The world is growing increasingly uncertain, and this uncertainty is expected to cause more fluctuations in inflation rates. Regular supply disruptions are prompting companies to adjust their prices more often, adding to the variability of inflation.
When larger shocks occur, they can set off feedback loops and nonlinear effects. Such situations can make the economic environment more unpredictable, affecting both businesses and consumers alike.
Shifts in Price Setting Behaviour
What’s clear from the trends we’ve been analysing is that price-setting behaviour among firms is shifting noticeably. Businesses, reacting to repeated supply issues, are no longer waiting for prolonged cost changes before altering what they charge. Instead of adjusting prices on a fixed schedule—say annually—many are now reviewing more often. While this does reflect normal adaptation in a faster-moving global economy, it introduces extra swings in month-to-month inflation data. These swings make it harder for central banks to separate noise from real signals. This matters because policies rely on understanding what’s changing permanently, and what’s just temporary disruption.
Gopinath’s insights build on this, explaining how recurring supply events—with energy or shipping for example—don’t simply push prices up once. They create second-round patterns. When firms expect more instability in input prices, they’re more likely to raise prices just in anticipation. This tends to fuel self-reinforcing cycles. We’ve seen this most clearly in services where wages are a key cost. If workers demand higher pay after a bout of inflation, and companies pass that through to prices, it risks making the situation worse.
Where it gets harder to manage is when the knock-on effects stop being linear. Powell recognised this, noting how sometimes a shock doesn’t just push inflation a little higher—it fundamentally changes how people expect prices to behave. In those cases, old models stop working. The assumption that inflation will gently return to target as activity slows breaks down. Moves in markets become harder to predict because participants no longer believe policy will behave quite as expected.
For those of us following contracts closely tied to rate expectations, these patterns demand careful observation. It would be a mistake to rely on old relationships between headline data and interest rate moves. The reaction function is more conditional now. If firms respond faster to supply-side hiccups, inflation may not behave as smoothly during typical cycles. We aren’t dealing with a classic demand-led situation either. That changes how we track core indicators like unit labour costs or trimmed mean CPI, since they may be telling us more than usual about persistence.
Influence of Price Level Volatility
What’s worth flagging is how price-level volatility itself influences expectations. That is, if there’s an extended run of unstable inflation, even if the average rate isn’t particularly high, it still shapes future pricing and wage-setting. The risk here lies not in runaway inflation—but in erratic swings that complicate both expectations and policy response. Persistently jumpy data can unsettle forwards and increase the margin of error in implied rate estimates.
We should be especially aware of feedbacks sparked by external constraints. Consider a scenario where trade bottlenecks hit intermittently over months. If firms start to internalise that pattern, they might build large buffers, bid up certain commodities, or hedge more aggressively. That could create pricing tails extending into contracts further out than might usually be the case. It also means that what may have started as a one-off delay in a port or rail terminal ends up creating reverberations in inflation-linked assets months later.
As we look ahead, positioning strategies will need to reflect not just macro forecasts but also behavioural shifts in how firms and consumers respond to changing inputs. Watch for hints in short-term volatility gauges and skew in options tied to price indices. If they begin diverging from rate vol, that’s a reliable sign that participants are assigning separate, non-policy-related risks to inflation.
In this environment, it’s imperative to shift attention towards more granular indicators. Aggregated data tends to miss changes in how often firms alter pricing and which categories of goods are moving first. We’ve found it helpful to monitor dispersion metrics hidden within national statistics—particularly those breaking down price changes by decile. A rise in upper-end volatility with stable medians can signal early stages of a potential price spiral.
Our approach now favours scenarios that weigh non-linear ramifications relatively higher than usual. A single shock isn’t always isolated—especially when market participants have seen a pattern of them in the recent past. Structured products that appear resilient under gradual and predictable policy moves may not hold up as well if reactions shift suddenly on the back of a one-off supply jolt. It is this asymmetry of reaction that perhaps deserves more attention than it has received so far.
