Estimating value added and employment of bioeconomy in EU regions: A methodological proposal

J.M. Lasarte-Lopez, T. Ronzon, M.G.A. van Leeuwen, W. Rossi Cervi, R. M'Barek

Research output: Book/ReportReportProfessional


The analysis and monitoring of the bioeconomy at the regional level is of interest for policy design and evaluation, and it aligns with the territorial approach called for by the Bioeconomy Strategy (2018) of the European Union (EU). Although some initiatives provided estimates of the size and/or regional distribution of the bioeconomy in some countries, there are no homogeneous data allowing the analysis of the regional dimension of the EU’s bioeconomy.
This report describes a methodology to estimate employment and value added of the bioeconomy sectors at the NUTS2 level in the EU. It consists of a systematic combination of Eurostat regional statistics with national bio-based shares from the public JRC-Bioeconomics database for allocating employment and value added in the bioeconomy sectors amongst regions. National bio-based shares are calculated following Ronzon et al. (2020)’s approach. When missing from Eurostat data sources, regional series are estimated by applying various criteria to regionalise national statistics. Finally, some missing data estimation algorithms are applied to complete the dataset.
Preliminary results evidence that this approach manages to fill in the majority of missing series and data in the initial datasets. We extract some key figures and trends for the regional bioeconomies in the EU. We discuss our results through the comparison with available official statistics, other previous estimates and expert feedback, and propose potential improvements.
Original languageEnglish
Number of pages32
ISBN (Electronic)9789276522690
Publication statusPublished - 2022

Publication series

NameJRC Technical Report
ISSN (Electronic)1831-9424


Dive into the research topics of 'Estimating value added and employment of bioeconomy in EU regions: A methodological proposal'. Together they form a unique fingerprint.

Cite this