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License information was derived automatically
This data repository provides the Food and Agriculture Biomass Input Output (FABIO) database, a global set of multi-regional physical supply-use and input-output tables covering global agriculture and forestry.
The work is based on mostly freely available data from FAOSTAT, IEA, EIA, and UN Comtrade/BACI. FABIO currently covers 191 countries + RoW, 118 processes and 125 commodities (raw and processed agricultural and food products) for 1986-2013. All R codes and auxilliary data are available on GitHub. For more information please refer to https://fabio.fineprint.global.
The database consists of the following main components, in compressed .rds format:
Z: the inter-commodity input-output matrix, displaying the relationships of intermediate use of each commodity in the production of each commodity, in physical units (tons). The matrix has 24000 rows and columns (125 commodities x 192 regions), and is available in two versions, based on the method to allocate inputs to outputs in production processes: Z_mass (mass allocation) and Z_value (value allocation). Note that the row sums of the Z matrix (= total intermediate use by commodity) are identical in both versions.
Y: the final demand matrix, denoting the consumption of all 24000 commodities by destination country and final use category. There are six final use categories (yielding 192 x 6 = 1152 columns): 1) food use, 2) other use (non-food), 3) losses, 4) stock addition, 5) balancing, and 6) unspecified.
X: the total output vector of all 24000 commodities. Total output is equal to the sum of intermediate and final use by commodity.
L: the Leontief inverse, computed as (I – A)-1, where A is the matrix of input coefficients derived from Z and x. Again, there are two versions, depending on the underlying version of Z (L_mass and L_value).
E: environmental extensions for each of the 24000 commodities, including four resource categories: 1) primary biomass extraction (in tons), 2) land use (in hectares), 3) blue water use (in m3)., and 4) green water use (in m3).
mr_sup_mass/mr_sup_value: For each allocation method (mass/value), the supply table gives the physical supply quantity of each commodity by producing process, with processes in the rows (118 processes x 192 regions = 22656 rows) and commodities in columns (24000 columns).
mr_use: the use table capture the quantities of each commodity (rows) used as an input in each process (columns).
A description of the included countries and commodities (i.e. the rows and columns of the Z matrix) can be found in the auxiliary file io_codes.csv. Separate lists of the country sample (including ISO3 codes and continental grouping) and commodities (including moisture content) are given in the files regions.csv and items.csv, respectively. For information on the individual processes, see auxiliary file su_codes.csv. RDS files can be opened in R. Information on how to read these files can be obtained here: https://www.rdocumentation.org/packages/base/versions/3.6.2/topics/readRDS
Except of X.rds, which contains a matrix, all variables are organized as lists, where each element contains a sparse matrix. Please note that values are always given in physical units, i.e. tonnes or head, as specified in items.csv. The suffixes value and mass only indicate the form of allocation chosen for the construction of the symmetric IO tables (for more details see Bruckner et al. 2019). Product, process and country classifications can be found in the file fabio_classifications.xlsx.
Footprint results are not contained in the database but can be calculated, e.g. by using this script: https://github.com/martinbruckner/fabio_comparison/blob/master/R/fabio_footprints.R
How to cite:
To cite FABIO work please refer to this paper:
Bruckner, M., Wood, R., Moran, D., Kuschnig, N., Wieland, H., Maus, V., Börner, J. 2019. FABIO – The Construction of the Food and Agriculture Input–Output Model. Environmental Science & Technology 53(19), 11302–11312. DOI: 10.1021/acs.est.9b03554
License:
This data repository is distributed under the CC BY-NC-SA 4.0 License. You are free to share and adapt the material for non-commercial purposes using proper citation. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. In case you are interested in a collaboration, I am happy to receive enquiries at martin.bruckner@wu.ac.at.
Known issues:
The underlying FAO data have been manipulated to the minimum extent necessary. Data filling and supply-use balancing, yet, required some adaptations. These are documented in the code and are also reflected in the balancing item in the final demand matrices. For a proper use of the database, I recommend to distribute the balancing item over all other uses proportionally and to do analyses with and without balancing to illustrate uncertainties.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Italy Imports of Beverages, spirits and vinegar was US$3.34 Billion during 2024, according to the United Nations COMTRADE database on international trade. Italy Imports of Beverages, spirits and vinegar - data, historical chart and statistics - was last updated on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Morocco Imports of rice from Brazil was US$175.31 Thousand during 2022, according to the United Nations COMTRADE database on international trade. Morocco Imports of rice from Brazil - data, historical chart and statistics - was last updated on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Japan's total Exports in 2024 were valued at US$707.39 Billion, according to the United Nations COMTRADE database on international trade. Japan's main export partners were: the United States, China and South Korea. The top three export commodities were: Vehicles other than railway, tramway; Machinery, nuclear reactors, boilers and Electrical, electronic equipment. Total Imports were valued at US$742.67 Billion. In 2024, Japan had a trade deficit of US$35.28 Billion.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Canada's total Exports in 2024 were valued at US$569.17 Billion, according to the United Nations COMTRADE database on international trade. Canada's main export partners were: the United States, China and the United Kingdom. The top three export commodities were: Mineral fuels, oils, distillation products; Vehicles other than railway, tramway and Machinery, nuclear reactors, boilers. Total Imports were valued at US$558.45 Billion. In 2024, Canada had a trade surplus of US$10.72 Billion.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
India Exports of organic chemicals was US$20.69 Billion during 2024, according to the United Nations COMTRADE database on international trade. India Exports of organic chemicals - data, historical chart and statistics - was last updated on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
China Exports to Sierra Leone was US$810.93 Million during 2024, according to the United Nations COMTRADE database on international trade. China Exports to Sierra Leone - data, historical chart and statistics - was last updated on August of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
China Exports to Japan was US$152.01 Billion during 2024, according to the United Nations COMTRADE database on international trade. China Exports to Japan - data, historical chart and statistics - was last updated on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Pakistan Exports of aluminum was US$153.22 Million during 2024, according to the United Nations COMTRADE database on international trade. Pakistan Exports of aluminum - data, historical chart and statistics - was last updated on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
India's total Exports in 2024 were valued at US$434.44 Billion, according to the United Nations COMTRADE database on international trade. India's main export partners were: the United States, the United Arab Emirates and the Netherlands. The top three export commodities were: Mineral fuels, oils, distillation products; Electrical, electronic equipment and Machinery, nuclear reactors, boilers. Total Imports were valued at US$697.75 Billion. In 2024, India had a trade deficit of US$263.31 Billion.
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License information was derived automatically
Bangladesh Imports from United Kingdom was US$287.42 Million during 2015, according to the United Nations COMTRADE database on international trade. Bangladesh Imports from United Kingdom - data, historical chart and statistics - was last updated on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Nigeria Exports to Egypt was US$106.25 Million during 2024, according to the United Nations COMTRADE database on international trade. Nigeria Exports to Egypt - data, historical chart and statistics - was last updated on July of 2025.
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License information was derived automatically
Afghanistan's total Exports in 2019 were valued at US$870.49 Million, according to the United Nations COMTRADE database on international trade. Afghanistan's main export partners were: India, Pakistan and China. The top three export commodities were: Edible fruits, nuts, peel of citrus fruit, melons; Lac, gums, resins and Edible vegetables and certain roots and tubers. Total Imports were valued at US$8.57 Billion. In 2019, Afghanistan had a trade deficit of US$7.70 Billion.
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License information was derived automatically
China Imports of Copper was US$72.57 Billion during 2024, according to the United Nations COMTRADE database on international trade. China Imports of Copper - data, historical chart and statistics - was last updated on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
India Exports to Pakistan was US$1.18 Billion during 2024, according to the United Nations COMTRADE database on international trade. India Exports to Pakistan - data, historical chart and statistics - was last updated on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
China's total Imports in 2024 were valued at US$2.59 Trillion, according to the United Nations COMTRADE database on international trade. China's main import partners were: South Korea, the United States and Japan. The top three import commodities were: Electrical, electronic equipment; Mineral fuels, oils, distillation products and Ores slag and ash. Total Exports were valued at US$3.58 Trillion. In 2024, China had a trade surplus of US$991.41 Billion.
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License information was derived automatically
Ethiopia's total Imports in 2023 were valued at US$17.05 Billion, according to the United Nations COMTRADE database on international trade. Ethiopia's main import partners were: China, India and Kuwait. The top three import commodities were: Mineral fuels, oils, distillation products; Machinery, nuclear reactors, boilers and Electrical, electronic equipment. Total Exports were valued at US$2.86 Billion. In 2023, Ethiopia had a trade deficit of US$14.19 Billion.
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License information was derived automatically
Pakistan Exports to Bangladesh was US$778.11 Million during 2024, according to the United Nations COMTRADE database on international trade. Pakistan Exports to Bangladesh - data, historical chart and statistics - was last updated on July of 2025.
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License information was derived automatically
Australia's total Imports in 2024 were valued at US$296.48 Billion, according to the United Nations COMTRADE database on international trade. Australia's main import partners were: China, the United States and Japan. The top three import commodities were: Vehicles other than railway, tramway; Machinery, nuclear reactors, boilers and Mineral fuels, oils, distillation products. Total Exports were valued at US$340.85 Billion. In 2024, Australia had a trade surplus of US$44.37 Billion.
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Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
License information was derived automatically
This data repository provides the Food and Agriculture Biomass Input Output (FABIO) database, a global set of multi-regional physical supply-use and input-output tables covering global agriculture and forestry.
The work is based on mostly freely available data from FAOSTAT, IEA, EIA, and UN Comtrade/BACI. FABIO currently covers 191 countries + RoW, 118 processes and 125 commodities (raw and processed agricultural and food products) for 1986-2013. All R codes and auxilliary data are available on GitHub. For more information please refer to https://fabio.fineprint.global.
The database consists of the following main components, in compressed .rds format:
Z: the inter-commodity input-output matrix, displaying the relationships of intermediate use of each commodity in the production of each commodity, in physical units (tons). The matrix has 24000 rows and columns (125 commodities x 192 regions), and is available in two versions, based on the method to allocate inputs to outputs in production processes: Z_mass (mass allocation) and Z_value (value allocation). Note that the row sums of the Z matrix (= total intermediate use by commodity) are identical in both versions.
Y: the final demand matrix, denoting the consumption of all 24000 commodities by destination country and final use category. There are six final use categories (yielding 192 x 6 = 1152 columns): 1) food use, 2) other use (non-food), 3) losses, 4) stock addition, 5) balancing, and 6) unspecified.
X: the total output vector of all 24000 commodities. Total output is equal to the sum of intermediate and final use by commodity.
L: the Leontief inverse, computed as (I – A)-1, where A is the matrix of input coefficients derived from Z and x. Again, there are two versions, depending on the underlying version of Z (L_mass and L_value).
E: environmental extensions for each of the 24000 commodities, including four resource categories: 1) primary biomass extraction (in tons), 2) land use (in hectares), 3) blue water use (in m3)., and 4) green water use (in m3).
mr_sup_mass/mr_sup_value: For each allocation method (mass/value), the supply table gives the physical supply quantity of each commodity by producing process, with processes in the rows (118 processes x 192 regions = 22656 rows) and commodities in columns (24000 columns).
mr_use: the use table capture the quantities of each commodity (rows) used as an input in each process (columns).
A description of the included countries and commodities (i.e. the rows and columns of the Z matrix) can be found in the auxiliary file io_codes.csv. Separate lists of the country sample (including ISO3 codes and continental grouping) and commodities (including moisture content) are given in the files regions.csv and items.csv, respectively. For information on the individual processes, see auxiliary file su_codes.csv. RDS files can be opened in R. Information on how to read these files can be obtained here: https://www.rdocumentation.org/packages/base/versions/3.6.2/topics/readRDS
Except of X.rds, which contains a matrix, all variables are organized as lists, where each element contains a sparse matrix. Please note that values are always given in physical units, i.e. tonnes or head, as specified in items.csv. The suffixes value and mass only indicate the form of allocation chosen for the construction of the symmetric IO tables (for more details see Bruckner et al. 2019). Product, process and country classifications can be found in the file fabio_classifications.xlsx.
Footprint results are not contained in the database but can be calculated, e.g. by using this script: https://github.com/martinbruckner/fabio_comparison/blob/master/R/fabio_footprints.R
How to cite:
To cite FABIO work please refer to this paper:
Bruckner, M., Wood, R., Moran, D., Kuschnig, N., Wieland, H., Maus, V., Börner, J. 2019. FABIO – The Construction of the Food and Agriculture Input–Output Model. Environmental Science & Technology 53(19), 11302–11312. DOI: 10.1021/acs.est.9b03554
License:
This data repository is distributed under the CC BY-NC-SA 4.0 License. You are free to share and adapt the material for non-commercial purposes using proper citation. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. In case you are interested in a collaboration, I am happy to receive enquiries at martin.bruckner@wu.ac.at.
Known issues:
The underlying FAO data have been manipulated to the minimum extent necessary. Data filling and supply-use balancing, yet, required some adaptations. These are documented in the code and are also reflected in the balancing item in the final demand matrices. For a proper use of the database, I recommend to distribute the balancing item over all other uses proportionally and to do analyses with and without balancing to illustrate uncertainties.