Start with a causal economic or physical mechanism: commodity supply, weather/crop stress, currency, energy, logistics, farm/wholesale transmission or retail confirmation.
Research informs the priors. History will calibrate them.
WillItCostMore uses published economic and climate research to decide which transmission channels deserve more or less structural weight. The papers support direction, relative importance, timing and heterogeneity—not exact WillItCostMore score coefficients.
The numerical weights are transparent priors, not fitted regression coefficients. They will only be recalibrated after enough same-model forecasts and realized outcomes exist for out-of-sample validation.
How the score is calculated
How the score is calculated
The model is additive and auditable. Every live contribution can be traced back to one normalized observation and one structural prior.
Score= clip[5,95]
( Base + Σ [ wcountry × signal × quality × freshness ] )Product baselineBase
Country-adjusted prior weightwcountry
Normalized signal (roughly −1 to +1)signal
Source qualityquality
Freshness multiplierfreshness
Freshness multipliers: 1.00 at ≤3 days, 0.80 at 4–10 days, 0.55 at 11–35 days, 0.30 after 35 days.
Confidence = quality- and freshness-weighted coverage ÷ total applicable prior weight, bounded to 16–96%. Missing or unusable inputs add zero score points and reduce confidence.
Evidence hierarchy ≠ exact coefficient
Research supports channel direction, hierarchy, timing and heterogeneity. The exact score-point priors are product-design assumptions frozen by model version until forecast outcomes are sufficient for out-of-sample calibration.
Model priors
How a prior weight is built
Map that mechanism to products. Cocoa can strongly affect chocolate but should not move electricity; Rhine logistics matters only where a product and market use that transport chain.
Use published evidence to determine relative salience and timing. Faster/direct channels get more potential influence than slow or mostly confirmatory channels, while correlated downstream signals are capped to reduce double counting.
Apply a country adjustment only where source coverage or a defensible structural exposure differs: local weather, import currency, domestic production, official market data or physical logistics.
The prior is not the contribution. At runtime it is multiplied by the normalized observation, source-quality score and freshness penalty. Weak or missing observations therefore lose influence automatically.
Freeze each model version and retain its forecasts. Re-estimate or shrink priors only after enough realized outcomes exist to test direction, lead time, false positives and calibration out of sample.
Country adjustments
These bounded multipliers encode structural applicability/exposure. They are transparent heuristics pending empirical calibration—not fitted scientific coefficients.
U.S.-specific outlooks only apply to the U.S.; EU farm/wholesale/retail layers only apply where their official series cover the market; Swiss and UK domestic layers remain market-specific.
For exposed products, local heat/dryness prior weights are multiplied by 1.12 in France, Italy and Spain. This is a bounded structural heuristic informed by evidence of stronger warm-country/seasonal responses—not a fitted coefficient.
The currency-import prior is multiplied by 1.15 in the UK as a transparent structural import/currency exposure assumption pending calibration.
Selected global wheat/feed/vegetable-oil priors are multiplied by 0.80 in the U.S. to encode greater domestic supply scale. Coffee and cocoa are not cushioned by this rule.
Rhine pressure is applied only to markets with configured physical exposure. Switzerland retains full modeled exposure, and heating oil, diesel and petrol carry larger Rhine priors than most foods.
What the literature changes
Strong evidence3 References
Global commodities
International commodity shocks matter, but food pass-through is incomplete and slower than fuel. That supports large product-specific commodity priors without treating world prices as the final shelf price.
Strong evidence3 References
Weather & crop stress
Heat, drought and crop conditions are allowed to matter most for fresh crops and other physically exposed products. The evidence also supports seasonal and country-specific differences rather than one global weather coefficient.
Strong evidence2 References
Exchange rate
Exchange-rate pass-through is real but weakens along the pricing chain and varies by sector. Currency therefore receives meaningful but usually smaller weight than the underlying imported commodity.
Strong evidence3 References
Energy inputs
Energy shocks transmit directly to fuels and utilities and indirectly through production, processing and transport. Energy therefore carries high weight for energy products and smaller input-cost weight for food.
Moderate evidence4 References
Logistics
Freight disruptions can raise inflation, but final-consumer pass-through is typically smaller than direct commodity shocks. Logistics weights stay modest unless a product/market has a concrete exposure such as Rhine fuel transport.
Strong evidence4 References
Farm & wholesale transmission
Farm-gate, input-cost and wholesale series help show whether an upstream shock is moving down the price chain. Their weights are deliberately smaller than the upstream shock to reduce double counting.
Supporting evidence2 References
Retail confirmation
Consumer-price momentum and official outlooks are useful corroboration, but they are partly backward-looking. They receive low weight so the model remains an early-warning system rather than a repackaged CPI nowcast.
Selected literature
Selected literature
Paper titles are shown in their original publication language. Links go to the publisher or institution. Technical summaries are written by WillItCostMore from the cited publications; paper titles and bibliographic metadata remain in the publication language.
International Monetary Fund · 2026References ↗
Pumps and Plates: Passthrough of International Fuel and Food Price Shocks to Domestic Markets
IMF Working Paper 2026/148 · DOI 10.5089/9798229054058.001
Technical source note
- Method
- Dynamic local projections across domestic/international price pairs since 2000
- Key result
- Pass-through is incomplete and heterogeneous; fuel transmits faster than food, and price increases tend to transmit more readily than decreases.
- Implication for WillItCostMore
- Supports stronger/faster energy priors, slower food horizons, country heterogeneity and asymmetric caution. It does not supply exact WillItCostMore weights.
International Monetary Fund · 2015References ↗
Global Food Prices and Domestic Inflation: Some Cross-Country Evidence
IMF Working Paper 2015/133 · DOI 10.5089/9781513542973.001
Technical source note
- Method
- Cross-country empirical analysis of global food-price shocks and domestic inflation
- Key result
- World food-price shocks matter for domestic food inflation, but pass-through is incomplete and differs across economies and over time.
- Implication for WillItCostMore
- Supports material but bounded global food-commodity weights and country-specific transmission rather than one universal coefficient.
European Central Bank · 2010References ↗
Food price pass-through in the euro area: The role of asymmetries and non-linearities
ECB Working Paper Series No. 1168 · Working Paper 1168
Technical source note
- Method
- Euro-area food-chain time-series models with aggregate/disaggregate data and nonlinear specifications
- Key result
- With appropriate food-chain data, commodity-price pass-through is significant and long-lasting; asymmetries and non-linearities matter.
- Implication for WillItCostMore
- Supports separating upstream commodities from farm/wholesale transmission and keeping downstream confirmation smaller to reduce double counting.
European Central Bank · 2023References ↗
The asymmetric effects of weather shocks on euro area inflation
ECB Working Paper Series No. 2798 · Working Paper 2798
Technical source note
- Method
- Bayesian VAR analysis of weather shocks and inflation across euro-area countries
- Key result
- Temperature effects are seasonal and asymmetric, with stronger food-price responses in warmer countries and for unprocessed food.
- Implication for WillItCostMore
- Supports product-specific weather exposure and the modest Southern-European heat/dryness uplift rather than one global weather coefficient.
International Monetary Fund · 2022References ↗
How Persistent are Climate-Related Price Shocks? Implications for Monetary Policy
IMF Working Paper 2022/207 · IMF Working Paper
Technical source note
- Method
- Cross-country empirical analysis of climate-related shocks and inflation persistence
- Key result
- Climate-related price shocks can have persistent and heterogeneous inflation effects depending on shock type and country conditions.
- Implication for WillItCostMore
- Supports a distinct physical-weather/crop channel and longer horizons for slower agricultural transmission.
European Central Bank · 2020References ↗
The transmission of exchange rate changes to euro area inflation
ECB Economic Bulletin, Issue 3/2020 · Economic Bulletin article
Technical source note
- Method
- ESCB research synthesis and empirical estimates across the pricing chain
- Key result
- Exchange-rate pass-through declines along the pricing chain and varies with import content, invoicing, market power and shock type.
- Implication for WillItCostMore
- Supports a meaningful but usually secondary currency weight and country/product heterogeneity rather than mechanically converting FX into shelf prices.
European Central Bank · 2021References ↗
Sectoral exchange rate pass-through in the euro area
ECB Working Paper Series No. 2634 · Working Paper 2634
Technical source note
- Method
- Sectoral VAR-X models of euro-area import-price pass-through
- Key result
- Pass-through varies materially by sector; market concentration and global-value-chain structure help explain the differences.
- Implication for WillItCostMore
- Supports sector/product-specific import sensitivity and a larger UK currency prior without assuming equal FX sensitivity everywhere.
International Monetary Fund · 2022References ↗
Shipping Costs and Inflation
IMF Working Paper 2022/061 · DOI 10.5089/9798400204685.001
Technical source note
- Method
- 46-country panel, 1992–2021; robustness includes an instrumental-variable strategy
- Key result
- Shipping-cost shocks raise import prices, producer prices and inflation, with effects depending on import intensity and macroeconomic structure.
- Implication for WillItCostMore
- Supports a distinct logistics channel, but with moderate exposure-specific weights rather than a universal retail-price driver.
European Commission Joint Research Centre · 2020References ↗
Forecasting the impacts of climate change on inland waterways
Transportation Research Part D: Transport and Environment · DOI 10.1016/j.trd.2019.10.012 · JRC116086
Technical source note
- Method
- Climate-model river-discharge scenarios with location-specific Rhine and Danube navigation analysis
- Key result
- Low water can disrupt inland navigation by forcing reduced vessel loads or making stretches non-navigable.
- Implication for WillItCostMore
- Supports retaining a targeted Rhine logistics signal for markets/products with physical river-freight exposure; it does not justify a universal inflation weight.
Deutsche Bundesbank · 2023References ↗
Climate change, biodiversity loss and the role of central banks
Bundesbank Spring Conference speech summarising ongoing research · 11 May 2023
Technical source note
- Method
- Institutional summary of Bundesbank research using roughly 30 years of Rhine/water-stress data
- Key result
- Low Rhine levels can disrupt supply chains; the Bundesbank reported preliminary evidence that German producer prices tend to rise in low-water months.
- Implication for WillItCostMore
- Supports Rhine as a real logistics-risk indicator while keeping the signal bounded and exposure-specific.
European Central Bank · 2026References ↗
Analytical perspectives on energy supply shocks
ECB speech · 13 May 2026
Technical source note
- Method
- Analytical synthesis of direct, indirect and second-round transmission of energy shocks
- Key result
- Transport-fuel effects can be immediate while electricity/heating and indirect input-cost effects can arrive with lags through production and distribution.
- Implication for WillItCostMore
- Supports high direct weights for energy products, smaller energy-input weights for food, and different horizons across energy categories.
European Central Bank · 2026References ↗
Supply chain uncertainty, energy prices, and inflation
ECB Working Paper Series No. 3230 · Working Paper 3230
Technical source note
- Method
- U.S. and euro-area empirical evidence plus a model of capacity-constrained transport networks
- Key result
- Energy-price pass-through is state-dependent and stronger when supply-chain uncertainty is elevated.
- Implication for WillItCostMore
- Supports keeping energy and logistics separate while recognising interaction and state dependence; exact interaction terms remain a future calibration topic.
Next scientific step: calibration
As forecast history accumulates, evaluate directional accuracy, lead time, false positives, stability and calibration by country, product and horizon. Only then should weights be re-estimated or shrunk.
Read full methodology →