Research project EWAGI
Energy transition and competitiveness: An analysis of the heterogeneous behaviour of companies and its macroeconomic implications
In order to achieve the goal of climate neutrality by 2045, the German government has introduced a series of measures such as the Renewable Energy Sources Act (EEG) and CO2 certificate trading. They aim to accelerate the transformation process, but ultimately also result in an increase in electricity prices. This can have a substantial impact on the cost structure of companies in the manufacturing sector in particular and lead to a competitive disadvantage. On the other hand, the steering function of the price can also have a positive effect on a company's own competitiveness, for example by encouraging a switch to other energy sources or self-generation. Against this background, the EWAGI research project (funded by the Federal Ministry for Economic Affairs and Climate Action) is analysing in detail how companies adapt their behaviour to rising electricity prices. The aim is to examine the behaviour of companies in response to changing electricity prices at the microeconomic level and to determine the effects on the competitiveness of companies. Building on this, an agent-based macroeconomic model will be used to analyse the effects of various electricity price scenarios on sectoral and macroeconomic development, taking particular account of the heterogeneous adjustment strategies of companies, and the effectiveness of potential economic and energy policy measures will be examined.
Research project EWAGI | |
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Duration | December 2022 to November 2025 |
Funded by | Federal Ministry for Economic Affairs and Climate Action |
Project participants | - Institute of Networked Energy Systems
- Universität Bielefeld – Fakultät für Wirtschaftswissenschaften – Economic Theory and Computational Economics
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In addition to empirically analysing the effects of electricity price changes on the competitiveness of companies, the EWAGI project is also concerned with the actual reaction to changing electricity prices. To this end, different types of behaviour are examined, including the tendency of companies to invest in energy efficiency and their tendency to change their energy mix or even generate their own electricity. The project also focuses on the development of an agent-based simulation model for the computer-aided analysis of the economic effects of selected energy policy scenarios and the investigation of various policy measures with regard to their effectiveness in avoiding possible long-term economic disadvantages due to changing energy prices. The project participants are pursuing the goal of combining two innovative methods: On the one hand, multi-level modelling (MLM) as an empirical tool, and on the other hand, agent-based modelling (ABM) as a computer-based simulation approach.
In the EWAGI research project, these two methods will be combined for the first time in order to analyse the effects of energy policy on sectoral and macroeconomic developments, taking particular account of the heterogeneous adaptation strategies of companies. It is expected to provide nuanced and novel insights by adequately modelling the behaviour, heterogeneity and interactions of firms at both the micro and macro levels.
The main focus of the Institute of Networked Energy Systems is to apply the multi-level modelling described above in the context of an analysis of industrial companies based on the AFiD database (Official company data for Germany). The aim is to statistically investigate the behaviour of industrial companies in response to changes in electricity prices and to make this information available in a form suitable for agent-based macroeconomic modelling. Furthermore, the Institute aims to prepare case studies of policy design options for industry in the context of the energy transition and to participate in analysing the macroeconomic impact analysis from an energy-economic perspective.
The agent-based model created as part of the project will subsequently be made available to the public as an open source tool. The data and assumptions used for the analyses within the model will also be made publicly available in a suitable format. It is also planned to document and publish all the analysis steps in detail.
