A significant share of empirical research seeks to determine how one variable affects another, making the treatment of endogeneity essential for credible causal inference. In a recent research seminar held by András Gyimesi on 14 November 2025, panel data and methods were highlighted as a powerful tool for reducing bias and strengthening the reliability of causal analysis. The talk reviewed widely used empirical methods such as difference-in-differences, fixed-effects models and dynamic panel approaches.
