A Very Nigerian Argument, Backed by Data
The Jollof Paradox
Your mother, haggling over tomatoes at the market, understands Nigerian inflation better than half the people who will campaign on it in 2027. This is the evidence — with receipts.
Daniel Oluwanifesimi David • Dept of Statistics, FUTA • 62 months of price data, dragged kicking and screaming into a spreadsheet.
The Brief — 30 Seconds
The Question
Politicians keep promising cheaper food by cutting fuel prices. Would that actually work?
The Data
62 months of retail food prices (NBS) for 9 foods, alongside petrol and exchange-rate series (Jan 2021–Feb 2026), modelled across the June 2023 subsidy removal and naira float.
The Finding
It depends on the food. Beef and bread respond to fuel and dollar moves, but with delays of about 2.6 and 6.4 months. For tomatoes, the model finds no measurable response (a ₦10/kg gap). Fixing perishable prices takes cold storage, not fuel policy.
Read time: ~8 min · Skip to: 01 Tale of the Tape · 06 For Recruiters
01 — Tale of the Tape
🥩 Beef Has a Transport Drama
If fuel drops to ₦630 → price drops
₦4,680 → ₦3,750/kg
Lag: 2.6 Months
"A cow doesn't fly business class from Sokoto to Lagos — it travels by road through checkpoints that all need settling. Beef is basically a trucking invoice wearing suya spices."
🍅 Tomatoes Have a Rot Drama
If fuel drops to ₦630 → price drops
₦1,120 → ₦1,110/kg
₦10difference!
Lag: none. The model finds no measurable transmission (a velocity of 0.0 months here means 'no response', not 'instant').
"Tomatoes rot in four days. They are not in a relationship with the Central Bank or the fuel pump. Tomatoes are single, thriving, and answer only to rain."
02 — The Argument
Somebody is already rehearsing the 2027 campaign speech. You know the one: "Vote for me, I will bring back fuel subsidy, pump price go go back to ₦200, and food go cheap like that." Nod along if you want. Just know that the market does not read manifestos, and the numbers say this particular promise is not just optimistic — it is mathematically confused, in a way that would fail a first-year statistics exam.
Because here's the thing your uncle at the family WhatsApp group won't tell you: food is not one thing. Bread, beef, and tomatoes are not cousins who move together. They are three different characters with three different problems, and only one of them cares what happens at the fuel station.
Fig. 1
Normalized Macro-Economic and Food Price Trajectories (Jan 2021 – Feb 2026)
Line chart, Jan 2021 = 100. The food index drifts to about 125 before June 2023, jumps to about 290 with petrol at the subsidy removal, peaks near 445 and ends near 410. The dollar rate rises steadily from 100 to about 320.
Bread Has a Dollar Problem. Beef Has a Fuel Problem. They Are Not the Same Wahala.
Start with bread, because bread is a liar dressed as a local staple. Nothing about a loaf screams "imported," but the wheat inside it came from a ship, priced in dollars. So when the naira weakens at the black market — sorry, "parallel market" — bread gets expensive whether or not a single fuel tanker moves that week. The numbers back this up hard: bread's price is glued to the dollar rate with a pass-through strong enough to bet on (ω₂ = +0.385, statistically serious), while its relationship with petrol is basically nonexistent (ω₁ = +0.025, not significant — bread does not care about your fuel scarcity queue).
Beef is the opposite kind of person. Beef has no dollar drama; beef has a transport drama. A cow doesn't fly business class from Sokoto to Lagos — it travels by road, on diesel, through checkpoints that all somehow need "settling." So when fuel goes up, beef goes up almost immediately (ω₁ = +0.191, very significant). Beef is basically a trucking invoice wearing suya spices.
Fig. 2
Who Moves Whom: Pass-Through Elasticities
Horizontal bars of petrol and dollar elasticities. Bread 0.025 petrol, 0.385 dollar; Veg. oil 0.032, 0.350; Beef 0.191, 0.092; Rice 0.059, 0.215; Eggs 0.105, 0.201; Beans 0.115, 0.140; Garri 0.048, 0.188; Tomatoes 0.042, 0.048; Onions 0.065, 0.075.
A cointegration test — think of it as a long-term relationship compatibility check — confirms bread and beef are genuinely "married" to macro conditions (bread scored 45.22, beef 43.10, both well past the 34.91 cutoff for "yes, this is a real relationship"). Tomatoes and onions, on the other hand, scored 12.50 and 14.20. They failed the test completely. Tomatoes are not in a relationship with the economy. Tomatoes are single, and thriving, and answer only to rainfall.
Fig. 3
Cointegration Trace Test vs 5% Critical Value (34.91)
Trace statistics against cutoff 34.91. Above: Bread 45.22, Beef 43.10, Veg. oil 41.15, Eggs 38.60, Beans 36.45. Below: Garri 21.15, Rice 18.40, Onions 14.20, Tomatoes 12.50.
03 — Boycott Mechanics & Volatility Memory
Why Boycotting the Tomato Seller Works, and Boycotting the Rice Man Is a Waste of Your Airtime
You've seen the WhatsApp broadcasts: "Everybody boycott [insert commodity] for one week, make them reduce price!" It never works for rice. It works surprisingly fast for tomatoes. There's a real reason, and it's not spiritual.
Tomatoes rot in three to four days. A trader sitting on unsold tomatoes isn't "holding out for a better price" — she's watching her capital turn into red water in real time. The moment demand dips even slightly, she panics and cuts price to salvage something. The data calls this a sharp shock reaction (α₁ = 0.361) that fades fast — within about 3 months, the drama is basically over.
Rice, meanwhile, does not rot. Rice sits in a warehouse looking at you, patiently, for over a year. A rice distributor can padlock the store, go for Hajj or a village chieftaincy title, and come back to find the market still there. The model shows rice-price volatility taking about 13.2 months to halve. Bread and vegetable oil are slower still: about 25.3 and 20.0 months, long after the actual crisis has left the group chat. That's not economics. That's slow-moving pricing wearing an inflation costume, and the data now puts a number on it.
Fig. 4
Volatility Shock Decay: How Long Panic Lasts
Decay curves of volatility remaining. Half-lives: Bread 25.3 months, Veg. oil 20.0, Rice 13.2, Tomatoes 3.0.
"Moral of the story: boycott what rots. Leave the rice man alone — he has time, and honestly, so does the bread man."
| COMMODITY | PANIC LEVEL | HOW LONG PRICE VOLATILITY TAKES TO HALVE | LIKELY EXPLANATION (A HYPOTHESIS) |
|---|---|---|---|
| Bread | Mild, slow-burning | 25.3 months | Possibly: bakers hold crisis margins for two years. |
| Vegetable Oil | Mild, slow-burning | 20.0 months | Possibly: industrial processing lag & import stickiness. |
| Beef | Moderate | 15.4 months | Possibly: interstate cattle logistics & haulage cartels. |
| Local Rice | Moderate | 13.2 months | Possibly: warehouse hoarding; grain does not rot. |
| Tomatoes | Sharp, fast-fading | 3.0 months | Possibly: physical rot forces immediate clearing. |
04 — The ₦630/L Counterfactual
So What Happens If Petrol Actually Drops to ₦630/L?
This is where the campaign promise gets tested properly. Simulate it: lock the dollar rate, force petrol down to ₦630/L, and hold it there for two years. ₦630 is a deliberately generous cut. A return to ₦200 would sit far outside anything in this data, so the model can't speak to it. Then watch, month by month, when relief actually reaches your plate.
Fig. 5
24-Month Policy Simulation: Beef (₦/kg)
Beef price history rises from about ₦3,800 to ₦4,500 by Feb 2026. Status quo forecast reaches ₦4,680 after 24 months; fuel at ₦630 falls to ₦3,750, mostly within 8 months.
| COMMODITY | IF FUEL STAYS HIGH | IF FUEL DROPS TO ₦630 | RELIEF ARRIVES AFTER |
|---|---|---|---|
| Beef | ₦4,680/kg | ₦3,750/kg | 2.6 months |
| Local Rice | ₦2,255/kg | ₦1,820/kg | 3.5 months |
| Bread | ₦1,980/loaf | ₦1,510/loaf | 6.4 months |
| Tomatoes | ₦1,120/kg | ₦1,110/kg | Never, basically |
Beef responds in under three months — a fair transport cost meeting a fairer one. Bread makes you wait over half a year, because bakers are still nursing a "crisis margin" from a crisis that ended a while ago. But tomatoes and onions? The gap between expensive fuel and cheap fuel is a whole ₦10 per kilo. That's not a delay. That's the policy lever completely disconnected from the machine — like pressing the remote and realizing the TV isn't even plugged in.
Policy Note
"The gap between expensive fuel and cheap fuel is a whole ₦10 per kilo. That's not a delay. That's pressing the remote and realizing the TV isn't even plugged in."
So the next time someone promises that reversing the fuel price will crash your Sunday jollof budget: ask them specifically which commodity they mean. If it's beef, fine, give them a few months. If it's tomatoes and onions — the actual soul of jollof — they are, respectfully, telling stories that touch.
05 — Action Matrix & Cold Chain
The Actual Fix Isn't at the Fuel Station. It's a Freezer.
Here's the part that should make policymakers slightly uncomfortable: Nigeria loses close to half of its fresh harvest to heat and spoilage before it even reaches Lagos or Port Harcourt (commonly cited estimate; source to be added). During harvest season, tomatoes are practically giving themselves away — a basket can go for ₦20,000. Two months later, with nothing left in storage anywhere, that same basket is ₦130,000 (commonly cited estimate; source to be added). Same tomato. Same country. About six and a half times the price, purely because nobody built anywhere to keep it cold in between.
Harvest
₦20,000
+2 Months
₦130,000 (6.5×)
A solar-powered cold storage hub that holds produce for even a month or two doesn't need to out-argue biology — it just needs to slow it down a little. Stretch the shelf life, and that brutal glut-then-scarcity cycle flattens into something almost boring, which is exactly what you want food prices to be. The government does not have a fuel problem here. It has a "nowhere to put the tomatoes" problem, and it's been solving the wrong problem for a very long time.
Who Should Actually Act On This
If You Run Procurement
- Separate your currency-linked stock (bread, oil) from your fuel-linked stock (beef, transport) — they need completely different hedges.
- Budget for 13–25 months of stubborn "crisis pricing" from non-perishable suppliers before it corrects (estimates, with wide uncertainty).
If You Shape Policy
- Stop trying to fix perishable food prices with fuel or interest rate levers — there's nothing there to move.
- Put the subsidy-sized money into cold-chain and storage instead.
If You Just Buy Food
- Stock up on storable staples during harvest gluts, not when fuel prices make headlines.
- When tomato season ends, lean on other staples for a bit — your wallet doesn't have to fight biology.
If You Run Pricing, FMCG or Logistics
- Classify every SKU by what drives it: dollar-linked, fuel-linked, or perishable. Each needs a different pricing rule.
- Plan for fuel-relief lags of roughly 2.6 months (beef) to 6.4 months (bread), and for processed-goods "crisis pricing" that can linger 13–25 months, before setting repricing triggers.
Limitations & Caveats — Read Before Quoting Any Number
- National averages only: regional supply-chain differences are not captured.
- 62 monthly observations (29 before, 33 after June 2023) is a short sample. GARCH half-lives come from about 61 observations, so treat them as rough estimates. They describe how long price volatility lingers, not how long margins stay elevated.
- Fuel prices and the exchange rate jumped together in June 2023. A step dummy absorbs the jump and the effects are estimated from month-to-month movements (VIF < 2.5), but separating the two remains difficult.
- No controls for general inflation, rainfall or one-off policies (for example, import-duty waivers on some staples in 2024).
- For tomatoes and onions the data show no detectable pass-through (non-significant coefficients, failed cointegration, low model fit). With 62 observations these tests have low power, so this is suggestive evidence of weak macro linkage, not proof of a zero effect.
- The ₦630/L result is a controlled what-if that holds the dollar fixed, although pump prices and the exchange rate normally move together. It is not a forecast.
- Lags and elasticities are point estimates; confidence intervals were not computed.
- Prophet is a forecasting benchmark: an additive time-series model, not a deep-learning system.
Methods & Diagnostics
- All 11 series are I(1): ADF fails to reject at levels and rejects at first differences (Table 4.3).
- Model orders chosen by AIC (Hyndman–Khandakar search).
- Residual check: Ljung–Box p-values 0.188–0.602 for all nine models (Table 4.6).
- Johansen trace test at the 5% critical value of 34.91 (Table 4.4).
- Rolling validation of ARIMAX/SARIMAX against Prophet (Tables 4.8–4.9).