Aggregated CFS Matrices for Sweden 2016 and 2021
Description
Aggregated CFS Matrices (Sweden, 2016 & 2021) Associated publication: Westin, J. (2025). A novel method for estimating multiregional input–output tables using data at different aggregation levels. Papers in Regional Science, 100111. Dataset contents The dataset consists of one Excel file: CFS_Sweden_NUTS2_MSEK_2016_2021.xlsx This file contains estimated and aggregated commodity flow survey (CFS) data in monetary terms (MSEK) for Swedish counties (län), covering 2016 and 2021. Each sheet corresponds to a commodity group × year combination. Structure of the Excel file Sheets: 22 sheets (11 commodity groups × 2 years). Sheet naming convention: CFS_[GroupCode]_[Year] Example: CFS_01_2016, CFS_01_2021 Each sheet contains: Origin–Destination matrix: County origins in rows, county destinations in columns. Values = commodity flows in MSEK. Supply vector (S): Row totals by origin (MSEK). Demand vector (D): Column totals by destination (MSEK). County names The following 21 counties are included as origins and destinations: 01 Stockholm 02 Uppsala 03 Södermanland 04 Östergötland 05 Jönköping 06 Kronoberg 07 Kalmar 08 Gotland 09 Blekinge 10 Skåne 11 Halland 12 Västra Götaland 13 Värmland 14 Örebro 15 Västmanland 16 Dalarna 17 Gävleborg 18 Västernorrland 19 Jämtland 20 Västerbotten 21 Norrbotten Commodity groups The dataset includes 11 aggregated commodity groups based on NST 2007: 01 Agriculture, forestry & fishing 03 Metal ores & minerals 04 Food, beverages & tobacco 05 Textiles & textile products 06 Wood, paper & pulp 08 Chemical products 09 Earth, stone & construction materials 10 Steel & metals 11 Machinery 12 Transport equipment 13 Other manufacturing Variables Within each sheet: Row labels: Origin county name (1–21). Column labels: Destination county name (1–21). Cell values: Flow values in MSEK. Row totals (S): Supply (MSEK). Column totals (D): Demand (MSEK). Notes The dataset replicates the matrices used in the article and supports replication of the MRIO estimation method. Please cite both Statistics Sweden (CFS) and the PiRS article when using this dataset.
Files
Steps to reproduce
Sources Original data: Swedish Commodity Flow Survey (CFS) 2016 & 2021, Statistics Sweden (SCB). Regional classification: Swedish counties (21 län). Commodity classification: Aggregated from NST 2007 codes into 11 groups. Aggregated flows: Estimated based on CFS data. Supply and demand totals: Constructed based on Swedish national accounts data (not directly from CFS). Transformations Estimated flows aggregated from CFS data to 11 commodity groups. Converted all flows into MSEK. Constructed Supply (S) and Demand (D) totals for each matrix based on national accounts data. Aggregated municipality-level flows to county level. Suppressed / confidential cells replaced with 0.
Institutions
- Umea UniversitetUmea