With this information overload, the decision-making process is more complicated than ever. The digital age is also revolutionising decision-making in an economy in ways that we only now are beginning to understand. The growing interconnectedness of economic agents, companies, machines, and computers forms new dynamic networks that have changed the nature of interactions and decisions.
The traditional view of economic agents making rational decisions is now being confronted with the empirical evidence of suboptimal decisions due to psychological reasons (emotions, social behavior, herd behavior etc.). As a consequence, human decisions are starting to being replaced by the algorithms, commonly denoted as Artificial Intelligence (AI). Like in other fields, economists call for rigorous theoretical research that will help us understand the role of AI, as well as the help of Machine Learning (ML) in the context of the decision-making process of economic agents.
In addition to theoretical research, applied research is at its very early stages, too. In our CENTRAL 2020 project, we would like to address current theoretical and empirical issues related to the application of AI and ML in economics. As for the theoretical issues, the inference in ML models and dynamic density forecasting will be of particular interest. In the empirical application, we will concentrate on the broad area of economic and finance such as business cycles and time series analysis, asset pricing, credit risk modelling, dynamic networks in cryptocurrency markets etc. There will be held two workshops in 2020: the first one in Prague (August 27/28), the other in Berlin by the end of the year.
- Partners: Charles University (Prague), Humboldt University Berlin, University of Warsaw
- Project Lead: Prof. Wolfgang Härdle, Humboldt University Berlin
- Year: 2020
