Endogeneity, Instruments, and Two-Stage Models
Lorenz Graf‐Vlachy, Stefan Wagner · 2024
Background: Studies in software engineering are often particularly useful if they make causal claims because this allows practitioners to identify how they can influence outcomes of interest. Unfortunately, many non-experimental studies suffer from potential endogeneity through omitted confounding variables, which precludes claims of causality. Aims and Method: We introduce instrumental variables and two-stage models as a means to account for endogeneity to the field of empirical software engineering. Results and Conclusions: We define endogeneity, explain its primary cause, and lay out the idea behind instrumental variable approaches and two-stage models.