A practical guide on mitigating endogeneity bias in empirical research
The resources available on this site are designed to help researchers address various forms of endogeneity bias, including omitted variable bias and selection bias. The project was initiated by Prof. Dr. David Bendig and Dr. Jonathan Hoke at University of Münster.
In light of the growing significance of endogeneity in modern research and the rigorous examination of econometric techniques by academic journals, we have witnessed an uptick in methodological inconsistencies in the utilization of intricate statistical methodologies. It can be challenging for scholars and practitioners to stay abreast of these developments. To address this issue, we have created comprehensive, accessible guides to statistical research methods that address endogeneity bias. These resources are designed to facilitate the application of these methods and techniques across different research models.
