India Rimmer, Hannah Copeland and Boromeus Wanengkirtyo
Global extreme weather events may feel far away, but they leave behind a trail of higher prices in our shopping baskets. As outlined in past Monetary Policy Reports, droughts, flooding and heatwaves occurring overseas often impact UK food inflation, which averaged 4.2% in 2025. But how much of the rise in food inflation last year can we blame on the weather? By constructing a new proxy for global weather shocks, we find that they increase UK food prices with a peak impact after one year. In the latest period, our model suggests that weather shocks contributed 0.8 percentage points to food inflation at peak in May 2025. Weather continues to matter for inflation amidst the current El Niño phenomenon.
Food prices have been blown off course
As set out in the August 2025 Monetary Policy Report, last year UK food and non-alcoholic beverage (hereafter ‘food’) inflation rose above its pre-Covid average of around 1.5%, peaking at 5.1% in August. This was partly due to higher labour costs and new packaging regulations, which increased costs for UK food producers.
But global weather shocks also contributed by reducing crop yields and raising food production costs (August 2025 Monetary Policy Report). Droughts in Brazil increased coffee prices while heavy rainfall and plant disease in West Africa raised the price of cocoa. Closer to home, beef and dairy prices rose after dry weather in the UK and elsewhere increased livestock feed costs. This is not a new problem, nor one that will go away. Climate change is increasing the frequency of extreme weather events across the globe, with consequences for the economy and monetary policy (Talbot (2026) and NGFS (2026)).
In particular, higher food commodity prices and with some delay UK consumer food prices seem to follow El Niño-Southern Oscillation (ENSO) phases, as suggested by Chart 1. ENSO is a weather phenomenon that affects temperature and precipitation across the world and can therefore have a large impact on global weather conditions. It has two opposite phases, El Niño (warmer-than-average) and La Niña (cooler-than-average).
Chart 1: Food commodity prices and UK food inflation
Notes: International Monetary Fund (IMF) food and beverage commodity price inflation and UK food and non-alcoholic beverage inflation alongside moderate-to-strong ENSO phases. Data to March 2026.
Sources: IMF Primary Commodity Prices, National Oceanic and Atmospheric Administration (NOAA) and Office for National Statistics (ONS).
A model to chart the storm
We calculate a new high-frequency proxy to estimate the economic impact of global weather shocks. This is a time series of unanticipated weather events, accounting for seasonality and the importance of each country for global agricultural exports. Proxies provide information about shocks that are otherwise difficult to measure.
To build our proxy we use European Commission warnings about crop conditions as outlined in Rembold (2018). This data set provides ten-daily warnings of climate anomalies for crop areas using data on rainfall and vegetation anomalies. To create a monthly series incorporating both positive and negative weather shocks, we calculate the deviation in the number of anomalies from the sample mean for each month and country. We calculate the mean over the entire sample period. As a result, we don’t capture climate trends, though this may be reasonable as our sample period is relatively short. Finally, we weight countries together by their share of global agricultural exports.
Chart 2 shows the resulting global weather shock series alongside moderate-to-strong ENSO phases. In constructing the series we find that localised weather shocks in countries with high weights, for example the US, Brazil, the Netherlands and China, have a large impact. However, as one can see in the chart, there is not such a clear-cut relationship with ENSO phases.
Chart 2: Global weather shock series
Notes: High-frequency global weather shock series alongside moderate-to-strong ENSO phases. Data to February 2026.
Sources: FAOSTAT, NOAA, Rembold (2018) and authors’ calculations.
To quantify the impact of global extreme weather events on UK food inflation, we estimate a proxy vector autoregression model using Bayesian methods (BVAR), partially identified by our new weather shocks series. The model builds on the methodology described in Arias et al (2021) and Copeland et al (2025), using a combination of proxies with zero and sign restrictions to identify the structural shocks.
We also use two other proxies, oil supply shocks from Känzig (2021) and gas supply shocks from Alessandri and Gazzani (2025). These help the model to differentiate between weather and energy supply shocks, which have often occurred independently but simultaneously, for example in 2022–23 when global adverse weather conditions coincided with a significant European energy shock.
In the spirit of De Winne and Peersman (2021), the target variable for the weather shock series, used to identify the structural shocks and determine instrument relevance, is a trade-weighted average of the IMF’s commodity price indices for four staple food commodities: wheat, rice, corn and soybeans. These groups make up a significant share of global food production as measured by caloric content and they are strongly affected by weather conditions (De Winne and Peersman (2021)). We also use real oil and gas prices, the sterling effective exchange rate index, a Covid-adjusted measure of UK real GDP, and UK food, energy and headline CPI inflation. The model is estimated on monthly data in log-levels, over a sample period of January 2006 to February 2026.
Results suggest we can blame (some of) it on the weather
Chart 3 shows the modelled impulse responses of UK food and headline CPI inflation to a weather-driven 1% rise in global food commodity prices. Food inflation rises by around 0.15 percentage points at peak after 12 months, while headline inflation increases by 0.09 percentage points, reflecting higher food, energy and core inflation. The rise in food inflation comes through with a lag, but is quite persistent, lasting for around 2½ years.
Chart 3: Impulse response functions of UK food and headline CPI inflation to global weather shocks scaled to increase grain commodity prices by 1% on impact
Notes: Impulse responses to the identified global weather shocks, normalised to increase grain commodity prices by 1% on impact. Estimation sample: January 2006 to February 2026. The solid line represents the median draw. The shaded areas are the 80% credible intervals.
Source: Authors’ calculations.
While our estimates are subject to uncertainty and represent only one approach to quantifying the impact of global weather shocks on consumer prices, the results are broadly consistent with expectations. Global weather shocks impact UK inflation moderately and with a lag, unsurprising given the length of harvest cycles. They also appear to have broad-based inflation impacts (NGFS (2026)) and seem to transmit to food and headline inflation indirectly, including via increased energy demand and prices. Higher energy prices may reflect weather shocks increasing demand for oil and gas via disruptions to biofuel production, for example. Similar studies also find moderate rises in energy prices in response to harvest shocks (Peersman (2022)). The impact to UK energy inflation in our model is non-trivial, 0.4 percentage points at peak.
Chart 4 presents the estimated historical contribution of global weather shocks to UK food inflation alongside moderate-to-strong ENSO phases. In the latest period, the model suggests that global weather shocks made a peak contribution of 0.8 percentage points in May 2025, when food inflation was 4.4%. This faded by September and more recently has been pushing down on food inflation in the UK. Although our proxy does not perfectly capture ENSO events, periods of moderate-to-strong ENSO generally coincide with higher UK food inflation, with varying lags and magnitudes. For example, the model estimates that weather shocks contributed 1.7 percentage points to UK food inflation at their peak in 2017, following the strong 2015–16 El Niño.
Chart 4: Historical decomposition of past contribution of global weather shocks to UK food inflation
Notes: Historical contribution of global weather shocks to UK food and non-alcoholic beverage inflation, alongside moderate-to-strong ENSO phases. Data to February 2026.
Sources: Bank of England Monetary Policy Reports, NOAA, ONS and authors’ calculations.
Conclusion
By constructing a new high-frequency series of weather shocks, we have estimated that extreme global weather events have played a non-trivial role in UK food and headline inflation over the past two decades. Our results suggest that global weather disruption can have a significant, lagged, and persistent impact on UK consumer food prices.
As our proxy is constructed using data available in near real-time and weather shocks feed through to UK consumer prices with a lag, with further refinement this model has the potential to estimate the impact of current global weather shocks over the monetary policy-relevant horizon.
India Rimmer works in the Bank’s International Surveillance Division, and Hannah Copeland and Boromeus Wanengkirtyo work in the Bank’s Structural Economics Division.
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