The full breakdown
How the figure for Cotton fabric is built
Every stage the model passes through, with its number. Each table below divides the same headline figure a different way, and each one adds up to it exactly — the page checks, and refuses to show a table that does not.
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The headline
One item is one kilogram of cotton fabric. Scenario Economic-embedded, using FIGARO 2023. Each figure is the middle result of 2,000 runs of the calculation, with the range that holds nine in ten of them beside it, and the grade that range earns.
Materials method — 3.9 × 10⁻⁸ per item(1.5–9.5 × 10⁻⁸)LOWS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r
Money method — 1.4 × 10⁻⁶ per €1,000 spent in its industry(0.93–2.2 × 10⁻⁶)MEDIUMS-MAX · run 2259 · methodology v1.0 · data dv-20261007-44r
Each step below is a middle estimate. The model works out a range for the whole figure, not for each step, so the range that applies to a step is the headline’s.
1 · What it is made of, and what each material carries
How much of each raw material is in one item, the deaths linked to each kilogram of it in this calculation, and the two multiplied together: its part of the headline figure.
| Material | Per item | Deaths per kg | Part of the figure | Share |
|---|---|---|---|---|
| Cotton | 0.0031 t | 1.2 × 10⁻⁸ | 3.9 × 10⁻⁸ | 100% |
| Total | 3.9 × 10⁻⁸ | = the headline figure, 3.9 × 10⁻⁸ | ||
2 · Where the harm was counted
The same headline, by the country where the harm the materials carry was counted.
| Country | Part of the figure | Share |
|---|---|---|
| Burkina Faso | 1.6 × 10⁻⁸ | 42% |
| Mali | 3.6 × 10⁻⁹ | 9.4% |
| Sudan | 2.6 × 10⁻⁹ | 6.7% |
| Mexico | 1.9 × 10⁻⁹ | 5.0% |
| Israel | 1.9 × 10⁻⁹ | 4.8% |
| Turkiye | 1.8 × 10⁻⁹ | 4.7% |
| Pakistan | 1.6 × 10⁻⁹ | 4.2% |
| Brazil | 1.4 × 10⁻⁹ | 3.6% |
| Cameroon | 1.2 × 10⁻⁹ | 3.1% |
| Myanmar | 9.0 × 10⁻¹⁰ | 2.3% |
| United States | 8.9 × 10⁻¹⁰ | 2.3% |
| Syrian Arab Republic | 7.5 × 10⁻¹⁰ | 1.9% |
| Ethiopia | 7.4 × 10⁻¹⁰ | 1.9% |
| Nigeria | 3.6 × 10⁻¹⁰ | 0.94% |
| Somalia, Fed. Rep. | 3.3 × 10⁻¹⁰ | 0.87% |
| Benin | 3.3 × 10⁻¹⁰ | 0.86% |
| Central African Republic | 3.2 × 10⁻¹⁰ | 0.84% |
| India | 3.1 × 10⁻¹⁰ | 0.80% |
| Afghanistan | 2.9 × 10⁻¹⁰ | 0.76% |
| Uzbekistan | 2.6 × 10⁻¹⁰ | 0.68% |
| Greece | 1.8 × 10⁻¹⁰ | 0.47% |
| Congo, Dem. Rep. | 1.2 × 10⁻¹⁰ | 0.30% |
| Azerbaijan | 1.1 × 10⁻¹⁰ | 0.29% |
| Australia | 1.1 × 10⁻¹⁰ | 0.28% |
| Togo | 9.0 × 10⁻¹¹ | 0.23% |
| Argentina | 8.1 × 10⁻¹¹ | 0.21% |
| Chad | 5.6 × 10⁻¹¹ | 0.15% |
| Colombia | 4.5 × 10⁻¹¹ | 0.12% |
| Mozambique | 4.4 × 10⁻¹¹ | 0.11% |
| Niger | 3.6 × 10⁻¹¹ | <0.1% |
| Spain | 3.4 × 10⁻¹¹ | <0.1% |
| Uganda | 3.2 × 10⁻¹¹ | <0.1% |
| Turkmenistan | 2.9 × 10⁻¹¹ | <0.1% |
| Yemen, Rep. | 2.4 × 10⁻¹¹ | <0.1% |
| Haiti | 1.6 × 10⁻¹¹ | <0.1% |
| Burundi | 3.0 × 10⁻¹² | <0.1% |
| Honduras | 2.8 × 10⁻¹² | <0.1% |
| Ecuador | 2.8 × 10⁻¹² | <0.1% |
| Kenya | 1.8 × 10⁻¹² | <0.1% |
| Thailand | 1.2 × 10⁻¹² | <0.1% |
| Egypt, Arab Rep. | 9.6 × 10⁻¹³ | <0.1% |
| Ghana | 6.7 × 10⁻¹³ | <0.1% |
| Iran, Islamic Rep. | 5.7 × 10⁻¹³ | <0.1% |
| Bangladesh | 3.8 × 10⁻¹³ | <0.1% |
| Peru | 2.6 × 10⁻¹³ | <0.1% |
| China | 2.5 × 10⁻¹³ | <0.1% |
| Eswatini | 2.2 × 10⁻¹³ | <0.1% |
| Guatemala | 1.9 × 10⁻¹³ | <0.1% |
| Tunisia | 1.3 × 10⁻¹³ | <0.1% |
| Costa Rica | 8.4 × 10⁻¹⁴ | <0.1% |
| South Africa | 8.4 × 10⁻¹⁴ | <0.1% |
| Venezuela, RB | 6.7 × 10⁻¹⁴ | <0.1% |
| Bolivia | 1.4 × 10⁻¹⁴ | <0.1% |
| Philippines | 1.1 × 10⁻¹⁴ | <0.1% |
| Morocco | 3.0 × 10⁻¹⁵ | <0.1% |
| Algeria | 4.2 × 10⁻¹⁷ | <0.1% |
| Total | 3.9 × 10⁻⁸ | = the headline figure, 3.9 × 10⁻⁸ |
3 · Through which kind of harm
The same headline, by kind of harm: war, work, poverty, pollution.
| Kind of harm | Part of the figure | Share |
|---|---|---|
| Conflict and political violence | 3.5 × 10⁻⁸ | 91% |
| Work | 3.3 × 10⁻⁹ | 8.7% |
| Total | 3.9 × 10⁻⁸ | = the headline figure, 3.9 × 10⁻⁸ |
4 · Which wars
The war deaths in the headline, by war. Harm of any other kind is the row that names no war.
| War | Part of the figure | Share |
|---|---|---|
| Burkina Faso: Government | 9.8 × 10⁻⁹ | 25% |
| Not placed | 3.3 × 10⁻⁹ | 8.7% |
| JNIM - Civilians | 2.8 × 10⁻⁹ | 7.2% |
| Burkina Faso: Islamic State | 2.0 × 10⁻⁹ | 5.2% |
| Israel: Palestine | 1.8 × 10⁻⁹ | 4.7% |
| Sudan: Government | 1.7 × 10⁻⁹ | 4.4% |
| Mali: Government | 1.4 × 10⁻⁹ | 3.8% |
| Pakistan: Government | 1.2 × 10⁻⁹ | 3.1% |
| Government of Burkina Faso - Civilians | 1.1 × 10⁻⁹ | 2.7% |
| IS - JNIM | 9.5 × 10⁻¹⁰ | 2.5% |
| IS - Civilians | 9.5 × 10⁻¹⁰ | 2.5% |
| Jalisco Cartel New Generation - Sinaloa Cartel | 7.6 × 10⁻¹⁰ | 2.0% |
| RSF - Civilians | 7.1 × 10⁻¹⁰ | 1.8% |
| Myanmar (Burma): Government | 5.0 × 10⁻¹⁰ | 1.3% |
| Comando Vermelho - PCC | 4.0 × 10⁻¹⁰ | 1.0% |
| Ethiopia: Government/Amhara | 3.9 × 10⁻¹⁰ | 1.0% |
| Government of Mali - Civilians | 3.6 × 10⁻¹⁰ | 0.94% |
| Cameroon: Ambazonia | 3.6 × 10⁻¹⁰ | 0.93% |
| Jalisco Cartel New Generation - Santa Rosa de Lima Cartel | 3.3 × 10⁻¹⁰ | 0.85% |
| Somalia: Government | 3.1 × 10⁻¹⁰ | 0.80% |
| Mali: Government/Azawad | 3.0 × 10⁻¹⁰ | 0.78% |
| Mali: Islamic State | 3.0 × 10⁻¹⁰ | 0.77% |
| Syria: Government | 3.0 × 10⁻¹⁰ | 0.77% |
| Juarez Cartel - Sinaloa Cartel | 2.9 × 10⁻¹⁰ | 0.76% |
| Carteles Unidos - Jalisco Cartel New Generation | 2.2 × 10⁻¹⁰ | 0.57% |
| JAS - Civilians | 2.2 × 10⁻¹⁰ | 0.56% |
| Cameroon: Government | 2.1 × 10⁻¹⁰ | 0.55% |
| Benin: Government | 2.0 × 10⁻¹⁰ | 0.52% |
| Ambazonia insurgents - Civilians | 1.9 × 10⁻¹⁰ | 0.51% |
| Central African Republic: Government | 1.9 × 10⁻¹⁰ | 0.50% |
| Government of Myanmar (Burma) - Civilians | 1.7 × 10⁻¹⁰ | 0.45% |
| Syria: Islamic State | 1.7 × 10⁻¹⁰ | 0.45% |
| Dan na Ambassagou - JNIM | 1.5 × 10⁻¹⁰ | 0.39% |
| Pakistan: Balochistan | 1.5 × 10⁻¹⁰ | 0.39% |
| Bonde do Maluco - Comando Vermelho | 1.4 × 10⁻¹⁰ | 0.38% |
| Ethiopia: Oromiya | 1.4 × 10⁻¹⁰ | 0.37% |
| Cartel do Norte - Comando Vermelho | 1.3 × 10⁻¹⁰ | 0.34% |
| Nigeria: Islamic State | 1.3 × 10⁻¹⁰ | 0.34% |
| Caborca Cartel, Sinaloa Cartel - Los Mayos - Sinaloa Cartel - Los Chapitos | 1.3 × 10⁻¹⁰ | 0.33% |
| Afghanistan: Islamic State | 1.2 × 10⁻¹⁰ | 0.32% |
| Pakistan: Islamic State | 1.2 × 10⁻¹⁰ | 0.30% |
| Cameroon: Islamic State | 9.9 × 10⁻¹¹ | 0.26% |
| SNA - SDF | 9.7 × 10⁻¹¹ | 0.25% |
| Azerbaijan: Artsakh (Nagorno-Karabakh) | 9.7 × 10⁻¹¹ | 0.25% |
| Turkey: Kurdistan | 9.5 × 10⁻¹¹ | 0.25% |
| Bonde dos 40 - PCC | 9.3 × 10⁻¹¹ | 0.24% |
| India: Kashmir | 9.0 × 10⁻¹¹ | 0.23% |
| Myanmar (Burma): Kachin | 8.6 × 10⁻¹¹ | 0.22% |
| Beni Halba Baggara - Salamat Baggara | 7.7 × 10⁻¹¹ | 0.20% |
| Kuki - Meitei | 7.7 × 10⁻¹¹ | 0.20% |
| AAKG - CPC | 7.7 × 10⁻¹¹ | 0.20% |
| India: Government | 7.2 × 10⁻¹¹ | 0.19% |
| Comando Vermelho - GDE | 7.1 × 10⁻¹¹ | 0.18% |
| Nova Okaida - Estados Unidos | 7.0 × 10⁻¹¹ | 0.18% |
| GDE, PCC - Sindicato do Crime | 6.9 × 10⁻¹¹ | 0.18% |
| Afghanistan: Government | 6.1 × 10⁻¹¹ | 0.16% |
| PCC - Sindicato do Crime | 6.1 × 10⁻¹¹ | 0.16% |
| Amigos Para Sempre - Família Terror Amapá | 6.1 × 10⁻¹¹ | 0.16% |
| Iran - Israel | 6.0 × 10⁻¹¹ | 0.16% |
| Government of Ethiopia - Civilians | 5.9 × 10⁻¹¹ | 0.15% |
| Myanmar (Burma): Karen | 5.6 × 10⁻¹¹ | 0.15% |
| Cartel Independiente de Acapulco - Los Rusos, UPOEG | 5.6 × 10⁻¹¹ | 0.14% |
| Habaniya - Salamat Baggara | 5.4 × 10⁻¹¹ | 0.14% |
| Nigeria: Government | 5.1 × 10⁻¹¹ | 0.13% |
| Comando Vermelho - Civilians | 5.1 × 10⁻¹¹ | 0.13% |
| Government of Cameroon - Civilians | 4.7 × 10⁻¹¹ | 0.12% |
| OLA - Civilians | 4.6 × 10⁻¹¹ | 0.12% |
| Hamas - Civilians | 4.5 × 10⁻¹¹ | 0.12% |
| IS - SDF | 4.5 × 10⁻¹¹ | 0.12% |
| Myanmar (Burma): Karenni | 4.4 × 10⁻¹¹ | 0.11% |
| Dozos (Mali) - JNIM | 4.1 × 10⁻¹¹ | 0.11% |
| Fano - Civilians | 4.1 × 10⁻¹¹ | 0.11% |
| Shia (Pakistan) - Sunni (Pakistan) | 3.9 × 10⁻¹¹ | 0.10% |
| Anuak - Nuer | 3.9 × 10⁻¹¹ | 0.10% |
| Arab - Gimir | 3.9 × 10⁻¹¹ | 0.10% |
| Bonde dos 13, PCC - Comando Vermelho | 3.7 × 10⁻¹¹ | <0.1% |
| Bonde dos 40 - Comando Vermelho | 3.7 × 10⁻¹¹ | <0.1% |
| Deir ez Zor Military Council - SDF | 3.5 × 10⁻¹¹ | <0.1% |
| Sinaloa Cartel - Los Chapitos - Sinaloa Cartel - Los Mayos | 3.5 × 10⁻¹¹ | <0.1% |
| Togo: Government | 3.4 × 10⁻¹¹ | <0.1% |
| Government of Afghanistan - Civilians | 3.3 × 10⁻¹¹ | <0.1% |
| CPI-Maoist - Civilians | 3.2 × 10⁻¹¹ | <0.1% |
| Carteles Unidos, Guerreros Unidos - Los Tlacos | 3.2 × 10⁻¹¹ | <0.1% |
| IS - JAS | 3.1 × 10⁻¹¹ | <0.1% |
| Chad: Government | 3.0 × 10⁻¹¹ | <0.1% |
| Mozambique: Islamic State | 2.8 × 10⁻¹¹ | <0.1% |
| Comités locaux de vigilance - JAS | 2.8 × 10⁻¹¹ | <0.1% |
| Comando Vermelho - Holanda | 2.6 × 10⁻¹¹ | <0.1% |
| Central African Republic: Logone | 2.4 × 10⁻¹¹ | <0.1% |
| Myanmar (Burma): Arakan | 2.4 × 10⁻¹¹ | <0.1% |
| Los Ardillos - Los Tlacos | 2.3 × 10⁻¹¹ | <0.1% |
| Dozos (Mali) - Civilians | 2.3 × 10⁻¹¹ | <0.1% |
| SSC-Khatumo Administration - Republic of Somaliland | 2.3 × 10⁻¹¹ | <0.1% |
| Farmers (Chad) - Herders (Chad) | 2.2 × 10⁻¹¹ | <0.1% |
| CPC - Civilians | 2.1 × 10⁻¹¹ | <0.1% |
| Yemen (North Yemen): Government | 2.0 × 10⁻¹¹ | <0.1% |
| Comando Vermelho - Massa | 2.0 × 10⁻¹¹ | <0.1% |
| Nova Okaida - PCC | 1.9 × 10⁻¹¹ | <0.1% |
| URDPC - Civilians | 1.9 × 10⁻¹¹ | <0.1% |
| Niger: Islamic State | 1.8 × 10⁻¹¹ | <0.1% |
| Fulani - Mwaghavul | 1.8 × 10⁻¹¹ | <0.1% |
| Bonde do Maluco - Katiara | 1.8 × 10⁻¹¹ | <0.1% |
| Bonde do Maluco - Civilians | 1.8 × 10⁻¹¹ | <0.1% |
| Jalisco Cartel New Generation - Zetas Vieja Escuela | 1.7 × 10⁻¹¹ | <0.1% |
| Fulani - Mwaghavul , Ron | 1.7 × 10⁻¹¹ | <0.1% |
| Twic Dinka - Ngok Dinka | 1.7 × 10⁻¹¹ | <0.1% |
| BRAS - Civilians | 1.6 × 10⁻¹¹ | <0.1% |
| Fulani - Tiv | 1.6 × 10⁻¹¹ | <0.1% |
| Syria: Government/Rojava Kurdistan | 1.5 × 10⁻¹¹ | <0.1% |
| Myanmar (Burma): Kokang | 1.4 × 10⁻¹¹ | <0.1% |
| Kashmir insurgents - Civilians | 1.4 × 10⁻¹¹ | <0.1% |
| Dan na Ambassagou - Civilians | 1.4 × 10⁻¹¹ | <0.1% |
| Afghanistan - Pakistan | 1.4 × 10⁻¹¹ | <0.1% |
| Bonde dos 40 - Civilians | 1.4 × 10⁻¹¹ | <0.1% |
| Farmers (Nigeria) - Herders (Nigeria) | 1.4 × 10⁻¹¹ | <0.1% |
| Comando Vermelho - Terceiro Comando Puro | 1.3 × 10⁻¹¹ | <0.1% |
| Lengola - Mbole | 1.2 × 10⁻¹¹ | <0.1% |
| Arab - Masalit | 1.2 × 10⁻¹¹ | <0.1% |
| GATIA - IS | 1.1 × 10⁻¹¹ | <0.1% |
| Amhara - Oromo | 1.1 × 10⁻¹¹ | <0.1% |
| PCC - Civilians | 1.0 × 10⁻¹¹ | <0.1% |
| Nigeria: Biafra | 9.7 × 10⁻¹² | <0.1% |
| TTP - Civilians | 9.5 × 10⁻¹² | <0.1% |
| Ajeita - Bonde do Maluco | 9.0 × 10⁻¹² | <0.1% |
| Uganda: Islamic State | 8.8 × 10⁻¹² | <0.1% |
| Government of Rwanda - Civilians | 8.7 × 10⁻¹² | <0.1% |
| DR Congo (Zaire): Government | 8.6 × 10⁻¹² | <0.1% |
| DR Congo (Zaire): Islamic State | 8.6 × 10⁻¹² | <0.1% |
| Hausa - Nuba | 7.7 × 10⁻¹² | <0.1% |
| Government of Pakistan - Civilians | 7.6 × 10⁻¹² | <0.1% |
| Birom - Fulani | 7.2 × 10⁻¹² | <0.1% |
| Government of Central African Republic - Civilians | 6.8 × 10⁻¹² | <0.1% |
| Government of Brazil - Civilians | 6.7 × 10⁻¹² | <0.1% |
| Israel - Syria | 6.4 × 10⁻¹² | <0.1% |
| Atyap - Fulani | 6.2 × 10⁻¹² | <0.1% |
| Anti-Bala - Bala na Cara | 6.2 × 10⁻¹² | <0.1% |
| Hindus (India) - Muslims (India) | 6.0 × 10⁻¹² | <0.1% |
| Karimjo - Wurukum | 5.9 × 10⁻¹² | <0.1% |
| Bonde dos 40 - PCM | 5.6 × 10⁻¹² | <0.1% |
| Black Axe - Eyie | 5.5 × 10⁻¹² | <0.1% |
| EGC - Civilians | 5.4 × 10⁻¹² | <0.1% |
| IS - MSA | 5.3 × 10⁻¹² | <0.1% |
| M23 - VDP | 5.3 × 10⁻¹² | <0.1% |
| Government of India - Civilians | 5.3 × 10⁻¹² | <0.1% |
| Mobondo - Civilians | 5.1 × 10⁻¹² | <0.1% |
| Los Rusos, UPOEG - Los Tlacos | 4.9 × 10⁻¹² | <0.1% |
| Forces of Terwase Akwanza - Civilians | 4.9 × 10⁻¹² | <0.1% |
| IS - Naparama | 4.8 × 10⁻¹² | <0.1% |
| Guraghe - Mareqo | 4.6 × 10⁻¹² | <0.1% |
| Fulani - Idoma | 4.5 × 10⁻¹² | <0.1% |
| NUG - Civilians | 4.4 × 10⁻¹² | <0.1% |
| Jalisco Cartel New Generation - Civilians | 4.4 × 10⁻¹² | <0.1% |
| Fulani - Kuteb | 4.3 × 10⁻¹² | <0.1% |
| M23 - Civilians | 4.1 × 10⁻¹² | <0.1% |
| Jalisco Cartel New Generation - Pájaros Sierra | 4.1 × 10⁻¹² | <0.1% |
| Rwanda: Government | 3.6 × 10⁻¹² | <0.1% |
| Niger: Government | 3.6 × 10⁻¹² | <0.1% |
| Government of Mexico - Civilians | 3.4 × 10⁻¹² | <0.1% |
| Syrian insurgents - Civilians | 3.4 × 10⁻¹² | <0.1% |
| Government of DR Congo (Zaire) - Civilians | 3.3 × 10⁻¹² | <0.1% |
| Al-Shabaab - Civilians | 3.2 × 10⁻¹² | <0.1% |
| Murle - Nuer | 3.1 × 10⁻¹² | <0.1% |
| Government of Israel - Civilians | 3.1 × 10⁻¹² | <0.1% |
| Hawazma - Nuba | 3.1 × 10⁻¹² | <0.1% |
| Colombia: Government | 3.0 × 10⁻¹² | <0.1% |
| Government of Nigeria - Civilians | 3.0 × 10⁻¹² | <0.1% |
| India: Western South East Asia | 3.0 × 10⁻¹² | <0.1% |
| Los Ardillos - Los Rojos | 2.9 × 10⁻¹² | <0.1% |
| Government of Haiti - Civilians | 2.9 × 10⁻¹² | <0.1% |
| FARC-EMC - Civilians | 2.9 × 10⁻¹² | <0.1% |
| Gulf Cartel - Los Zetas - Cártel del Noreste faction | 2.8 × 10⁻¹² | <0.1% |
| Hausa - Funj | 2.8 × 10⁻¹² | <0.1% |
| AQAP - Forces of the Presidential Leadership Council | 2.7 × 10⁻¹² | <0.1% |
| G9 - G-Pep | 2.7 × 10⁻¹² | <0.1% |
| SDF - Civilians | 2.6 × 10⁻¹² | <0.1% |
| Chain Guys - Full Force | 2.5 × 10⁻¹² | <0.1% |
| Terre Noire - Civilians | 2.5 × 10⁻¹² | <0.1% |
| Government of Sudan - Civilians | 2.5 × 10⁻¹² | <0.1% |
| 5 Segond, Taliban - Civilians | 2.4 × 10⁻¹² | <0.1% |
| M18 - MS-13 | 2.4 × 10⁻¹² | <0.1% |
| Grand Ravine - Civilians | 2.3 × 10⁻¹² | <0.1% |
| Burundi: Government | 2.3 × 10⁻¹² | <0.1% |
| Government of Mozambique - Civilians | 2.1 × 10⁻¹² | <0.1% |
| Choa Arab - Kotoko | 1.9 × 10⁻¹² | <0.1% |
| Choa Arab - Musgum | 1.9 × 10⁻¹² | <0.1% |
| FARC-EMC - ELN | 1.9 × 10⁻¹² | <0.1% |
| PKK - Civilians | 1.8 × 10⁻¹² | <0.1% |
| G-Pep - Civilians | 1.7 × 10⁻¹² | <0.1% |
| URDPC - Zaire self-defense group | 1.7 × 10⁻¹² | <0.1% |
| Sa'ad subclan of Habar Gidir clan (Hawiye) - Leelkase subclan (Darod) | 1.6 × 10⁻¹² | <0.1% |
| Kenya: Northeastern Province and Coast | 1.6 × 10⁻¹² | <0.1% |
| Farmers (CAR) - Herders (CAR) | 1.5 × 10⁻¹² | <0.1% |
| AAKG - Civilians | 1.5 × 10⁻¹² | <0.1% |
| VHP - Civilians | 1.5 × 10⁻¹² | <0.1% |
| Zaire self-defense group - Civilians | 1.5 × 10⁻¹² | <0.1% |
| VDP - Civilians | 1.4 × 10⁻¹² | <0.1% |
| Hausa - Fulani | 1.4 × 10⁻¹² | <0.1% |
| Israel: Southern Lebanon | 1.4 × 10⁻¹² | <0.1% |
| Djerma (Zherma) - Fulani | 1.4 × 10⁻¹² | <0.1% |
| LeJ - Civilians | 1.4 × 10⁻¹² | <0.1% |
| FARC - Segunda Marquetalia - Civilians | 1.2 × 10⁻¹² | <0.1% |
| Somalia: Islamic State | 1.2 × 10⁻¹² | <0.1% |
| ELN - Civilians | 1.2 × 10⁻¹² | <0.1% |
| FPIC Chambre noire sanduku - URDPC | 1.1 × 10⁻¹² | <0.1% |
| FPIC Chambre noire sanduku - Civilians | 1.1 × 10⁻¹² | <0.1% |
| Fulani - Irigwe | 1.0 × 10⁻¹² | <0.1% |
| Los Costenos - Los Pepes | 9.8 × 10⁻¹³ | <0.1% |
| Gulf Cartel - Sinaloa Cartel | 9.8 × 10⁻¹³ | <0.1% |
| Gulf Cartel - Jalisco Cartel New Generation | 9.8 × 10⁻¹³ | <0.1% |
| Government of Burundi - Civilians | 9.5 × 10⁻¹³ | <0.1% |
| EGC - ELN, FARC-EMC | 9.5 × 10⁻¹³ | <0.1% |
| Amhara - Gumuz | 9.3 × 10⁻¹³ | <0.1% |
| EGC - ELN | 9.1 × 10⁻¹³ | <0.1% |
| Los Choneros - Los Lobos | 9.0 × 10⁻¹³ | <0.1% |
| Fulani - Igala | 8.4 × 10⁻¹³ | <0.1% |
| Government of Egypt - Civilians | 8.0 × 10⁻¹³ | <0.1% |
| AFC - Civilians | 7.9 × 10⁻¹³ | <0.1% |
| Greenlanders - NDV | 7.5 × 10⁻¹³ | <0.1% |
| Black Axe - Maphite | 7.5 × 10⁻¹³ | <0.1% |
| India - Pakistan | 7.5 × 10⁻¹³ | <0.1% |
| India: Nagaland | 7.5 × 10⁻¹³ | <0.1% |
| NSCN-IM - Civilians | 7.5 × 10⁻¹³ | <0.1% |
| PLFI - Civilians | 7.5 × 10⁻¹³ | <0.1% |
| AFP-Gutabara - CNPSC, FABB | 7.4 × 10⁻¹³ | <0.1% |
| Kusasi - Mamprusi | 6.7 × 10⁻¹³ | <0.1% |
| Gran Grif - Civilians | 6.6 × 10⁻¹³ | <0.1% |
| 400 Mawozo - Civilians | 6.6 × 10⁻¹³ | <0.1% |
| Misseriya - Ngok Dinka | 6.1 × 10⁻¹³ | <0.1% |
| Myanmar (Burma): Shan | 5.9 × 10⁻¹³ | <0.1% |
| ARSA - Civilians | 5.8 × 10⁻¹³ | <0.1% |
| Amigos dos Amigos - Comando Vermelho | 5.6 × 10⁻¹³ | <0.1% |
| FDN - PCC | 5.6 × 10⁻¹³ | <0.1% |
| M18 - Civilians | 5.1 × 10⁻¹³ | <0.1% |
| Supporters of APC - Supporters of PDP | 5.0 × 10⁻¹³ | <0.1% |
| Iran: Government | 4.8 × 10⁻¹³ | <0.1% |
| United Kingdom, United States of America - Yemen | 4.3 × 10⁻¹³ | <0.1% |
| Black Axe - SVC | 4.2 × 10⁻¹³ | <0.1% |
| IPOB - Civilians | 4.2 × 10⁻¹³ | <0.1% |
| EGC - Autodefensas Conquistadoras de la Sierra Nevada | 4.0 × 10⁻¹³ | <0.1% |
| IS - HTS | 3.8 × 10⁻¹³ | <0.1% |
| Fatales, Los Aguilas - Los Lobos , Los Tiguerones | 3.8 × 10⁻¹³ | <0.1% |
| Agatu - Fulani | 3.4 × 10⁻¹³ | <0.1% |
| IS - Yan Gora | 3.4 × 10⁻¹³ | <0.1% |
| Deebam - NDV | 3.4 × 10⁻¹³ | <0.1% |
| Government of Colombia - Civilians | 3.3 × 10⁻¹³ | <0.1% |
| Government of Somalia - Civilians | 3.2 × 10⁻¹³ | <0.1% |
| Los Chone Killers - Latin Kings | 3.1 × 10⁻¹³ | <0.1% |
| Government of Yemen (North Yemen) - Civilians | 3.1 × 10⁻¹³ | <0.1% |
| Los Aguilas - Los Lobos | 2.8 × 10⁻¹³ | <0.1% |
| AFP-Gutabara - FABB | 2.7 × 10⁻¹³ | <0.1% |
| Peru: Government | 2.6 × 10⁻¹³ | <0.1% |
| Los Choneros - Los Lagartos | 2.5 × 10⁻¹³ | <0.1% |
| Los Lobos - Los Tiguerones | 2.5 × 10⁻¹³ | <0.1% |
| Los Lagartos - Mafia 18 | 2.5 × 10⁻¹³ | <0.1% |
| Government of eSwatini (Swaziland) - Civilians | 2.2 × 10⁻¹³ | <0.1% |
| FRPI - Civilians | 2.2 × 10⁻¹³ | <0.1% |
| DZ Mafia - Yoda | 2.0 × 10⁻¹³ | <0.1% |
| Los Aguilas - Los Lobos , Los Tiguerones | 1.9 × 10⁻¹³ | <0.1% |
| Jukun - Tiv | 1.7 × 10⁻¹³ | <0.1% |
| Guerreros Unidos - Los Tlacos | 1.6 × 10⁻¹³ | <0.1% |
| Egypt: Islamic State | 1.6 × 10⁻¹³ | <0.1% |
| Al-Shabaab - IS | 1.6 × 10⁻¹³ | <0.1% |
| Basonge - Bena Nkoma (Bakwa Luntu, Luba) | 1.5 × 10⁻¹³ | <0.1% |
| Comandos de la Frontera - Civilians | 1.5 × 10⁻¹³ | <0.1% |
| Tunisia: Government | 1.3 × 10⁻¹³ | <0.1% |
| FDLR-FOCA - Civilians | 1.2 × 10⁻¹³ | <0.1% |
| FPIC Chambre noire sanduku - FRPI | 1.2 × 10⁻¹³ | <0.1% |
| Autodefensas Conquistadoras de la Sierra Nevada - Civilians | 1.1 × 10⁻¹³ | <0.1% |
| MS-13 - Civilians | 1.1 × 10⁻¹³ | <0.1% |
| Mayi Mayi Chini ya Tuna - Civilians | 9.9 × 10⁻¹⁴ | <0.1% |
| Forces of Tony Peña - Los Hondureños | 8.4 × 10⁻¹⁴ | <0.1% |
| South Sudan: Government | 7.4 × 10⁻¹⁴ | <0.1% |
| Luba - Batwa | 7.4 × 10⁻¹⁴ | <0.1% |
| Los Costenos - Civilians | 7.3 × 10⁻¹⁴ | <0.1% |
| Kokorat sans ras - Civilians | 7.0 × 10⁻¹⁴ | <0.1% |
| Supporters of Awami League - Supporters of BNP | 6.3 × 10⁻¹⁴ | <0.1% |
| Government of Venezuela - Civilians | 5.5 × 10⁻¹⁴ | <0.1% |
| Thailand: Patani | 5.4 × 10⁻¹⁴ | <0.1% |
| Iran: Islamic State | 5.3 × 10⁻¹⁴ | <0.1% |
| CATA - Codeta | 5.0 × 10⁻¹⁴ | <0.1% |
| Government of Iran - Civilians | 4.0 × 10⁻¹⁴ | <0.1% |
| Government of South Africa - Civilians | 3.3 × 10⁻¹⁴ | <0.1% |
| Supporters of Awami League - Supporters of Jamaat-e-Islami | 3.1 × 10⁻¹⁴ | <0.1% |
| DR Congo (Zaire): Katanga | 2.5 × 10⁻¹⁴ | <0.1% |
| Government of Uganda - Civilians | 2.5 × 10⁻¹⁴ | <0.1% |
| Twiganeho - Civilians | 2.5 × 10⁻¹⁴ | <0.1% |
| AFC - VDP | 2.5 × 10⁻¹⁴ | <0.1% |
| RED-TABARA - Civilians | 2.4 × 10⁻¹⁴ | <0.1% |
| Los Lobos - R7 | 2.1 × 10⁻¹⁴ | <0.1% |
| Philippines: Government | 6.9 × 10⁻¹⁵ | <0.1% |
| Philippines: Islamic State | 3.3 × 10⁻¹⁵ | <0.1% |
| Morocco: Sahrawi Arab Democratic Republic (Western Sahara) | 3.0 × 10⁻¹⁵ | <0.1% |
| Patani insurgents - Civilians | 1.8 × 10⁻¹⁵ | <0.1% |
| CPP - Civilians | 6.7 × 10⁻¹⁶ | <0.1% |
| Philippines: Mindanao | 8.4 × 10⁻¹⁷ | <0.1% |
| Government of Philippines - Civilians | 8.4 × 10⁻¹⁷ | <0.1% |
| Algeria: Government | 4.2 × 10⁻¹⁷ | <0.1% |
| Total | 3.9 × 10⁻⁸ | = the headline figure, 3.9 × 10⁻⁸ |
5 · The money method: which industries
The figure per €1,000, by the industry where the harm happened, anywhere in the supply chain.
| Industry | Part of the figure | Share |
|---|---|---|
| Mining and quarrying | 8.0 × 10⁻⁷ | 56% |
| Crop and animal production, hunting and related service activities | 3.2 × 10⁻⁷ | 22% |
| Land transport and transport via pipelines | 5.9 × 10⁻⁸ | 4.1% |
| Manufacture of textiles, wearing apparel, leather and related products | 5.4 × 10⁻⁸ | 3.8% |
| Water transport | 3.8 × 10⁻⁸ | 2.7% |
| Manufacture of basic metals | 3.1 × 10⁻⁸ | 2.2% |
| Warehousing and support activities for transportation | 2.6 × 10⁻⁸ | 1.8% |
| Forestry and logging | 2.4 × 10⁻⁸ | 1.7% |
| Air transport | 1.9 × 10⁻⁸ | 1.3% |
| Wholesale trade, except of motor vehicles and motorcycles | 1.4 × 10⁻⁸ | 1.0% |
| Retail trade, except of motor vehicles and motorcycles | 6.5 × 10⁻⁹ | 0.46% |
| Postal and courier activities | 4.4 × 10⁻⁹ | 0.31% |
| Manufacture of chemicals and chemical products | 3.8 × 10⁻⁹ | 0.26% |
| Water collection, treatment and supply | 3.5 × 10⁻⁹ | 0.24% |
| Construction | 2.4 × 10⁻⁹ | 0.17% |
| Manufacture of fabricated metal products, except machinery and equipment | 2.3 × 10⁻⁹ | 0.16% |
| Manufacture of coke and refined petroleum products | 2.3 × 10⁻⁹ | 0.16% |
| Public administration and defence; compulsory social security | 2.0 × 10⁻⁹ | 0.14% |
| Manufacture of other transport equipment | 1.8 × 10⁻⁹ | 0.12% |
| Security and investigation, service and landscape, office administrative and support activities | 1.8 × 10⁻⁹ | 0.12% |
| Electricity, gas, steam and air conditioning supply | 1.7 × 10⁻⁹ | 0.12% |
| Employment activities | 1.0 × 10⁻⁹ | <0.1% |
| Rental and leasing activities | 9.8 × 10⁻¹⁰ | <0.1% |
| Manufacture of rubber and plastic products | 9.1 × 10⁻¹⁰ | <0.1% |
| Manufacture of food products; beverages and tobacco products | 8.8 × 10⁻¹⁰ | <0.1% |
| Sewerage, waste management, remediation activities | 8.8 × 10⁻¹⁰ | <0.1% |
| Wholesale and retail trade and repair of motor vehicles and motorcycles | 8.7 × 10⁻¹⁰ | <0.1% |
| Manufacture of paper and paper products | 6.9 × 10⁻¹⁰ | <0.1% |
| Legal and accounting activities; activities of head offices; management consultancy activities | 6.1 × 10⁻¹⁰ | <0.1% |
| Accommodation and food service activities | 5.6 × 10⁻¹⁰ | <0.1% |
| Manufacture of computer, electronic and optical products | 4.0 × 10⁻¹⁰ | <0.1% |
| Manufacture of machinery and equipment n.e.c. | 3.5 × 10⁻¹⁰ | <0.1% |
| Repair and installation of machinery and equipment | 3.0 × 10⁻¹⁰ | <0.1% |
| Manufacture of other non-metallic mineral products | 2.7 × 10⁻¹⁰ | <0.1% |
| Real estate activities | 2.6 × 10⁻¹⁰ | <0.1% |
| Manufacture of electrical equipment | 2.5 × 10⁻¹⁰ | <0.1% |
| Manufacture of motor vehicles, trailers and semi-trailers | 2.5 × 10⁻¹⁰ | <0.1% |
| Human health activities | 1.9 × 10⁻¹⁰ | <0.1% |
| Manufacture of furniture; other manufacturing | 1.9 × 10⁻¹⁰ | <0.1% |
| Advertising and market research | 1.8 × 10⁻¹⁰ | <0.1% |
| Architectural and engineering activities; technical testing and analysis | 1.8 × 10⁻¹⁰ | <0.1% |
| Travel agency, tour operator reservation service and related activities | 1.5 × 10⁻¹⁰ | <0.1% |
| Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials | 1.4 × 10⁻¹⁰ | <0.1% |
| Printing and reproduction of recorded media | 1.3 × 10⁻¹⁰ | <0.1% |
| Repair of computers and personal and household goods | 1.2 × 10⁻¹⁰ | <0.1% |
| Computer programming, consultancy, and information service activities | 1.2 × 10⁻¹⁰ | <0.1% |
| Other professional, scientific and technical activities; veterinary activities | 1.2 × 10⁻¹⁰ | <0.1% |
| Fishing and aquaculture | 1.2 × 10⁻¹⁰ | <0.1% |
| Activities of membership organisations | 1.2 × 10⁻¹⁰ | <0.1% |
| Financial service activities, except insurance and pension funding | 1.1 × 10⁻¹⁰ | <0.1% |
| Other personal service activities | 1.1 × 10⁻¹⁰ | <0.1% |
| Manufacture of basic pharmaceutical products and pharmaceutical preparations | 9.3 × 10⁻¹¹ | <0.1% |
| Telecommunications | 6.7 × 10⁻¹¹ | <0.1% |
| Sports activities and amusement and recreation activities | 5.1 × 10⁻¹¹ | <0.1% |
| Creative, arts and entertainment activities; libraries, archives, museums and other cultural activities; gambling and betting activities | 4.5 × 10⁻¹¹ | <0.1% |
| Education | 4.3 × 10⁻¹¹ | <0.1% |
| Motion picture, video, television programme production; programming and broadcasting activities | 2.9 × 10⁻¹¹ | <0.1% |
| Insurance, reinsurance and pension funding, except compulsory social security | 2.8 × 10⁻¹¹ | <0.1% |
| Activities auxiliary to financial services and insurance activities | 2.5 × 10⁻¹¹ | <0.1% |
| Publishing activities | 2.2 × 10⁻¹¹ | <0.1% |
| Residential care activities and social work activities without accommodation | 1.9 × 10⁻¹¹ | <0.1% |
| Scientific research and development | 1.5 × 10⁻¹¹ | <0.1% |
| Activities of households as employers; undifferentiated goods- and services-producing activities of households for own use | 1.6 × 10⁻¹² | <0.1% |
| Total | 1.4 × 10⁻⁶ | = the headline figure, 1.4 × 10⁻⁶ |
6 · The money method: which countries
The figure per €1,000, by the country of the industry where the harm happened.
| Country | Part of the figure | Share |
|---|---|---|
| Not placed | 1.2 × 10⁻⁶ | 87% |
| Mexico | 4.7 × 10⁻⁸ | 3.3% |
| Turkiye | 4.4 × 10⁻⁸ | 3.1% |
| Brazil | 2.7 × 10⁻⁸ | 1.9% |
| United States | 9.6 × 10⁻⁹ | 0.67% |
| Russian Federation | 9.0 × 10⁻⁹ | 0.63% |
| India | 7.9 × 10⁻⁹ | 0.55% |
| Korea, Rep. | 7.8 × 10⁻⁹ | 0.54% |
| Italy | 5.9 × 10⁻⁹ | 0.41% |
| France | 3.7 × 10⁻⁹ | 0.26% |
| Canada | 2.4 × 10⁻⁹ | 0.17% |
| Japan | 2.2 × 10⁻⁹ | 0.16% |
| Argentina | 1.9 × 10⁻⁹ | 0.13% |
| Spain | 1.8 × 10⁻⁹ | 0.13% |
| Portugal | 1.7 × 10⁻⁹ | 0.12% |
| Indonesia | 1.4 × 10⁻⁹ | <0.1% |
| Germany | 1.3 × 10⁻⁹ | <0.1% |
| Romania | 8.5 × 10⁻¹⁰ | <0.1% |
| Poland | 7.1 × 10⁻¹⁰ | <0.1% |
| Bulgaria | 5.9 × 10⁻¹⁰ | <0.1% |
| Australia | 5.8 × 10⁻¹⁰ | <0.1% |
| Austria | 3.2 × 10⁻¹⁰ | <0.1% |
| Czechia | 2.8 × 10⁻¹⁰ | <0.1% |
| Lithuania | 2.4 × 10⁻¹⁰ | <0.1% |
| Greece | 2.3 × 10⁻¹⁰ | <0.1% |
| Belgium | 2.0 × 10⁻¹⁰ | <0.1% |
| Hungary | 1.8 × 10⁻¹⁰ | <0.1% |
| Croatia | 1.8 × 10⁻¹⁰ | <0.1% |
| Switzerland | 1.4 × 10⁻¹⁰ | <0.1% |
| Denmark | 1.3 × 10⁻¹⁰ | <0.1% |
| Netherlands | 1.3 × 10⁻¹⁰ | <0.1% |
| Latvia | 1.2 × 10⁻¹⁰ | <0.1% |
| Sweden | 1.2 × 10⁻¹⁰ | <0.1% |
| Norway | 1.1 × 10⁻¹⁰ | <0.1% |
| Finland | 1.0 × 10⁻¹⁰ | <0.1% |
| Slovenia | 9.5 × 10⁻¹¹ | <0.1% |
| Saudi Arabia | 8.9 × 10⁻¹¹ | <0.1% |
| Slovak Republic | 8.2 × 10⁻¹¹ | <0.1% |
| Ireland | 8.1 × 10⁻¹¹ | <0.1% |
| South Africa | 4.3 × 10⁻¹¹ | <0.1% |
| Estonia | 4.3 × 10⁻¹¹ | <0.1% |
| Luxembourg | 4.2 × 10⁻¹¹ | <0.1% |
| China | 3.1 × 10⁻¹¹ | <0.1% |
| Cyprus | 3.1 × 10⁻¹¹ | <0.1% |
| United Kingdom | 1.5 × 10⁻¹¹ | <0.1% |
| Malta | 6.8 × 10⁻¹² | <0.1% |
| Serbia | 1.2 × 10⁻¹⁴ | <0.1% |
| Total | 1.4 × 10⁻⁶ | = the headline figure, 1.4 × 10⁻⁶ |
What this trail does not show
- Each table is a separate way of dividing the figure. “Cobalt accounts for 40%” and “one country accounts for 60%” are two views of one figure, not a path through it: the calculation stores the figure divided each way on its own, not every combination of them.
- A range belongs to the whole figure. A step’s number is only its middle estimate.
- Production phase only. Harm from using the product — driving the car, charging the phone — is not in this figure.
Sources behind this figure
- CEPII, BACI — Gaulier, G. and Zignago, S. (2010), BACI: International Trade Database at the Product-Level, CEPII Working Paper 2010-23. CEPII did not endorse these derived figures — HS92_V202601-20260130, retrieved 2026-09-29 from https://www.cepii.fr/DATA_DOWNLOAD/baci/data/BACI_HS92_V202601.zip. Licensed under Open Licence 2.0 (Licence Ouverte, Etalab) (https://www.etalab.gouv.fr/wp-content/uploads/2018/11/open-licence.pdf).
- Eurostat, Euro/ECU exchange rates - annual data (ert_bil_eur_a) — ert_bil_eur_a-USD-20261006, retrieved 2026-10-06 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/ert_bil_eur_a/A.AVG.NAC.USD?format=SDMX-CSV&startPeriod=1995. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- Eurostat, European Commission — esaw-fatal-20260910, retrieved 2026-09-10 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/hsw_n2_02?format=SDMX-CSV. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- Eurostat, European Commission — esaw-fatal-20261006, retrieved 2026-10-06 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/hsw_n2_02?format=SDMX-CSV. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- Eurostat, European Commission — esaw-non_fatal-20260910, retrieved 2026-09-10 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/hsw_n2_01?format=SDMX-CSV. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- Eurostat, European Commission — esaw-non_fatal-20261006, retrieved 2026-10-06 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/hsw_n2_01?format=SDMX-CSV. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- Eurostat, FIGARO inter-country input-output tables — ii1-20260718, retrieved 2026-09-29 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/naio_10_fcp_ii1?format=SDMX-CSV&compressed=true. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- Eurostat, FIGARO inter-country input-output tables — ii2-20260718, retrieved 2026-09-29 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/naio_10_fcp_ii2?format=SDMX-CSV&compressed=true. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- Eurostat, FIGARO inter-country input-output tables — ii3-20260718, retrieved 2026-09-29 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/naio_10_fcp_ii3?format=SDMX-CSV&compressed=true. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- Eurostat, FIGARO inter-country input-output tables — ii4-20260720, retrieved 2026-09-29 from https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/naio_10_fcp_ii4?format=SDMX-CSV&compressed=true. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- FAO. AQUASTAT, FAO's Global Information System on Water and Agriculture: municipal water withdrawal. Licence: CC-BY-4.0. FAO endorsement of these derived figures is neither stated nor implied — ds-20260713, retrieved 2026-10-06 from https://api.data.apps.fao.org/api/v2/bigquery. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- FAO. Food and Agriculture Organization of the United Nations, FAOSTAT. Licence: CC-BY-4.0. FAO endorsement of these derived figures is neither stated nor implied — fo-20260109, retrieved 2026-09-29 from https://bulks-faostat.fao.org/production/Forestry_E_All_Data_(Normalized).zip. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- FAO. Food and Agriculture Organization of the United Nations, FAOSTAT. Licence: CC-BY-4.0. FAO endorsement of these derived figures is neither stated nor implied — qcl-20251231, retrieved 2026-09-29 from https://bulks-faostat.fao.org/production/Production_Crops_Livestock_E_All_Data_(Normalized).zip. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- FAO. Food and Agriculture Organization of the United Nations, FAOSTAT. Licence: CC-BY-4.0. FAO endorsement of these derived figures is neither stated nor implied — rfb-20260730, retrieved 2026-09-29 from https://bulks-faostat.fao.org/production/Inputs_FertilizersProduct_E_All_Data_(Normalized).zip. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- FAO. Food and Agriculture Organization of the United Nations, FAOSTAT. Licence: CC-BY-4.0. FAO endorsement of these derived figures is neither stated nor implied — rl-20261002, retrieved 2026-10-06 from https://bulks-faostat.fao.org/production/Inputs_LandUse_E_All_Data_(Normalized).zip. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- Information from the Stockholm International Peace Research Institute (SIPRI) — arms-register-1950-2025, retrieved 2026-09-29 from https://atbackend.sipri.org/api/p/trades/trade-register-csv/. Used under SIPRI terms and conditions — fair-use policy; see https://www.sipri.org/about/terms-and-conditions.
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- International Labour Organization, ILOSTAT. The ILO did not prepare, review or endorse these derived figures; responsibility for them rests solely with Quiescence — emp-20261006, retrieved 2026-10-06 from https://sdmx.ilo.org/rest/data/ILO,DF_EMP_TEMP_SEX_ECO_NB,1.0/.A..SEX_T.. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- International Labour Organization, ILOSTAT. The ILO did not prepare, review or endorse these derived figures; responsibility for them rests solely with Quiescence — emp-20261007, retrieved 2026-10-06 from https://sdmx.ilo.org/rest/data/ILO,DF_EMP_TEMP_SEX_ECO_NB,1.0/.A..SEX_T.. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- International Labour Organization, ILOSTAT. The ILO did not prepare, review or endorse these derived figures; responsibility for them rests solely with Quiescence — fatal-20261006, retrieved 2026-10-06 from https://sdmx.ilo.org/rest/data/ILO,DF_INJ_FATL_ECO_NB,1.0/all. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- International Labour Organization, ILOSTAT. The ILO did not prepare, review or endorse these derived figures; responsibility for them rests solely with Quiescence — non_fatal-20261006, retrieved 2026-10-06 from https://sdmx.ilo.org/rest/data/ILO,DF_INJ_NFTL_ECO_NB,1.0/all. Licensed under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). Data modified by HumanToll.
- OECD. (2025) OECD Inter-Country Input-Output Tables, https://oe.cd/icio — 1995-2000_SML-20260112, retrieved 2026-09-22 from https://webfs-sti.oecd.org/files/STI-PIE/ICIO/2025/1995-2000_SML.zip. Used under OECD Terms and Conditions — section 3, Data; see https://www.oecd.org/en/about/terms-conditions.html.
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