Data for environmental policy: core economic sectors redefined

The European Green Deal is driving the transition to a resource-efficient and competitive economy. It creates jobs and gives Europe a sustainable competitive advantage in the global market. In order to develop the right policy measures, these changes must be closely monitored. In addition to environmental issues, economic data from companies in environmentally relevant sectors play a key role. Since Eurostat introduced data sets on environmental goods and services sectors (EGSS), interest in the economic analysis of these areas has been growing.

Prognos and DevStat developed a new methodology for regular data collection for these environmental sectors on behalf of Eurostat.

Data for environmental policy

There is a need to generate information on environmental economic sectors such as climate protection (net-zero), circular economy, environmental protection, bioeconomy, and climate adaptation. To this end, an approach has been developed, tested and applied that captures economic indicators such as production, gross value added, jobs, exports and investments. The project resulted in an automated solution for calculation and estimation based on the R programming language. This enables Eurostat to provide regularly updated data on these sectors. The data supports policy decisions and opens up new perspectives for a resource-efficient economy.

Prognos carried out the following work steps:

• Development of a new methodology for estimating various core economic indicators for the Environmental Goods and Services Sector (EGSS)
• Support for the development of an automated R tool that accurately and efficiently processes economic data for the EGSS.
• Provision of up-to-date, evidence-based economic information on the sectors: circular economy, bioeconomy, climate protection and climate adaptation.
• Updating of the methodological guidelines for national statistical offices on the collection of EGSS data.

Our approach

Prognos drew on experience from similar projects and modelling work (envigos) to develop an approach that uses economic statistics and classifications for estimation. This allows regular updates to be carried out without primary surveys, reducing the administrative burden on Member States and Eurostat. Existing methodological approaches were analysed and further developed. For regular implementation, we developed an automated procedure based on the R programming language.

Project team: Jannis Lambert, Robert Norpoth, Richard Simpson

Latest update: 20.08.2025