FIGARO-E3: a high-resolution extended multi-regional input-output database consistent with official statistics.

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2025-04-04 DOI:10.1038/s41597-025-04431-z

Ignacio Cazcarro, Arkaitz Usubiaga-Liaño, Marίa Victoria Román, Pablo Piñero, Erik Dietzenbacher, José Manuel Rueda-Cantuche, Iñaki Arto

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引用次数: 0

Abstract

Existing 'official' multi-regional input-output (MRIO) databases lack sufficient sectoral detail and extensions for calculating accurate environmental and social footprints. FIGARO-E3 is a highly disaggregated MRIO database for 2015 with labour and environmental extensions largely consistent with official statistics. The database has been created by disaggregating the official FIGARO database (46 countries, 64 industries/products) to achieve a resolution of 175 industries and 213 products based on the monetary structures of EXIOBASE. Labour accounts (including total employment and employment by gender and by skill) are based on OECD data and EXIOBASE structures. Energy accounts (primary energy supply, net, final and non-energy uses, energy industry own use and energy losses) are based on the IEA's extended energy balances and FIGARO-E3 MRIO tables. GHG emission accounts (covering four types of GHGs: CO2, CH4, N2O and fluorinated gases, both for combustion and non-combustion processes) are based on IEA and EDGAR data. GHG emission accounts for European countries have been reconciled with data from Eurostat. The FIGARO-E3 database is largely consistent with official statistics.

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.