Bridging the gap between econometric analysis and dynamic economic models with public and private information

In the social sciences, a gap exists between complex dynamic models and the practical limitations imposed by commonly used econometric and statistical tools, making it challenging to translate theoretical predictions into verifiable questions using real-world data. This project aims to develop a novel methodological framework to enhance interpretability and transparency in dynamic models and statistical procedures. Results will consist of innovative mathematical and statistical tools facilitating the generation of sound, statistically grounded conclusions from economic predictions. The project will advance knowledge frontiers in econometrics, empirical economics, and finance, ultimately enhancing data-driven policy making.