Description
EC policy priorities include both digital and green transformations as key areas of interest, and are now being reinforced in the strategy designed to alleviate the consequences of the pandemic structured by the EU Next Generation Recovery Plan, the European Green Deal, and the EU’s Digital Decade. To monitor the evolution of the European economy towards these objectives, the availability of data that allows the measurement of the progress in digitalisation and in environmental aspects is crucial. The PREDICT Dataset focuses on one aspect of the digital transformation, namely the importance and development of the ICT, media content and retail sale via mail order houses or via internet sector. The Twin Transition Dataset widens the scope with the inclusion of indicators of the digital transformation and R&D intensity in all industries of the economy, as well as information on environmental protection activities. However, it not only includes ICT producing sectors, but also a detailed industry disaggregation (33 industries) so that the whole economy can be traced. Additionally, each industry is classified according to the intensity of the impact of digital transformation within the sector. One of the main advantages of the data is that the information is internally in accord with the PREDICT dataset, which follows the National Accounts framework and the guidelines set out in the Frascati Manual for R&D variables. More precisely, the Twin Transition Dataset database is composed of two different thematic datasets: digitalisation and environment. The economic variables in each dataset are the following: 1. Digitalisation 1.1 Gross Value Added and Gross Output 1.2 Employment and Hours Worked 1.3 Labour productivity 1.4 Business R&D Expenditure 1.5 R&D personnel 1.6 R&D researchers 1.7 Gross Fixed Capital Formation 1.8 Net capital Stock 2. Environment 2.1 Gross Value Added 2.2 Gross Output 2.3 Employment 2.4 Labour productivity
Contact
Contributors
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- Elisa Calza
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- Juan Torrecillas
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- Fernando Pascual
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- Giuditta De Prato
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- Melisande Cardona
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- Riccardo Righi
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0000-0002-7472-4293
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- Miguel Vazquez-Prada Baillet
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- Michail Papazoglou
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- Matilde Mas
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0000-0003-1151-099X
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- Juan Fernández de Guevara
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0000-0003-0590-612X
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- Eva Benages
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- Laura Hernández
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- Consuelo Mínguez
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- Juan Pérez
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- Juan Carlos Robledo
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- Jimena Salamanca
How to cite
Elisa Calza; Juan Torrecillas; Fernando Pascual; Giuditta De Prato; Cardona, Melisande; Righi, Riccardo; Vazquez-Prada Baillet, Miguel; Papazoglou, Michail; Mas, Matilde; Fernández de Guevara, Juan; Benages, Eva; Hernández, Laura; Mínguez, Consuelo; Pérez, Juan; Robledo, Juan Carlos; Salamanca, Jimena (2023): 2023 PREDICT Twin Transition Dataset. European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/02807ef4-b75d-4777-869a-349aec2aaa5f
Keywords
digital economy environment twin transition
Data access
Temporal coverage
| From date | To date |
|---|---|
| 2014-01-01 | 2020-01-01 |
Additional information
- Published by
- European Commission, Joint Research Centre
- Created date
- 2023-07-20
- Modified date
- 2023-07-20
- Issued date
- 2023-07-24
- Data theme(s)
- Economy and finance, Environment
- Update frequency
- unknown
- Identifier
- http://data.europa.eu/89h/02807ef4-b75d-4777-869a-349aec2aaa5f
- Popularity
-