Network Embedding for Economic Issues
Project title: Consideration of Contextual Factors and Structural Conditions in a Dynamic Framework (KONECO)
Project partner: Chair of Empirical Economics - Prof. Dr. Mario Larch
Funding agency: German Federal Ministry of Education and Research (BMBF)
Funding period: 2022-2024
The goal of the KONECO project is to use machine learning algorithms from graph theory, more precisely node and graph embedding, to account for the complexity of trade markets and to adapt the methods in such a way that three questions from economic research on trade markets can be answered better than before. The determinants of membership in free trade agreements, network properties of trade flows, and the specifics of European energy markets are to be investigated and explained in unprecedented depth. The influences of contextual factors will be taken into account and a dynamic view will be taken, which has not been possible so far in the analysis of economic networks.
The project builds on a close interdisciplinary cooperation between a scientist from the field of economics and a scientist from the field of computer science. The communication between disciplines and their respective models of thinking will be observed as part of this research in order to consolidate the interdisciplinary knowledge creation process and create a sensitivity for the challenges of interdisciplinary collaboration on data analysis.