War involving a government
Nigeria: Government
Nine criteria, each scored from 0 to 10 using a published guide, each with the source it was scored from. The scores are turned into a share for each industry, and five scenarios filter those shares in five different ways.
This page shows how a war is linked to industries, and it shows no death toll per industry. The shares below are settings of the model, each with sources behind it; multiplying a share by a number of deaths gives a result, and no result is published until it comes from a recorded calculation with a range and a confidence grade. Read the scores, follow the links, and question the method while there is still nothing to quote out of context.
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The products it reaches
Each product the model links deaths from Nigeria: Government to, with its deaths per item and the part of that figure this war accounts for.
Scenario Economic-embedded, using FIGARO 2023.
| Product | Deaths per item |
|---|---|
| Cocoa butter Part from here: 3.7% | 4.1 × 10⁻⁸ per item(0.16–1.1 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cocoa mass Part from here: 3.7% | 4.1 × 10⁻⁸ per item(0.16–1.0 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Chocolate bar Part from here: 3.3% | 2.5 × 10⁻⁹ per item(1.2–5.8 × 10⁻⁹)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Bag of charcoal Part from here: 0.34% | 1.5 × 10⁻⁷ per item(0.61–3.5 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Pack of cigarettes Part from here: 0.15% | 3.6 × 10⁻¹⁰ per item(1.4–8.8 × 10⁻¹⁰)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cotton fabric Part from here: 0.13% | 3.9 × 10⁻⁸ per item(1.5–9.5 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cotton T-shirt Part from here: 0.13% | 6.4 × 10⁻⁹ per item(0.25–1.6 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Cotton yarn Part from here: 0.13% | 3.8 × 10⁻⁸ per item(1.5–9.3 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Denim fabric Part from here: 0.13% | 3.8 × 10⁻⁸ per item(1.5–9.8 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Jeans Part from here: 0.13% | 3.2 × 10⁻⁸ per item(1.2–8.0 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Butter Part from here: <0.1% | 3.2 × 10⁻⁷ per item(1.3–7.2 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Croissant Part from here: <0.1% | 0.42–2.4 × 10⁻⁸ per itemINDICATIVES-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Refined sugar Part from here: <0.1% | 6.1 × 10⁻⁹ per item(0.24–1.5 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Coffee, one cup Part from here: <0.1% | 4.7 × 10⁻¹⁰ per item(0.19–1.2 × 10⁻⁹)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Roasted coffee Part from here: <0.1% | 6.7 × 10⁻⁸ per item(0.27–1.7 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Printed circuit board assembly Part from here: <0.1% | 1.6 × 10⁻⁶ per item(0.60–3.4 × 10⁻⁶)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Smartphone Part from here: <0.1% | 3.0 × 10⁻⁸ per item(1.2–6.3 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Laptop Part from here: <0.1% | 5.4 × 10⁻⁷ per item(0.21–1.2 × 10⁻⁶)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Steel Part from here: <0.1% | 3.1 × 10⁻⁹ per item(1.7–6.7 × 10⁻⁹)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Passenger car tyre Part from here: <0.1% | 5.2 × 10⁻¹⁰ per item(0.27–1.1 × 10⁻⁹)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Wheat flour Part from here: <0.1% | 1.1 × 10⁻⁸ per item(0.44–2.6 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Petrol car Part from here: <0.1% | 9.5 × 10⁻⁶ per item(0.55–1.7 × 10⁻⁵)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Electric car Part from here: <0.1% | 3.0 × 10⁻⁵ per item(1.8–5.5 × 10⁻⁵)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
| Lithium-ion battery pack Part from here: <0.1% | 6.9 × 10⁻⁸ per item(0.36–1.4 × 10⁻⁷)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r |
The figure is the product’s own, with its range. The share beside it is a middle estimate only: the calculation stores a range for each figure, not for each part of one.
What is on this page, and what is not
A share is not a toll. Everything below is either a count published by the Uppsala Conflict Data Program — shown here with the credit its licence asks for — or a setting of the model: a 0-to-10 score against a guide anyone can read, the source it came from, and the share those scores add up to.
Nothing on this page multiplies one by the other. That multiplication is the result the project exists to produce, and it is not published until a calculation produces it with a range and a confidence grade. A project can only publish a wrong figure for how many people died for a barrel of oil once.
What the Uppsala Conflict Data Program recorded
The publisher’s own figures for this war, from the version of the data listed on the sources page. Nothing here has been linked to anything yet.
14,618
Deaths recorded
1,305
Events
2009–2025
Years
4
Countries
85.3%
Precisely located
The last figure is the share of recorded deaths whose location is known more precisely than a province. It matters because it limits one of the nine criteria: a war whose events are known only to the level of a country cannot show it was fought close to a mine or a field, so if fewer than half its deaths are precisely located, that score cannot go above the middle of the scale.
Scenario
One set of scores, five filters. A scenario never stretches a share and never deletes one — what it declines to pass on moves to Other and stays in the total. Switching below changes what you are looking at, not what was scored.
Routes the entire attributable toll through the economic system, including the share no specific sector can be evidenced for: that share follows the production basket of the country where each death was counted, an assumption graded low. Quantifies the economic activity associated with conflict rather than the motivation of anyone fighting it.
2009–2025 The north-eastern insurgency
THE DISCIPLINE CASE, and it is in this dataset to be scored LOW on oil. Nigeria is the clearest petro-state in the ledger, and this conflict is a jihadist insurgency in the north-east, roughly a thousand kilometres from the oil. A model that cannot separate "the country runs on oil" from "the war is about oil" will attribute every Nigerian death to a barrel of crude, and the nine criteria exist to stop it.
Share by industry
| Industry | Share | Confidence |
|---|---|---|
| Other and unattributed economic activity OTHER |
23.9% | MEDIUM |
| Extraction of crude petroleum and natural gas 06 |
22.7% | MEDIUM |
| Crop and animal production, hunting and related service activities 01 |
21.5% | MEDIUM |
| Transportation and storage H |
14.7% | MEDIUM |
| Water collection, treatment and supply 36 |
10.4% | MEDIUM |
| Wholesale and retail trade; repair of motor vehicles and motorcycles G |
6.7% | MEDIUM |
Shares add up to exactly 100%, Other included. That is checked every time the model is built, and a build that loses even a fraction of a percent between two steps stops with an error rather than rounding it away.
23.9% of this war goes to Other — economic activity that none of the named industries above accounts for.
Reviewed: truly outside the named industries. The sink holds a religious and political insurgency in a region with no extractive economy. THE OIL SHARE THIS CONFLICT STILL CARRIES COMES ENTIRELY FROM THE THREE STRUCTURAL CRITERIA — export share, revenue share, traded output — and from none of the four conflict-specific ones, three of which are explicit zeros: no territory, no location, no control. That residue is the equal-weight default speaking rather than the evidence, and plan/14 S9's record says so.
The scores, and what each one is based on
Each cell links to the source it was scored from; hover over it for the reference and the reasoning. The letter beside a score says how strong that kind of evidence is: H for official statistics or a UN expert panel, M for research checked by other experts or a report by a major institution, L for news reports. Deaths recorded in this period: 14,618.
| Industry | Territorial dependence | Export dependence | Government-revenue dependence | Conflict-location proximity | Actor statements | Resource control | Trade dependency | Arms relationship | Historical evidence | Weighted score |
|---|---|---|---|---|---|---|---|---|---|---|
| Other and unattributed economic activity OTHER |
5 M | 2 H | 4 H | 5 M | 9 M | 6 M | – | – | 8 M | 39 |
| Extraction of crude petroleum and natural gas 06 |
1 H | 10 H | 8 H | 0 M | 2 M | 0 H | 8 H | 5 M | 3 M | 37 |
| Crop and animal production, hunting and related service activities 01 |
7 H | 2 H | – | 8 M | 5 M | 6 H | – | – | 7 M | 35 |
| Transportation and storage H |
5 M | – | – | 6 M | – | 7 M | – | – | 6 M | 24 |
| Water collection, treatment and supply 36 |
6 H | – | – | 5 M | – | – | – | – | 6 M | 17 |
| Wholesale and retail trade; repair of motor vehicles and motorcycles G |
– | – | – | – | – | 6 M | – | – | 5 M | 11 |
An empty cell is a criterion nobody has scored yet, not a zero. Nothing was assumed about it, and the weight it would have carried stays in Other rather than being spread over the criteria that were scored. A 0 written in says something different: somebody looked and found no link.
Evidence
- Uppsala Conflict Data Program, Conflict Encyclopedia, conflict 297 (Nigeria: Government): background, actors and incompatibility. report by a major institution · MEDIUM · 19 scores
- World Bank World Integrated Trade Solution, NGA country profile: merchandise exports by product group. official statistic · HIGH · 4 scores
- Extractive Industries Transparency Initiative, Nigeria country page: reconciled government revenue from the extractive sector. official statistic · HIGH · 2 scores
- FAO, FAOSTAT, land use: cropland, arable land and permanent pasture by country and year. official statistic · HIGH · 2 scores
- U.S. Energy Information Administration, country analysis brief for NGA: reserves, production and export infrastructure. official statistic · HIGH · 2 scores
- FAO, FAOSTAT, crops and livestock production by country and year. official statistic · HIGH · 1 scores
- SIPRI Military Expenditure Database: military spending by country, compiled from official budget documents. report by a major institution · MEDIUM · 1 scores
The nine criteria, and how each is scored
Without worked examples, two people would score the same war differently, and the model would measure the person rather than the war. So every criterion spells out what a 0, a 5 and a 10 look like, and four of the nine are tied to published statistics rather than to a form of words.
Territorial dependence — Does control of the contested territory amount to control of this sector?
- 0
- No known deposit, field, plantation, facility or right-of-way of this sector lies inside the contested area.
- 5
- The sector is present in the contested area but not concentrated there: the area holds roughly the share of national capacity its size would suggest.
- 10
- The contested area contains the great majority — three quarters or more — of the country's known capacity for this sector, so holding the ground IS holding the sector.
Check it against: National geological or agricultural surveys; USGS Minerals Yearbook country chapters; the operator's own concession maps.
Export dependence — How much of what the country sells abroad is this sector?
- 0
- Under 2% of merchandise exports over the period, or not exported at all.
- 5
- Between 20% and 35% of merchandise exports — a major earner among several.
- 10
- 70% or more of merchandise exports: the country sells this and comparatively little else.
Check it against: World Bank WITS country profile, merchandise exports by product group, averaged over the period; UN Comtrade mirrored data where WITS is thin.
Government-revenue dependence — How much of what the state spends comes from this sector?
- 0
- Under 2% of general government revenue, or no fiscal link at all.
- 5
- Between 20% and 35% of general government revenue.
- 10
- 60% or more of general government revenue: the state is substantially this sector's fiscal agent.
Check it against: IMF Article IV staff reports, fiscal tables; EITI country reports; World Bank natural resource rents as a share of GDP (NY.GDP.TOTL.RT.ZS and its components).
Conflict-location proximity — Did the recorded violence actually happen where this sector operates?
- 0
- No spatial relationship between the recorded events and the sector's sites — or the events are too coarsely located to support any claim about where they were.
- 5
- A substantial minority of recorded deaths fall in administrative areas containing the sector's principal sites.
- 10
- The majority of recorded deaths fall in administrative areas containing the sector's principal sites.
Check it against: UCDP GED event coordinates and adm_1, filtered on where_prec; the sector's site locations from a survey or operator map.
Actor statements — Do the armed parties themselves name this sector as an aim or a means?
- 0
- No party names it, in any founding document, communiqué, demand or negotiation position.
- 5
- A party names it among several aims, or the claim reaches us through a third party rather than from the actor.
- 10
- A party's own founding document, communiqué or negotiating demand names control of this sector, or of its revenue, as a principal aim.
Check it against: UCDP Conflict Encyclopedia actor pages; peace-agreement texts in the UN Peacemaker database; the actor's own published statements.
Resource control — Did armed parties hold, tax or sell this sector's output?
- 0
- No evidence that any party controlled, taxed or traded the sector's output.
- 5
- A party taxed, extorted or licensed production it did not itself control.
- 10
- A party held production sites and sold the output, and an official investigation documents it.
Check it against: UN Security Council panels and groups of experts; sanctions-committee reports; Kimberley Process and OECD due-diligence findings.
Trade dependency — Does an identifiable market outside the country take this output?
- 0
- Output is consumed domestically, or is not traded in any traceable form.
- 5
- Exported, but into diversified markets with no dominant buyer and no traceability regime.
- 10
- Exported and traceable to a specific downstream industry or buyer country — typically because a due-diligence regime exists for it (3TG conflict minerals, the Kimberley Process, EUDR).
Check it against: World Bank WITS bilateral flows; OECD due-diligence guidance and its covered commodities; the EU conflict-minerals and deforestation regulations.
Arms relationship — Did this sector pay for weapons, or is it weapons?
- 0
- No documented link between the sector and the procurement of arms.
- 5
- The sector contributes to general state revenue, which funds a defence budget — an indirect, non-earmarked link.
- 10
- Output was directly exchanged for weapons, or the sector IS arms manufacture or military procurement.
Check it against: SIPRI Arms Transfers Database and Military Expenditure Database; UN Register of Conventional Arms; sanctions-committee findings on barter arrangements.
Historical evidence — Does the scholarly and official record already make this link?
- 0
- No peer-reviewed study or official inquiry makes the link.
- 5
- Contested: some peer-reviewed work makes the link and other work of comparable standing rejects it.
- 10
- The link is the mainstream reading in the peer-reviewed literature and in official inquiries, and its critics argue about magnitude rather than existence.
Check it against: Peer-reviewed political economy of the specific conflict; truth commissions and official inquiries; the UCDP Conflict Encyclopedia's own background text.