Publication in the ACM Transactions on Software Engineering and Methodology
Introduction to the use of instrumental variables for causal inference
Inferring causal relationships between variables from observational data is a common goal in empirical social research. However, the phenomenon of endogeneity often makes such inferences difficult. In their new article in the ACM Transactions on Software Engineering and Methodology, Prof. Dr. Lorenz Graf-Vlachy and Prof. Dr. Stefan Wagner from TUM introduce instrumental variables to the research field of software engineering. This method is already widely used in other disciplines and can often help to eliminate endogeneity problems.
Read the entire study here.
Graf-Vlachy, L. & Wagner, S. 2024. Cleaning Up Confounding: Accounting for Endogeneity Using Instrumental Variables and Two-Stage Models. ACM Transactions on Software Engineering and Methodology, forthcoming.