on the offices overlooking the National Mall.
“Don’t you think we have to find out what happened there?” the president told Fox. “I have to find out.” He added, “I’ve held back from firing him. I’ve wanted to fire him, but I hate to be controversial, you know?”
In pursuing Powell, Trump has placed an obstacle in the path of Warsh, his own nominee.
Among Republicans, Warsh is seen as something an ideal candidate: He is a staunch advocate of Fed independence (a relief to both Wall Street analysts and D.C. policymakers); he knows the central bank, having served under chairman Ben Bernanke; and he has signaled a more optimistic outlook on the U.S. economy than the current incumbent at the Fed.
Warsh’s path back to the central bank includes Senate Banking Committee hearings, penciled in for April 21. The committee is held by a slim Republican majority of 13, two ahead of their Democratic counterparts. One of those Republicans, Thom Tillis, has made it clear he will block Warsh’s progression through the process if the case against Powell isn’t dropped.
It’s nothing personal. Tillis previously said: “My position has not changed: I will oppose the confirmation of any Federal Reserve nominee, including for the position of Chairman, until the DOJ’s inquiry into Chairman Powell is fully and transparently resolved.”
Republican sources told Fortune that it was unlikely Warsh himself would be the cause of any vote against his candidacy, while Democrat sources say there is little he could do to convince critics that he isn’t a puppet for the White House.
If Tillis were to block Warsh, the committee would be split—indeed, it would only take one maverick vote among the remaining Republicans to nix his chance. It seems Trump is betting on Tillis to back down, telling Fox: “He’s on his way out … and I think he doesn’t want the legacy of stopping a great person who could be great … I know he said what he said, and maybe it’s true, in which case I’ll have to live with it.”
A hill to climb for Warsh
On the issue of Fed independence, the president hasn’t been hugely helpful. Markets and lawmakers are already sensitive to the suggestion that the influence of politicians may be seeping into the U.S. Federal Reserve: Trump has threatened to fire Powell a number of times, as well as insulting his character and policies. Meanwhile, Trump has been clear that whoever landed the nomination would have to be more dovish than Powell, and has piled praise on Warsh.
If and when Warsh does make it to the chairman’s office at the Fed (albeit not in the same building he previously served in) his job will likely be harder: He’ll have to convince colleagues who have built their careers on institutional credibility and independence that he is not the White House pawn naysayers fear.
Among a raft of reforms Warsh has previously indicated he’d like to see at the central bank, he has advanced a bullish outlook on the productivity benefits of AI, the strength of which could provide the basis for an argument to begin a rate-cutting cycle. Despite those opinions being public and stated for some time, selling them internally at the Fed may be harder due to heightened skepticism about his motives.
Yet despite the early snags, Trump’s preoccupation with the Fed building—in the event that Warsh makes it through the hearings process—may prove useful. Trump has brought his penchant for real estate development to the White House (just look at the East Wing), perhaps explaining his focus on the Fed’s bricks-and-mortar activities. If Trump’s focus on the Fed is drawn away from policy, it may give Warsh some much-needed breathing room.
While Powell and Warsh may disagree on the path of policy, they can agree on one thing: The Fed should be kept well away from politics, and even further away from the court system. “Stay out of elected politics,” was Powell’s advice to his successor.
That is precisely the plan. Warsh has continually advocated for the Fed to be scaled back to its core remit: An economist who wants to fundamentally reshape the Fed’s relationship with the bond market isn’t a man who wants the Fed tangled in the court system.
With increased availability of big data and computing power, more firms are adopting algorithmic and AI-powered pricing to adjust prices rapidly in response to changing economic conditions over time and across consumers. This post reviews the existing research, draws implications for central banks, and identifies areas for further research on this topic. The research reviewed here was also used to inform Lombardelli and Patel (2026). The existing research suggests that new pricing technologies will lead to faster pass-through of shocks to prices, greater market segmentation, and may improve the inflation-output trade-off for monetary policy makers. To ensure price stability, central banks will need to monitor granular, high-frequency price data to gauge the impact of shocks on prices and inflation expectations.
Have prices become more flexible?
Improvements in pricing technology, such as electronic shelf labels and real-time algorithmic pricing, reduce the cost of changing prices and increase the frequency of price adjustments, thus making prices more flexible. The average length of time retail prices are fixed in the US has roughly halved over the past decade (Cavallo (2019)). Online prices change more often than offline prices (Gorodnichenko et al (2018)), suggesting that overall prices faced by consumers could become more flexible as more transactions move online.
The lower cost of changing prices may speed up pass‑through of shocks to aggregate price levels. Using more than 20 million prices for multiple online sellers, Gorodnichenko and Talavera (2017) and Cavallo (2019) report stronger pass-through and faster convergence of prices to new equilibrium levels in response to exchange rate and gas price shocks. However, the extent of price stickiness and pass-through varies by item (eg brand loyalty), sector (eg firm-entry costs) and the market (eg degree of competition) (Gorodnichenko and Talavera (2017)). So central banks will need to monitor granular, high-frequency data to understand the speed of pass-through across different segments of the economy.
A micro lens: do algorithms raise prices or just disperse them?
Historically, dynamic pricing – whereby firms adjust prices over time in response to changing economic conditions – has been used to manage capacity through price discrimination. Airlines, for example, use dynamic pricing to reallocate demand across time (Puller and Taylor (2012)), while ticket sellers extract surplus through timing discounts rather than increasing mark‑ups (Sweeting (2012)).
The impact of algorithmic pricing – whereby firms use data-driven, rule-based processes to adjust prices – on retail prices is mixed. The possibility that algorithms interact to raise prices has been shown in simulated marketplaces (Calvano et al (2020)), but there is limited real-world evidence on this (Schwalbe (2019)). Assad et al (2024) find that algorithmic pricing increases margins by 15% in a cross-country study of the retail gasoline sector. By contrast, Brown and MacKay (2023) report that drug retailers charge lower prices when algorithms respond rapidly to competitors’ prices. Overall, existing research is inconclusive as to whether algorithmic pricing increases prices.
Algorithmic and AI-based pricing can be used not only to adjust prices across time, but also across consumers, for example by enhancing firms’ ability to personalise prices based on consumers’ characteristics. This may lead to higher price dispersion as individuals with high willingness-to-pay subsidise those with lower willingness-to-pay. There is established evidence that US retailers adjust prices in response to local demand conditions (Stroebel and Vavra (2019)). Although the extent to which pricing technology is currently used to target demand at a highly granular level remains unclear, it is likely to result in a wider array of prices faced by consumers, increasing price dispersion.
A macro lens: what happens to inflation?
If more flexible micro prices translate to more flexible aggregate price levels, then inflation will respond more strongly to real economic conditions. In a standard framework, less price stickiness yields a steeper Phillips curve, implying that central banks can lower inflation with a smaller sacrifice in terms of unemployment or output. An inflation-accelerator mechanism could also amplify inflation if firms raise markups more aggressively when inflation is already high. In Blanco et al (2024)’s framework, a self-fulfilling cycle occurs as the fraction of price changes increases with inflation, leading to more price increases. The consequence is again a steeper Phillips curve in high-inflation periods.
Market features, such as the extent of competition and returns to scale (whether a firm’s production gets more efficient with its size), also influence monetary policy transmission. Further research should examine how algorithmic pricing shapes competition and firm cost structures, which will affect aggregate price markups. For example, access to customer data may serve as a barrier to entry, strengthening the market power of incumbent firms, which is perhaps already on the rise in the US (De Loecker et al (2020)) and the UK (Savagar et al (2024)). Greater market power enables firms to price further above cost, raising the price level. Conversely, the new pricing technologies could lower costs. For example, better pricing technology could minimise waste of perishables, improve inventory management, and so mitigate upward pressure on food prices resulting from shocks to energy prices. This mechanism could be further enhanced if increasing returns to scale lower costs for the largest firms. Thus, new pricing technologies may shake-up existing market structures, change the balance between incumbents and new innovators, and alter how shocks to costs translate to prices and inflation.
Will it affect inflation expectations?
Anchoring inflation expectations is central to monetary policy effectiveness. Firms’ pricing decisions play a key role in shaping consumers’ inflation expectations. In that context, it is notable that Cavallo et al (2017) find that consumers focus on retail prices rather than official inflation statistics, with food and other frequently purchased items appearing particularly important in shaping inflation expectations (Anesti et al (2025) and D’Acunto et al (2021)).
Further research is needed to examine how algorithmic pricing – which could increase the frequency of price changes and dispersion of prices – influences inflation expectations. For instance, algorithmic pricing could increase expected inflation volatility and thus could increase precautionary savings. Similarly, rapid pass-through of cost shocks could risk de-anchoring of inflation expectations. Reis (2022) emphasises that unanchored inflation expectations during periods of inflation can extend the lifespan of otherwise transitory shocks.
If we all pay different prices, what even is inflation?
Algorithmic pricing also complicates the measurement of inflation itself. When algorithms reprice products frequently, conventional CPI sampling (monthly, store-level) will understate the true frequency and variance of adjustment (Cavallo (2019); Leung et al (2023); Davies (2021)). Moreover, posted prices may differ substantially from transaction prices once discounts and personalised offers are taken into account, straining the concept of a ‘representative’ price (Lombardelli and Patel (2026)).
As a result, official inflation measures may diverge from consumers’ lived experience. Statistical agencies, including the Office for National Statistics, are responding to this challenge by using new data sources, such as groceries scanner data which allow for high frequency, broad-based and automated collection of prices that accurately reflect prices paid by consumers. Several central banks are also using web-scraped data to study heterogeneity in realised inflation (Messner and Rumler (2024)), nowcasting (Macias et al (2023)) and high-frequency pass-through (Gautier et al (2023)).
Conclusion
New pricing technologies increase frequency of price adjustment, with ambiguous effects on price levels. It enhances pass-through of shocks to prices and enables market segmentation, but it does not necessarily imply greater macro-volatility or a worsening trade-off for monetary policy makers.
Further research is needed to understand how changes in pricing technologies and strategies are shaping the macroeconomy, as well as inflation expectations. This includes construction of high-frequency, granular data sets to enable central banks to monitor the speed of pass-through of shocks, as well as their impact on inflation expectations. More work is also needed to examine how dynamic pricing, along with agentic AI and more personalised pricing, reshape competition across sectors and affect consumer welfare.
Anthony Savagar and Misa Tanaka work in the Bank’s Research Hub and Jagdish Tripathy works in the Bank’s Centre for Central Banking Studies.
If you want to get in touch, please email us at bankunderground@bankofengland.co.uk or leave a comment below.
Comments will only appear once approved by a moderator, and are only published where a full name is supplied. Bank Underground is a blog for Bank of England staff to share views that challenge – or support – prevailing policy orthodoxies. The views expressed here are those of the authors, and are not necessarily those of the Bank of England, or its policy committees.
Share the post “What machines taking over pricing means for central banks”
Here’s a number that should make you both furious and curious: approximately 1 in 7 people in the U.S. have unclaimed cash or property waiting to be claimed, according to the National Association of Unclaimed Property Administrators (NAUPA). That’s not a typo: 1 in 7. And it gets worse. In fiscal year 2024, states returned over $4.49 billion to owners — meaning billions more are still sitting in…
The SEP IRA allows you to contribute up to 25% of your compensation, or up to $72,000 in 2026.
Remember, you can contribute to your SEP IRA all the way up until the tax deadline – April 15.
Whether you’re a side hustler or a full-time entrepreneur, a SEP IRA or Simplified Employee Pension Individual Retirement Account, may allow you to boost investment returns by reducing your taxes while saving for retirement.
SEPs were created for small business owners with employees and those who are self-employed, without any employees. They’re a sort of like a mix between a 401(k) and traditional IRA.
Before you open an account, find out whether you’re eligible and how much the contribution limits are.
What is SEP IRA?
A SEP IRA is a retirement account designed specifically for the self-employed and people that own small businesses. Business owners can make contributions to SEP accounts for themselves and employees. Once the contributions are made, the account is owned completely by the employee. However, employees can’t make their own contributions to the plans.
Compared with traditional 401(k) plans, SEP IRAs are typically easier for you, the business owner, to create and maintain without a lot of accounting stress. Most brokerages allow you to open SEP accounts for yourself and your employees. You can make contributions by mailing in checks or through electronic transfers.
Who is Eligible to Start a SEP IRA?
Anyone with self-employed or small business income may qualify to contribute to a SEP-IRA. If you have employees, you must contribute an equal portion of compensation for yourself and your employees. Most people working in the gig economy will qualify to open a SEP IRA since they earn 1099-NEC income.
SEP IRA Contribution Limits
In 2026, you can contribute 25% of your total compensation to an IRA with a maximum contribution of $72,000.
For self-employed people compensation is your revenue, less expenses including half of your self employed taxes. The example below shows how a self-employed person can figure out their maximum contribution.
Total Revenue
$200,000
Expenses and COGS
$50,000
Net Income (Revenue minus Expenses)
$150,000
Income, less self-employed taxes
(Net Income minus half of self-employed taxes
(Net Income x 7.65%)
$150,000 – $11,475 = $138,525
Contribution Limit (25% of above)
$138,525 x 0.25 = $34,631.25
Should I Contribute To My SEP IRA Or My 401(k)?
If you have a workplace 401(k) and a SEP IRA, you can contribute to both of these accounts. In 2026, you can contribute $24,500 to a 401(k) and up to $72,000 to a SEP-IRA (depending on your earnings). If you have employees, you must contribute at the same rate for them as you do for yourself.
Remember, a SEP IRA is a traditional IRA. As such, you can make traditional IRA contributions to it as well as your employer. Employer contributions don’t contribute to your IRA contribution limit, but your contributions would.
Note: Be careful if you have a third retirement account, such as a Roth IRA. Funds that you contribute (not the employer) to a SEP IRA will reduce the amount you can contribute to your other IRAs.
If you contribute $5,000 to a SEP IRA, you can contribute up to $2,500 to the Roth IRA.
If you contribute $7,500 or more to your SEP IRA, you cannot contribute to a Roth IRA or traditional IRA.
Should I Open a Traditional IRA, Roth IRA, or SEP IRA?
You can typically choose between a traditional IRA, a Roth IRA and SEP IRA for retirement contributions. Each account has its own benefits and drawbacks. This chart compares some of the attributes for each account type.
Remember, though, that the SEP IRA requires you to have a business.
Here are the 2026 SEP IRA contribution limits:
Why Would a Small Business Owner Choose a SEP IRA?
If you own a business, you’ll likely need to choose between a small business 401(k) and a SEP for their business. A SEP is entirely funded by employer contributions, whereas a 401(k) is funded by both employee and employer contributions.
If you have employees you may choose a SEP IRA for the contribution flexibility. Your contribution rate and your employees range from 0% up to 25% of total compensation.
There are restrictions you can choose to limit contributions. For example, you only contribute if your employees meet all three of the following criteria:
Is at least 21 years old
Has worked for the company three out of the last five years
Earned at least $650 in compensation
You can also choose to make contributions for yourself and employees per year instead of worrying about contributing with each paycheck, unlike a 401(k).
Our Picks for the Best Self-Employed Retirement Plans
Setting up these accounts was one of the biggest issues we hear from readers, so we put this review together for you.
READ NOW
When Do You Have to Contribute?
Contributions for yourself and your employees are due by the tax filing due date (including extensions). That means you must make a contribution by April 15 or October 15 if you filed an extension.
Is a SEP Right for Your Business?
Investing in a retirement account offers tremendous tax advantages, but you may not want to lock your money away.
If you have major investments or expenses coming up, you may want to delay contributions until next year. But don’t wait too long to invest so you can take advantage of compounding growth as soon as possible.
The Best Online Stock Brokers—According to Readers
If you’re still stuck in choosing a SEP IRA, Solo 401(k), or SIMPLE IRA for your business, you can use any of these top online brokers to help you open an account. We polled our readers for this one!
Editor: Claire Tak
Reviewed by: Robert Farrington
The post SEP IRA Contribution Limits For 2026 appeared first on The College Investor.
Air New Zealand has revealed its latest innovation, Skynest, which offers lie-flat bunk beds in Economy.
Tucked between the Economy and Premium Economy cabins of Boeing 787-9 aircraft, Skynest features six individual lie-flat pods arranged in a bunk-style configuration.
Air New Zealand Chief Executive Nikhil Ravishankar frames Skynest as a strategic move for a nation whose tourism industry depends on people being willing to make the trip. By making ultra long-haul travel more manageable, the airline is effectively lowering the psychological barrier to visiting.
Each Skynest pod is a private, quiet cocoon: a full-length mattress with fresh bedding, a privacy curtain, ambient lighting tuned for natural sleep and wake cycles, personal storage, USB-A and USB-C charging, and a ventilation outlet. There’s even a “Nestcessities” kit with an eye mask, earplugs, socks, and Aotea skincare products.
Sessions run for four hours, which is designed around natural sleep cycles to allow time to settle in, sleep, and wake gradually. Initially, two sessions will be available per flight, bookable as an add-on by anyone holding an Economy or Premium Economy seat.
Skynest is the result of years of development and testing with more than 200 customers. It follows in the tradition of Air New Zealand’s Skycouch, which reimagined the Economy row as a shared flat surface for couples and families. United will launch its own version of the Skycouch next year.
Economy Skynest Details
Lie-flat sleep pods in the sky for Economy and Premium Economy passengers
Six individual pods arranged in a bunk-style layout
Located between Economy and Premium Economy cabins on Boeing 787-9 aircraft
Four-hour sessions
Two sessions available per flight (initially)
Priced around $290 per session
Available to book from May 18, 2026
Available on flights from November 2026
Economy Skynest Experience
Each Skynest session includes:
A lie-flat sleeping pod with full-length mattress
Fresh bedding including pillow, sheets and blanket, changed in between sessions
Privacy curtain
Ambient lighting designed for rest and wake
Personal stowage and charging (USB-A and USB-C)
Reading light and ventilation outlet
Crew call button and in-pod seatbelt
“Nestcessities” kit including eye mask, ear plugs, socks and Aotea skincare
With the planting season ending in six weeks, skyrocketing fertilizer prices are forcing farmers into an impossible choice: cut back and lose crop yield or stay the course and lose money.
A survey published Tuesday of 5,700 farmers conducted by the Farm Bureau shows that around 70% of farmers are unable to afford all the fertilizer they need, while nearly six in 10 said their finances have worsened due to the rising cost of both fertilizer and fuel.
The new data comes as the Iran war has strangled the global supply chain as Iran exerts its control over the Strait of Hormuz, through which one-third of the global fertilizer shipments flowed before the war. While more than 20 commercial ships passed through the strait over the past several days—an improvement from earlier this month when Iran essentially shut down the strait—it’s unclear whether the flow of ships will improve as the war drags on well nearing its seventh week, despite a ceasefire between the U.S. and Iran signed last week, and a potential extension on the way.
As a result, prices for the three major fertilizers farmers use (nitrogen, phosphorus, and potassium), have all increased by double digits, according to Josh Linville, vice president of fertilizer at financial services firm StoneX Group.
It is the 6-week anniversary of the closure of the Strait of Hormuz. Fert price comparisons:
NOLA urea – +$230 or 49% NOLA UAN – +$145 or 38% Midwest NH3 – +$245 or 32% NOLA DAP – +$130 or 21% NOLA potash – +$10 or 3%
These rising fertilizer prices are taking a toll on farmers who for years have struggled with low commodity prices for the two major crops grown in the U.S., corn and soybeans, which have fallen 40% and 37%, respectively, from their highs in 2022. As of this week, the average price of corn was hovering at $4.15 per bushel down from a high of $6.86 a bushel in 2022. The average price of soybean was $10.30 per bushel, down from a high of about $16.40 in 2022, according to the United States Department of Agriculture (USDA).
The decision to cut back on fertilizer is weighing most on farmers in the South, where only 19% of farmers bought fertilizer ahead of time, according to the Farm Bureau report. The crops these farmers grow—cotton, rice, corn, soybean, and peanuts—rely heavily on added nutrients which leaves them most at risk when fertilizer prices increase, the report claimed.
Farmers’ limited time before planting season ends
The clock is ticking. These farmers have only until the middle of May when planting season ends to decide whether they will scale back on their fertilizer use—which in the long run could lead to lower crop yields—or absorb the elevated costs and potentially lose money on their harvest. Otherwise, some farmers may even choose to sit out the season and potentially add debt through borrowing to make ends meet, Bryan Hansel, chief revenue officer at regenerative agriculture company Holganix, told Fortune.
“This is heart-wrenching for farmers to decide, do I lose money, or do I cut fertilizer, or, like, what do I do?” he said.
To reduce farmers’ demand on fertilizer, one of the best options may be regenerative farming, said Hansel, whose company sells a product, Bio 800, which helps build up the microbiome of topsoil.
Farmers’ overreliance on fertilizers
Decades of American farmers’ overreliance on both fertilizers and quick chemical solutions like pesticides and herbicides have slowly chipped away at soil health for decades. A February report by the Union of Concerned Scientists found that every year, U.S. farmers apply between 30% and 50% more synthetic nitrogen fertilizer than their crops need. These fertilizers cost farmers an estimated $35.8 billion in 2023, according to the USDA.
Heavy fertilizer use has trapped farmers in a vicious cycle. Constantly using more fertilizer than crops require degrades the soil’s natural microbiome, making soil less productive over time, which requires farmers to use more fertilizer to compensate. Reducing fertilizer use would increase crop yields and cut costs for farmers, the study claimed.
And yet, farmers have been hesitant to switch to regenerative farming techniques that, among other adjustments, include putting a stop to over-tilling, which can cause damage to soil structure. Farmers can also plant cover crops, such as grasses or legumes, or rotate the crops grown in each field yearly that can improve the nutrients and organic matter in the soil.
But because these methods often take years to start showing effects—and because American farmers have relied on fertilizers to enable steady crop yields for so long—some are hesitant to sway from the norm, Hansel said.
Rising fertilizer prices may be changing the equation: Demand for Holganix’s Bio 800, which serves as a sort of probiotic for topsoil, has doubled compared to last year, Hansel said, partly because it can help reduce fertilizer needs in a shorter time compared to other regenerative farming methods.
While most farms use at least one regenerative farming method, such as reducing tilling, only about 1.5% of the more than 300 million acres dedicated to row crops in the U.S. are farmed fully regeneratively, according to Regenerative Farmers of America.
Much of the reason why can be explained by the fact that for regenerative farming to work, farmers have to reduce the amount of fertilizer they use, a distressing change for some given the common belief reducing fertilizer brings lower crop yields, Hansel said.
However, if fertilizer costs continue to rise, farmers may have no better alternative.
“Nature is no longer on our side, helping us raise these crops,” Hansel said. “It’s chemistry that something has raised these crops. We need to reverse that.”
Boromeus Wanengkirtyo, Ivan Yotzov and Mishel Ghassibe
Can tomorrow’s costs affect firm prices today? When a temporary tariff schedule on imported inputs was announced in March 2019, many UK firms adjusted prices in anticipation – despite the potential cost change being in the future. In a recent working paper, we use firm‑level survey data to estimate ‘intertemporal pass‑through’ (IPT): how much expected future marginal costs move current prices. Consistent with modern macroeconomic theory, we find big differences across firms: those that change prices less often, and expect the shock sooner, responded the most. A model shows this variation across firms makes aggregate inflation more forward‑looking, so announcements of future policies can move inflation today.
Methodology
To construct exogenous variation in firms’ expected future marginal costs, we use the announcement in March 2019 of a temporary tariff schedule in the event of a ‘No-Deal’ Brexit. This implied that in the event of no free trade deal with the European Union (EU), UK firms that import inputs from the EU would unilaterally face tariffs that are substantially lower than the likely alternative Most Favoured Nation (MFN) rates. As such, this is a precise and narrow ‘news shock’ – not an evaluation of Brexit’s inflation effects. Since the proposed reductions differ across products, the announcement generates sectoral variation in future effective tariffs, depending on the composition of intermediate inputs. We further account for the indirect effects of the announcement along the supply chain, using an input-output table. Crucially, since the tariffs were lower than the MFN tariffs which would otherwise have taken effect (in the case of a no-deal Brexit), the announcement was a downward news cost shock. In Chart 1 we present the distribution of the news shock across sectors of the economy, after applying the input-output table adjustment. There is substantial heterogeneity, with the largest effects in the accommodation and food and manufacturing sectors. The average news shock across sectors is -4.1%.
Chart 1: Sectoral average effective tariff news shocks
We combine this sectoral variation with firm-level data from the Decision Maker Panel (DMP) Survey on (i) the perceived probability of a ‘No-Deal’ outcome and (ii) the intermediate inputs imported from the EU as a share of total costs. We additionally scale the import cost share by the ratio of total to variable costs at the sectoral level, to get as close as possible to a shock to marginal costs. All combined, this gives us a firm-level tariff news cost shock. The average firm-level tariff news shock is -0.7%, with a standard deviation of 1.3%. We then estimate firm-level IPT by regressing survey-based non-zero price changes after the announcement on the constructed news shocks. In the regressions, we control for the probability of no-deal, the import cost share, the sectoral fixed cost share, exporter status, firm investment, firm employment, and we include time fixed effects. Our main sample period is 2019 Q2 to 2019 Q4.
Main findings
A model of price-setting with firm heterogeneity would predict that IPT varies along at least two key margins. First, firms with longer average price durations (ie ‘stickier’ prices) would have stronger IPT. Intuitively, these firms are more forward-looking because they internalise that they may not get another chance to change prices by the time the shock arrives. Second, firms which expect the shock to arrive sooner would also have higher IPT. Again, the intuition is that if the shock is expected to arrive sooner, the probability that the current reset price is fixed until that period is higher, and therefore firms adjust by more today. In the data, we find evidence consistent with these theoretical predictions. The IPT increases monotonically with average price duration and decreases with the horizon of the shock. Price durations (or the average number of months prices remain unchanged) are estimated using CPI/PPI micro data at the sectoral level, whereas the expected Brexit date is measured using direct survey questions in the DMP. Firms with average price durations of 10–20 months that expected Brexit to occur in 2019 have an IPT of 44% (blue coefficients in Chart 2). This increases to 62% for firms with an average price duration of more than 20 months. These effects are statistically significant. Likewise, expecting the shock to occur sooner leads to a higher IPT. The red coefficients in Chart 2 present the corresponding estimates of IPT for firms that expect Brexit to occur in 2020 instead of 2019. Consistent with the logic above, we do not find evidence of positive and significant IPT for these firms, even for those with stickier prices.
Chart 2: Estimated IPT – interaction with price durations and perceived Brexit horizon
Notes: The chart presents the effect of the tariff import cost shock on firm prices, with interactions for average price duration and expected Brexit date. Standard errors are clustered at the SIC2 level and 90% confidence intervals are reported. The regression results are reported in Column 5 of Table 1 in Ghassibe et al (2025).
We also show that IPT varies depending on a firm’s typical price-setting behaviour. Firms in the DMP are asked whether they typically change prices at regular intervals (ie time-dependent) or in response to changes in demand or costs (ie state-dependent). We find that firms that engage in time-dependent pricing have higher IPT than firms which use more state-dependent pricing. This is consistent with state-dependent firms being more flexible in their price-setting, although crucially the results are robust to controlling for the average price duration.
Does intertemporal pass-through depend on the size of the shock? Using a model solved with fully non-linear methods, we show that IPT increases less than proportionately with shock size. The intuition for this result stems from the fact that these are expectedcost shocks. As the shocks grow in size, firms endogenously revise their perceived probability of adjustment in the period when the shock arrives, which in turn lower the IPT. In the limit, as the shock becomes extremely large, firms revise the probably upwards to one, delivering IPT of zero. Importantly, this result contrasts the faster pass-through of large contemporaneous cost shocks which has been documented in the literature (eg Cavallo et al (2024)). In the data, we find similar evidence of a non-linearity in the estimated IPT. Specifically, as the tariff news shock becomes bigger (in absolute value), the impact on price adjustment changes less than proportionately in magnitude. This is shown by the red line in Chart 3, which allows for non-linearity in the estimated IPT. For example, the impact of a -5% tariff news shock on the price level is -3% when allowing for non-linearities, compared with -4.25% under the linear specification (blue line).
Chart 3: Estimated IPT – linear versus non-linear effects
Note: The chart presents the linear and non-linear predicted effect of the tariff import cost shock on firm prices. The results are based on Column 4 from Table 3 in Ghassibe et al (2025). The predicted values are for firms who have a modal expected Brexit year of 2019.
Finally, we use our model to show that the firm-level differences in IPT have important implications for aggregate inflation dynamics. In particular, taking the heterogeneities in perceived shock horizons and adjustment frequencies into account amplifies the response of aggregate inflation to anticipated future shocks, relative to a model with no heterogeneity. This is shown in Chart 4. The solid blue line shows the average IPT with both dimensions of heterogeneity. Turning off heterogeneity in perceived shock horizons (Homogeneous Horizon) implies a slightly lower IPT. However, turning off heterogeneity in price stickiness (Homogeneous Calvo) implies a much lower IPT, closer to the model without any heterogeneity (Homogeneous Calvo and Horizon). Thus, while both dimensions matter for the amplification in the response of inflation to future shocks, we find that heterogeneity in price rigidity is quantitatively more relevant. Importantly, this finding is in contrast to existing results for realised shocks, which suggest that heterogeneity in price rigidity dampens aggregate price movements.
Chart 4: Role of different dimensions of micro heterogeneity for average IPT
Conclusion
Our empirical estimates provide evidence that firm prices respond significantly to expected future cost shocks, in ways predicted by standard models of price-setting. Furthermore, our theoretical results imply that microeconomic heterogeneity in price-setting can amplify the contemporaneous aggregate effects of future policy announcements. For example, announcements about the future path of monetary policy or fiscal policy, to the extent that they affect firms’ expected costs, can have significant impacts on current pricing decisions and therefore inflation dynamics. The non-linearity we find in the pass-through of news shocks can also have potentially far-reaching implications for the optimal size of promises about future policy interventions. If policymakers wish to maximise the contemporaneous price impact of announcing future policies, this suggests they should gradually release information over time (rather than a ‘big bang’ approach), and vice versa.
Boromeus Wanengkirtyo and Ivan Yotzov work in the Bank’s Structural Economics Division and Mishel Ghassibe is an Assistant Professor at the Centre de Recerca en Economia Internacional (CREi).
If you want to get in touch, please email us at bankunderground@bankofengland.co.uk or leave a comment below.
Comments will only appear once approved by a moderator, and are only published where a full name is supplied. Bank Underground is a blog for Bank of England staff to share views that challenge – or support – prevailing policy orthodoxies. The views expressed here are those of the authors, and are not necessarily those of the Bank of England, or its policy committees.
Share the post “Tomorrow’s costs, today’s prices: why expectations matter for inflation”
